WorldWideScience

Sample records for factorization scale uncertainty

  1. Scaling factors for ab initio vibrational frequencies: comparison of uncertainty models for quantified prediction

    CERN Document Server

    Pernot, Pascal

    2009-01-01

    Bayesian Model Calibration is used to revisit the problem of scaling factor calibration for semi-empirical correction of ab initio calculations. A particular attention is devoted to uncertainty evaluation for scaling factors, and to their effect on prediction of observables involving scaled properties. We argue that linear models used for calibration of scaling factors are generally not statistically valid, in the sense that they are not able to fit calibration data within their uncertainty limits. Uncertainty evaluation and uncertainty propagation by statistical methods from such invalid models are doomed to failure. To relieve this problem, a stochastic function is included in the model to account for model inadequacy, according to the Bayesian Model Calibration approach. In this framework, we demonstrate that standard calibration summary statistics, as optimal scaling factor and root mean square, can be safely used for uncertainty propagation only when large calibration sets of precise data are used. For s...

  2. Toward a definition of intolerance of uncertainty: a review of factor analytical studies of the Intolerance of Uncertainty Scale.

    Science.gov (United States)

    Birrell, Jane; Meares, Kevin; Wilkinson, Andrew; Freeston, Mark

    2011-11-01

    Since its emergence in the early 1990s, a narrow but concentrated body of research has developed examining the role of intolerance of uncertainty (IU) in worry, and yet we still know little about its phenomenology. In an attempt to clarify our understanding of this construct, this paper traces the way in which our understanding and definition of IU have evolved throughout the literature. This paper also aims to further our understanding of IU by exploring the latent variables measures by the Intolerance of Uncertainty Scale (IUS; Freeston, Rheaume, Letarte, Dugas & Ladouceur, 1994). A review of the literature surrounding IU confirmed that the current definitions are categorical and lack specificity. A critical review of existing factor analytic studies was carried out in order to determine the underlying factors measured by the IUS. Systematic searches yielded 9 papers for review. Two factors with 12 consistent items emerged throughout the exploratory studies, and the stability of models containing these two factors was demonstrated in subsequent confirmatory studies. It is proposed that these factors represent (i) desire for predictability and an active engagement in seeking certainty, and (ii) paralysis of cognition and action in the face of uncertainty. It is suggested that these factors may represent approach and avoidance responses to uncertainty. Further research is required to confirm the construct validity of these factors and to determine the stability of this structure within clinical samples.

  3. Semi-empirical correction of ab initio harmonic properties by scaling factors: a validated uncertainty model for calibration and prediction

    CERN Document Server

    Pernot, Pascal

    2010-01-01

    Bayesian Model Calibration is used to revisit the problem of scaling factor calibration for semi-empirical correction of ab initio harmonic properties (e.g. vibrational frequencies and zero-point energies). A particular attention is devoted to the evaluation of scaling factor uncertainty, and to its effect on the accuracy of scaled properties. We argue that in most cases of interest the standard calibration model is not statistically valid, in the sense that it is not able to fit experimental calibration data within their uncertainty limits. This impairs any attempt to use the results of the standard model for uncertainty analysis and/or uncertainty propagation. We propose to include a stochastic term in the calibration model to account for model inadequacy. This new model is validated in the Bayesian Model Calibration framework. We provide explicit formulae for prediction uncertainty in typical limit cases: large and small calibration sets of data with negligible measurement uncertainty, and datasets with la...

  4. Assessing positive matrix factorization model fit: a new method to estimate uncertainty and bias in factor contributions at the measurement time scale

    Directory of Open Access Journals (Sweden)

    J. G. Hemann

    2009-01-01

    Full Text Available A Positive Matrix Factorization receptor model for aerosol pollution source apportionment was fit to a synthetic dataset simulating one year of daily measurements of ambient PM2.5 concentrations, comprised of 39 chemical species from nine pollutant sources. A novel method was developed to estimate model fit uncertainty and bias at the daily time scale, as related to factor contributions. A circular block bootstrap is used to create replicate datasets, with the same receptor model then fit to the data. Neural networks are trained to classify factors based upon chemical profiles, as opposed to correlating contribution time series, and this classification is used to align factor orderings across the model results associated with the replicate datasets. Factor contribution uncertainty is assessed from the distribution of results associated with each factor. Comparing modeled factors with input factors used to create the synthetic data assesses bias. The results indicate that variability in factor contribution estimates does not necessarily encompass model error: contribution estimates can have small associated variability across results yet also be very biased. These findings are likely dependent on characteristics of the data.

  5. Visualizing large-scale uncertainty in astrophysical data.

    Science.gov (United States)

    Li, Hongwei; Fu, Chi-Wing; Li, Yinggang; Hanson, Andrew

    2007-01-01

    Visualization of uncertainty or error in astrophysical data is seldom available in simulations of astronomical phenomena, and yet almost all rendered attributes possess some degree of uncertainty due to observational error. Uncertainties associated with spatial location typically vary signicantly with scale and thus introduce further complexity in the interpretation of a given visualization. This paper introduces effective techniques for visualizing uncertainty in large-scale virtual astrophysical environments. Building upon our previous transparently scalable visualization architecture, we develop tools that enhance the perception and comprehension of uncertainty across wide scale ranges. Our methods include a unified color-coding scheme for representing log-scale distances and percentage errors, an ellipsoid model to represent positional uncertainty, an ellipsoid envelope model to expose trajectory uncertainty, and a magic-glass design supporting the selection of ranges of log-scale distance and uncertainty parameters, as well as an overview mode and a scalable WIM tool for exposing the magnitudes of spatial context and uncertainty.

  6. Spatial uncertainty assessment in modelling reference evapotranspiration at regional scale

    Directory of Open Access Journals (Sweden)

    G. Buttafuoco

    2010-07-01

    Full Text Available Evapotranspiration is one of the major components of the water balance and has been identified as a key factor in hydrological modelling. For this reason, several methods have been developed to calculate the reference evapotranspiration (ET0. In modelling reference evapotranspiration it is inevitable that both model and data input will present some uncertainty. Whatever model is used, the errors in the input will propagate to the output of the calculated ET0. Neglecting information about estimation uncertainty, however, may lead to improper decision-making and water resources management. One geostatistical approach to spatial analysis is stochastic simulation, which draws alternative and equally probable, realizations of a regionalized variable. Differences between the realizations provide a measure of spatial uncertainty and allow to carry out an error propagation analysis. Among the evapotranspiration models, the Hargreaves-Samani model was used.

    The aim of this paper was to assess spatial uncertainty of a monthly reference evapotranspiration model resulting from the uncertainties in the input attributes (mainly temperature at regional scale. A case study was presented for Calabria region (southern Italy. Temperature data were jointly simulated by conditional turning bands simulation with elevation as external drift and 500 realizations were generated.

    The ET0 was then estimated for each set of the 500 realizations of the input variables, and the ensemble of the model outputs was used to infer the reference evapotranspiration probability distribution function. This approach allowed to delineate the areas characterized by greater uncertainty, to improve supplementary sampling strategies and ET0 value predictions.

  7. Quantifying uncertainty and computational complexity for pore-scale simulations

    Science.gov (United States)

    Chen, C.; Yuan, Z.; Wang, P.; Yang, X.; Zhenyan, L.

    2016-12-01

    Pore-scale simulation is an essential tool to understand the complex physical process in many environmental problems, from multi-phase flow in the subsurface to fuel cells. However, in practice, factors such as sample heterogeneity, data sparsity and in general, our insufficient knowledge of the underlying process, render many simulation parameters and hence the prediction results uncertain. Meanwhile, most pore-scale simulations (in particular, direct numerical simulation) incur high computational cost due to finely-resolved spatio-temporal scales, which further limits our data/samples collection. To address those challenges, we propose a novel framework based on the general polynomial chaos (gPC) and build a surrogate model representing the essential features of the underlying system. To be specific, we apply the novel framework to analyze the uncertainties of the system behavior based on a series of pore-scale numerical experiments, such as flow and reactive transport in 2D heterogeneous porous media and 3D packed beds. Comparing with recent pore-scale uncertainty quantification studies using Monte Carlo techniques, our new framework requires fewer number of realizations and hence considerably reduce the overall computational cost, while maintaining the desired accuracy.

  8. Reducing, Maintaining, or Escalating Uncertainty? The Development and Validation of Four Uncertainty Preference Scales Related to Cancer Information Seeking and Avoidance.

    Science.gov (United States)

    Carcioppolo, Nick; Yang, Fan; Yang, Qinghua

    2016-09-01

    Uncertainty is a central characteristic of many aspects of cancer prevention, screening, diagnosis, and treatment. Brashers's (2001) uncertainty management theory details the multifaceted nature of uncertainty and describes situations in which uncertainty can both positively and negatively affect health outcomes. The current study extends theory on uncertainty management by developing four scale measures of uncertainty preferences in the context of cancer. Two national surveys were conducted to validate the scales and assess convergent and concurrent validity. Results support the factor structure of each measure and provide general support across multiple validity assessments. These scales can advance research on uncertainty and cancer communication by providing researchers with measures that address multiple aspects of uncertainty management.

  9. Advances in the study of uncertainty quantification of large-scale hydrological modeling system

    Institute of Scientific and Technical Information of China (English)

    SONG Xiaomeng; ZHAN Chesheng; KONG Fanzhe; XIA Jun

    2011-01-01

    The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex system.However,there have not been effective methods for the model reliability and uncertainty analysis due to its complexity and difficulty.The uncertainties in hydrological modeling come from four important aspects:uncertainties in input data and parameters,uncertainties in model structure,uncertainties in analysis method and the initial and boundary conditions.This paper systematically reviewed the recent advances in the study of the uncertainty analysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources.Also,the shortcomings and insufficiencies in the uncertainty analysis for complex hydrological models are pointed out.And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods were introduced,which will be a powerful tool and platform for uncertainty analysis of large-scale complex hydrological models.Finally,some future perspectives on uncertainty quantification are put forward.

  10. Effects of input uncertainty on cross-scale crop modeling

    Science.gov (United States)

    Waha, Katharina; Huth, Neil; Carberry, Peter

    2014-05-01

    The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input

  11. Uncertainties in the simulation of groundwater recharge at different scales

    Directory of Open Access Journals (Sweden)

    H. Bogena

    2005-01-01

    Full Text Available Digital spatial data always imply some kind of uncertainty. The source of this uncertainty can be found in their compilation as well as the conceptual design that causes a more or less exact abstraction of the real world, depending on the scale under consideration. Within the framework of hydrological modelling, in which numerous data sets from diverse sources of uneven quality are combined, the various uncertainties are accumulated. In this study, the GROWA model is taken as an example to examine the effects of different types of uncertainties on the calculated groundwater recharge. Distributed input errors are determined for the parameters' slope and aspect using a Monte Carlo approach. Landcover classification uncertainties are analysed by using the conditional probabilities of a remote sensing classification procedure. The uncertainties of data ensembles at different scales and study areas are discussed. The present uncertainty analysis showed that the Gaussian error propagation method is a useful technique for analysing the influence of input data on the simulated groundwater recharge. The uncertainties involved in the land use classification procedure and the digital elevation model can be significant in some parts of the study area. However, for the specific model used in this study it was shown that the precipitation uncertainties have the greatest impact on the total groundwater recharge error.

  12. Uncertainty Consideration in Watershed Scale Models

    Science.gov (United States)

    Watershed scale hydrologic and water quality models have been used with increasing frequency to devise alternative pollution control strategies. With recent reenactment of the 1972 Clean Water Act’s TMDL (total maximum daily load) component, some of the watershed scale models are being recommended ...

  13. Quantifying uncertainty in NIF implosion performance across target scales

    Science.gov (United States)

    Spears, Brian; Baker, K.; Brandon, S.; Buchoff, M.; Callahan, D.; Casey, D.; Field, J.; Gaffney, J.; Hammer, J.; Humbird, K.; Hurricane, O.; Kruse, M.; Munro, D.; Nora, R.; Peterson, L.; Springer, P.; Thomas, C.

    2016-10-01

    Ignition experiments at NIF are being performed at a variety of target scales. Smaller targets require less energy and can be fielded more frequently. Successful small target designs can be scaled up to take advantage of the full NIF laser energy and power. In this talk, we will consider a rigorous framework for scaling from smaller to larger targets. The framework uses both simulation and experimental results to build a statistical prediction of target performance as scale is increased. Our emphasis is on quantifying uncertainty in scaling predictions with the goal of identifying the dominant contributors to that uncertainty. We take as a particular example the Big Foot platform that produces a round, 0.8 scale implosion with the potential to scale to full NIF size (1.0 scale). This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  14. Determining the Jet Energy Scale Uncertainty in the ATLAS detector

    CERN Document Server

    Kogan, L A; The ATLAS collaboration

    2012-01-01

    Using jets from proton-proton collisions at a centre of mass energy of s = 7 TeV measured with the ATLAS detector at the LHC the Jet Energy Scale and its systematic uncertainty have been determined. A Jet Energy Scale systematic uncertainty between 2-4% for jet pT >20GeV in the pseudo-rapidity region up to |η|=4.5 has been obtained. This uncertainty was derived from a combination of systematic variations in Monte Carlo simulations and single hadron response measurements performed in-situ and using test beam data. The uncertainty is confirmed using in-situ methods where a well measured reference object is balanced against the jet.

  15. String theory, scale relativity and the generalized uncertainty principle

    CERN Document Server

    Castro, C

    1995-01-01

    An extension/ modification of the Stringy Heisenberg Uncertainty principle is derived within the framework of the theory of Special Scale-Relativity proposed by Nottale. Based on the fractal structure of two dimensional Quantum Gravity which has attracted considerable interest recently we conjecture that the underlying fundamental principle behind String theory should be based on an extension of Scale Relativity where both dynamics as well as scales are incorporated in the same footing.

  16. Large-Scale Inverse Problems and Quantification of Uncertainty

    CERN Document Server

    Biegler, Lorenz; Ghattas, Omar

    2010-01-01

    Large-scale inverse problems and associated uncertainty quantification has become an important area of research, central to a wide range of science and engineering applications. Written by leading experts in the field, Large-scale Inverse Problems and Quantification of Uncertainty focuses on the computational methods used to analyze and simulate inverse problems. The text provides PhD students, researchers, advanced undergraduate students, and engineering practitioners with the perspectives of researchers in areas of inverse problems and data assimilation, ranging from statistics and large-sca

  17. Impact of observational uncertainties on universal scaling of MHD turbulence

    CERN Document Server

    Gogoberidze, G; Hnat, B; Dunlop, M W

    2011-01-01

    Scaling exponents are the central quantitative prediction of theories of turbulence and in-situ satellite observations of the high Reynolds number solar wind flow have provided an extensive testbed of these. We propose a general, instrument independent method to estimate the uncertainty of velocity field fluctuations. We obtain the systematic shift that this uncertainty introduces into the observed spectral exponent. This shift is essential for the correct interpretation of observed scaling exponents. It is sufficient to explain the contradiction between spectral features of the Elsasser fields observed in the solar wind with both theoretical models and numerical simulations of Magnetohydrodynamic turbulence.

  18. On the dominant uncertainty source of climate change projections at the local scale

    Science.gov (United States)

    Fatichi, Simone; Ivanov, Valeriy; Paschalis, Athanasios; Molnar, Peter; Rimkus, Stefan; Kim, Jongho; Peleg, Nadav; Burlando, Paolo; Caporali, Enrica

    2016-04-01

    Decision makers and stakeholders are usually concerned about climate change projections at local spatial scales and fine temporal resolutions. This contrasts with the reliability of climate models, which is typically higher at the global and regional scales, Therefore, there is a demand for advanced methodologies that offer the capability of transferring predictions of climate models and relative uncertainty to scales commensurate with practical applications and for higher order statistics (e.g., few square kilometres and sub-daily scale). A stochastic downscaling technique that makes use of an hourly weather generator (AWE-GEN) and of a Bayesian methodology to weight realizations from different climate models is used to generate local scale meteorological time series of plausible "futures". We computed factors of change from realizations of 32 climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and for different emission scenarios (RCP 4.5 and RCP 8.5). Future climate projections for several meteorological variables (precipitation, air temperature, relative humidity, shortwave radiation) are simulated at three locations characterized by remarkably different climates, Zurich (Switzlerand), Miami and San Francisco (USA). The methodology is designed to partition three main sources of uncertainty: uncertainty due to climate models (model epistemic uncertainty), anthropogenic forcings (scenario uncertainty), and internal climate variability (stochastic uncertainty). The three types of uncertainty sources are considered as dependent, implicitly accounting for possible co-variances among the sources. For air temperature, the magnitude of the different uncertainty sources is comparable for mid-of-the-century projections, while scenario uncertainty dominates at large lead-times. The dominant source of uncertainty for changes in precipitation mean and extremes is internal climate variability, which is accounting for more than 80% of the total

  19. Characterizing Sources of Uncertainty in Item Response Theory Scale Scores

    Science.gov (United States)

    Yang, Ji Seung; Hansen, Mark; Cai, Li

    2012-01-01

    Traditional estimators of item response theory scale scores ignore uncertainty carried over from the item calibration process, which can lead to incorrect estimates of the standard errors of measurement (SEMs). Here, the authors review a variety of approaches that have been applied to this problem and compare them on the basis of their statistical…

  20. Characterizing Sources of Uncertainty in IRT Scale Scores

    Science.gov (United States)

    Yang, Ji Seung; Hansen, Mark; Cai, Li

    2011-01-01

    Traditional estimators of item response theory (IRT) scale scores ignore uncertainty carried over from the item calibration process, which can lead to incorrect estimates of standard errors of measurement (SEM). Here, we review a variety of approaches that have been applied to this problem and compare them on the basis of their statistical methods and goals. We then elaborate on the particular flexibility and usefulness of a Multiple Imputation (MI) based approach, which can be easily applied to tests with mixed item types and multiple underlying dimensions. This proposed method obtains corrected estimates of individual scale scores, as well as their SEM. Furthermore, this approach enables a more complete characterization of the impact of parameter uncertainty by generating confidence envelopes (intervals) for item tracelines, test information functions, conditional SEM curves, and the marginal reliability coefficient. The MI based approach is illustrated through the analysis of an artificial data set, then applied to data from a large educational assessment. A simulation study was also conducted to examine the relative contribution of item parameter uncertainty to the variability in score estimates under various conditions. We found that the impact of item parameter uncertainty is generally quite small, though there are some conditions under which the uncertainty carried over from item calibration contributes substantially to variability in the scores. This may be the case when the calibration sample is small relative to the number of item parameters to be estimated, or when the IRT model fit to the data is multidimensional. PMID:23049139

  1. Uncertainty in Analyzed Water and Energy Budgets at Continental Scales

    Science.gov (United States)

    Bosilovich, Michael G.; Robertson, F. R.; Mocko, D.; Chen, J.

    2011-01-01

    Operational analyses and retrospective-analyses provide all the physical terms of mater and energy budgets, guided by the assimilation of atmospheric observations. However, there is significant reliance on the numerical models, and so, uncertainty in the budget terms is always present. Here, we use a recently developed data set consisting of a mix of 10 analyses (both operational and retrospective) to quantify the uncertainty of analyzed water and energy budget terms for GEWEX continental-scale regions, following the evaluation of Dr. John Roads using individual reanalyses data sets.

  2. Uncertainty Quantification for Large-Scale Ice Sheet Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Ghattas, Omar [Univ. of Texas, Austin, TX (United States)

    2016-02-05

    This report summarizes our work to develop advanced forward and inverse solvers and uncertainty quantification capabilities for a nonlinear 3D full Stokes continental-scale ice sheet flow model. The components include: (1) forward solver: a new state-of-the-art parallel adaptive scalable high-order-accurate mass-conservative Newton-based 3D nonlinear full Stokes ice sheet flow simulator; (2) inverse solver: a new adjoint-based inexact Newton method for solution of deterministic inverse problems governed by the above 3D nonlinear full Stokes ice flow model; and (3) uncertainty quantification: a novel Hessian-based Bayesian method for quantifying uncertainties in the inverse ice sheet flow solution and propagating them forward into predictions of quantities of interest such as ice mass flux to the ocean.

  3. Psychometric Properties of the Intolerance of Uncertainty Scale (IUS in a Lithuanian-speaking population

    Directory of Open Access Journals (Sweden)

    Augustinas Rotomskis

    2014-03-01

    Full Text Available Research suggests that intolerance of uncertainty may be important in understanding worry and may play a key role in the etiology and maintenance of worry. Intolerance of uncertainty is measured using the Intolerance of Uncertainty Scale (IUS, which has been shown to be reliable and valid in many studies. The aim of the present study was to develop a Lithuanian version of this instrument. 228 university students completed the scale. The Lithuanian version of the IUS was found to have good psychometric properties. The IUS showed high internal consistency and good test-retest reliability over a five-week period, and good convergent and divergent validity when assessed with measures of trait anxiety, situational anxiety, and depression. Factor analysis indicated that the IUS has a two-factor structure that represents the beliefs that “uncertainty about the future is unfair” and that “uncertainty has negative behavioral and self-referent implications”. In conclusion, it was found that the Lithuanian version of the IUS is a sound scale for assessing intolerance of uncertainty.

  4. Structural uncertainty in air mass factor calculation for NO

    NARCIS (Netherlands)

    Lorente Delgado, Alba; Folkert Boersma, K.; Yu, Huan; Dörner, Steffen; Hilboll, Andreas; Richter, Andreas; Liu, Mengyao; Lamsal, Lok N.; Barkley, Michael; Smedt, De Isabelle; Roozendael, Van Michel; Wang, Yang; Wagner, Thomas; Beirle, Steffen; Lin, Jin Tai; Krotkov, Nickolay; Stammes, Piet; Wang, Ping; Eskes, Henk J.; Krol, Maarten

    2017-01-01

    Air mass factor (AMF) calculation is the largest source of uncertainty in NO2 and HCHO satellite retrievals in situations with enhanced trace gas concentrations in the lower troposphere. Structural uncertainty arises when different retrieval methodologies are applied within the scientific community

  5. A Wildland Fire Emission Inventory for the Western United States -Uncertainty Across Spatial and Temporal Scales

    Science.gov (United States)

    Urbanski, S. P.; Hao, W.

    2010-12-01

    Emissions of trace gases and aerosols by biomass burning (BB) have a significant influence on the chemical composition of the atmosphere, air quality, and climate. BB emissions depend on a range of variables including burned area, fuels, meteorology, combustion completeness, and emission factors (EF). Emission algorithms provide BB emission inventories (EI) which serve as critical input for Chemical Transport Models (CTM) employed in atmospheric sciences in a wide array of studies. Many different BB EI are commonly used and agreement among these EI is often poor. In general, the sensitivity of the emission estimates to the algorithm components is not well characterized and the performance of most algorithms have not been examined across the scales they are used. Understanding the sensitivity of EI to algorithm component uncertainties is crucial for assessing their impact on CTM simulations. We examine the spatial and temporal sensitivity of BB emission estimates of CO to uncertainties in mapped fuel loading, fuel consumption, burned area and emission factors. The study focuses on wildland fire in the western United States(2003 - 2008). Two fuel loading maps and 2 fuel consumption models provided 4 fuel load consumption emission scenarios with identical burned area and meteorology. The burned area used in the study was mapped using a MODIS burn scar algorithm. The emission algorithm was run at 1-day and 1-km2. Each of the 4 EI was aggregated across multiple spatial (dx= 10 - 200km2) and temporal (dt= 5day - 1yr) scales to evaluate the algorithm sensitivity to scale. At each (dx, dt) the native scale EI of the 4 scenarios were averaged to provide a ‘best estimate’ EI. The uncertainty associated with fuel load consumption (Uflc) was taken as half the range of emissions predicted by the 4 scenarios at each (dx, dt). Estimated uncertainties for the burned area (Ua) and EF (Uef) were combined with Uflc to provide the CO emissions uncertainty (U). The sensitivity of U

  6. Validation and cultural adaptation of a German version of the Physicians' Reactions to Uncertainty scales

    Directory of Open Access Journals (Sweden)

    Joest Katharina

    2007-06-01

    Full Text Available Abstract Background The aim of the study was to examine the validity of a translated and culturally adapted version of the Physicians' Reaction to Uncertainty scales (PRU in primary care physicians. Methods In a structured process, the original questionnaire was translated, culturally adapted and assessed after administering it to 93 GPs. Test-retest reliability was tested by sending the questionnaire to the GPs again after two weeks. Results The principal factor analysis confirmed the postulated four-factor structure underlying the 15 items. In contrast to the original version, item 5 achieved a higher loading on the 'concern about bad outcomes' scale. Consequently, we rearranged the scales. Good item-scale correlations were obtained, with Pearson's correlation coefficient ranging from 0.56–0.84. As regards the item-discriminant validity between the scales 'anxiety due to uncertainty' and 'concern about bad outcomes', partially high correlations (Pearson's correlation coefficient 0.02–0.69; p Conclusion Dealing with uncertainty is an important issue in daily practice. The psychometric properties of the rearranged German version of the PRU are satisfying. The revealed floor effects do not limit the significance of the questionnaire. Thus, the German version of the PRU could contribute to the further evaluation of the impact of uncertainty in primary care physicians.

  7. Spatial precision vs large scale uncertainties in climate change scenario

    Science.gov (United States)

    Dubrovsky, M.; Potuznikova, K.

    2009-04-01

    In assessing climate change impacts on various weather dependent processes, weather series representing changed climate are required as an input to the impact models (for example crop growth models). In producing these series, the weather generator (WG) is often employed: WG parameters are derived from the observed series and then modified using the climate change scenario, which defines changes in the relevant climatic characteristics. These scenarios use to be derived either from GCM or RCM simulations. An advantage of using RCMs (with respect to using GCMs) consists in higher spatial resolution of simulated processes and thereby in higher spatial precision of RCM-based climate change scenario. On the other hand, advantage of using GCM-based scenarios consists in larger number of available GCM simulations, which allows to better account for the uncertainty in larger-scale patterns of climate change. This contribution aims to contribute to the discussion on the usefulness of RCMs in developing the climate change scenarios. To show the significancy of high resolution RCM based spatial signal in changes in relevant climatic characteristics, this signal will be compared with the uncertainty in GCM-simulated larger scale patterns of change. The former RCM-based signal will be derived from the RCM simulations made for the PRUDENCE project, the latter GCM based uncertainty will be based on simulations from a larger number of GCMs. The results will be shown in terms of maps for a whole Europe. Acknowledgements: The study is supported by 6th FP EU research project CECILIA (no GOCE 037005) and GAAV grant agency (project IAA300420806 - "PRASCE").

  8. Methods for estimating uncertainty in factor analytic solutions

    Directory of Open Access Journals (Sweden)

    P. Paatero

    2013-08-01

    Full Text Available EPA PMF version 5.0 and the underlying multilinear engine executable ME-2 contain three methods for estimating uncertainty in factor analytic models: classical bootstrap (BS, displacement of factor elements (DISP, and bootstrap enhanced by displacement of factor elements (BS-DISP. The goal of these methods is to capture the uncertainty of PMF analyses due to random errors and rotational ambiguity. It is shown that the three methods complement each other: depending on characteristics of the data set, one method may provide better results than the other two. Results are presented using synthetic data sets, including interpretation of diagnostics, and recommendations are given for parameters to report when documenting uncertainty estimates from EPA PMF or ME-2 applications.

  9. Pore-scale uncertainty quantification with multilevel Monte Carlo

    KAUST Repository

    Icardi, Matteo

    2014-01-06

    Computational fluid dynamics (CFD) simulations of pore-scale transport processes in porous media have recently gained large popularity. However the geometrical details of the pore structures can be known only in a very low number of samples and the detailed flow computations can be carried out only on a limited number of cases. The explicit introduction of randomness in the geometry and in other setup parameters can be crucial for the optimization of pore-scale investigations for random homogenization. Since there are no generic ways to parametrize the randomness in the porescale structures, Monte Carlo techniques are the most accessible to compute statistics. We propose a multilevel Monte Carlo (MLMC) technique to reduce the computational cost of estimating quantities of interest within a prescribed accuracy constraint. Random samples of pore geometries with a hierarchy of geometrical complexities and grid refinements, are synthetically generated and used to propagate the uncertainties in the flow simulations and compute statistics of macro-scale effective parameters.

  10. Optimal management of large scale aquifers under uncertainty

    Science.gov (United States)

    Ghorbanidehno, H.; Kokkinaki, A.; Kitanidis, P. K.; Darve, E. F.

    2016-12-01

    Water resources systems, and especially groundwater reservoirs, are a valuable resource that is often being endangered by contamination and over-exploitation. Optimal control techniques can be applied for groundwater management to ensure the long-term sustainability of this vulnerable resource. Linear Quadratic Gaussian (LQG) control is an optimal control method that combines a Kalman filter for real time estimation with a linear quadratic regulator for dynamic optimization. The LQG controller can be used to determine the optimal controls (e.g. pumping schedule) upon receiving feedback about the system from incomplete noisy measurements. However, applying LQG control for systems of large dimension is computationally expensive. This work presents the Spectral Linear Quadratic Gaussian (SpecLQG) control, a new fast LQG controller that can be used for large scale problems. SpecLQG control combines the Spectral Kalman filter, which is a fast Kalman filter algorithm, with an efficient low rank LQR, and provides a practical approach for combined monitoring, parameter estimation, uncertainty quantification and optimal control for linear and weakly non-linear systems. The computational cost of SpecLQG controller scales linearly with the number of unknowns, a great improvement compared to the quadratic cost of basic LQG. We demonstrate the accuracy and computational efficiency of SpecLQG control using two applications: first, a linear validation case for pumping schedule management in a small homogeneous confined aquifer; and second, a larger scale nonlinear case with unknown heterogeneities in aquifer properties and boundary conditions.

  11. Evaluation of peaking factors uncertainty for CASMO-3

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Kang Suk; Song, Jae Seung; Kim, Yong Rae; Ji, Seong Kyun [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1996-02-01

    This document evaluates the pin-to-box factor uncertainty based on using the CASMO-3 with 40-group J-library. Five CE criticals performed by Westinghouse, two by B and W and four RPI criticals were analyzed, using cross sections by CASMO-3. DOT was used for the core calculation. THis is one hof series of efforts to verify ADONIS procedure which is a new core design package under development by KAERI. The expected outcome of this analysis is CASMO-3 pin peak uncertainty applicable to CE type fuel assembly design. The evaluated uncertainty of peaking factors for CASMO-3 was 1.863%. 21 tabs., 23 figs., 12 refs. (Author) .new.

  12. Uncertainty and sensitivity analysis of fission gas behavior in engineering-scale fuel modeling

    Energy Technology Data Exchange (ETDEWEB)

    Pastore, Giovanni, E-mail: Giovanni.Pastore@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Swiler, L.P., E-mail: LPSwile@sandia.gov [Optimization and Uncertainty Quantification, Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185-1318 (United States); Hales, J.D., E-mail: Jason.Hales@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Novascone, S.R., E-mail: Stephen.Novascone@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Perez, D.M., E-mail: Danielle.Perez@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Spencer, B.W., E-mail: Benjamin.Spencer@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Luzzi, L., E-mail: Lelio.Luzzi@polimi.it [Politecnico di Milano, Department of Energy, Nuclear Engineering Division, via La Masa 34, I-20156 Milano (Italy); Van Uffelen, P., E-mail: Paul.Van-Uffelen@ec.europa.eu [European Commission, Joint Research Centre, Institute for Transuranium Elements, Hermann-von-Helmholtz-Platz 1, D-76344 Karlsruhe (Germany); Williamson, R.L., E-mail: Richard.Williamson@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States)

    2015-01-15

    The role of uncertainties in fission gas behavior calculations as part of engineering-scale nuclear fuel modeling is investigated using the BISON fuel performance code with a recently implemented physics-based model for fission gas release and swelling. Through the integration of BISON with the DAKOTA software, a sensitivity analysis of the results to selected model parameters is carried out based on UO{sub 2} single-pellet simulations covering different power regimes. The parameters are varied within ranges representative of the relative uncertainties and consistent with the information in the open literature. The study leads to an initial quantitative assessment of the uncertainty in fission gas behavior predictions with the parameter characterization presently available. Also, the relative importance of the single parameters is evaluated. Moreover, a sensitivity analysis is carried out based on simulations of a fuel rod irradiation experiment, pointing out a significant impact of the considered uncertainties on the calculated fission gas release and cladding diametral strain. The results of the study indicate that the commonly accepted deviation between calculated and measured fission gas release by a factor of 2 approximately corresponds to the inherent modeling uncertainty at high fission gas release. Nevertheless, significantly higher deviations may be expected for values around 10% and lower. Implications are discussed in terms of directions of research for the improved modeling of fission gas behavior for engineering purposes.

  13. General Analyzing and Research on Uncertainty of Multi-Scale Representation for Street-Block Settlement

    Science.gov (United States)

    Xu, F.; Niu, J.; Chi, Z.; Xie, W.

    2013-05-01

    Analyzing and evaluating the reliability of multi-scale representation of spatial data are already becoming an important issue of the current digital cartography and GIS. Settlement place is the main content of maps. For this reason, studying on the uncertainty of multi-scale representation of settlement place is one of important contents of the uncertainty of multi-scale representation of spatial data. In this paper, uncertainty of multi-scale representation of street-block settlement was get comprehensive analysis and system research. This paper holds that map generalization is the essential cause leading to uncertainty of multi-scale representation of streetblock settlement. First, it is explored of essence and types of uncertainty on multi-scale representation of street-block settlement, and it divides these uncertainties into four large classes and seven subclasses. Second, among all kinds of uncertainties of multi-scale representation of street-block settlement, this paper mainly studies the uncertainty of settlement of street-block symbolic representation, and establishes the evaluation content and evaluation indexes and computing method of uncertainty of street-block and street network generalization and building generalization. The result can use for evaluating the good and bad of scale transfer methods and the uncertainty of products of multi-scale representation of street-block settlement.

  14. Evaluating the uncertainty of predicting future climate time series at the hourly time scale

    Science.gov (United States)

    Caporali, E.; Fatichi, S.; Ivanov, V. Y.

    2011-12-01

    A stochastic downscaling methodology is developed to generate hourly, point-scale time series for several meteorological variables, such as precipitation, cloud cover, shortwave radiation, air temperature, relative humidity, wind speed, and atmospheric pressure. The methodology uses multi-model General Circulation Model (GCM) realizations and an hourly weather generator, AWE-GEN. Probabilistic descriptions of factors of change (a measure of climate change with respect to historic conditions) are computed for several climate statistics and different aggregation times using a Bayesian approach that weights the individual GCM contributions. The Monte Carlo method is applied to sample the factors of change from their respective distributions thereby permitting the generation of time series in an ensemble fashion, which reflects the uncertainty of climate projections of future as well as the uncertainty of the downscaling procedure. Applications of the methodology and probabilistic expressions of certainty in reproducing future climates for the periods, 2000 - 2009, 2046 - 2065 and 2081 - 2100, using the 1962 - 1992 period as the baseline, are discussed for the location of Firenze (Italy). The climate predictions for the period of 2000 - 2009 are tested against observations permitting to assess the reliability and uncertainties of the methodology in reproducing statistics of meteorological variables at different time scales.

  15. Measurement of backscatter factor for diagnostic radiology: methodology and uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Rosado, P.H.G.; Nogueira, M.D.S.; Squair, P.L.; Da Silva, T.A. [Centro de Desenvolvimento da Tecnoogia Nuclear (CDTN/CNEN) 30123-970, Minas Gerais (Brazil)]. e-mail: phgr@cdtn.br

    2007-07-01

    Full text: Backscatter factors were experimentally determined for the diagnostic X-ray qualities recommended by the International Electrotechnical Commission (IEC) for primary beams (RQR). Harshaw LiF-1 100H thermoluminescent dosemeters used for determining the backscatter were calibrated against an ionization chamber traceable to the National Metrology Laboratory. A 300mm x 300mm x 150mm PMMA slab phantom was used for deep-doses measurements. To perform the in-phantom measurements, the dosemeters were placed in the central axis of the x-ray beam at five different depths d in the phantom (5, 10, 15, 25 and 35 mm) upstream the beam direction. The typical combined standard uncertainty of the backscatter factor value was 6%. The main sources of uncertainties were the calibration procedure, the TLD dosimetry and the use of deep-dose curves. (Author)

  16. Simulating space-time uncertainty in continental-scale gridded precipitation fields for agrometeorological modelling

    NARCIS (Netherlands)

    Wit, de A.J.W.; Bruin, de S.

    2006-01-01

    Previous analyses of the effects of uncertainty in precipitation fields on the output of EU Crop Growth Monitoring System (CGMS) demonstrated that the influence on simulated crop yield was limited at national scale, but considerable at local and regional scales. We aim to propagate uncertainty due t

  17. Uncertainty analysis for a field-scale P loss model

    Science.gov (United States)

    Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study we assessed the effect of model input error on predic...

  18. Uncertainty quantification for large-scale ocean circulation predictions.

    Energy Technology Data Exchange (ETDEWEB)

    Safta, Cosmin; Debusschere, Bert J.; Najm, Habib N.; Sargsyan, Khachik

    2010-09-01

    Uncertainty quantificatio in climate models is challenged by the sparsity of the available climate data due to the high computational cost of the model runs. Another feature that prevents classical uncertainty analyses from being easily applicable is the bifurcative behavior in the climate data with respect to certain parameters. A typical example is the Meridional Overturning Circulation in the Atlantic Ocean. The maximum overturning stream function exhibits discontinuity across a curve in the space of two uncertain parameters, namely climate sensitivity and CO{sub 2} forcing. We develop a methodology that performs uncertainty quantificatio in the presence of limited data that have discontinuous character. Our approach is two-fold. First we detect the discontinuity location with a Bayesian inference, thus obtaining a probabilistic representation of the discontinuity curve location in presence of arbitrarily distributed input parameter values. Furthermore, we developed a spectral approach that relies on Polynomial Chaos (PC) expansions on each sides of the discontinuity curve leading to an averaged-PC representation of the forward model that allows efficient uncertainty quantification and propagation. The methodology is tested on synthetic examples of discontinuous data with adjustable sharpness and structure.

  19. On the predictivity of pore-scale simulations: Estimating uncertainties with multilevel Monte Carlo

    Science.gov (United States)

    Icardi, Matteo; Boccardo, Gianluca; Tempone, Raúl

    2016-09-01

    A fast method with tunable accuracy is proposed to estimate errors and uncertainties in pore-scale and Digital Rock Physics (DRP) problems. The overall predictivity of these studies can be, in fact, hindered by many factors including sample heterogeneity, computational and imaging limitations, model inadequacy and not perfectly known physical parameters. The typical objective of pore-scale studies is the estimation of macroscopic effective parameters such as permeability, effective diffusivity and hydrodynamic dispersion. However, these are often non-deterministic quantities (i.e., results obtained for specific pore-scale sample and setup are not totally reproducible by another "equivalent" sample and setup). The stochastic nature can arise due to the multi-scale heterogeneity, the computational and experimental limitations in considering large samples, and the complexity of the physical models. These approximations, in fact, introduce an error that, being dependent on a large number of complex factors, can be modeled as random. We propose a general simulation tool, based on multilevel Monte Carlo, that can reduce drastically the computational cost needed for computing accurate statistics of effective parameters and other quantities of interest, under any of these random errors. This is, to our knowledge, the first attempt to include Uncertainty Quantification (UQ) in pore-scale physics and simulation. The method can also provide estimates of the discretization error and it is tested on three-dimensional transport problems in heterogeneous materials, where the sampling procedure is done by generation algorithms able to reproduce realistic consolidated and unconsolidated random sphere and ellipsoid packings and arrangements. A totally automatic workflow is developed in an open-source code [1], that include rigid body physics and random packing algorithms, unstructured mesh discretization, finite volume solvers, extrapolation and post-processing techniques. The

  20. On the predictivity of pore-scale simulations: estimating uncertainties with multilevel Monte Carlo

    KAUST Repository

    Icardi, Matteo

    2016-02-08

    A fast method with tunable accuracy is proposed to estimate errors and uncertainties in pore-scale and Digital Rock Physics (DRP) problems. The overall predictivity of these studies can be, in fact, hindered by many factors including sample heterogeneity, computational and imaging limitations, model inadequacy and not perfectly known physical parameters. The typical objective of pore-scale studies is the estimation of macroscopic effective parameters such as permeability, effective diffusivity and hydrodynamic dispersion. However, these are often non-deterministic quantities (i.e., results obtained for specific pore-scale sample and setup are not totally reproducible by another “equivalent” sample and setup). The stochastic nature can arise due to the multi-scale heterogeneity, the computational and experimental limitations in considering large samples, and the complexity of the physical models. These approximations, in fact, introduce an error that, being dependent on a large number of complex factors, can be modeled as random. We propose a general simulation tool, based on multilevel Monte Carlo, that can reduce drastically the computational cost needed for computing accurate statistics of effective parameters and other quantities of interest, under any of these random errors. This is, to our knowledge, the first attempt to include Uncertainty Quantification (UQ) in pore-scale physics and simulation. The method can also provide estimates of the discretization error and it is tested on three-dimensional transport problems in heterogeneous materials, where the sampling procedure is done by generation algorithms able to reproduce realistic consolidated and unconsolidated random sphere and ellipsoid packings and arrangements. A totally automatic workflow is developed in an open-source code [2015. https://bitbucket.org/micardi/porescalemc.], that include rigid body physics and random packing algorithms, unstructured mesh discretization, finite volume solvers

  1. Lorentz invariance, nonzero minimal uncertainty in position, and inhomogeneity of space at the Planck scale

    CERN Document Server

    Bose, Arko

    2010-01-01

    The suspicion that the existence of a minimal uncertainty in position measurements violates Lorentz invariance seems unfounded. It is shown that the existence of such a nonzero minimal uncertainty in position is not only consistent with Lorentz invariance, but that the latter also fixes the algebra between position and momentum which gives rise to this minimal uncertainty. We also investigate how this algebra affects the underlying quantum mechanical structure, and why, at the Planck scale, space can no longer be considered homogeneous.

  2. Impact Assessment of Uncertainty Propagation of Ensemble NWP Rainfall to Flood Forecasting with Catchment Scale

    OpenAIRE

    Wansik Yu; Eiichi Nakakita; Sunmin Kim; Kosei Yamaguchi

    2016-01-01

    The common approach to quantifying the precipitation forecast uncertainty is ensemble simulations where a numerical weather prediction (NWP) model is run for a number of cases with slightly different initial conditions. In practice, the spread of ensemble members in terms of flood discharge is used as a measure of forecast uncertainty due to uncertain precipitation forecasts. This study presents the uncertainty propagation of rainfall forecast into hydrological response with catchment scale t...

  3. Developing scales measuring disorder-specific intolerance of uncertainty (DSIU) : a new perspective on transdiagnostic

    NARCIS (Netherlands)

    Thibodeau, Michel A; Carleton, R Nicholas; McEvoy, Peter M; Zvolensky, Michael J; Brandt, Charles P; Boelen, Paul A; Mahoney, Alison E J; Deacon, Brett J; Asmundson, Gordon J G

    2015-01-01

    Intolerance of uncertainty (IU) is a construct of growing prominence in literature on anxiety disorders and major depressive disorder. Existing measures of IU do not define the uncertainty that respondents perceive as distressing. To address this limitation, we developed eight scales measuring disor

  4. Towards national-scale greenhouse gas emissions evaluation with robust uncertainty estimates

    Science.gov (United States)

    Rigby, Matthew; Swallow, Ben; Lunt, Mark; Manning, Alistair; Ganesan, Anita; Stavert, Ann; Stanley, Kieran; O'Doherty, Simon

    2016-04-01

    Through the Deriving Emissions related to Climate Change (DECC) network and the Greenhouse gAs Uk and Global Emissions (GAUGE) programme, the UK's greenhouse gases are now monitored by instruments mounted on telecommunications towers and churches, on a ferry that performs regular transects of the North Sea, on-board a research aircraft and from space. When combined with information from high-resolution chemical transport models such as the Met Office Numerical Atmospheric dispersion Modelling Environment (NAME), these measurements are allowing us to evaluate emissions more accurately than has previously been possible. However, it has long been appreciated that current methods for quantifying fluxes using atmospheric data suffer from uncertainties, primarily relating to the chemical transport model, that have been largely ignored to date. Here, we use novel model reduction techniques for quantifying the influence of a set of potential systematic model errors on the outcome of a national-scale inversion. This new technique has been incorporated into a hierarchical Bayesian framework, which can be shown to reduce the influence of subjective choices on the outcome of inverse modelling studies. Using estimates of the UK's methane emissions derived from DECC and GAUGE tall-tower measurements as a case study, we will show that such model systematic errors have the potential to significantly increase the uncertainty on national-scale emissions estimates. Therefore, we conclude that these factors must be incorporated in national emissions evaluation efforts, if they are to be credible.

  5. ATLAS Calorimeter Response to Single Isolated Hadrons and Estimation of the Calorimeter Jet Scale Uncertainty

    CERN Document Server

    The ATLAS collaboration

    2011-01-01

    The ATLAS calorimeter response to single isolated hadrons is measured using an integrated luminosity of approximately 866~$mu b^{-1}$ of proton-proton collisions at a center-of-mass energy of $\\sqrt{s} = 7$ TeV collected during 2010 by the ATLAS experiment. The calorimeter jet energy scale uncertainty is also addressed, propagating the response uncertainty of single charged and neutral particles to jets. The calorimeter uncertainty is 2--5\\% on central isolated hadrons and 1--3\\% on the final calorimeter jet energy scale.

  6. Scaling of the local quantum uncertainty at quantum phase transitions

    Energy Technology Data Exchange (ETDEWEB)

    Coulamy, I.B.; Warnes, J.H.; Sarandy, M.S., E-mail: msarandy@if.uff.br; Saguia, A.

    2016-04-29

    We investigate the local quantum uncertainty (LQU) between a block of L qubits and one single qubit in a composite system of n qubits driven through a quantum phase transition (QPT). A first-order QPT is analytically considered through a Hamiltonian implementation of the quantum search. In the case of second-order QPTs, we consider the transverse-field Ising chain via a numerical analysis through density matrix renormalization group. For both cases, we compute the LQU for finite-sizes as a function of L and of the coupling parameter, analyzing its pronounced behavior at the QPT. - Highlights: • LQU is suitable for the analysis of block correlations. • LQU exhibits pronounced behavior at quantum phase transitions. • LQU exponentially saturates in the quantum search. • Concavity of LQU indicates criticality in the Ising chain.

  7. Quantification of Uncertainty in Extreme Scale Computations (QUEST)

    Energy Technology Data Exchange (ETDEWEB)

    Ghanem, Roger [Univ. of Southern California, Los Angeles, CA (United States)

    2017-04-18

    QUEST was a SciDAC Institute comprising Sandia National Laboratories, Los Alamos National Laboratory, the University of Southern California, the Massachusetts Institute of Technology, the University of Texas at Austin, and Duke University. The mission of QUEST is to: (1) develop a broad class of uncertainty quantification (UQ) methods/tools, and (2) provide UQ expertise and software to other SciDAC projects, thereby enabling/guiding their UQ activities. The USC effort centered on the development of reduced models and efficient algorithms for implementing various components of the UQ pipeline. USC personnel were responsible for the development of adaptive bases, adaptive quadrature, and reduced models to be used in estimation and inference.

  8. Quantifying the uncertainties of China's emission inventory for industrial sources: From national to provincial and city scales

    Science.gov (United States)

    Zhao, Yu; Zhou, Yaduan; Qiu, Liping; Zhang, Jie

    2017-09-01

    A comprehensive uncertainty analysis was conducted on emission inventories for industrial sources at national (China), provincial (Jiangsu), and city (Nanjing) scales for 2012. Based on various methods and data sources, Monte-Carlo simulation was applied at sector level for national inventory, and at plant level (whenever possible) for provincial and city inventories. The uncertainties of national inventory were estimated at -17-37% (expressed as 95% confidence intervals, CIs), -21-35%, -19-34%, -29-40%, -22-47%, -21-54%, -33-84%, and -32-92% for SO2, NOX, CO, TSP (total suspended particles), PM10, PM2.5, black carbon (BC), and organic carbon (OC) emissions respectively for the whole country. At provincial and city levels, the uncertainties of corresponding pollutant emissions were estimated at -15-18%, -18-33%, -16-37%, -20-30%, -23-45%, -26-50%, -33-79%, and -33-71% for Jiangsu, and -17-22%, -10-33%, -23-75%, -19-36%, -23-41%, -28-48%, -45-82%, and -34-96% for Nanjing, respectively. Emission factors (or associated parameters) were identified as the biggest contributors to the uncertainties of emissions for most source categories except iron & steel production in the national inventory. Compared to national one, uncertainties of total emissions in the provincial and city-scale inventories were not significantly reduced for most species with an exception of SO2. For power and other industrial boilers, the uncertainties were reduced, and the plant-specific parameters played more important roles to the uncertainties. Much larger PM10 and PM2.5 emissions for Jiangsu were estimated in this provincial inventory than other studies, implying the big discrepancies on data sources of emission factors and activity data between local and national inventories. Although the uncertainty analysis of bottom-up emission inventories at national and local scales partly supported the ;top-down; estimates using observation and/or chemistry transport models, detailed investigations and

  9. How uncertainty in socio-economic variables affects large-scale transport model forecasts

    DEFF Research Database (Denmark)

    Manzo, Stefano; Nielsen, Otto Anker; Prato, Carlo Giacomo

    2015-01-01

    A strategic task assigned to large-scale transport models is to forecast the demand for transport over long periods of time to assess transport projects. However, by modelling complex systems transport models have an inherent uncertainty which increases over time. As a consequence, the longer...... time, especially with respect to large-scale transport models. The study described in this paper contributes to fill the gap by investigating the effects of uncertainty in socio-economic variables growth rate projections on large-scale transport model forecasts, using the Danish National Transport...... the period forecasted the less reliable is the forecasted model output. Describing uncertainty propagation patterns over time is therefore important in order to provide complete information to the decision makers. Among the existing literature only few studies analyze uncertainty propagation patterns over...

  10. Impact Assessment of Uncertainty Propagation of Ensemble NWP Rainfall to Flood Forecasting with Catchment Scale

    Directory of Open Access Journals (Sweden)

    Wansik Yu

    2016-01-01

    Full Text Available The common approach to quantifying the precipitation forecast uncertainty is ensemble simulations where a numerical weather prediction (NWP model is run for a number of cases with slightly different initial conditions. In practice, the spread of ensemble members in terms of flood discharge is used as a measure of forecast uncertainty due to uncertain precipitation forecasts. This study presents the uncertainty propagation of rainfall forecast into hydrological response with catchment scale through distributed rainfall-runoff modeling based on the forecasted ensemble rainfall of NWP model. At first, forecast rainfall error based on the BIAS is compared with flood forecast error to assess the error propagation. Second, the variability of flood forecast uncertainty according to catchment scale is discussed using ensemble spread. Then we also assess the flood forecast uncertainty with catchment scale using an estimation regression equation between ensemble rainfall BIAS and discharge BIAS. Finally, the flood forecast uncertainty with RMSE using specific discharge in catchment scale is discussed. Our study is carried out and verified using the largest flood event by typhoon “Talas” of 2011 over the 33 subcatchments of Shingu river basin (2,360 km2, which is located in the Kii Peninsula, Japan.

  11. Quantifying measurement uncertainty in full-scale compost piles using organic micro-pollutant concentrations.

    Science.gov (United States)

    Sadef, Yumna; Poulsen, Tjalfe G; Bester, Kai

    2014-05-01

    Reductions in measurement uncertainty for organic micro-pollutant concentrations in full scale compost piles using comprehensive sampling and allowing equilibration time before sampling were quantified. Results showed that both application of a comprehensive sampling procedure (involving sample crushing) and allowing one week of equilibration time before sampling reduces measurement uncertainty by about 50%. Results further showed that for measurements carried out on samples collected using a comprehensive procedure, measurement uncertainty was associated exclusively with the analytic methods applied. Application of statistical analyses confirmed that these results were significant at the 95% confidence level. Overall implications of these results are (1) that it is possible to eliminate uncertainty associated with material inhomogeneity and (2) that in order to reduce uncertainty, sampling procedure is very important early in the composting process but less so later in the process.

  12. TSUNAMI Primer: A Primer for Sensitivity/Uncertainty Calculations with SCALE

    Energy Technology Data Exchange (ETDEWEB)

    Rearden, Bradley T [ORNL; Mueller, Don [ORNL; Bowman, Stephen M [ORNL; Busch, Robert D. [University of New Mexico, Albuquerque; Emerson, Scott [University of New Mexico, Albuquerque

    2009-01-01

    This primer presents examples in the application of the SCALE/TSUNAMI tools to generate k{sub eff} sensitivity data for one- and three-dimensional models using TSUNAMI-1D and -3D and to examine uncertainties in the computed k{sub eff} values due to uncertainties in the cross-section data used in their calculation. The proper use of unit cell data and need for confirming the appropriate selection of input parameters through direct perturbations are described. The uses of sensitivity and uncertainty data to identify and rank potential sources of computational bias in an application system and TSUNAMI tools for assessment of system similarity using sensitivity and uncertainty criteria are demonstrated. Uses of these criteria in trending analyses to assess computational biases, bias uncertainties, and gap analyses are also described. Additionally, an application of the data adjustment tool TSURFER is provided, including identification of specific details of sources of computational bias.

  13. Theoretical uncertainty of the supersymmetric dark matter relic density from scheme and scale variations

    Science.gov (United States)

    Harz, J.; Herrmann, B.; Klasen, M.; Kovařík, K.; Steppeler, P.

    2016-06-01

    For particle physics observables at colliders such as the LHC at CERN, it has been common practice for many decades to estimate the theoretical uncertainty by studying the variations of the predicted cross sections with a priori unpredictable scales. In astroparticle physics, this has so far not been possible, since most of the observables were calculated at Born level only, so that the renormalization scheme and scale dependence could not be studied in a meaningful way. In this paper, we present the first quantitative study of the theoretical uncertainty of the neutralino dark matter relic density from scheme and scale variations. We first explain in detail how the renormalization scale enters the tree-level calculations through coupling constants, masses and mixing angles. We then demonstrate a reduction of the renormalization scale dependence through one-loop SUSY-QCD corrections in many different dark matter annihilation channels and enhanced perturbative stability of a mixed on-shell /DR ¯ renormalization scheme over a pure DR ¯ scheme in the top-quark sector. In the stop-stop annihilation channel, the Sommerfeld enhancement and its scale dependence are shown to be of particular importance. Finally, the impact of our higher-order SUSY-QCD corrections and their scale uncertainties are studied in three typical scenarios of the phenomenological minimal supersymmetric standard model with eleven parameters (pMSSM-11). We find that the theoretical uncertainty is reduced in many cases and can become comparable to the size of the experimental one in some scenarios.

  14. Planning under uncertainty solving large-scale stochastic linear programs

    Energy Technology Data Exchange (ETDEWEB)

    Infanger, G. (Stanford Univ., CA (United States). Dept. of Operations Research Technische Univ., Vienna (Austria). Inst. fuer Energiewirtschaft)

    1992-12-01

    For many practical problems, solutions obtained from deterministic models are unsatisfactory because they fail to hedge against certain contingencies that may occur in the future. Stochastic models address this shortcoming, but up to recently seemed to be intractable due to their size. Recent advances both in solution algorithms and in computer technology now allow us to solve important and general classes of practical stochastic problems. We show how large-scale stochastic linear programs can be efficiently solved by combining classical decomposition and Monte Carlo (importance) sampling techniques. We discuss the methodology for solving two-stage stochastic linear programs with recourse, present numerical results of large problems with numerous stochastic parameters, show how to efficiently implement the methodology on a parallel multi-computer and derive the theory for solving a general class of multi-stage problems with dependency of the stochastic parameters within a stage and between different stages.

  15. Event-scale power law recession analysis: quantifying methodological uncertainty

    Science.gov (United States)

    Dralle, David N.; Karst, Nathaniel J.; Charalampous, Kyriakos; Veenstra, Andrew; Thompson, Sally E.

    2017-01-01

    The study of single streamflow recession events is receiving increasing attention following the presentation of novel theoretical explanations for the emergence of power law forms of the recession relationship, and drivers of its variability. Individually characterizing streamflow recessions often involves describing the similarities and differences between model parameters fitted to each recession time series. Significant methodological sensitivity has been identified in the fitting and parameterization of models that describe populations of many recessions, but the dependence of estimated model parameters on methodological choices has not been evaluated for event-by-event forms of analysis. Here, we use daily streamflow data from 16 catchments in northern California and southern Oregon to investigate how combinations of commonly used streamflow recession definitions and fitting techniques impact parameter estimates of a widely used power law recession model. Results are relevant to watersheds that are relatively steep, forested, and rain-dominated. The highly seasonal mediterranean climate of northern California and southern Oregon ensures study catchments explore a wide range of recession behaviors and wetness states, ideal for a sensitivity analysis. In such catchments, we show the following: (i) methodological decisions, including ones that have received little attention in the literature, can impact parameter value estimates and model goodness of fit; (ii) the central tendencies of event-scale recession parameter probability distributions are largely robust to methodological choices, in the sense that differing methods rank catchments similarly according to the medians of these distributions; (iii) recession parameter distributions are method-dependent, but roughly catchment-independent, such that changing the choices made about a particular method affects a given parameter in similar ways across most catchments; and (iv) the observed correlative relationship

  16. Theoretical uncertainty of the supersymmetric dark matter relic density from scheme and scale variations

    CERN Document Server

    Harz, J; Klasen, M; Kovarik, K; Steppeler, P

    2016-01-01

    For particle physics observables at colliders such as the LHC at CERN, it has been common practice for many decades to estimate the theoretical uncertainty by studying the variations of the predicted cross sections with a priori unpredictable scales. In astroparticle physics, this has so far not been possible, since most of the observables were calculated at Born level only, so that the renormalization scheme and scale dependence could not be studied in a meaningful way. In this paper, we present the first quantitative study of the theoretical uncertainty of the neutralino dark matter relic density from scheme and scale variations. We first explain in detail how the renormalization scale enters the tree-level calculations through coupling constants, masses and mixing angles. We then demonstrate a reduction of the renormalization scale dependence through one-loop SUSY-QCD corrections in many different dark matter annihilation channels and enhanced perturbative stability of a mixed on-shell/$\\bar{\\rm DR}$ renor...

  17. Multi-Scale Fusion of Information for Uncertainty Quantification and Management in Large-Scale Simulations

    Science.gov (United States)

    2015-12-02

    of completely new nonlinear Malliavin calculus . This type of calculus is important for the analysis and simulation of stationary and/or “causal...under uncertainty. We tested new developments on nonlinear Malliavin calculus , combining reduced basis methods with ANOVA, model validation, on... DOI :10.1137/140996495 3. H. Cho, X. Yang, D. Venturi and G.E. Karniadakis, Algorithms for propagating uncertainty across heterogeneous domains

  18. Quantitative Evaluation Research on Uncertainty Factors in Production Scheduling of Manufacturing Enterprises

    Institute of Scientific and Technical Information of China (English)

    WU Bo; SHI Guoxin; DING Yufeng; JIANG Zhengfeng

    2006-01-01

    Shop scheduling problem is core part and research hot in modern manufacture system, it has important meaning for decreasing operating costs, shortening production period and so on. Based on shop scheduling problems, this paper mainly discuss and classify uncertainty factors of the shop scheduling, Meanwhile set up corresponding reliability evaluation model according to some uncertainty factors, and so it can better direct shop scheduling.

  19. On the Scale Uncertainties in the $B \\to X_s \\gamma$ Decay

    CERN Document Server

    Buras, Andrzej J; Pott, N; Buras, Andrzej J.; Kwiatkowski, Axel; Pott, Nicolas

    1997-01-01

    We analyze the theoretical uncertainties in $Br(B\\to X_s\\gamma)$ due to the choice of the high energy matching scale $\\mu_W=\\ord(\\mw)$ and the scale end we have repeated the calculation of the initial conditions confirming the final results of Adel and Yao and Greub and Hurth and generalizing them to include the dependences on $\\mu_t$ and $\\mu_W$ with $\\mu_t\

  20. Water quality modeling under hydrologic variability and parameter uncertainty using erosion-scaled export coefficients

    Science.gov (United States)

    Khadam, Ibrahim M.; Kaluarachchi, Jagath J.

    2006-10-01

    SummaryWater quality modeling is important to assess the health of a watershed and to make necessary management decisions to control existing and future pollution of receiving water bodies. The existing export coefficient approach is attractive due to minimum data requirements; however, this method does not account for hydrologic variability. In this paper, an erosion-scaled export coefficient approach is proposed that can model and explain the hydrologic variability in predicting the annual phosphorus (P) loading to the receiving stream. Here sediment discharge was introduced into the export coefficient model as a surrogate for hydrologic variability. Application of this approach to model P in the Fishtrap Creek of Washington State showed the superiority of this approach compared to the traditional export coefficient approach, while maintaining its simplicity and low data requirement characteristics. In addition, a Bayesian framework is proposed to assess the parameter uncertainty of the export coefficient method instead of subjective assignment of uncertainty. This work also showed through a joint variability-uncertainty analysis the importance of separate consideration of hydrologic variability and parameter uncertainty, as these represent two independent and important characteristics of the overall model uncertainty. The paper also recommends the use of a longitudinal data collection scheme to reduce the uncertainty in export coefficients.

  1. Sensitivity Analysis and Insights into Hydrological Processes and Uncertainty at Different Scales

    Science.gov (United States)

    Haghnegahdar, A.; Razavi, S.; Wheater, H. S.; Gupta, H. V.

    2015-12-01

    Sensitivity analysis (SA) is an essential tool for providing insight into model behavior, and conducting model calibration and uncertainty assessment. Numerous techniques have been used in environmental modelling studies for sensitivity analysis. However, it is often overlooked that the scale of modelling study, and the metric choice can significantly change the assessment of model sensitivity and uncertainty. In order to identify important hydrological processes across various scales, we conducted a multi-criteria sensitivity analysis using a novel and efficient technique, Variogram Analysis of Response Surfaces (VARS). The analysis was conducted using three different hydrological models, HydroGeoSphere (HGS), Soil and Water Assessment Tool (SWAT), and Modélisation Environmentale-Surface et Hydrologie (MESH). Models were applied at various scales ranging from small (hillslope) to large (watershed) scales. In each case, the sensitivity of simulated streamflow to model processes (represented through parameters) were measured using different metrics selected based on various hydrograph characteristics such as high flows, low flows, and volume. We demonstrate how the scale of the case study and the choice of sensitivity metric(s) can change our assessment of sensitivity and uncertainty. We present some guidelines to better align the metric choice with the objective and scale of a modelling study.

  2. High-pT Jet Energy Scale Uncertainty from single hadron response with the ATLAS detector

    CERN Document Server

    Poulsen, Trine; The ATLAS collaboration

    2016-01-01

    The jet energy scale (JES) uncertainty is estimated using different methods at different p$_\\text{T}$ ranges. In-situ techniques exploiting the p$_\\text{T}$ balance between a jet and a reference object (e.g. Z or gamma) are used at lower p$_\\text{T}$, but at very high p$_\\text{T}$ (> 2.5 TeV) there is not enough statistics for such in-situ techniques. A low JES uncertainty at high-p$_\\text{T}$ is important in several searches for new phenomena, e.g. the dijet resonance and angular searches. In the highest p$_\\text{T}$ range, the JES uncertainty is estimated using the calorimeter response to single hadrons. In this method, jets are treated as a superposition of energy depositions of single particles. An uncertainty is applied to each energy deposition belonging to the particles within the jet, and propagated to the final jet energy scale. This poster presents the JES uncertainty found with this method at sqrt(s) = 8 TeV and its developments.

  3. A generalised framework for large-scale evaluation of discharge uncertainties across England and Wales

    Science.gov (United States)

    Coxon, Gemma; Freer, Jim; Westerberg, Ida; Woods, Ross; Smith, Paul; Wagener, Thorsten

    2014-05-01

    Benchmarking the information content and quality of discharge data in England and Wales is essential for analyses of catchment behaviour and modelling results for research and water management. This is particularly pertinent for comparative hydrological analysis and modelling performance conducted over regional and national scales to ensure the information content of discharge data is effectively characterised. In this study, the first country-wide assessment of discharge uncertainty in England and Wales is undertaken. We analyse rating-curve data and stage-discharge measurements for over 700 gauging stations and present a novel, generalised framework for quantifying discharge uncertainty that is readily applicable to many gauging stations. Our methodology utilises a non-parametric regression technique for fitting the rating curve, specifically accounting for measurement error by bootstrap sampling from derived measurement uncertainties and for scatter in the stage-discharge relationship. Additionally, the framework incorporates techniques to account for different types of stage-discharge relationships, including time-variable rating curves, gauging station changes and outliers in the stage-discharge measurement data. Results for all gauging stations across England and Wales are presented demonstrating (1) how discharge uncertainty varies spatially for low, mean and high flows, (2) how the framework captures place-specific uncertainties for a number of case studies and (3) the links that can be drawn between catchment characteristics and discharge uncertainty. We also analyse changes in the official rating curves to deduce the stability of the stage-discharge relationship and find this is dependent on catchment dynamics. Finally, we discuss the significance of these results for national scale uncertainty analyses and comparative hydrological assessments. This methodology is applicable to any catchment with comparable stage-discharge information.

  4. Evaluating uncertainties in regional climate simulations over South America at the seasonal scale

    Energy Technology Data Exchange (ETDEWEB)

    Solman, Silvina A. [Centro de Investigaciones del Mar y la Atmosfera CIMA/CONICET-UBA, DCAO/FCEN, UMI-IFAECI/CNRS, CIMA-Ciudad Universitaria, Buenos Aires (Argentina); Pessacg, Natalia L. [Centro Nacional Patagonico (CONICET), Puerto Madryn, Chubut (Argentina)

    2012-07-15

    This work focuses on the evaluation of different sources of uncertainty affecting regional climate simulations over South America at the seasonal scale, using the MM5 model. The simulations cover a 3-month period for the austral spring season. Several four-member ensembles were performed in order to quantify the uncertainty due to: the internal variability; the definition of the regional model domain; the choice of physical parameterizations and the selection of physical parameters within a particular cumulus scheme. The uncertainty was measured by means of the spread among individual members of each ensemble during the integration period. Results show that the internal variability, triggered by differences in the initial conditions, represents the lowest level of uncertainty for every variable analyzed. The geographic distribution of the spread among ensemble members depends on the variable: for precipitation and temperature the largest spread is found over tropical South America while for the mean sea level pressure the largest spread is located over the southeastern Atlantic Ocean, where large synoptic-scale activity occurs. Using nudging techniques to ingest the boundary conditions reduces dramatically the internal variability. The uncertainty due to the domain choice displays a similar spatial pattern compared with the internal variability, except for the mean sea level pressure field, though its magnitude is larger all over the model domain for every variable. The largest spread among ensemble members is found for the ensemble in which different combinations of physical parameterizations are selected. The perturbed physics ensemble produces a level of uncertainty slightly larger than the internal variability. This study suggests that no matter what the source of uncertainty is, the geographical distribution of the spread among members of the ensembles is invariant, particularly for precipitation and temperature. (orig.)

  5. Effects of macro-scale uncertainties on the imaging and automatic manipulation of nanoparticles

    Energy Technology Data Exchange (ETDEWEB)

    Korayem, M. H., E-mail: hkorayem@iust.ac.ir; Sadeghzadeh, S.; Homayooni, A. [Iran University of Science and Technology, Robotic Research Laboratory, School of Mechanical Engineering (Iran, Islamic Republic of)

    2013-01-15

    The steering, positioning, and fabrication operations in nano scale have been hampered by the uncertainties which come from the macro parts of nano-positioners. Among those uncertainties, the nonlinearities of piezo scanners have the highest contribution, which should be identified and compensated. On the other hand, the recognition of the effects of macro-scale nonlinearities on small-scale dynamics requires the simultaneous consideration of both the macro- and small-scale dynamics. This necessitates the implementation of multi-scale methods. In this article, a fixed interfacial multi-scale method (FIMM) that includes the effects of hysteresis has been used for the computationally and mathematically efficient modeling of nano-positioners. This method presents an improved coupling approach that can be used to study the imaging and manipulation of nanoparticles (from one to several hundred nanometers in diameter) subjected to nonlinear as well as linear positioning schemes. After comparing the applied hysteresis model with some previous experimental works, the dynamics of imaging and automatic manipulation of nanoparticles have been studied and some useful results have been presented. This paper opens a new window to the recognition and compensation of the errors of macro-scale nonlinearities imposed on small-scale dynamics.

  6. Factor Composition of the Suicide Intent Scale.

    Science.gov (United States)

    Mieczkowski, Tammy A.; And Others

    1993-01-01

    Analyzed Suicide Intent Scale using data from 98 psychiatric inpatients who had attempted suicide. Analysis resulted in two-factor solution: Lethal Intent factor contained items pertaining to subjective level of lethal intent; Planning factor contained items related to objective planning for attempt. Findings suggest that Suicide Intent Scale can…

  7. Experimental and Measurement Uncertainty Associated with Characterizing Slurry Mixing Performance of Pulsating Jets at Multiple Scales

    Energy Technology Data Exchange (ETDEWEB)

    Bamberger, Judith A.; Piepel, Gregory F.; Enderlin, Carl W.; Amidan, Brett G.; Heredia-Langner, Alejandro

    2015-09-10

    Understanding how uncertainty manifests itself in complex experiments is important for developing the testing protocol and interpreting the experimental results. This paper describes experimental and measurement uncertainties, and how they can depend on the order of performing experimental tests. Experiments with pulse-jet mixers in tanks at three scales were conducted to characterize the performance of transient-developing periodic flows in Newtonian slurries. Other test parameters included the simulant, solids concentration, and nozzle exit velocity. Critical suspension velocity and cloud height were the metrics used to characterize Newtonian slurry flow associated with mobilization and mixing. During testing, near-replicate and near-repeat tests were conducted. The experimental results were used to quantify the combined experimental and measurement uncertainties using standard deviations and percent relative standard deviations (%RSD) The uncertainties in critical suspension velocity and cloud height tend to increase with the values of these responses. Hence, the %RSD values are the more appropriate summary measure of near-replicate testing and measurement uncertainty.

  8. The method of belief scales as a means for dealing with uncertainty in tough regulatory decisions.

    Energy Technology Data Exchange (ETDEWEB)

    Pilch, Martin M.

    2005-10-01

    Modeling and simulation is playing an increasing role in supporting tough regulatory decisions, which are typically characterized by variabilities and uncertainties in the scenarios, input conditions, failure criteria, model parameters, and even model form. Variability exists when there is a statistically significant database that is fully relevant to the application. Uncertainty, on the other hand, is characterized by some degree of ignorance. A simple algebraic problem was used to illustrate how various risk methodologies address variability and uncertainty in a regulatory context. These traditional risk methodologies include probabilistic methods (including frequensic and Bayesian perspectives) and second-order methods where variabilities and uncertainties are treated separately. Representing uncertainties with (subjective) probability distributions and using probabilistic methods to propagate subjective distributions can lead to results that are not logically consistent with available knowledge and that may not be conservative. The Method of Belief Scales (MBS) is developed as a means to logically aggregate uncertain input information and to propagate that information through the model to a set of results that are scrutable, easily interpretable by the nonexpert, and logically consistent with the available input information. The MBS, particularly in conjunction with sensitivity analyses, has the potential to be more computationally efficient than other risk methodologies. The regulatory language must be tailored to the specific risk methodology if ambiguity and conflict are to be avoided.

  9. Sediment delivery ratio and its uncertainties on flood event scale:Quantification for the Lower Yellow River

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Sediment delivery ratio(SDR)for fluvial rivers was formulated with sediment rating curve.The observed data of SDR on flood event scale of the Lower Yellow River(LYR)were adopted to examine the formulation and to calibrate the model parameters.A regression formula of SDR was then established and its 95%prediction interval was accordingly quantified to represent its overall uncertainties.Three types of factors including diversity of the incoming flow conditions,river self-regulation processes,and human activities were ascribed to the uncertainties.The following were shown:(1)With the incoming sediment coefficient(ISC)being a variable,it was not necessary to adopt the incoming flow discharge as the second variable in the formulation of SDR;and(2)ISC=0.003 and therefore SDR=2 might be a threshold for distinguishing the characteristics of sediment transport within the LYR.These findings would highlight sediment transport characteristics on the scale of flood event and contribute to uncertainty based analysis of water volume required for sediment transport and channel maintenance of the LYR.

  10. Rainfall Interpolation and Uncertainty Assessment at different Temporal and Spatial Scales

    Science.gov (United States)

    Bárdossy, A.; Pegram, G.

    2012-04-01

    Spatial interpolation of rainfall over different time and spatial scales is necessary in many applications of hydrometeorology including (i) catchment modelling, (ii) blending/conditioning of radar-rainfall images and (iii) correction of remote sensing estimates of rainfall (for example using TRMM) which are known to be biased, to name three. The specific problems encountered in rainfall interpolation include: • the large number of calculations which need to be performed automatically • the quantification of the influence of topography, usually the most influential of exogenous variables • how to use observed zero (dry) values in interpolation, because their proportion increases with shorter time scales • the need to estimate a reasonable uncertainty of the modelled point/pixel distributions • the difficulty of estimating uncertainty of accumulations over a range of spatial scales The approaches used and described in the presentation employ the variables rainfall and altitude. The methods of interpolation, restricted to 10 controls neighbouring the target, include (i) Ordinary Kriging of the rainfall without altitude, (ii) External Drift Kriging with altitude as an exogenous variable, and less conventionally, (iii) truncated Gaussian copulas and v-copulas, both omitting and including the altitude of the control stations as well as that of the target. It is found that truncated Gaussian copulas, with the target's and all control the stations' altitudes included as exogenous variables, produce the lowest Mean Square error in cross-validation and, as a bonus, model with the least bias. In contrast, the uncertainty of interpolation is better described by the v-copulas, but the Gaussian copulas have the computational advantage (by three orders of magnitude) which justifies their use in practice. It turns out that the uncertainty estimates of the OK and EDK interpolants are not competitive at any time scale, from daily to annual.

  11. Reducing uncertainty in calibrating aquifer flow model with multiple scales of heterogeneity.

    Science.gov (United States)

    Zhang, Ye

    2014-01-01

    Modeling and calibration of natural aquifers with multiple scales of heterogeneity is a challenging task due to limited subsurface access. While computer modeling plays an essential role in aquifer studies, large uncertainty exists in developing a conceptual model of an aquifer and in calibrating the model for decision making. Due to uncertainties such as a lack of understanding of subsurface processes and a lack of techniques to parameterize the subsurface environment (including hydraulic conductivity, source/sink rate, and aquifer boundary conditions), existing aquifer models often suffer nonuniqueness in calibration, leading to poor predictive capability. A robust calibration methodology is needed that can address the simultaneous estimations of aquifer parameters, source/sink, and boundary conditions. In this paper, we propose a multistage and multiscale approach that addresses subsurface heterogeneity at multiple scales, while reducing uncertainty in estimating the model parameters and model boundary conditions. The key to this approach lies in the appropriate development, verification, and synthesis of existing and new techniques of static and dynamic data integration. In particular, based on a given set of observation data, new inversion techniques can be first used to estimate aquifer large-scale effective parameters and smoothed boundary conditions, based on which parameter and boundary condition estimation can be refined at increasing detail using standard or highly parameterized estimation techniques.

  12. Health impact assessment of traffic-related air pollution at the urban project scale: influence of variability and uncertainty.

    Science.gov (United States)

    Chart-Asa, Chidsanuphong; Gibson, Jacqueline MacDonald

    2015-02-15

    This paper develops and then demonstrates a new approach for quantifying health impacts of traffic-related particulate matter air pollution at the urban project scale that includes variability and uncertainty in the analysis. We focus on primary particulate matter having a diameter less than 2.5 μm (PM2.5). The new approach accounts for variability in vehicle emissions due to temperature, road grade, and traffic behavior variability; seasonal variability in concentration-response coefficients; demographic variability at a fine spatial scale; uncertainty in air quality model accuracy; and uncertainty in concentration-response coefficients. We demonstrate the approach for a case study roadway corridor with a population of 16,000, where a new extension of the University of North Carolina (UNC) at Chapel Hill campus is slated for construction. The results indicate that at this case study site, health impact estimates increased by factors of 4-9, depending on the health impact considered, compared to using a conventional health impact assessment approach that overlooks these variability and uncertainty sources. In addition, we demonstrate how the method can be used to assess health disparities. For example, in the case study corridor, our method demonstrates the existence of statistically significant racial disparities in exposure to traffic-related PM2.5 under present-day traffic conditions: the correlation between percent black and annual attributable deaths in each census block is 0.37 (t(114)=4.2, p<0.0001). Overall, our results show that the proposed new campus will cause only a small incremental increase in health risks (annual risk 6×10(-10); lifetime risk 4×10(-8)), compared to if the campus is not built. Nonetheless, the approach we illustrate could be useful for improving the quality of information to support decision-making for other urban development projects.

  13. Quantifying Uncertainty from Computational Factors in Simulations of a Model Ballistic System

    Science.gov (United States)

    2017-08-01

    ARL-TR-8074 ● AUG 2017 US Army Research Laboratory Quantifying Uncertainty from Computational Factors in Simulations of a Model...Uncertainty from Computational Factors in Simulations of a Model Ballistic System by Daniel J Hornbaker Weapons and Materials Research...penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM

  14. Potential for improved radiation thermometry measurement uncertainty through implementing a primary scale in an industrial laboratory

    Science.gov (United States)

    Willmott, Jon R.; Lowe, David; Broughton, Mick; White, Ben S.; Machin, Graham

    2016-09-01

    A primary temperature scale requires realising a unit in terms of its definition. For high temperature radiation thermometry in terms of the International Temperature Scale of 1990 this means extrapolating from the signal measured at the freezing temperature of gold, silver or copper using Planck’s radiation law. The difficulty in doing this means that primary scales above 1000 °C require specialist equipment and careful characterisation in order to achieve the extrapolation with sufficient accuracy. As such, maintenance of the scale at high temperatures is usually only practicable for National Metrology Institutes, and calibration laboratories have to rely on a scale calibrated against transfer standards. At lower temperatures it is practicable for an industrial calibration laboratory to have its own primary temperature scale, which reduces the number of steps between the primary scale and end user. Proposed changes to the SI that will introduce internationally accepted high temperature reference standards might make it practicable to have a primary high temperature scale in a calibration laboratory. In this study such a scale was established by calibrating radiation thermometers directly to high temperature reference standards. The possible reduction in uncertainty to an end user as a result of the reduced calibration chain was evaluated.

  15. Crossing Science-Policy-Societal Boundaries to Reduce Scientific and Institutional Uncertainty in Small-Scale Fisheries

    Science.gov (United States)

    Sutton, Abigail M.; Rudd, Murray A.

    2016-10-01

    The governance of small-scale fisheries (SSF) is challenging due to the uncertainty, complexity, and interconnectedness of social, political, ecological, and economical processes. Conventional SSF management has focused on a centralized and top-down approach. A major criticism of conventional management is the over-reliance on `expert science' to guide decision-making and poor consideration of fishers' contextually rich knowledge. That is thought to exacerbate the already low governance potential of SSF. Integrating scientific knowledge with fishers' knowledge is increasingly popular and is often assumed to help reduce levels of biophysical and institutional uncertainties. Many projects aimed at encouraging knowledge integration have, however, been unsuccessful. Our objective in this research was to assess factors that influence knowledge integration and the uptake of integrated knowledge into policy-making. We report results from 54 semi-structured interviews with SSF researchers and practitioners from around the globe. Our analysis is framed in terms of scientific credibility, societal legitimacy, and policy saliency, and we discuss cases that have been partially or fully successful in reducing uncertainty via push-and-pull-oriented boundary crossing initiatives. Our findings suggest that two important factors affect the science-policy-societal boundary: a lack of consensus among stakeholders about what constitutes credible knowledge and institutional uncertainty resulting from shifting policies and leadership change. A lack of training for scientific leaders and an apparent `shelf-life' for community organizations highlight the importance of ongoing institutional support for knowledge integration projects. Institutional support may be enhanced through such investments, such as capacity building and specialized platforms for knowledge integration.

  16. Crossing Science-Policy-Societal Boundaries to Reduce Scientific and Institutional Uncertainty in Small-Scale Fisheries.

    Science.gov (United States)

    Sutton, Abigail M; Rudd, Murray A

    2016-10-01

    The governance of small-scale fisheries (SSF) is challenging due to the uncertainty, complexity, and interconnectedness of social, political, ecological, and economical processes. Conventional SSF management has focused on a centralized and top-down approach. A major criticism of conventional management is the over-reliance on 'expert science' to guide decision-making and poor consideration of fishers' contextually rich knowledge. That is thought to exacerbate the already low governance potential of SSF. Integrating scientific knowledge with fishers' knowledge is increasingly popular and is often assumed to help reduce levels of biophysical and institutional uncertainties. Many projects aimed at encouraging knowledge integration have, however, been unsuccessful. Our objective in this research was to assess factors that influence knowledge integration and the uptake of integrated knowledge into policy-making. We report results from 54 semi-structured interviews with SSF researchers and practitioners from around the globe. Our analysis is framed in terms of scientific credibility, societal legitimacy, and policy saliency, and we discuss cases that have been partially or fully successful in reducing uncertainty via push-and-pull-oriented boundary crossing initiatives. Our findings suggest that two important factors affect the science-policy-societal boundary: a lack of consensus among stakeholders about what constitutes credible knowledge and institutional uncertainty resulting from shifting policies and leadership change. A lack of training for scientific leaders and an apparent 'shelf-life' for community organizations highlight the importance of ongoing institutional support for knowledge integration projects. Institutional support may be enhanced through such investments, such as capacity building and specialized platforms for knowledge integration.

  17. The deformed uncertainty relation and the corresponding beam quality factor

    CERN Document Server

    Li, K; Wang, S M; Li, Kang; Zhao, Dao Mu; Wang, Shao Min

    1996-01-01

    By using the theory of deformed quantum mechanics, we study the deformed light beam theoretically. The deformed beam quality factor M_q^2 is given explicitly under the case of deformed light in coherent state. When the deformation parameter q being a root of unity, the beam quality factor M_q^2 \\leq 1.

  18. Uncertainty and Evaluation of Impacts Modeling at Regional Scales in Integrated Assessment: the Case of Buildings

    Science.gov (United States)

    Clarke, L.; Zhou, Y.; Eom, J.; Kyle, P.; Daly, D.

    2012-12-01

    Integrated assessment (IA) models have traditionally focused on the evaluation of climate mitigation strategies. However, in recent years, efforts to consider both impacts and mitigation simultaneously have expanded dramatically. Because climate impacts are inherently regional in scale, the incorporation of impacts into IA modeling - which is inherently global in character - raises a range of challenges beyond the already substantial challenges associated with modeling impacts. In particular, it raises questions about how to best evaluate and diagnose the resulting representations of impacts, and how to characterize the uncertainty surrounding associated projections. This presentation will provide an overview of the challenges and uncertainties surrounding modeling climate impacts on building heating and cooling demands in an integrated assessment modeling framework - the Global Change Assessment Model (GCAM). The presentation will first discuss the issues associated with modeling building heating and cooling degree days in IA models. It will review research using spatially explicit climate and population information to inform a standard version of GCAM with fourteen geopolitical regions. It will discuss a new subregional version of GCAM in which building energy consumption is resolved at a fifty-state level. The presentation will also characterize efforts to link GCAM to more technologically resolved buildings models to gain insights about demands at higher temporal resolution. The second portion of the presentation will discuss the uncertainties associated with projections of building heating and cooling demands at various scales. A range of key uncertainties are important. This includes a range of uncertainties surrounding the nature of changes to global and regional climates, with particular emphasis on the uncertainty surrounding temperature projections. In addition, the linkage in this research between human and Earth systems means that the projections are

  19. Quantification of Monte Carlo event generator scale-uncertainties with an example ATLAS analysis studying underlying event properties

    Energy Technology Data Exchange (ETDEWEB)

    Brandt, Gerhard [University of Oxford (United Kingdom); Krauss, Frank [IPPP Durham (United Kingdom); Lacker, Heiko; Leyton, Michael; Mamach, Martin; Schulz, Holger; Weyh, Daniel [Humboldt University of Berlin (Germany)

    2012-07-01

    Monte Carlo (MC) event generators are widely employed in the analysis of experimental data also for LHC in order to predict the features of observables and test analyses with them. These generators rely on phenomenological models containing various parameters which are free in certain ranges. Variations of these parameters relative to their default lead to uncertainties on the predictions of the event generators and, in turn, on the results of any experimental data analysis making use of the event generator. A Generalized method for quantifying a certain class of these generator based uncertainties will be presented in this talk. We study for the SHERPA event generator the effect on the analysis results from uncertainties in the choice of the merging and factorization scale. The quantification is done within an example ATLAS analysis measuring underlying event UE properties in Z-boson production limited to low transverse momenta (p{sub T}{sup Z}<3 GeV) of the Z-boson. The analysis extracts event-shape distributions from charged particles in the event that do not belong to the Z decay for generate Monte Carlo event and data which are unfolded back to the generator level.

  20. Flood risk assessment at the regional scale: Computational challenges and the monster of uncertainty

    Science.gov (United States)

    Efstratiadis, Andreas; Papalexiou, Simon-Michael; Markonis, Yiannis; Koukouvinos, Antonis; Vasiliades, Lampros; Papaioannou, George; Loukas, Athanasios

    2016-04-01

    We present a methodological framework for flood risk assessment at the regional scale, developed within the implementation of the EU Directive 2007/60 in Greece. This comprises three phases: (a) statistical analysis of extreme rainfall data, resulting to spatially-distributed parameters of intensity-duration-frequency (IDF) relationships and their confidence intervals, (b) hydrological simulations, using event-based semi-distributed rainfall-runoff approaches, and (c) hydraulic simulations, employing the propagation of flood hydrographs across the river network and the mapping of inundated areas. The flood risk assessment procedure is employed over the River Basin District of Thessaly, Greece, which requires schematization and modelling of hundreds of sub-catchments, each one examined for several risk scenarios. This is a challenging task, involving multiple computational issues to handle, such as the organization, control and processing of huge amount of hydrometeorological and geographical data, the configuration of model inputs and outputs, and the co-operation of several software tools. In this context, we have developed supporting applications allowing massive data processing and effective model coupling, thus drastically reducing the need for manual interventions and, consequently, the time of the study. Within flood risk computations we also account for three major sources of uncertainty, in an attempt to provide upper and lower confidence bounds of flood maps, i.e. (a) statistical uncertainty of IDF curves, (b) structural uncertainty of hydrological models, due to varying anteceded soil moisture conditions, and (c) parameter uncertainty of hydraulic models, with emphasis to roughness coefficients. Our investigations indicate that the combined effect of the above uncertainties (which are certainly not the unique ones) result to extremely large bounds of potential inundation, thus rising many questions about the interpretation and usefulness of current flood

  1. Hierarchical multi-scale approach to validation and uncertainty quantification of hyper-spectral image modeling

    Science.gov (United States)

    Engel, Dave W.; Reichardt, Thomas A.; Kulp, Thomas J.; Graff, David L.; Thompson, Sandra E.

    2016-05-01

    Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensor level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.

  2. Hierarchical Multi-Scale Approach To Validation and Uncertainty Quantification of Hyper-Spectral Image Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Engel, David W.; Reichardt, Thomas A.; Kulp, Thomas J.; Graff, David; Thompson, Sandra E.

    2016-09-17

    Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensor level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.

  3. Sustainable water management under future uncertainty with eco-engineering decision scaling

    Science.gov (United States)

    Poff, N. Leroy; Brown, Casey M.; Grantham, Theodore E.; Matthews, John H.; Palmer, Margaret A.; Spence, Caitlin M.; Wilby, Robert L.; Haasnoot, Marjolijn; Mendoza, Guillermo F.; Dominique, Kathleen C.; Baeza, Andres

    2016-01-01

    Managing freshwater resources sustainably under future climatic and hydrological uncertainty poses novel challenges. Rehabilitation of ageing infrastructure and construction of new dams are widely viewed as solutions to diminish climate risk, but attaining the broad goal of freshwater sustainability will require expansion of the prevailing water resources management paradigm beyond narrow economic criteria to include socially valued ecosystem functions and services. We introduce a new decision framework, eco-engineering decision scaling (EEDS), that explicitly and quantitatively explores trade-offs in stakeholder-defined engineering and ecological performance metrics across a range of possible management actions under unknown future hydrological and climate states. We illustrate its potential application through a hypothetical case study of the Iowa River, USA. EEDS holds promise as a powerful framework for operationalizing freshwater sustainability under future hydrological uncertainty by fostering collaboration across historically conflicting perspectives of water resource engineering and river conservation ecology to design and operate water infrastructure for social and environmental benefits.

  4. Sustainable water management under future uncertainty with eco-engineering decision scaling

    Science.gov (United States)

    Poff, N LeRoy; Brown, Casey M; Grantham, Theodore E.; Matthews, John H; Palmer, Margaret A.; Spence, Caitlin M; Wilby, Robert L.; Haasnoot, Marjolijn; Mendoza, Guillermo F; Dominique, Kathleen C; Baeza, Andres

    2015-01-01

    Managing freshwater resources sustainably under future climatic and hydrological uncertainty poses novel challenges. Rehabilitation of ageing infrastructure and construction of new dams are widely viewed as solutions to diminish climate risk, but attaining the broad goal of freshwater sustainability will require expansion of the prevailing water resources management paradigm beyond narrow economic criteria to include socially valued ecosystem functions and services. We introduce a new decision framework, eco-engineering decision scaling (EEDS), that explicitly and quantitatively explores trade-offs in stakeholder-defined engineering and ecological performance metrics across a range of possible management actions under unknown future hydrological and climate states. We illustrate its potential application through a hypothetical case study of the Iowa River, USA. EEDS holds promise as a powerful framework for operationalizing freshwater sustainability under future hydrological uncertainty by fostering collaboration across historically conflicting perspectives of water resource engineering and river conservation ecology to design and operate water infrastructure for social and environmental benefits.

  5. Improving the Factor Structure of Psychological Scales

    Science.gov (United States)

    Zhang, Xijuan; Savalei, Victoria

    2015-01-01

    Many psychological scales written in the Likert format include reverse worded (RW) items in order to control acquiescence bias. However, studies have shown that RW items often contaminate the factor structure of the scale by creating one or more method factors. The present study examines an alternative scale format, called the Expanded format, which replaces each response option in the Likert scale with a full sentence. We hypothesized that this format would result in a cleaner factor structure as compared with the Likert format. We tested this hypothesis on three popular psychological scales: the Rosenberg Self-Esteem scale, the Conscientiousness subscale of the Big Five Inventory, and the Beck Depression Inventory II. Scales in both formats showed comparable reliabilities. However, scales in the Expanded format had better (i.e., lower and more theoretically defensible) dimensionalities than scales in the Likert format, as assessed by both exploratory factor analyses and confirmatory factor analyses. We encourage further study and wider use of the Expanded format, particularly when a scale’s dimensionality is of theoretical interest. PMID:27182074

  6. Uncertainty assessment of water quality modeling for a small-scale urban catchment using the GLUE methodology: a case study in Shanghai, China.

    Science.gov (United States)

    Zhang, Wei; Li, Tian; Dai, Meihong

    2015-06-01

    There is often great uncertainty in water quality modeling for urban drainage systems because water quality variation in systems is complex and affected by many factors. The stormwater management model (SWMM) was applied to a small-scale urban catchment with a simple and well-maintained stormwater drainage system without illicit connections. This was done to assess uncertainty in build-up and wash-off modeling of pollutants within the generalized likelihood uncertainty estimation (GLUE) methodology, based on a well-calibrated water quantity model. The results indicated great uncertainty of water quality modeling within the GLUE methodology. Comparison of uncertainties in various pollutant build-up and wash-off models that were available in SWMM indicated that those uncertainties varied slightly. This may be a consequence of the specific characteristics of rainfall events and experimental sites used in the study. The uncertainty analysis of water quality parameters in SWMM is conducive to effectively evaluating model reliability, and provides an experience base for similar research and applications.

  7. New uncertainties in QCD-QED rescaling factors using quadrature method

    Indian Academy of Sciences (India)

    Mahadev Patgiri; N Nimai Singh

    2005-12-01

    In this paper we briefly outline the quadrature method for estimating uncertainties in a function which depends on several variables, and apply it to estimate the numerical uncertainties in QCD-QED rescaling factors. We employ here the one-loop order in QED and three-loop order in QCD evolution equations of the fermion mass renormalisation. Our present calculation is found to be new and also reliable when compared to the earlier values employed by various authors.

  8. Stability Criteria for Large-Scale Linear Systems with Structured Uncertainties

    Institute of Scientific and Technical Information of China (English)

    Cao Dengqing

    1996-01-01

    The robust stability analysis for large-scale linear systems with structured timevarying uncertainties is investigated in this paper. By using the scalar Lyapunov functions and the properties of M-matrix and nonnegative matrix, stability robustness measures are proposed. The robust stability criteria obtained are applied to derive an algebric criterion which is expressed directly in terms of plant parameters and is shown to be less conservative than the existing ones. A numerical example is given to demonstrate the stability criteria obtained and to compare them with the previous ones.

  9. Uncertainty analysis and validation of the estimation of effective hydraulic properties at the Darcy scale

    Science.gov (United States)

    Mesgouez, A.; Buis, S.; Ruy, S.; Lefeuve-Mesgouez, G.

    2014-05-01

    The determination of the hydraulic properties of heterogeneous soils or porous media remains challenging. In the present study, we focus on determining the effective properties of heterogeneous porous media at the Darcy scale with an analysis of their uncertainties. Preliminary, experimental measurements of the hydraulic properties of each component of the heterogeneous medium are obtained. The properties of the effective medium, representing an equivalent homogeneous material, are determined numerically by simulating a water flow in a three-dimensional representation of the heterogeneous medium, under steady-state scenarios and using its component properties. One of the major aspects of this study is to take into account the uncertainties of these properties in the computation and evaluation of the effective properties. This is done using a bootstrap method. Numerical evaporation experiments are conducted both on the heterogeneous and on the effective homogeneous materials to evaluate the effectiveness of the proposed approach. First, the impact of the uncertainties of the component properties on the simulated water matric potential is found to be high for the heterogeneous material configuration. Second, it is shown that the strategy developed herein leads to a reduction of this impact. Finally, the adequacy between the mean of the simulations for the two configurations confirms the suitability of the homogenization approach, even in the case of dynamic scenarios. Although it is applied to green roof substrates, a two-component media composed of bark compost and pozzolan used in the construction of buildings, the methodology proposed in this study is generic.

  10. Local scale multiple quantitative risk assessment and uncertainty evaluation in a densely urbanised area (Brescia, Italy

    Directory of Open Access Journals (Sweden)

    S. Lari

    2012-11-01

    Full Text Available The study of the interactions between natural and anthropogenic risks is necessary for quantitative risk assessment in areas affected by active natural processes, high population density and strong economic activities.

    We present a multiple quantitative risk assessment on a 420 km2 high risk area (Brescia and surroundings, Lombardy, Northern Italy, for flood, seismic and industrial accident scenarios. Expected economic annual losses are quantified for each scenario and annual exceedance probability-loss curves are calculated. Uncertainty on the input variables is propagated by means of three different methodologies: Monte-Carlo-Simulation, First Order Second Moment, and point estimate.

    Expected losses calculated by means of the three approaches show similar values for the whole study area, about 64 000 000 € for earthquakes, about 10 000 000 € for floods, and about 3000 € for industrial accidents. Locally, expected losses assume quite different values if calculated with the three different approaches, with differences up to 19%.

    The uncertainties on the expected losses and their propagation, performed with the three methods, are compared and discussed in the paper. In some cases, uncertainty reaches significant values (up to almost 50% of the expected loss. This underlines the necessity of including uncertainty in quantitative risk assessment, especially when it is used as a support for territorial planning and decision making. The method is developed thinking at a possible application at a regional-national scale, on the basis of data available in Italy over the national territory.

  11. Analysis of the uncertainty in the monetary valuation of ecosystem services--A case study at the river basin scale.

    Science.gov (United States)

    Boithias, Laurie; Terrado, Marta; Corominas, Lluís; Ziv, Guy; Kumar, Vikas; Marqués, Montse; Schuhmacher, Marta; Acuña, Vicenç

    2016-02-01

    Ecosystem services provide multiple benefits to human wellbeing and are increasingly considered by policy-makers in environmental management. However, the uncertainty related with the monetary valuation of these benefits is not yet adequately defined or integrated by policy-makers. Given this background, our aim was to quantify different sources of uncertainty when performing monetary valuation of ecosystem services, in order to provide a series of guidelines to reduce them. With an example of 4 ecosystem services (i.e., water provisioning, waste treatment, erosion protection, and habitat for species) provided at the river basin scale, we quantified the uncertainty associated with the following sources: (1) the number of services considered, (2) the number of benefits considered for each service, (3) the valuation metrics (i.e. valuation methods) used to value benefits, and (4) the uncertainty of the parameters included in the valuation metrics. Results indicate that the highest uncertainty was caused by the number of services considered, as well as by the number of benefits considered for each service, whereas the parametric uncertainty was similar to the one related to the selection of valuation metric, thus suggesting that the parametric uncertainty, which is the only uncertainty type commonly considered, was less critical than the structural uncertainty, which is in turn mainly dependent on the decision-making context. Given the uncertainty associated to the valuation structure, special attention should be given to the selection of services, benefits and metrics according to a given context.

  12. Gray cases of child abuse: Investigating factors associated with uncertainty.

    Science.gov (United States)

    Chaiyachati, Barbara H; Asnes, Andrea G; Moles, Rebecca L; Schaeffer, Paula; Leventhal, John M

    2016-01-01

    Research in child abuse pediatrics has advanced clinicians' abilities to discriminate abusive from accidental injuries. Less attention, however, has been paid to cases with uncertain diagnoses. These uncertain cases - the "gray" cases between decisions of abuse and not abuse - represent a meaningful challenge in the practice of child abuse pediatricians. In this study, we describe a series of gray cases, representing 17% of 134 consecutive children who were hospitalized at a single pediatric hospital and referred to a child abuse pediatrician for concerns of possible abuse. Gray cases were defined by scores of 3, 4, or 5 on a 7-point clinical judgment scale of the likelihood of abuse. We evaluated details of the case presentation, including incident history, patient medical and developmental histories, family social histories, medical studies, and injuries from the medical record and sought to identify unique and shared characteristics compared with abuse and accidental cases. Overall, the gray cases had incident histories that were ambiguous, medical and social histories that were more similar to abuse cases, and injuries that were similar to accidental injuries. Thus, the lack of clarity in these cases was not attributable to any single element of the incident, history, or injury. Gray cases represent a clinical challenge in child abuse pediatrics and deserve continued attention in research.

  13. Managing Risk and Uncertainty in Large-Scale University Research Projects

    Science.gov (United States)

    Moore, Sharlissa; Shangraw, R. F., Jr.

    2011-01-01

    Both publicly and privately funded research projects managed by universities are growing in size and scope. Complex, large-scale projects (over $50 million) pose new management challenges and risks for universities. This paper explores the relationship between project success and a variety of factors in large-scale university projects. First, we…

  14. Landscape Change in the Southern Piedmont: Challenges, Solutions, and Uncertainty Across Scales

    Directory of Open Access Journals (Sweden)

    James T. Peterson

    2003-12-01

    Full Text Available The southern Piedmont of the southeastern United States epitomizes the complex and seemingly intractable problems and hard decisions that result from uncontrolled urban and suburban sprawl. Here we consider three recurrent themes in complicated problems involving complex systems: (1 scale dependencies and cross-scale, often nonlinear relationships; (2 resilience, in particular the potential for complex systems to move to alternate stable states with decreased ecological and/or economic value; and (3 uncertainty in the ability to understand and predict outcomes, perhaps particularly those that occur as a result of human impacts. We consider these issues in the context of landscape-level decision making, using as an example water resources and lotic systems in the Piedmont region of the southeastern United States.

  15. Double Vagueness:Uncertainty in Multi-scale Fuzzy Assignment of Duneness

    Institute of Scientific and Technical Information of China (English)

    CHENG Tao; Pete Fisher; LI Zhilin

    2004-01-01

    In the automation of identification of landscape features the vagueness arises from the fact that the attributes and parameters that make up a landscape vary over space and scale. In most of existing studies, these two kinds of vagueness are studied separately. This paper investigates their combination in identification of coast landscape units. Fuzzy set theory is used to describe the vagueness of geomorphic features due to the continuity in space. The vagueness resulted from the scale of measurement is evaluated by statistic indicators. The differences of fuzzy objects derived from data at differing resolutions (in size from 3×3 cells to 25×25 cells) are studied in order to examine these higher-order uncertainties.

  16. A Scale-Driven Change Detection Method Incorporating Uncertainty Analysis for Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Ming Hao

    2016-09-01

    Full Text Available Change detection (CD based on remote sensing images plays an important role in Earth observation. However, the CD accuracy is usually affected by sunlight and atmospheric conditions and sensor calibration. In this study, a scale-driven CD method incorporating uncertainty analysis is proposed to increase CD accuracy. First, two temporal images are stacked and segmented into multiscale segmentation maps. Then, a pixel-based change map with memberships belonging to changed and unchanged parts is obtained by fuzzy c-means clustering. Finally, based on the Dempster-Shafer evidence theory, the proposed scale-driven CD method incorporating uncertainty analysis is performed on the multiscale segmentation maps and the pixel-based change map. Two experiments were carried out on Landsat-7 Enhanced Thematic Mapper Plus (ETM+ and SPOT 5 data sets. The ratio of total errors can be reduced to 4.0% and 7.5% for the ETM+ and SPOT 5 data sets in this study, respectively. Moreover, the proposed approach outperforms some state-of-the-art CD methods and provides an effective solution for CD.

  17. Decentralized robust stabilization of discrete-time fuzzy large-scale systems with parametric uncertainties: a LMI method

    Institute of Scientific and Technical Information of China (English)

    Zhang Yougang; Xu Bugong

    2006-01-01

    Decentralized robust stabilization problem of discrete-time fuzzy large-scale systems with parametric uncertainties is considered. This uncertain fuzzy large-scale system consists of N interconnected T-S fuzzy subsystems, and the parametric uncertainties are unknown but norm-bounded. Based on Lyapunov stability theory and decentralized control theory of large-scale system, the design schema of decentralized parallel distributed compensation (DPDC) fuzzy controllers to ensure the asymptotic stability of the whole fuzzy large-scale system is proposed. The existence conditions for these controllers take the forms of LMIs. Finally a numerical simulation example is given to show the utility of the method proposed.

  18. Estimating riverine nutrient concentrations in agricultural catchments - Do we reduce uncertainty by using local scale data?

    Science.gov (United States)

    Capell, Rene; Hankin, Barry; Strömqvist, Johan; Lamb, Rob; Arheimer, Berit

    2017-04-01

    Nutrient transport models are important tools for large scale assessments of macro-nutrient fluxes (nitrate, phosphate) and thus can serve as support tool for environmental assessment and management. Results from model applications over large areas, i.e. on major river basin to continental scales can fill a gap where monitoring data is not available. However, both phosphate and nitrate transport are highly complex processes, and nutrient models must balance data requirements and process simplification. Data typically become increasingly sparse and less detailed with increasing spatial scale. Here, we compare model estimates of riverine nitrate concentrations in the Weaver-Dane basin (UK) and to evaluate the role of available environmental data sources for model performance by using (a) open environmental data sources available at European scale and (b) closed data sources which are more localised and typically not openly available. In particular, we aim to evaluate, how model structure, spatial model resolution, climate forcing products, and land use and management information impact on model-estimated nitrate concentrations. We use the European rainfall-runoff and nutrient model E-HYPE (http://hypeweb.smhi.se/europehype/about/) as a baseline large-scale model built on open data sources, and compare with more detailed model set-ups in different configurations using local data. Nitrate estimates are compared using a GLUE uncertainty framework.

  19. The treatment of uncertainties in reactive pollution dispersion models at urban scales.

    Science.gov (United States)

    Tomlin, A S; Ziehn, T; Goodman, P; Tate, J E; Dixon, N S

    2016-07-18

    The ability to predict NO2 concentrations ([NO2]) within urban street networks is important for the evaluation of strategies to reduce exposure to NO2. However, models aiming to make such predictions involve the coupling of several complex processes: traffic emissions under different levels of congestion; dispersion via turbulent mixing; chemical processes of relevance at the street-scale. Parameterisations of these processes are challenging to quantify with precision. Predictions are therefore subject to uncertainties which should be taken into account when using models within decision making. This paper presents an analysis of mean [NO2] predictions from such a complex modelling system applied to a street canyon within the city of York, UK including the treatment of model uncertainties and their causes. The model system consists of a micro-scale traffic simulation and emissions model, and a Reynolds averaged turbulent flow model coupled to a reactive Lagrangian particle dispersion model. The analysis focuses on the sensitivity of predicted in-street increments of [NO2] at different locations in the street to uncertainties in the model inputs. These include physical characteristics such as background wind direction, temperature and background ozone concentrations; traffic parameters such as overall demand and primary NO2 fraction; as well as model parameterisations such as roughness lengths, turbulent time- and length-scales and chemical reaction rate coefficients. Predicted [NO2] is shown to be relatively robust with respect to model parameterisations, although there are significant sensitivities to the activation energy for the reaction NO + O3 as well as the canyon wall roughness length. Under off-peak traffic conditions, demand is the key traffic parameter. Under peak conditions where the network saturates, road-side [NO2] is relatively insensitive to changes in demand and more sensitive to the primary NO2 fraction. The most important physical parameter was

  20. Propagation of uncertainty in photochemical mechanisms through urban/regional scale grid-based air pollution models

    Energy Technology Data Exchange (ETDEWEB)

    Isukapalli, S.S.; Georgopoulos, P.G. [Environmental and Occupational Health Sciences Inst., Piscataway, NJ (United States)

    1997-12-31

    Uncertainty in biogenic emission estimates and photochemical reaction rates can contribute significantly to modeling error in Photochemical Air Quality Simulation Models (PAQSMs). Uncertainties in isoprene emissions from biogenic sources, and isoprene atmospheric degradation rates have recently received considerable attention with respect to control strategy selection for the reduction of tropospheric ozone levels. This study addresses the effects of uncertainties in isoprene emissions and reaction rates on ambient ozone concentrations predicted by PAQSMs. Since PAQSMs are computationally intensive, propagation of uncertainty in reaction rate constants using traditional methods, such as Monte Carlo methods, is not computationally feasible. Here, a novel computationally efficient method of uncertainty analysis, called the Stochastic Response Surface Method (SRSM), is applied to propagate uncertainty in isoprene emissions and reaction rate parameters. Case studies include estimation of uncertainty in ozone concentrations predicted by (a) a box-model, (b) a plume trajectory model, the Reactive Plume Model (RPM), and (c) an urban-to-regional scale grid model, the Urban Airshed Model (UAM). The results of this analysis are used to characterize the relative importance of uncertainties in isoprene emissions and reaction rates on ozone levels for a wide range of conditions. Furthermore, this work demonstrates the applicability of the SRSM uncertainty propagation methodology to computationally intensive models such as the UAM.

  1. Uncertainties in ecosystem service maps: a comparison on the European scale.

    Science.gov (United States)

    Schulp, Catharina J E; Burkhard, Benjamin; Maes, Joachim; Van Vliet, Jasper; Verburg, Peter H

    2014-01-01

    Safeguarding the benefits that ecosystems provide to society is increasingly included as a target in international policies. To support such policies, ecosystem service maps are made. However, there is little attention for the accuracy of these maps. We made a systematic review and quantitative comparison of ecosystem service maps on the European scale to generate insights in the uncertainty of ecosystem service maps and discuss the possibilities for quantitative validation. Maps of climate regulation and recreation were reasonably similar while large uncertainties among maps of erosion protection and flood regulation were observed. Pollination maps had a moderate similarity. Differences among the maps were caused by differences in indicator definition, level of process understanding, mapping aim, data sources and methodology. Absence of suitable observed data on ecosystem services provisioning hampers independent validation of the maps. Consequently, there are, so far, no accurate measures for ecosystem service map quality. Policy makers and other users need to be cautious when applying ecosystem service maps for decision-making. The results illustrate the need for better process understanding and data acquisition to advance ecosystem service mapping, modelling and validation.

  2. Properties of the scale factor measure

    CERN Document Server

    Bousso, Raphael; Yang, I-Sheng

    2008-01-01

    We show that in expanding regions, the scale factor measure can be reformulated as a local measure: Observations are weighted by integrating their physical density along a geodesic that starts in the longest-lived metastable vacuum. This explains why some of its properties are similar to those of the causal diamond measure. In particular, both measures are free of Boltzmann brains, subject to nearly the same conditions on vacuum stability. However, the scale factor measure assigns a much smaller probability to the observed value of the cosmological constant. The probability decreases further, like the inverse sixth power of the primordial density contrast, if the latter is allowed to vary.

  3. Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

    CERN Document Server

    Aad, Georges; Abdallah, Jalal; Abdelalim, Ahmed Ali; Abdesselam, Abdelouahab; Abdinov, Ovsat; Abi, Babak; Abolins, Maris; AbouZeid, Ossama; Abramowicz, Halina; Abreu, Henso; Acerbi, Emilio; Acharya, Bobby Samir; Adamczyk, Leszek; Adams, David; Addy, Tetteh; Adelman, Jahred; Aderholz, Michael; Adomeit, Stefanie; Adragna, Paolo; Adye, Tim; Aefsky, Scott; Aguilar-Saavedra, Juan Antonio; Aharrouche, Mohamed; Ahlen, Steven; Ahles, Florian; Ahmad, Ashfaq; Ahsan, Mahsana; Aielli, Giulio; Akdogan, Taylan; Åkesson, Torsten Paul Ake; Akimoto, Ginga; Akimov, Andrei; Akiyama, Kunihiro; Alam, Mohammad; Alam, Muhammad Aftab; Albert, Justin; Albrand, Solveig; Aleksa, Martin; Aleksandrov, Igor; Alessandria, Franco; Alexa, Calin; Alexander, Gideon; Alexandre, Gauthier; Alexopoulos, Theodoros; Alhroob, Muhammad; Aliev, Malik; Alimonti, Gianluca; Alison, John; Aliyev, Magsud; Allbrooke, Benedict; Allport, Phillip; Allwood-Spiers, Sarah; Almond, John; Aloisio, Alberto; Alon, Raz; Alonso, Alejandro; Alvarez Gonzalez, Barbara; Alviggi, Mariagrazia; Amako, Katsuya; Amaral, Pedro; Amelung, Christoph; Ammosov, Vladimir; Amorim, Antonio; Amorós, Gabriel; Amram, Nir; Anastopoulos, Christos; Ancu, Lucian Stefan; Andari, Nansi; Andeen, Timothy; Anders, Christoph Falk; Anders, Gabriel; Anderson, Kelby; Andreazza, Attilio; Andrei, George Victor; Andrieux, Marie-Laure; Anduaga, Xabier; Angerami, Aaron; Anghinolfi, Francis; Anisenkov, Alexey; Anjos, Nuno; Annovi, Alberto; Antonaki, Ariadni; Antonelli, Mario; Antonov, Alexey; Antos, Jaroslav; Anulli, Fabio; Aoun, Sahar; Aperio Bella, Ludovica; Apolle, Rudi; Arabidze, Giorgi; Aracena, Ignacio; Arai, Yasuo; Arce, Ayana; Arfaoui, Samir; Arguin, Jean-Francois; Arik, Engin; Arik, Metin; Armbruster, Aaron James; Arnaez, Olivier; Arnault, Christian; Artamonov, Andrei; Artoni, Giacomo; Arutinov, David; Asai, Shoji; Asfandiyarov, Ruslan; Ask, Stefan; Åsman, Barbro; Asquith, Lily; Assamagan, Ketevi; Astbury, Alan; Astvatsatourov, Anatoli; Aubert, Bernard; Auge, Etienne; Augsten, Kamil; Aurousseau, Mathieu; Avolio, Giuseppe; Avramidou, Rachel Maria; Axen, David; Ay, Cano; Azuelos, Georges; Azuma, Yuya; Baak, Max; Baccaglioni, Giuseppe; Bacci, Cesare; Bach, Andre; Bachacou, Henri; Bachas, Konstantinos; Backes, Moritz; Backhaus, Malte; Badescu, Elisabeta; Bagnaia, Paolo; Bahinipati, Seema; Bai, Yu; Bailey, David; Bain, Travis; Baines, John; Baker, Oliver Keith; Baker, Mark; Baker, Sarah; Banas, Elzbieta; Banerjee, Piyali; Banerjee, Swagato; Banfi, Danilo; Bangert, Andrea Michelle; Bansal, Vikas; Bansil, Hardeep Singh; Barak, Liron; Baranov, Sergei; Barashkou, Andrei; Barbaro Galtieri, Angela; Barber, Tom; Barberio, Elisabetta Luigia; Barberis, Dario; Barbero, Marlon; Bardin, Dmitri; Barillari, Teresa; Barisonzi, Marcello; Barklow, Timothy; Barlow, Nick; Barnett, Bruce; Barnett, Michael; Baroncelli, Antonio; Barone, Gaetano; Barr, Alan; Barreiro, Fernando; Barreiro Guimarães da Costa, João; Barrillon, Pierre; Bartoldus, Rainer; Barton, Adam Edward; Bartsch, Valeria; Bates, Richard; Batkova, Lucia; Batley, Richard; Battaglia, Andreas; Battistin, Michele; Bauer, Florian; Bawa, Harinder Singh; Beale, Steven; Beau, Tristan; Beauchemin, Pierre-Hugues; Beccherle, Roberto; Bechtle, Philip; Beck, Hans Peter; Becker, Sebastian; Beckingham, Matthew; Becks, Karl-Heinz; Beddall, Andrew; Beddall, Ayda; Bedikian, Sourpouhi; Bednyakov, Vadim; Bee, Christopher; Begel, Michael; Behar Harpaz, Silvia; Behera, Prafulla; Beimforde, Michael; Belanger-Champagne, Camille; Bell, Paul; Bell, William; Bella, Gideon; Bellagamba, Lorenzo; Bellina, Francesco; Bellomo, Massimiliano; Belloni, Alberto; Beloborodova, Olga; Belotskiy, Konstantin; Beltramello, Olga; Ben Ami, Sagi; Benary, Odette; Benchekroun, Driss; Benchouk, Chafik; Bendel, Markus; Benekos, Nektarios; Benhammou, Yan; Benhar Noccioli, Eleonora; Benitez Garcia, Jorge-Armando; Benjamin, Douglas; Benoit, Mathieu; Bensinger, James; Benslama, Kamal; Bentvelsen, Stan; Berge, David; Bergeaas Kuutmann, Elin; Berger, Nicolas; Berghaus, Frank; Berglund, Elina; Beringer, Jürg; Bernat, Pauline; Bernhard, Ralf; Bernius, Catrin; Berry, Tracey; Bertella, Claudia; Bertin, Antonio; Bertinelli, Francesco; Bertolucci, Federico; Besana, Maria Ilaria; Besson, Nathalie; Bethke, Siegfried; Bhimji, Wahid; Bianchi, Riccardo-Maria; Bianco, Michele; Biebel, Otmar; Bieniek, Stephen Paul; Bierwagen, Katharina; Biesiada, Jed; Biglietti, Michela; Bilokon, Halina; Bindi, Marcello; Binet, Sebastien; Bingul, Ahmet; Bini, Cesare; Biscarat, Catherine; Bitenc, Urban; Black, Kevin; Blair, Robert

    2013-01-01

    The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of $\\sqrt{s}$ = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.

  4. Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

    CERN Document Server

    Aad, Georges; Abdallah, Jalal; Abdelalim, Ahmed Ali; Abdesselam, Abdelouahab; Abdinov, Ovsat; Abi, Babak; Abolins, Maris; AbouZeid, Ossama; Abramowicz, Halina; Abreu, Henso; Acerbi, Emilio; Acharya, Bobby Samir; Adamczyk, Leszek; Adams, David; Addy, Tetteh; Adelman, Jahred; Aderholz, Michael; Adomeit, Stefanie; Adragna, Paolo; Adye, Tim; Aefsky, Scott; Aguilar-Saavedra, Juan Antonio; Aharrouche, Mohamed; Ahlen, Steven; Ahles, Florian; Ahmad, Ashfaq; Ahsan, Mahsana; Aielli, Giulio; Akdogan, Taylan; Åkesson, Torsten Paul Ake; Akimoto, Ginga; Akimov, Andrei; Akiyama, Kunihiro; Alam, Mohammad; Alam, Muhammad Aftab; Albert, Justin; Albrand, Solveig; Aleksa, Martin; Aleksandrov, Igor; Alessandria, Franco; Alexa, Calin; Alexander, Gideon; Alexandre, Gauthier; Alexopoulos, Theodoros; Alhroob, Muhammad; Aliev, Malik; Alimonti, Gianluca; Alison, John; Aliyev, Magsud; Allbrooke, Benedict; Allport, Phillip; Allwood-Spiers, Sarah; Almond, John; Aloisio, Alberto; Alon, Raz; Alonso, Alejandro; Alvarez Gonzalez, Barbara; Alviggi, Mariagrazia; Amako, Katsuya; Amaral, Pedro; Amelung, Christoph; Ammosov, Vladimir; Amorim, Antonio; Amorós, Gabriel; Amram, Nir; Anastopoulos, Christos; Ancu, Lucian Stefan; Andari, Nansi; Andeen, Timothy; Anders, Christoph Falk; Anders, Gabriel; Anderson, Kelby; Andreazza, Attilio; Andrei, George Victor; Andrieux, Marie-Laure; Anduaga, Xabier; Angerami, Aaron; Anghinolfi, Francis; Anisenkov, Alexey; Anjos, Nuno; Annovi, Alberto; Antonaki, Ariadni; Antonelli, Mario; Antonov, Alexey; Antos, Jaroslav; Anulli, Fabio; Aoun, Sahar; Aperio Bella, Ludovica; Apolle, Rudi; Arabidze, Giorgi; Aracena, Ignacio; Arai, Yasuo; Arce, Ayana; Arfaoui, Samir; Arguin, Jean-Francois; Arik, Engin; Arik, Metin; Armbruster, Aaron James; Arnaez, Olivier; Arnault, Christian; Artamonov, Andrei; Artoni, Giacomo; Arutinov, David; Asai, Shoji; Asfandiyarov, Ruslan; Ask, Stefan; Å sman, Barbro; Asquith, Lily; Assamagan, Ketevi; Astbury, Alan; Astvatsatourov, Anatoli; Aubert, Bernard; Auge, Etienne; Augsten, Kamil; Aurousseau, Mathieu; Avolio, Giuseppe; Avramidou, Rachel Maria; Axen, David; Ay, Cano; Azuelos, Georges; Azuma, Yuya; Baak, Max; Baccaglioni, Giuseppe; Bacci, Cesare; Bach, Andre; Bachacou, Henri; Bachas, Konstantinos; Backes, Moritz; Backhaus, Malte; Badescu, Elisabeta; Bagnaia, Paolo; Bahinipati, Seema; Bai, Yu; Bailey, David; Bain, Travis; Baines, John; Baker, Oliver Keith; Baker, Mark; Baker, Sarah; Banas, Elzbieta; Banerjee, Piyali; Banerjee, Swagato; Banfi, Danilo; Bangert, Andrea Michelle; Bansal, Vikas; Bansil, Hardeep Singh; Barak, Liron; Baranov, Sergei; Barashkou, Andrei; Barbaro Galtieri, Angela; Barber, Tom; Barberio, Elisabetta Luigia; Barberis, Dario; Barbero, Marlon; Bardin, Dmitri; Barillari, Teresa; Barisonzi, Marcello; Barklow, Timothy; Barlow, Nick; Barnett, Bruce; Barnett, Michael; Baroncelli, Antonio; Barone, Gaetano; Barr, Alan; Barreiro, Fernando; Barreiro Guimarães da Costa, João; Barrillon, Pierre; Bartoldus, Rainer; Barton, Adam Edward; Bartsch, Valeria; Bates, Richard; Batkova, Lucia; Batley, Richard; Battaglia, Andreas; Battistin, Michele; Bauer, Florian; Bawa, Harinder Singh; Beale, Steven; Beau, Tristan; Beauchemin, Pierre-Hugues; Beccherle, Roberto; Bechtle, Philip; Beck, Hans Peter; Becker, Sebastian; Beckingham, Matthew; Becks, Karl-Heinz; Beddall, Andrew; Beddall, Ayda; Bedikian, Sourpouhi; Bednyakov, Vadim; Bee, Christopher; Begel, Michael; Behar Harpaz, Silvia; Behera, Prafulla; Beimforde, Michael; Belanger-Champagne, Camille; Bell, Paul; Bell, William; Bella, Gideon; Bellagamba, Lorenzo; Bellina, Francesco; Bellomo, Massimiliano; Belloni, Alberto; Beloborodova, Olga; Belotskiy, Konstantin; Beltramello, Olga; Ben Ami, Sagi; Benary, Odette; Benchekroun, Driss; Benchouk, Chafik; Bendel, Markus; Benekos, Nektarios; Benhammou, Yan; Benhar Noccioli, Eleonora; Benitez Garcia, Jorge-Armando; Benjamin, Douglas; Benoit, Mathieu; Bensinger, James; Benslama, Kamal; Bentvelsen, Stan; Berge, David; Bergeaas Kuutmann, Elin; Berger, Nicolas; Berghaus, Frank; Berglund, Elina; Beringer, Jürg; Bernat, Pauline; Bernhard, Ralf; Bernius, Catrin; Berry, Tracey; Bertella, Claudia; Bertin, Antonio; Bertinelli, Francesco; Bertolucci, Federico; Besana, Maria Ilaria; Besson, Nathalie; Bethke, Siegfried; Bhimji, Wahid; Bianchi, Riccardo-Maria; Bianco, Michele; Biebel, Otmar; Bieniek, Stephen Paul; Bierwagen, Katharina; Biesiada, Jed; Biglietti, Michela; Bilokon, Halina; Bindi, Marcello; Binet, Sebastien; Bingul, Ahmet; Bini, Cesare; Biscarat, Catherine; Bitenc, Urban; Black, Kevin; Blair, Robert; Blanchard, Jean-Baptiste; Blanchot, Georges; Blazek, Tomas; Blocker, Craig; Blocki, Jacek; Blondel, Alain; Blum, Walter; Blumenschein, Ulrike; Bobbink, Gerjan; Bobrovnikov, Victor; Bocchetta, Simona Serena; Bocci, Andrea; Boddy, Christopher Richard; Boehler, Michael; Boek, Jennifer; Boelaert, Nele; Bogaerts, Joannes Andreas; Bogdanchikov, Alexander; Bogouch, Andrei; Bohm, Christian; Boisvert, Veronique; Bold, Tomasz; Boldea, Venera; Bolnet, Nayanka Myriam; Bona, Marcella; Bondarenko, Valery; Bondioli, Mario; Boonekamp, Maarten; Booth, Chris; Bordoni, Stefania; Borer, Claudia; Borisov, Anatoly; Borissov, Guennadi; Borjanovic, Iris; Borri, Marcello; Borroni, Sara; Bortolotto, Valerio; Bos, Kors; Boscherini, Davide; Bosman, Martine; Boterenbrood, Hendrik; Botterill, David; Bouchami, Jihene; Boudreau, Joseph; Bouhova-Thacker, Evelina Vassileva; Boumediene, Djamel Eddine; Bourdarios, Claire; Bousson, Nicolas; Boveia, Antonio; Boyd, James; Boyko, Igor; Bozhko, Nikolay; Bozovic-Jelisavcic, Ivanka; Bracinik, Juraj; Braem, André; Branchini, Paolo; Brandenburg, George; Brandt, Andrew; Brandt, Gerhard; Brandt, Oleg; Bratzler, Uwe; Brau, Benjamin; Brau, James; Braun, Helmut; Brelier, Bertrand; Bremer, Johan; Brenner, Richard; Bressler, Shikma; Britton, Dave; Brochu, Frederic; Brock, Ian; Brock, Raymond; Brodbeck, Timothy; Brodet, Eyal; Broggi, Francesco; Bromberg, Carl; Bronner, Johanna; Brooijmans, Gustaaf; Brooks, William; Brown, Gareth; Brown, Heather; Bruckman de Renstrom, Pawel; Bruncko, Dusan; Bruneliere, Renaud; Brunet, Sylvie; Bruni, Alessia; Bruni, Graziano; Bruschi, Marco; Buanes, Trygve; Buat, Quentin; Bucci, Francesca; Buchanan, James; Buchanan, Norman; Buchholz, Peter; Buckingham, Ryan; Buckley, Andrew; Buda, Stelian Ioan; Budagov, Ioulian; Budick, Burton; Büscher, Volker; Bugge, Lars; Bulekov, Oleg; Bunse, Moritz; Buran, Torleiv; Burckhart, Helfried; Burdin, Sergey; Burgard, Carsten Daniel; Burgess, Thomas; Burke, Stephen; Busato, Emmanuel; Bussey, Peter; Buszello, Claus-Peter; Butin, François; Butler, Bart; Butler, John; Buttar, Craig; Butterworth, Jonathan; Buttinger, William; Cabrera Urbán, Susana; Caforio, Davide; Cakir, Orhan; Calafiura, Paolo; Calderini, Giovanni; Calfayan, Philippe; Calkins, Robert; Caloba, Luiz; Caloi, Rita; Calvet, David; Calvet, Samuel; Camacho Toro, Reina; Camarri, Paolo; Cambiaghi, Mario; Cameron, David; Caminada, Lea Michaela; Campana, Simone; Campanelli, Mario; Canale, Vincenzo; Canelli, Florencia; Canepa, Anadi; Cantero, Josu; Capasso, Luciano; Capeans Garrido, Maria Del Mar; Caprini, Irinel; Caprini, Mihai; Capriotti, Daniele; Capua, Marcella; Caputo, Regina; Caramarcu, Costin; Cardarelli, Roberto; Carli, Tancredi; Carlino, Gianpaolo; Carminati, Leonardo; Caron, Bryan; Caron, Sascha; Carrillo Montoya, German D; Carter, Antony; Carter, Janet; Carvalho, João; Casadei, Diego; Casado, Maria Pilar; Cascella, Michele; Caso, Carlo; Castaneda Hernandez, Alfredo Martin; Castaneda-Miranda, Elizabeth; Castillo Gimenez, Victoria; Castro, Nuno Filipe; Cataldi, Gabriella; Cataneo, Fernando; Catinaccio, Andrea; Catmore, James; Cattai, Ariella; Cattani, Giordano; Caughron, Seth; Cauz, Diego; Cavalleri, Pietro; Cavalli, Donatella; Cavalli-Sforza, Matteo; Cavasinni, Vincenzo; Ceradini, Filippo; Cerqueira, Augusto Santiago; Cerri, Alessandro; Cerrito, Lucio; Cerutti, Fabio; Cetin, Serkant Ali; Cevenini, Francesco; Chafaq, Aziz; Chakraborty, Dhiman; Chan, Kevin; Chapleau, Bertrand; Chapman, John Derek; Chapman, John Wehrley; Chareyre, Eve; Charlton, Dave; Chavda, Vikash; Chavez Barajas, Carlos Alberto; Cheatham, Susan; Chekanov, Sergei; Chekulaev, Sergey; Chelkov, Gueorgui; Chelstowska, Magda Anna; Chen, Chunhui; Chen, Hucheng; Chen, Shenjian; Chen, Tingyang; Chen, Xin; Cheng, Shaochen; Cheplakov, Alexander; Chepurnov, Vladimir; Cherkaoui El Moursli, Rajaa; Chernyatin, Valeriy; Cheu, Elliott; Cheung, Sing-Leung; Chevalier, Laurent; Chiefari, Giovanni; Chikovani, Leila; Childers, John Taylor; Chilingarov, Alexandre; Chiodini, Gabriele; Chisholm, Andrew; Chizhov, Mihail; Choudalakis, Georgios; Chouridou, Sofia; Christidi, Illectra-Athanasia; Christov, Asen; Chromek-Burckhart, Doris; Chu, Ming-Lee; Chudoba, Jiri; Ciapetti, Guido; Ciba, Krzysztof; Ciftci, Abbas Kenan; Ciftci, Rena; Cinca, Diane; Cindro, Vladimir; Ciobotaru, Matei Dan; Ciocca, Claudia; Ciocio, Alessandra; Cirilli, Manuela; Citterio, Mauro; Ciubancan, Mihai; Clark, Allan G; Clark, Philip James; Cleland, Bill; Clemens, Jean-Claude; Clement, Benoit; Clement, Christophe; Clifft, Roger; Coadou, Yann; Cobal, Marina; Coccaro, Andrea; Cochran, James H; Coe, Paul; Cogan, Joshua Godfrey; Coggeshall, James; Cogneras, Eric; Colas, Jacques; Colijn, Auke-Pieter; Collard, Caroline; Collins, Neil; Collins-Tooth, Christopher; Collot, Johann; Colon, German; Conde Muiño, Patricia; Coniavitis, Elias; Conidi, Maria Chiara; Consonni, Michele; Consorti, Valerio; Constantinescu, Serban; Conta, Claudio; Conventi, Francesco; Cook, James; Cooke, Mark; Cooper, Ben; Cooper-Sarkar, Amanda; Copic, Katherine; Cornelissen, Thijs; Corradi, Massimo; Corriveau, Francois; Cortes-Gonzalez, Arely; Cortiana, Giorgio; Costa, Giuseppe; Costa, María José; Costanzo, Davide; Costin, Tudor; Côté, David; Coura Torres, Rodrigo; Courneyea, Lorraine; Cowan, Glen; Cowden, Christopher; Cox, Brian; Cranmer, Kyle; Crescioli, Francesco; Cristinziani, Markus; Crosetti, Giovanni; Crupi, Roberto; Crépé-Renaudin, Sabine; Cuciuc, Constantin-Mihai; Cuenca Almenar, Cristóbal; Cuhadar Donszelmann, Tulay; Curatolo, Maria; Curtis, Chris; Cuthbert, Cameron; Cwetanski, Peter; Czirr, Hendrik; Czodrowski, Patrick; Czyczula, Zofia; D'Auria, Saverio; D'Onofrio, Monica; D'Orazio, Alessia; Da Silva, Paulo Vitor; Da Via, Cinzia; Dabrowski, Wladyslaw; Dai, Tiesheng; Dallapiccola, Carlo; Dam, Mogens; Dameri, Mauro; Damiani, Daniel; Danielsson, Hans Olof; Dannheim, Dominik; Dao, Valerio; Darbo, Giovanni; Darlea, Georgiana Lavinia; Davey, Will; Davidek, Tomas; Davidson, Nadia; Davidson, Ruth; Davies, Eleanor; Davies, Merlin; Davison, Adam; Davygora, Yuriy; Dawe, Edmund; Dawson, Ian; Dawson, John; Daya, Rozmin; De, Kaushik; de Asmundis, Riccardo; De Castro, Stefano; De Castro Faria Salgado, Pedro; De Cecco, Sandro; de Graat, Julien; De Groot, Nicolo; de Jong, Paul; De La Taille, Christophe; De la Torre, Hector; De Lotto, Barbara; de Mora, Lee; De Nooij, Lucie; De Pedis, Daniele; De Salvo, Alessandro; De Sanctis, Umberto; De Santo, Antonella; De Vivie De Regie, Jean-Baptiste; Dean, Simon; Dearnaley, William James; Debbe, Ramiro; Debenedetti, Chiara; Dedovich, Dmitri; Degenhardt, James; Dehchar, Mohamed; Del Papa, Carlo; Del Peso, Jose; Del Prete, Tarcisio; Delemontex, Thomas; Deliyergiyev, Maksym; Dell'Acqua, Andrea; Dell'Asta, Lidia; Della Pietra, Massimo; della Volpe, Domenico; Delmastro, Marco; Delruelle, Nicolas; Delsart, Pierre-Antoine; Deluca, Carolina; Demers, Sarah; Demichev, Mikhail; Demirkoz, Bilge; Deng, Jianrong; Denisov, Sergey; Derendarz, Dominik; Derkaoui, Jamal Eddine; Derue, Frederic; Dervan, Paul; Desch, Klaus Kurt; Devetak, Erik; Deviveiros, Pier-Olivier; Dewhurst, Alastair; DeWilde, Burton; Dhaliwal, Saminder; Dhullipudi, Ramasudhakar; Di Ciaccio, Anna; Di Ciaccio, Lucia; Di Girolamo, Alessandro; Di Girolamo, Beniamino; Di Luise, Silvestro; Di Mattia, Alessandro; Di Micco, Biagio; Di Nardo, Roberto; Di Simone, Andrea; Di Sipio, Riccardo; Diaz, Marco Aurelio; Diblen, Faruk; Diehl, Edward; Dietrich, Janet; Dietzsch, Thorsten; Diglio, Sara; Dindar Yagci, Kamile; Dingfelder, Jochen; Dionisi, Carlo; Dita, Petre; Dita, Sanda; Dittus, Fridolin; Djama, Fares; Djobava, Tamar; do Vale, Maria Aline Barros; Do Valle Wemans, André; Doan, Thi Kieu Oanh; Dobbs, Matt; Dobinson, Robert; Dobos, Daniel; Dobson, Ellie; Dobson, Marc; Dodd, Jeremy; Doglioni, Caterina; Doherty, Tom; Doi, Yoshikuni; Dolejsi, Jiri; Dolenc, Irena; Dolezal, Zdenek; Dolgoshein, Boris; Dohmae, Takeshi; Donadelli, Marisilvia; Donega, Mauro; Donini, Julien; Dopke, Jens; Doria, Alessandra; Dos Anjos, Andre; Dosil, Mireia; Dotti, Andrea; Dova, Maria-Teresa; Dowell, John; Doxiadis, Alexander; Doyle, Tony; Drasal, Zbynek; Drees, Jürgen; Dressnandt, Nandor; Drevermann, Hans; Driouichi, Chafik; Dris, Manolis; Dubbert, Jörg; Dube, Sourabh; Duchovni, Ehud; Duckeck, Guenter; Dudarev, Alexey; Dudziak, Fanny; Dührssen, Michael; Duerdoth, Ian; Duflot, Laurent; Dufour, Marc-Andre; Dunford, Monica; Duran Yildiz, Hatice; Duxfield, Robert; Dwuznik, Michal; Dydak, Friedrich; Düren, Michael; Ebenstein, William; Ebke, Johannes; Eckweiler, Sebastian; Edmonds, Keith; Edwards, Clive; Edwards, Nicholas Charles; Ehrenfeld, Wolfgang; Ehrich, Thies; Eifert, Till; Eigen, Gerald; Einsweiler, Kevin; Eisenhandler, Eric; Ekelof, Tord; El Kacimi, Mohamed; Ellert, Mattias; Elles, Sabine; Ellinghaus, Frank; Ellis, Katherine; Ellis, Nicolas; Elmsheuser, Johannes; Elsing, Markus; Emeliyanov, Dmitry; Engelmann, Roderich; Engl, Albert; Epp, Brigitte; Eppig, Andrew; Erdmann, Johannes; Ereditato, Antonio; Eriksson, Daniel; Ernst, Jesse; Ernst, Michael; Ernwein, Jean; Errede, Deborah; Errede, Steven; Ertel, Eugen; Escalier, Marc; Escobar, Carlos; Espinal Curull, Xavier; Esposito, Bellisario; Etienne, Francois; Etienvre, Anne-Isabelle; Etzion, Erez; Evangelakou, Despoina; Evans, Hal; Fabbri, Laura; Fabre, Caroline; Fakhrutdinov, Rinat; Falciano, Speranza; Fang, Yaquan; Fanti, Marcello; Farbin, Amir; Farilla, Addolorata; Farley, Jason; Farooque, Trisha; Farrington, Sinead; Farthouat, Philippe; Fassnacht, Patrick; Fassouliotis, Dimitrios; Fatholahzadeh, Baharak; Favareto, Andrea; Fayard, Louis; Fazio, Salvatore; Febbraro, Renato; Federic, Pavol; Fedin, Oleg; Fedorko, Woiciech; Fehling-Kaschek, Mirjam; Feligioni, Lorenzo; Fellmann, Denis; Feng, Cunfeng; Feng, Eric; Fenyuk, Alexander; Ferencei, Jozef; Ferland, Jonathan; Fernando, Waruna; Ferrag, Samir; Ferrando, James; Ferrara, Valentina; Ferrari, Arnaud; Ferrari, Pamela; Ferrari, Roberto; Ferreira de Lima, Danilo Enoque; Ferrer, Antonio; Ferrer, Maria Lorenza; Ferrere, Didier; Ferretti, Claudio; Ferretto Parodi, Andrea; Fiascaris, Maria; Fiedler, Frank; Filipčič, Andrej; Filippas, Anastasios; Filthaut, Frank; Fincke-Keeler, Margret; Fiolhais, Miguel; Fiorini, Luca; Firan, Ana; Fischer, Gordon; Fischer, Peter; Fisher, Matthew; Flechl, Martin; Fleck, Ivor; Fleckner, Johanna; Fleischmann, Philipp; Fleischmann, Sebastian; Flick, Tobias; Floderus, Anders; Flores Castillo, Luis; Flowerdew, Michael; Fokitis, Manolis; Fonseca Martin, Teresa; Forbush, David Alan; Formica, Andrea; Forti, Alessandra; Fortin, Dominique; Foster, Joe; Fournier, Daniel; Foussat, Arnaud; Fowler, Andrew; Fowler, Ken; Fox, Harald; Francavilla, Paolo; Franchino, Silvia; Francis, David; Frank, Tal; Franklin, Melissa; Franz, Sebastien; Fraternali, Marco; Fratina, Sasa; French, Sky; Friedrich, Felix; Froeschl, Robert; Froidevaux, Daniel; Frost, James; Fukunaga, Chikara; Fullana Torregrosa, Esteban; Fuster, Juan; Gabaldon, Carolina; Gabizon, Ofir; Gadfort, Thomas; Gadomski, Szymon; Gagliardi, Guido; Gagnon, Pauline; Galea, Cristina; Gallas, Elizabeth; Gallo, Valentina Santina; Gallop, Bruce; Gallus, Petr; Gan, KK; Gao, Yongsheng; Gapienko, Vladimir; Gaponenko, Andrei; Garberson, Ford; Garcia-Sciveres, Maurice; García, Carmen; García Navarro, José Enrique; Gardner, Robert; Garelli, Nicoletta; Garitaonandia, Hegoi; Garonne, Vincent; Garvey, John; Gatti, Claudio; Gaudio, Gabriella; Gaur, Bakul; Gauthier, Lea; Gavrilenko, Igor; Gay, Colin; Gaycken, Goetz; Gayde, Jean-Christophe; Gazis, Evangelos; Ge, Peng; Gee, Norman; Geerts, Daniël Alphonsus Adrianus; Geich-Gimbel, Christoph; Gellerstedt, Karl; Gemme, Claudia; Gemmell, Alistair; Genest, Marie-Hélène; Gentile, Simonetta; George, Matthias; George, Simon; Gerlach, Peter; Gershon, Avi; Geweniger, Christoph; Ghazlane, Hamid; Ghodbane, Nabil; Giacobbe, Benedetto; Giagu, Stefano; Giakoumopoulou, Victoria; Giangiobbe, Vincent; Gianotti, Fabiola; Gibbard, Bruce; Gibson, Adam; Gibson, Stephen; Gilbert, Laura; Gilewsky, Valentin; Gillberg, Dag; Gillman, Tony; Gingrich, Douglas; Ginzburg, Jonatan; Giokaris, Nikos; Giordani, MarioPaolo; Giordano, Raffaele; Giorgi, Francesco Michelangelo; Giovannini, Paola; Giraud, Pierre-Francois; Giugni, Danilo; Giunta, Michele; Giusti, Paolo; Gjelsten, Bø rge Kile; Gladilin, Leonid; Glasman, Claudia; Glatzer, Julian; Glazov, Alexandre; Glitza, Karl-Walter; Glonti, George; Goddard, Jack Robert; Godfrey, Jennifer; Godlewski, Jan; Goebel, Martin; Göpfert, Thomas; Goeringer, Christian; Gössling, Claus; Göttfert, Tobias; Goldfarb, Steven; Golling, Tobias; Gomes, Agostinho; Gomez Fajardo, Luz Stella; Gonçalo, Ricardo; Goncalves Pinto Firmino Da Costa, Joao; Gonella, Laura; Gonidec, Allain; Gonzalez, Saul; González de la Hoz, Santiago; Gonzalez Parra, Garoe; Gonzalez Silva, Laura; Gonzalez-Sevilla, Sergio; Goodson, Jeremiah Jet; Goossens, Luc; Gorbounov, Petr Andreevich; Gordon, Howard; Gorelov, Igor; Gorfine, Grant; Gorini, Benedetto; Gorini, Edoardo; Gorišek, Andrej; Gornicki, Edward; Gorokhov, Serguei; Goryachev, Vladimir; Gosdzik, Bjoern; Gosselink, Martijn; Gostkin, Mikhail Ivanovitch; Gough Eschrich, Ivo; Gouighri, Mohamed; Goujdami, Driss; Goulette, Marc Phillippe; Goussiou, Anna; Goy, Corinne; Gozpinar, Serdar; Grabowska-Bold, Iwona; Grafström, Per; Grahn, Karl-Johan; Grancagnolo, Francesco; Grancagnolo, Sergio; Grassi, Valerio; Gratchev, Vadim; Grau, Nathan; Gray, Heather; Gray, Julia Ann; Graziani, Enrico; Grebenyuk, Oleg; Greenshaw, Timothy; Greenwood, Zeno Dixon; Gregersen, Kristian; Gregor, Ingrid-Maria; Grenier, Philippe; Griffiths, Justin; Grigalashvili, Nugzar; Grillo, Alexander; Grinstein, Sebastian; Grishkevich, Yaroslav; Grivaz, Jean-Francois; Groh, Manfred; Gross, Eilam; Grosse-Knetter, Joern; Groth-Jensen, Jacob; Grybel, Kai; Guarino, Victor; Guest, Daniel; Guicheney, Christophe; Guida, Angelo; Guindon, Stefan; Guler, Hulya; Gunther, Jaroslav; Guo, Bin; Guo, Jun; Gupta, Ambreesh; Gusakov, Yury; Gushchin, Vladimir; Gutierrez, Phillip; Guttman, Nir; Gutzwiller, Olivier; Guyot, Claude; Gwenlan, Claire; Gwilliam, Carl; Haas, Andy; Haas, Stefan; Haber, Carl; Hackenburg, Robert; Hadavand, Haleh Khani; Hadley, David; Haefner, Petra; Hahn, Ferdinand; Haider, Stefan; Hajduk, Zbigniew; Hakobyan, Hrachya; Hall, David; Haller, Johannes; Hamacher, Klaus; Hamal, Petr; Hamer, Matthias; Hamilton, Andrew; Hamilton, Samuel; Han, Hongguang; Han, Liang; Hanagaki, Kazunori; Hanawa, Keita; Hance, Michael; Handel, Carsten; Hanke, Paul; Hansen, John Renner; Hansen, Jø rgen Beck; Hansen, Jorn Dines; Hansen, Peter Henrik; Hansson, Per; Hara, Kazuhiko; Hare, Gabriel; Harenberg, Torsten; Harkusha, Siarhei; Harper, Devin; Harrington, Robert; Harris, Orin; Harrison, Karl; Hartert, Jochen; Hartjes, Fred; Haruyama, Tomiyoshi; Harvey, Alex; Hasegawa, Satoshi; Hasegawa, Yoji; Hassani, Samira; Hatch, Mark; Hauff, Dieter; Haug, Sigve; Hauschild, Michael; Hauser, Reiner; Havranek, Miroslav; Hawes, Brian; Hawkes, Christopher; Hawkings, Richard John; Hawkins, Anthony David; Hawkins, Donovan; Hayakawa, Takashi; Hayashi, Takayasu; Hayden, Daniel; Hayward, Helen; Haywood, Stephen; Hazen, Eric; He, Mao; Head, Simon; Hedberg, Vincent; Heelan, Louise; Heim, Sarah; Heinemann, Beate; Heisterkamp, Simon; Helary, Louis; Heller, Claudio; Heller, Matthieu; Hellman, Sten; Hellmich, Dennis; Helsens, Clement; Henderson, Robert; Henke, Michael; Henrichs, Anna; Henriques Correia, Ana Maria; Henrot-Versille, Sophie; Henry-Couannier, Frédéric; Hensel, Carsten; Henß, Tobias; Hernandez, Carlos Medina; Hernández Jiménez, Yesenia; Herrberg, Ruth; Hershenhorn, Alon David; Herten, Gregor; Hertenberger, Ralf; Hervas, Luis; Hesketh, Gavin Grant; Hessey, Nigel; Higón-Rodriguez, Emilio; Hill, Daniel; Hill, John; Hill, Norman; Hiller, Karl Heinz; Hillert, Sonja; Hillier, Stephen; Hinchliffe, Ian; Hines, Elizabeth; Hirose, Minoru; Hirsch, Florian; Hirschbuehl, Dominic; Hobbs, John; Hod, Noam; Hodgkinson, Mark; Hodgson, Paul; Hoecker, Andreas; Hoeferkamp, Martin; Hoffman, Julia; Hoffmann, Dirk; Hohlfeld, Marc; Holder, Martin; Holmgren, Sven-Olof; Holy, Tomas; Holzbauer, Jenny; Homma, Yasuhiro; Hong, Tae Min; Hooft van Huysduynen, Loek; Horazdovsky, Tomas; Horn, Claus; Horner, Stephan; Hostachy, Jean-Yves; Hou, Suen; Houlden, Michael; Hoummada, Abdeslam; Howarth, James; Howell, David; Hristova, Ivana; Hrivnac, Julius; Hruska, Ivan; Hryn'ova, Tetiana; Hsu, Pai-hsien Jennifer; Hsu, Shih-Chieh; Huang, Guang Shun; Hubacek, Zdenek; Hubaut, Fabrice; Huegging, Fabian; Huettmann, Antje; Huffman, Todd Brian; Hughes, Emlyn; Hughes, Gareth; Hughes-Jones, Richard; Huhtinen, Mika; Hurst, Peter; Hurwitz, Martina; Husemann, Ulrich; Huseynov, Nazim; Huston, Joey; Huth, John; Iacobucci, Giuseppe; Iakovidis, Georgios; Ibbotson, Michael; Ibragimov, Iskander; Ichimiya, Ryo; Iconomidou-Fayard, Lydia; Idarraga, John; Iengo, Paolo; Igonkina, Olga; Ikegami, Yoichi; Ikeno, Masahiro; Ilchenko, Yuri; Iliadis, Dimitrios; Ilic, Nikolina; Imori, Masatoshi; Ince, Tayfun; Inigo-Golfin, Joaquin; Ioannou, Pavlos; Iodice, Mauro; Ippolito, Valerio; Irles Quiles, Adrian; Isaksson, Charlie; Ishikawa, Akimasa; Ishino, Masaya; Ishmukhametov, Renat; Issever, Cigdem; Istin, Serhat; Ivashin, Anton; Iwanski, Wieslaw; Iwasaki, Hiroyuki; Izen, Joseph; Izzo, Vincenzo; Jackson, Brett; Jackson, John; Jackson, Paul; Jaekel, Martin; Jain, Vivek; Jakobs, Karl; Jakobsen, Sune; Jakubek, Jan; Jana, Dilip; Jankowski, Ernest; Jansen, Eric; Jansen, Hendrik; Jantsch, Andreas; Janus, Michel; Jarlskog, Göran; Jeanty, Laura; Jelen, Kazimierz; Jen-La Plante, Imai; Jenni, Peter; Jeremie, Andrea; Jež, Pavel; Jézéquel, Stéphane; Jha, Manoj Kumar; Ji, Haoshuang; Ji, Weina; Jia, Jiangyong; Jiang, Yi; Jimenez Belenguer, Marcos; Jin, Ge; Jin, Shan; Jinnouchi, Osamu; Joergensen, Morten Dam; Joffe, David; Johansen, Lars; Johansen, Marianne; Johansson, Erik; Johansson, Per; Johnert, Sebastian; Johns, Kenneth; Jon-And, Kerstin; Jones, Graham; Jones, Roger; Jones, Tegid; Jones, Tim; Jonsson, Ove; Joram, Christian; Jorge, Pedro; Joseph, John; Jovicevic, Jelena; Jovin, Tatjana; Ju, Xiangyang; Jung, Christian; Jungst, Ralph Markus; Juranek, Vojtech; Jussel, Patrick; Juste Rozas, Aurelio; Kabachenko, Vasily; Kabana, Sonja; Kaci, Mohammed; Kaczmarska, Anna; Kadlecik, Peter; Kado, Marumi; Kagan, Harris; Kagan, Michael; Kaiser, Steffen; Kajomovitz, Enrique; Kalinin, Sergey; Kalinovskaya, Lidia; Kama, Sami; Kanaya, Naoko; Kaneda, Michiru; Kaneti, Steven; Kanno, Takayuki; Kantserov, Vadim; Kanzaki, Junichi; Kaplan, Benjamin; Kapliy, Anton; Kaplon, Jan; Kar, Deepak; Karagoz, Muge; Karnevskiy, Mikhail; Karr, Kristo; Kartvelishvili, Vakhtang; Karyukhin, Andrey; Kashif, Lashkar; Kasieczka, Gregor; Kasmi, Azzedine; Kass, Richard; Kastanas, Alex; Kataoka, Mayuko; Kataoka, Yousuke; Katsoufis, Elias; Katzy, Judith; Kaushik, Venkatesh; Kawagoe, Kiyotomo; Kawamoto, Tatsuo; Kawamura, Gen; Kayl, Manuel; Kazanin, Vassili; Kazarinov, Makhail; Keeler, Richard; Kehoe, Robert; Keil, Markus; Kekelidze, George; Kennedy, John; Kenney, Christopher John; Kenyon, Mike; Kepka, Oldrich; Kerschen, Nicolas; Kerševan, Borut Paul; Kersten, Susanne; Kessoku, Kohei; Keung, Justin; Khakzad, Mohsen; Khalil-zada, Farkhad; Khandanyan, Hovhannes; Khanov, Alexander; Kharchenko, Dmitri; Khodinov, Alexander; Kholodenko, Anatoli; Khomich, Andrei; Khoo, Teng Jian; Khoriauli, Gia; Khoroshilov, Andrey; Khovanskiy, Nikolai; Khovanskiy, Valery; Khramov, Evgeniy; Khubua, Jemal; Kim, Hyeon Jin; Kim, Min Suk; Kim, Shinhong; Kimura, Naoki; Kind, Oliver; King, Barry; King, Matthew; King, Robert Steven Beaufoy; Kirk, Julie; Kirsch, Lawrence; Kiryunin, Andrey; Kishimoto, Tomoe; Kisielewska, Danuta; Kittelmann, Thomas; Kiver, Andrey; Kladiva, Eduard; Klaiber-Lodewigs, Jonas; Klein, Max; Klein, Uta; Kleinknecht, Konrad; Klemetti, Miika; Klier, Amit; Klimek, Pawel; Klimentov, Alexei; Klingenberg, Reiner; Klinger, Joel Alexander; Klinkby, Esben; Klioutchnikova, Tatiana; Klok, Peter; Klous, Sander; Kluge, Eike-Erik; Kluge, Thomas; Kluit, Peter; Kluth, Stefan; Knecht, Neil; Kneringer, Emmerich; Knobloch, Juergen; Knoops, Edith; Knue, Andrea; Ko, Byeong Rok; Kobayashi, Tomio; Kobel, Michael; Kocian, Martin; Kodys, Peter; Köneke, Karsten; König, Adriaan; Koenig, Sebastian; Köpke, Lutz; Koetsveld, Folkert; Koevesarki, Peter; Koffas, Thomas; Koffeman, Els; Kogan, Lucy Anne; Kohn, Fabian; Kohout, Zdenek; Kohriki, Takashi; Koi, Tatsumi; Kokott, Thomas; Kolachev, Guennady; Kolanoski, Hermann; Kolesnikov, Vladimir; Koletsou, Iro; Koll, James; Kollefrath, Michael; Kolya, Scott; Komar, Aston; Komori, Yuto; Kondo, Takahiko; Kono, Takanori; Kononov, Anatoly; Konoplich, Rostislav; Konstantinidis, Nikolaos; Kootz, Andreas; Koperny, Stefan; Korcyl, Krzysztof; Kordas, Kostantinos; Koreshev, Victor; Korn, Andreas; Korol, Aleksandr; Korolkov, Ilya; Korolkova, Elena; Korotkov, Vladislav; Kortner, Oliver; Kortner, Sandra; Kostyukhin, Vadim; Kotamäki, Miikka Juhani; Kotov, Sergey; Kotov, Vladislav; Kotwal, Ashutosh; Kourkoumelis, Christine; Kouskoura, Vasiliki; Koutsman, Alex; Kowalewski, Robert Victor; Kowalski, Tadeusz; Kozanecki, Witold; Kozhin, Anatoly; Kral, Vlastimil; Kramarenko, Viktor; Kramberger, Gregor; Krasny, Mieczyslaw Witold; Krasznahorkay, Attila; Kraus, James; Kraus, Jana; Kreisel, Arik; Krejci, Frantisek; Kretzschmar, Jan; Krieger, Nina; Krieger, Peter; Kroeninger, Kevin; Kroha, Hubert; Kroll, Joe; Kroseberg, Juergen; Krstic, Jelena; Kruchonak, Uladzimir; Krüger, Hans; Kruker, Tobias; Krumnack, Nils; Krumshteyn, Zinovii; Kruth, Andre; Kubota, Takashi; Kuday, Sinan; Kuehn, Susanne; Kugel, Andreas; Kuhl, Thorsten; Kuhn, Dietmar; Kukhtin, Victor; Kulchitsky, Yuri; Kuleshov, Sergey; Kummer, Christian; Kuna, Marine; Kundu, Nikhil; Kunkle, Joshua; Kupco, Alexander; Kurashige, Hisaya; Kurata, Masakazu; Kurochkin, Yurii; Kus, Vlastimil; Kuwertz, Emma Sian; Kuze, Masahiro; Kvita, Jiri; Kwee, Regina; La Rosa, Alessandro; La Rotonda, Laura; Labarga, Luis; Labbe, Julien; Lablak, Said; Lacasta, Carlos; Lacava, Francesco; Lacker, Heiko; Lacour, Didier; Lacuesta, Vicente Ramón; Ladygin, Evgueni; Lafaye, Remi; Laforge, Bertrand; Lagouri, Theodota; Lai, Stanley; Laisne, Emmanuel; Lamanna, Massimo; Lampen, Caleb; Lampl, Walter; Lancon, Eric; Landgraf, Ulrich; Landon, Murrough; Lane, Jenna; Lange, Clemens; Lankford, Andrew; Lanni, Francesco; Lantzsch, Kerstin; Laplace, Sandrine; Lapoire, Cecile; Laporte, Jean-Francois; Lari, Tommaso; Larionov, Anatoly; Larner, Aimee; Lasseur, Christian; Lassnig, Mario; Laurelli, Paolo; Lavorini, Vincenzo; Lavrijsen, Wim; Laycock, Paul; Lazarev, Alexandre; Le Dortz, Olivier; Le Guirriec, Emmanuel; Le Maner, Christophe; Le Menedeu, Eve; Lebel, Céline; LeCompte, Thomas; Ledroit-Guillon, Fabienne Agnes Marie; Lee, Hurng-Chun; Lee, Jason; Lee, Shih-Chang; Lee, Lawrence; Lefebvre, Michel; Legendre, Marie; Leger, Annie; LeGeyt, Benjamin; Legger, Federica; Leggett, Charles; Lehmacher, Marc; Lehmann Miotto, Giovanna; Lei, Xiaowen; Leite, Marco Aurelio Lisboa; Leitner, Rupert; Lellouch, Daniel; Leltchouk, Mikhail; Lemmer, Boris; Lendermann, Victor; Leney, Katharine; Lenz, Tatiana; Lenzen, Georg; Lenzi, Bruno; Leonhardt, Kathrin; Leontsinis, Stefanos; Leroy, Claude; Lessard, Jean-Raphael; Lesser, Jonas; Lester, Christopher; Leung Fook Cheong, Annabelle; Levêque, Jessica; Levin, Daniel; Levinson, Lorne; Levitski, Mikhail; Lewis, Adrian; Lewis, George; Leyko, Agnieszka; Leyton, Michael; Li, Bo; Li, Haifeng; Li, Shu; Li, Xuefei; Liang, Zhijun; Liao, Hongbo; Liberti, Barbara; Lichard, Peter; Lichtnecker, Markus; Lie, Ki; Liebig, Wolfgang; Lifshitz, Ronen; Lilley, Joseph; Limbach, Christian; Limosani, Antonio; Limper, Maaike; Lin, Simon; Linde, Frank; Linnemann, James; Lipeles, Elliot; Lipinsky, Lukas; Lipniacka, Anna; Liss, Tony; Lissauer, David; Lister, Alison; Litke, Alan; Liu, Chuanlei; Liu, Dong; Liu, Hao; Liu, Jianbei; Liu, Minghui; Liu, Yanwen; Livan, Michele; Livermore, Sarah; Lleres, Annick; Llorente Merino, Javier; Lloyd, Stephen; Lobodzinska, Ewelina; Loch, Peter; Lockman, William; Loddenkoetter, Thomas; Loebinger, Fred; Loginov, Andrey; Loh, Chang Wei; Lohse, Thomas; Lohwasser, Kristin; Lokajicek, Milos; Loken, James; Lombardo, Vincenzo Paolo; Long, Robin Eamonn; Lopes, Lourenco; Lopez Mateos, David; Lorenz, Jeanette; Lorenzo Martinez, Narei; Losada, Marta; Loscutoff, Peter; Lo Sterzo, Francesco; Losty, Michael; Lou, Xinchou; Lounis, Abdenour; Loureiro, Karina; Love, Jeremy; Love, Peter; Lowe, Andrew; Lu, Feng; Lubatti, Henry; Luci, Claudio; Lucotte, Arnaud; Ludwig, Andreas; Ludwig, Dörthe; Ludwig, Inga; Ludwig, Jens; Luehring, Frederick; Luijckx, Guy; Lumb, Debra; Luminari, Lamberto; Lund, Esben; Lund-Jensen, Bengt; Lundberg, Björn; Lundberg, Johan; Lundquist, Johan; Lungwitz, Matthias; Lutz, Gerhard; Lynn, David; Lys, Jeremy; Lytken, Else; Ma, Hong; Ma, Lian Liang; Macana Goia, Jorge Andres; Maccarrone, Giovanni; Macchiolo, Anna; Maček, Boštjan; Machado Miguens, Joana; Mackeprang, Rasmus; Madaras, Ronald; Mader, Wolfgang; Maenner, Reinhard; Maeno, Tadashi; Mättig, Peter; Mättig, Stefan; Magnoni, Luca; Magradze, Erekle; Mahalalel, Yair; Mahboubi, Kambiz; Mahout, Gilles; Maiani, Camilla; Maidantchik, Carmen; Maio, Amélia; Majewski, Stephanie; Makida, Yasuhiro; Makovec, Nikola; Mal, Prolay; Malaescu, Bogdan; Malecki, Pawel; Malecki, Piotr; Maleev, Victor; Malek, Fairouz; Mallik, Usha; Malon, David; Malone, Caitlin; Maltezos, Stavros; Malyshev, Vladimir; Malyukov, Sergei; Mameghani, Raphael; Mamuzic, Judita; Manabe, Atsushi; Mandelli, Luciano; Mandić, Igor; Mandrysch, Rocco; Maneira, José; Mangeard, Pierre-Simon; Manhaes de Andrade Filho, Luciano; Manjavidze, Ioseb; Mann, Alexander; Manning, Peter; Manousakis-Katsikakis, Arkadios; Mansoulie, Bruno; Manz, Andreas; Mapelli, Alessandro; Mapelli, Livio; March, Luis; Marchand, Jean-Francois; Marchese, Fabrizio; Marchiori, Giovanni; Marcisovsky, Michal; Marin, Alexandru; Marino, Christopher; Marroquim, Fernando; Marshall, Robin; Marshall, Zach; Martens, Kalen; Marti-Garcia, Salvador; Martin, Andrew; Martin, Brian; Martin, Brian; Martin, Franck Francois; Martin, Jean-Pierre; Martin, Philippe; Martin, Tim; Martin, Victoria Jane; Martin dit Latour, Bertrand; Martin-Haugh, Stewart; Martinez, Mario; Martinez Outschoorn, Verena; Martyniuk, Alex; Marx, Marilyn; Marzano, Francesco; Marzin, Antoine; Masetti, Lucia; Mashimo, Tetsuro; Mashinistov, Ruslan; Masik, Jiri; Maslennikov, Alexey; Massa, Ignazio; Massaro, Graziano; Massol, Nicolas; Mastrandrea, Paolo; Mastroberardino, Anna; Masubuchi, Tatsuya; Mathes, Markus; Matricon, Pierre; Matsumoto, Hiroshi; Matsunaga, Hiroyuki; Matsushita, Takashi; Mattravers, Carly; Maugain, Jean-Marie; Maurer, Julien; Maxfield, Stephen; Maximov, Dmitriy; May, Edward; Mayne, Anna; Mazini, Rachid; Mazur, Michael; Mazzanti, Marcello; Mazzoni, Enrico; Mc Kee, Shawn Patrick; McCarn, Allison; McCarthy, Robert; McCarthy, Tom; McCubbin, Norman; McFarlane, Kenneth; Mcfayden, Josh; McGlone, Helen; Mchedlidze, Gvantsa; McLaren, Robert Andrew; Mclaughlan, Tom; McMahon, Steve; McPherson, Robert; Meade, Andrew; Mechnich, Joerg; Mechtel, Markus; Medinnis, Mike; Meera-Lebbai, Razzak; Meguro, Tatsuma; Mehdiyev, Rashid; Mehlhase, Sascha; Mehta, Andrew; Meier, Karlheinz; Meirose, Bernhard; Melachrinos, Constantinos; Mellado Garcia, Bruce Rafael; Mendoza Navas, Luis; Meng, Zhaoxia; Mengarelli, Alberto; Menke, Sven; Menot, Claude; Meoni, Evelin; Mercurio, Kevin Michael; Mermod, Philippe; Merola, Leonardo; Meroni, Chiara; Merritt, Frank; Merritt, Hayes; Messina, Andrea; Metcalfe, Jessica; Mete, Alaettin Serhan; Meyer, Carsten; Meyer, Christopher; Meyer, Jean-Pierre; Meyer, Jochen; Meyer, Joerg; Meyer, Thomas Christian; Meyer, W Thomas; Miao, Jiayuan; Michal, Sebastien; Micu, Liliana; Middleton, Robin; Migas, Sylwia; Mijović, Liza; Mikenberg, Giora; Mikestikova, Marcela; Mikuž, Marko; Miller, David; Miller, Robert; Mills, Bill; Mills, Corrinne; Milov, Alexander; Milstead, David; Milstein, Dmitry; Minaenko, Andrey; Miñano Moya, Mercedes; Minashvili, Irakli; Mincer, Allen; Mindur, Bartosz; Mineev, Mikhail; Ming, Yao; Mir, Lluisa-Maria; Mirabelli, Giovanni; Miralles Verge, Lluis; Misiejuk, Andrzej; Mitrevski, Jovan; Mitrofanov, Gennady; Mitsou, Vasiliki A; Mitsui, Shingo; Miyagawa, Paul; Miyazaki, Kazuki; Mjörnmark, Jan-Ulf; Moa, Torbjoern; Mockett, Paul; Moed, Shulamit; Moeller, Victoria; Mönig, Klaus; Möser, Nicolas; Mohapatra, Soumya; Mohr, Wolfgang; Mohrdieck-Möck, Susanne; Moisseev, Artemy; Moles-Valls, Regina; Molina-Perez, Jorge; Monk, James; Monnier, Emmanuel; Montesano, Simone; Monticelli, Fernando; Monzani, Simone; Moore, Roger; Moorhead, Gareth; Mora Herrera, Clemencia; Moraes, Arthur; Morange, Nicolas; Morel, Julien; Morello, Gianfranco; Moreno, Deywis; Moreno Llácer, María; Morettini, Paolo; Morgenstern, Marcus; Morii, Masahiro; Morin, Jerome; Morley, Anthony Keith; Mornacchi, Giuseppe; Morozov, Sergey; Morris, John; Morvaj, Ljiljana; Moser, Hans-Guenther; Mosidze, Maia; Moss, Josh; Mount, Richard; Mountricha, Eleni; Mouraviev, Sergei; Moyse, Edward; Mudrinic, Mihajlo; Mueller, Felix; Mueller, James; Mueller, Klemens; Müller, Thomas; Mueller, Timo; Muenstermann, Daniel; Muir, Alex; Munwes, Yonathan; Murray, Bill; Mussche, Ido; Musto, Elisa; Myagkov, Alexey; Nadal, Jordi; Nagai, Koichi; Nagano, Kunihiro; Nagarkar, Advait; Nagasaka, Yasushi; Nagel, Martin; Nairz, Armin Michael; Nakahama, Yu; Nakamura, Koji; Nakamura, Tomoaki; Nakano, Itsuo; Nanava, Gizo; Napier, Austin; Narayan, Rohin; Nash, Michael; Nation, Nigel; Nattermann, Till; Naumann, Thomas; Navarro, Gabriela; Neal, Homer; Nebot, Eduardo; Nechaeva, Polina; Neep, Thomas James; Negri, Andrea; Negri, Guido; Nektarijevic, Snezana; Nelson, Andrew; Nelson, Silke; Nelson, Timothy Knight; Nemecek, Stanislav; Nemethy, Peter; Nepomuceno, Andre Asevedo; Nessi, Marzio; Neubauer, Mark; Neusiedl, Andrea; Neves, Ricardo; Nevski, Pavel; Newman, Paul; Nguyen Thi Hong, Van; Nickerson, Richard; Nicolaidou, Rosy; Nicolas, Ludovic; Nicquevert, Bertrand; Niedercorn, Francois; Nielsen, Jason; Niinikoski, Tapio; Nikiforou, Nikiforos; Nikiforov, Andriy; Nikolaenko, Vladimir; Nikolaev, Kirill; Nikolic-Audit, Irena; Nikolics, Katalin; Nikolopoulos, Konstantinos; Nilsen, Henrik; Nilsson, Paul; Ninomiya, Yoichi; Nisati, Aleandro; Nishiyama, Tomonori; Nisius, Richard; Nodulman, Lawrence; Nomachi, Masaharu; Nomidis, Ioannis; Nordberg, Markus; Nordkvist, Bjoern; Norton, Peter; Novakova, Jana; Nozaki, Mitsuaki; Nozka, Libor; Nugent, Ian Michael; Nuncio-Quiroz, Adriana-Elizabeth; Nunes Hanninger, Guilherme; Nunnemann, Thomas; Nurse, Emily; O'Brien, Brendan Joseph; O'Neale, Steve; O'Neil, Dugan; O'Shea, Val; Oakes, Louise Beth; Oakham, Gerald; Oberlack, Horst; Ocariz, Jose; Ochi, Atsuhiko; Oda, Susumu; Odaka, Shigeru; Odier, Jerome; Ogren, Harold; Oh, Alexander; Oh, Seog; Ohm, Christian; Ohshima, Takayoshi; Ohshita, Hidetoshi; Ohsugi, Takashi; Okada, Shogo; Okawa, Hideki; Okumura, Yasuyuki; Okuyama, Toyonobu; Olariu, Albert; Olcese, Marco; Olchevski, Alexander; Olivares Pino, Sebastian Andres; Oliveira, Miguel Alfonso; Oliveira Damazio, Denis; Oliver Garcia, Elena; Olivito, Dominick; Olszewski, Andrzej; Olszowska, Jolanta; Omachi, Chihiro; Onofre, António; Onyisi, Peter; Oram, Christopher; Oreglia, Mark; Oren, Yona; Orestano, Domizia; Orlov, Iliya; Oropeza Barrera, Cristina; Orr, Robert; Osculati, Bianca; Ospanov, Rustem; Osuna, Carlos; Otero y Garzon, Gustavo; Ottersbach, John; Ouchrif, Mohamed; Ouellette, Eric; Ould-Saada, Farid; Ouraou, Ahmimed; Ouyang, Qun; Ovcharova, Ana; Owen, Mark; Owen, Simon; Ozcan, Veysi Erkcan; Ozturk, Nurcan; Pacheco Pages, Andres; Padilla Aranda, Cristobal; Pagan Griso, Simone; Paganis, Efstathios; Paige, Frank; Pais, Preema; Pajchel, Katarina; Palacino, Gabriel; Paleari, Chiara; Palestini, Sandro; Pallin, Dominique; Palma, Alberto; Palmer, Jody; Pan, Yibin; Panagiotopoulou, Evgenia; Panes, Boris; Panikashvili, Natalia; Panitkin, Sergey; Pantea, Dan; Panuskova, Monika; Paolone, Vittorio; Papadelis, Aras; Papadopoulou, Theodora; Paramonov, Alexander; Park, Woochun; Parker, Andy; Parodi, Fabrizio; Parsons, John; Parzefall, Ulrich; Pasqualucci, Enrico; Passaggio, Stefano; Passeri, Antonio; Pastore, Fernanda; Pastore, Francesca; Pásztor, Gabriella; Pataraia, Sophio; Patel, Nikhul; Pater, Joleen; Patricelli, Sergio; Pauly, Thilo; Pecsy, Martin; Pedraza Morales, Maria Isabel; Peleganchuk, Sergey; Peng, Haiping; Pengo, Ruggero; Penning, Bjoern; Penson, Alexander; Penwell, John; Perantoni, Marcelo; Perez, Kerstin; Perez Cavalcanti, Tiago; Perez Codina, Estel; Pérez García-Estañ, María Teresa; Perez Reale, Valeria; Perini, Laura; Pernegger, Heinz; Perrino, Roberto; Perrodo, Pascal; Persembe, Seda; Perus, Antoine; Peshekhonov, Vladimir; Peters, Krisztian; Petersen, Brian; Petersen, Jorgen; Petersen, Troels; Petit, Elisabeth; Petridis, Andreas; Petridou, Chariclia; Petrolo, Emilio; Petrucci, Fabrizio; Petschull, Dennis; Petteni, Michele; Pezoa, Raquel; Phan, Anna; Phillips, Peter William; Piacquadio, Giacinto; Piccaro, Elisa; Piccinini, Maurizio; Piec, Sebastian Marcin; Piegaia, Ricardo; Pignotti, David; Pilcher, James; Pilkington, Andrew; Pina, João Antonio; Pinamonti, Michele; Pinder, Alex; Pinfold, James; Ping, Jialun; Pinto, Belmiro; Pirotte, Olivier; Pizio, Caterina; Placakyte, Ringaile; Plamondon, Mathieu; Pleier, Marc-Andre; Pleskach, Anatoly; Poblaguev, Andrei; Poddar, Sahill; Podlyski, Fabrice; Poggioli, Luc; Poghosyan, Tatevik; Pohl, Martin; Polci, Francesco; Polesello, Giacomo; Policicchio, Antonio; Polini, Alessandro; Poll, James; Polychronakos, Venetios; Pomarede, Daniel Marc; Pomeroy, Daniel; Pommès, Kathy; Pontecorvo, Ludovico; Pope, Bernard; Popeneciu, Gabriel Alexandru; Popovic, Dragan; Poppleton, Alan; Portell Bueso, Xavier; Posch, Christoph; Pospelov, Guennady; Pospisil, Stanislav; Potrap, Igor; Potter, Christina; Potter, Christopher; Poulard, Gilbert; Poveda, Joaquin; Pozdnyakov, Valery; Prabhu, Robindra; Pralavorio, Pascal; Pranko, Aliaksandr; Prasad, Srivas; Pravahan, Rishiraj; Prell, Soeren; Pretzl, Klaus Peter; Pribyl, Lukas; Price, Darren; Price, Joe; Price, Lawrence; Price, Michael John; Prieur, Damien; Primavera, Margherita; Prokofiev, Kirill; Prokoshin, Fedor; Protopopescu, Serban; Proudfoot, James; Prudent, Xavier; Przybycien, Mariusz; Przysiezniak, Helenka; Psoroulas, Serena; Ptacek, Elizabeth; Pueschel, Elisa; Purdham, John; Purohit, Milind; Puzo, Patrick; Pylypchenko, Yuriy; Qian, Jianming; Qian, Zuxuan; Qin, Zhonghua; Quadt, Arnulf; Quarrie, David; Quayle, William; Quinonez, Fernando; Raas, Marcel; Radescu, Voica; Radics, Balint; Radloff, Peter; Rador, Tonguc; Ragusa, Francesco; Rahal, Ghita; Rahimi, Amir; Rahm, David; Rajagopalan, Srinivasan; Rammensee, Michael; Rammes, Marcus; Randle-Conde, Aidan Sean; Randrianarivony, Koloina; Ratoff, Peter; Rauscher, Felix; Rave, Tobias Christian; Raymond, Michel; Read, Alexander Lincoln; Rebuzzi, Daniela; Redelbach, Andreas; Redlinger, George; Reece, Ryan; Reeves, Kendall; Reichold, Armin; Reinherz-Aronis, Erez; Reinsch, Andreas; Reisinger, Ingo; Rembser, Christoph; Ren, Zhongliang; Renaud, Adrien; Renkel, Peter; Rescigno, Marco; Resconi, Silvia; Resende, Bernardo; Reznicek, Pavel; Rezvani, Reyhaneh; Richards, Alexander; Richter, Robert; Richter-Was, Elzbieta; Ridel, Melissa; Rijpstra, Manouk; Rijssenbeek, Michael; Rimoldi, Adele; Rinaldi, Lorenzo; Rios, Ryan Randy; Riu, Imma; Rivoltella, Giancesare; Rizatdinova, Flera; Rizvi, Eram; Robertson, Steven; Robichaud-Veronneau, Andree; Robinson, Dave; Robinson, James; Robinson, Mary; Robson, Aidan; Rocha de Lima, Jose Guilherme; Roda, Chiara; Roda Dos Santos, Denis; Rodriguez, Diego; Roe, Adam; Roe, Shaun; Røhne, Ole; Rojo, Victoria; Rolli, Simona; Romaniouk, Anatoli; Romano, Marino; Romanov, Victor; Romeo, Gaston; Romero Adam, Elena; Roos, Lydia; Ros, Eduardo; Rosati, Stefano; Rosbach, Kilian; Rose, Anthony; Rose, Matthew; Rosenbaum, Gabriel; Rosenberg, Eli; Rosendahl, Peter Lundgaard; Rosenthal, Oliver; Rosselet, Laurent; Rossetti, Valerio; Rossi, Elvira; Rossi, Leonardo Paolo; Rotaru, Marina; Roth, Itamar; Rothberg, Joseph; Rousseau, David; Royon, Christophe; Rozanov, Alexander; Rozen, Yoram; Ruan, Xifeng; Rubinskiy, Igor; Ruckert, Benjamin; Ruckstuhl, Nicole; Rud, Viacheslav; Rudolph, Christian; Rudolph, Gerald; Rühr, Frederik; Ruggieri, Federico; Ruiz-Martinez, Aranzazu; Rumiantsev, Viktor; Rumyantsev, Leonid; Runge, Kay; Rurikova, Zuzana; Rusakovich, Nikolai; Rust, Dave; Rutherfoord, John; Ruwiedel, Christoph; Ruzicka, Pavel; Ryabov, Yury; Ryadovikov, Vasily; Ryan, Patrick; Rybar, Martin; Rybkin, Grigori; Ryder, Nick; Rzaeva, Sevda; Saavedra, Aldo; Sadeh, Iftach; Sadrozinski, Hartmut; Sadykov, Renat; Safai Tehrani, Francesco; Sakamoto, Hiroshi; Salamanna, Giuseppe; Salamon, Andrea; Saleem, Muhammad; Salihagic, Denis; Salnikov, Andrei; Salt, José; Salvachua Ferrando, Belén; Salvatore, Daniela; Salvatore, Pasquale Fabrizio; Salvucci, Antonio; Salzburger, Andreas; Sampsonidis, Dimitrios; Samset, Björn Hallvard; Sanchez, Arturo; Sanchez Martinez, Victoria; Sandaker, Heidi; Sander, Heinz Georg; Sanders, Michiel; Sandhoff, Marisa; Sandoval, Tanya; Sandoval, Carlos; Sandstroem, Rikard; Sandvoss, Stephan; Sankey, Dave; Sansoni, Andrea; Santamarina Rios, Cibran; Santoni, Claudio; Santonico, Rinaldo; Santos, Helena; Saraiva, João; Sarangi, Tapas; Sarkisyan-Grinbaum, Edward; Sarri, Francesca; Sartisohn, Georg; Sasaki, Osamu; Sasaki, Takashi; Sasao, Noboru; Satsounkevitch, Igor; Sauvage, Gilles; Sauvan, Emmanuel; Sauvan, Jean-Baptiste; Savard, Pierre; Savinov, Vladimir; Savu, Dan Octavian; Sawyer, Lee; Saxon, David; Says, Louis-Pierre; Sbarra, Carla; Sbrizzi, Antonio; Scallon, Olivia; Scannicchio, Diana; Scarcella, Mark; Schaarschmidt, Jana; Schacht, Peter; Schäfer, Uli; Schaepe, Steffen; Schaetzel, Sebastian; Schaffer, Arthur; Schaile, Dorothee; Schamberger, R~Dean; Schamov, Andrey; Scharf, Veit; Schegelsky, Valery; Scheirich, Daniel; Schernau, Michael; Scherzer, Max; Schiavi, Carlo; Schieck, Jochen; Schioppa, Marco; Schlenker, Stefan; Schlereth, James; Schmidt, Evelyn; Schmieden, Kristof; Schmitt, Christian; Schmitt, Sebastian; Schmitz, Martin; Schöning, André; Schott, Matthias; Schouten, Doug; Schovancova, Jaroslava; Schram, Malachi; Schroeder, Christian; Schroer, Nicolai; Schuh, Silvia; Schuler, Georges; Schultens, Martin Johannes; Schultes, Joachim; Schultz-Coulon, Hans-Christian; Schulz, Holger; Schumacher, Jan; Schumacher, Markus; Schumm, Bruce; Schune, Philippe; Schwanenberger, Christian; Schwartzman, Ariel; Schwemling, Philippe; Schwienhorst, Reinhard; Schwierz, Rainer; Schwindling, Jerome; Schwindt, Thomas; Schwoerer, Maud; Scott, Bill; Searcy, Jacob; Sedov, George; Sedykh, Evgeny; Segura, Ester; Seidel, Sally; Seiden, Abraham; Seifert, Frank; Seixas, José; Sekhniaidze, Givi; Selbach, Karoline Elfriede; 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Skottowe, Hugh Philip; Skovpen, Kirill; Skubic, Patrick; Skvorodnev, Nikolai; Slater, Mark; Slavicek, Tomas; Sliwa, Krzysztof; Sloper, John erik; Smakhtin, Vladimir; Smart, Ben; Smirnov, Sergei; Smirnov, Yury; Smirnova, Lidia; Smirnova, Oxana; Smith, Ben Campbell; Smith, Douglas; Smith, Kenway; Smizanska, Maria; Smolek, Karel; Snesarev, Andrei; Snow, Steve; Snow, Joel; Snuverink, Jochem; Snyder, Scott; Soares, Mara; Sobie, Randall; Sodomka, Jaromir; Soffer, Abner; Solans, Carlos; Solar, Michael; Solc, Jaroslav; Soldatov, Evgeny; Soldevila, Urmila; Solfaroli Camillocci, Elena; Solodkov, Alexander; Solovyanov, Oleg; Soni, Nitesh; Sopko, Vit; Sopko, Bruno; Sosebee, Mark; Soualah, Rachik; Soukharev, Andrey; Spagnolo, Stefania; Spanò, Francesco; Spighi, Roberto; Spigo, Giancarlo; Spila, Federico; Spiwoks, Ralf; Spousta, Martin; Spreitzer, Teresa; Spurlock, Barry; St Denis, Richard Dante; Stahlman, Jonathan; Stamen, Rainer; Stanecka, Ewa; Stanek, Robert; Stanescu, Cristian; Stapnes, Steinar; 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Sushkov, Serge; Susinno, Giancarlo; Sutton, Mark; Suzuki, Yu; Suzuki, Yuta; Svatos, Michal; Sviridov, Yuri; Swedish, Stephen; Sykora, Ivan; Sykora, Tomas; Szeless, Balazs; Sánchez, Javier; Ta, Duc; Tackmann, Kerstin; Taffard, Anyes; Tafirout, Reda; Taiblum, Nimrod; Takahashi, Yuta; Takai, Helio; Takashima, Ryuichi; Takeda, Hiroshi; Takeshita, Tohru; Takubo, Yosuke; Talby, Mossadek; Talyshev, Alexey; Tamsett, Matthew; Tanaka, Junichi; Tanaka, Reisaburo; Tanaka, Satoshi; Tanaka, Shuji; Tanaka, Yoshito; Tanasijczuk, Andres Jorge; Tani, Kazutoshi; Tannoury, Nancy; Tappern, Geoffrey; Tapprogge, Stefan; Tardif, Dominique; Tarem, Shlomit; Tarrade, Fabien; Tartarelli, Giuseppe Francesco; Tas, Petr; Tasevsky, Marek; Tassi, Enrico; Tatarkhanov, Mous; Tayalati, Yahya; Taylor, Christopher; Taylor, Frank; Taylor, Geoffrey; Taylor, Wendy; Teinturier, Marthe; Teixeira Dias Castanheira, Matilde; Teixeira-Dias, Pedro; Temming, Kim Katrin; Ten Kate, Herman; Teng, Ping-Kun; Terada, Susumu; Terashi, Koji; Terron, Juan; Testa, Marianna; Teuscher, Richard; Thadome, Jocelyn; Therhaag, Jan; Theveneaux-Pelzer, Timothée; Thioye, Moustapha; Thoma, Sascha; Thomas, Juergen; Thompson, Emily; Thompson, Paul; Thompson, Peter; Thompson, Stan; Thomsen, Lotte Ansgaard; Thomson, Evelyn; Thomson, Mark; Thun, Rudolf; Tian, Feng; Tibbetts, Mark James; Tic, Tomáš; Tikhomirov, Vladimir; Tikhonov, Yury; Timoshenko, Sergey; Tipton, Paul; Tique Aires Viegas, Florbela De Jes; Tisserant, Sylvain; Tobias, Jürgen; Toczek, Barbara; Todorov, Theodore; Todorova-Nova, Sharka; Toggerson, Brokk; Tojo, Junji; Tokár, Stanislav; Tokunaga, Kaoru; Tokushuku, Katsuo; Tollefson, Kirsten; Tomoto, Makoto; Tompkins, Lauren; Toms, Konstantin; Tong, Guoliang; Tonoyan, Arshak; Topfel, Cyril; Topilin, Nikolai; Torchiani, Ingo; Torrence, Eric; Torres, Heberth; Torró Pastor, Emma; Toth, Jozsef; Touchard, Francois; Tovey, Daniel; Trefzger, Thomas; Tremblet, Louis; Tricoli, Alesandro; Trigger, Isabel Marian; Trincaz-Duvoid, Sophie; Trinh, Thi Nguyet; Tripiana, Martin; Trischuk, William; Trivedi, Arjun; Trocmé, Benjamin; Troncon, Clara; Trottier-McDonald, Michel; Trzebinski, Maciej; Trzupek, Adam; Tsarouchas, Charilaos; Tseng, Jeffrey; Tsiakiris, Menelaos; Tsiareshka, Pavel; Tsionou, Dimitra; Tsipolitis, Georgios; Tsiskaridze, Vakhtang; Tskhadadze, Edisher; Tsukerman, Ilya; Tsulaia, Vakhtang; Tsung, Jieh-Wen; Tsuno, Soshi; Tsybychev, Dmitri; Tua, Alan; Tudorache, Alexandra; Tudorache, Valentina; Tuggle, Joseph; Turala, Michal; Turecek, Daniel; Turk Cakir, Ilkay; Turlay, Emmanuel; Turra, Ruggero; Tuts, Michael; Tykhonov, Andrii; Tylmad, Maja; Tyndel, Mike; Tzanakos, George; Uchida, Kirika; Ueda, Ikuo; Ueno, Ryuichi; Ugland, Maren; Uhlenbrock, Mathias; Uhrmacher, Michael; Ukegawa, Fumihiko; Unal, Guillaume; Underwood, David; Undrus, Alexander; Unel, Gokhan; Unno, Yoshinobu; Urbaniec, Dustin; Usai, Giulio; Uslenghi, Massimiliano; Vacavant, Laurent; Vacek, Vaclav; Vachon, Brigitte; Vahsen, Sven; Valenta, Jan; Valente, Paolo; Valentinetti, Sara; Valkar, Stefan; Valladolid Gallego, Eva; Vallecorsa, Sofia; Valls Ferrer, Juan Antonio; van der Graaf, Harry; van der Kraaij, Erik; Van Der Leeuw, Robin; van der Poel, Egge; van der Ster, Daniel; van Eldik, Niels; van Gemmeren, Peter; van Kesteren, Zdenko; van Vulpen, Ivo; Vanadia, Marco; Vandelli, Wainer; Vandoni, Giovanna; Vaniachine, Alexandre; Vankov, Peter; Vannucci, Francois; Varela Rodriguez, Fernando; Vari, Riccardo; Varnes, Erich; Varouchas, Dimitris; Vartapetian, Armen; Varvell, Kevin; Vassilakopoulos, Vassilios; Vazeille, Francois; Vegni, Guido; Veillet, Jean-Jacques; Vellidis, Constantine; Veloso, Filipe; Veness, Raymond; Veneziano, Stefano; Ventura, Andrea; Ventura, Daniel; Venturi, Manuela; Venturi, Nicola; Vercesi, Valerio; Verducci, Monica; Verkerke, Wouter; Vermeulen, Jos; Vest, Anja; Vetterli, Michel; Vichou, Irene; Vickey, Trevor; Vickey Boeriu, Oana Elena; Viehhauser, Georg; Viel, Simon; Villa, Mauro; Villaplana Perez, Miguel; Vilucchi, Elisabetta; Vincter, Manuella; Vinek, Elisabeth; Vinogradov, Vladimir; Virchaux, Marc; Virzi, Joseph; Vitells, Ofer; Viti, Michele; Vivarelli, Iacopo; Vives Vaque, Francesc; Vlachos, Sotirios; Vladoiu, Dan; Vlasak, Michal; Vlasov, Nikolai; Vogel, Adrian; Vokac, Petr; Volpi, Guido; Volpi, Matteo; Volpini, Giovanni; von der Schmitt, Hans; von Loeben, Joerg; von Radziewski, Holger; von Toerne, Eckhard; Vorobel, Vit; Vorobiev, Alexander; Vorwerk, Volker; Vos, Marcel; Voss, Rudiger; Voss, Thorsten Tobias; Vossebeld, Joost; Vranjes, Nenad; Vranjes Milosavljevic, Marija; Vrba, Vaclav; Vreeswijk, Marcel; Vu Anh, Tuan; Vuillermet, Raphael; Vukotic, Ilija; Wagner, Wolfgang; Wagner, Peter; Wahlen, Helmut; Wakabayashi, Jun; Walbersloh, Jorg; Walch, Shannon; Walder, James; Walker, Rodney; Walkowiak, Wolfgang; Wall, Richard; Waller, Peter; Wang, Chiho; Wang, Haichen; Wang, Hulin; Wang, Jike; Wang, Jin; Wang, Joshua C; Wang, Rui; Wang, Song-Ming; Warburton, Andreas; Ward, Patricia; Warsinsky, Markus; Watkins, Peter; Watson, Alan; Watson, Ian; Watson, Miriam; Watts, Gordon; Watts, Stephen; Waugh, Anthony; Waugh, Ben; Weber, Marc; Weber, Michele; Weber, Pavel; Weidberg, Anthony; Weigell, Philipp; Weingarten, Jens; Weiser, Christian; Wellenstein, Hermann; Wells, Phillippa; Wen, Mei; Wenaus, Torre; Wendland, Dennis; Wendler, Shanti; Weng, Zhili; Wengler, Thorsten; Wenig, Siegfried; Wermes, Norbert; Werner, Matthias; Werner, Per; Werth, Michael; Wessels, Martin; Weydert, Carole; Whalen, Kathleen; Wheeler-Ellis, Sarah Jane; Whitaker, Scott; White, Andrew; White, Martin; Whitehead, Samuel Robert; Whiteson, Daniel; Whittington, Denver; Wicek, Francois; Wicke, Daniel; Wickens, Fred; Wiedenmann, Werner; Wielers, Monika; Wienemann, Peter; Wiglesworth, Craig; Wiik, Liv Antje Mari; Wijeratne, Peter Alexander; Wildauer, Andreas; Wildt, Martin Andre; Wilhelm, Ivan; Wilkens, Henric George; Will, Jonas Zacharias; Williams, Eric; Williams, Hugh; Willis, William; Willocq, Stephane; Wilson, John; Wilson, Michael Galante; Wilson, Alan; Wingerter-Seez, Isabelle; Winkelmann, Stefan; Winklmeier, Frank; Wittgen, Matthias; Wolter, Marcin Wladyslaw; Wolters, Helmut; Wong, Wei-Cheng; Wooden, Gemma; Wosiek, Barbara; Wotschack, Jorg; Woudstra, Martin; Wozniak, Krzysztof; Wraight, Kenneth; Wright, Catherine; Wright, Michael; Wrona, Bozydar; Wu, Sau Lan; Wu, Xin; Wu, Yusheng; Wulf, Evan; Wunstorf, Renate; Wynne, Benjamin; Xella, Stefania; Xiao, Meng; Xie, Song; Xie, Yigang; Xu, Chao; Xu, Da; Xu, Guofa; Yabsley, Bruce; Yacoob, Sahal; Yamada, Miho; Yamaguchi, Hiroshi; Yamamoto, Akira; Yamamoto, Kyoko; Yamamoto, Shimpei; Yamamura, Taiki; Yamanaka, Takashi; Yamaoka, Jared; Yamazaki, Takayuki; Yamazaki, Yuji; Yan, Zhen; Yang, Haijun; Yang, Un-Ki; Yang, Yi; Yang, Yi; Yang, Zhaoyu; Yanush, Serguei; Yao, Yushu; Yasu, Yoshiji; Ybeles Smit, Gabriel Valentijn; Ye, Jingbo; Ye, Shuwei; Yilmaz, Metin; Yoosoofmiya, Reza; Yorita, Kohei; Yoshida, Riktura; Young, Charles; Youssef, Saul; Yu, Dantong; Yu, Jaehoon; Yu, Jie; Yuan, Li; Yurkewicz, Adam; Zabinski, Bartlomiej; Zaets, Vassilli; Zaidan, Remi; Zaitsev, Alexander; Zajacova, Zuzana; Zanello, Lucia; Zarzhitsky, Pavel; Zaytsev, Alexander; Zeitnitz, Christian; Zeller, Michael; Zeman, Martin; Zemla, Andrzej; Zendler, Carolin; Zenin, Oleg; Ženiš, Tibor; Zenonos, Zenonas; Zenz, Seth; Zerwas, Dirk; Zevi della Porta, Giovanni; Zhan, Zhichao; Zhang, Dongliang; Zhang, Huaqiao; Zhang, Jinlong; Zhang, Xueyao; Zhang, Zhiqing; Zhao, Long; Zhao, Tianchi; Zhao, Zhengguo; Zhemchugov, Alexey; Zheng, Shuchen; Zhong, Jiahang; Zhou, Bing; Zhou, Ning; Zhou, Yue; Zhu, Cheng Guang; Zhu, Hongbo; Zhu, Junjie; Zhu, Yingchun; Zhuang, Xuai; Zhuravlov, Vadym; Zieminska, Daria; Zimmermann, Robert; Zimmermann, Simone; Zimmermann, Stephanie; Ziolkowski, Michael; Zitoun, Robert; Živković, Lidija; Zmouchko, Viatcheslav; Zobernig, Georg; Zoccoli, Antonio; Zolnierowski, Yves; Zsenei, Andras; zur Nedden, Martin; Zutshi, Vishnu; Zwalinski, Lukasz

    2013-01-01

    The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of $\\sqrt{s}$ = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.

  5. Jet Energy Scale and its Uncertainties using the Heavy Ion Jet Reconstruction Algorithm in pp Collisions

    CERN Document Server

    Puri, Akshat; The ATLAS collaboration

    2017-01-01

    ATLAS uses a jet reconstruction algorithm in heavy ion collisions that takes as input calorimeter towers of size $0.1 \\times \\pi/32$ in $\\Delta\\eta \\times \\Delta\\phi$ and iteratively determines the underlying event background. This algorithm, which is different from the standard jet reconstruction used in ATLAS, is also used in the proton-proton collisions used as reference data for the Pb+Pb and p+Pb. This poster provides details of the heavy ion jet reconstruction algorithm and its performance in pp collisions. The calibration procedure is described in detail and cross checks using photon- jet balance are shown. The uncertainties on the jet energy scale and the jet energy resolution are described.

  6. Scale-dependent estimates of the growth of forecast uncertainties in a global prediction system

    Science.gov (United States)

    Žagar, Nedjeljka; Horvat, Martin; Zaplotnik, Žiga; Magnusson, Linus

    2017-04-01

    The representation of the growth of forecast errors by simple parametric models has a long tradition in numerical weather prediction (NWP). A well-known three-parameter model introduced by A. Dalcher and E. Kalnay in 1987 describes the error growth rate proportional to the amount by which the errors fall short of saturation. This standard model has traditionally been applied to estimate the root mean square errors of the geopotential height at 500 hPa level in extratropics. The two model parameters, the so-called α and β terms, have been used to discuss the chaotic error growth and the growth due to model deficiencies. Geopotential height field at 500 hPa is dominated by large-scale features and quasi-geostrophic balance which is well analysed by data assimilation schemes. Small scales which tend to grow at a faster rate than the larger scales of motions, have little variance at 500 hPa. It is thus interesting to provide a picture of the forecast errors growth as a function of scale from the initial uncertainties simulated by the operational ensemble prediction systems. We conducted such study to assess the scale-dependent growth of forecast errors based on a 50-member global forecast ensemble of the European Centre for Medium Range Weather Forecasts. Simulated forecast errors are fitted by a new parametric model with an analytical solution given by a combination of hyperbolic tangent functions. The new fit does not involve computation of the time derivatives of empirical data and it proves robust to reliably model the error growth across many scales. The results quantify a scale-dependent increase of the period of a slow exponential growth. The asymptotic errors in each scale are computed from the model constants. According to the new fit, the range of useful prediction skill, estimated as a scale when the growth of simulated forecast errors reaches 60% of their asymptotic values is around one week in large scales and 2-3 days at 1000 km scale. These estimates

  7. Sources of uncertainties in modelling black carbon at the global scale

    Directory of Open Access Journals (Sweden)

    E. Vignati

    2010-03-01

    Full Text Available Our understanding of the global black carbon (BC cycle is essentially qualitative due to uncertainties in our knowledge of its properties. This work investigates two source of uncertainties in modelling black carbon: those due to the use of different schemes for BC ageing and its removal rate in the global Transport-Chemistry model TM5 and those due to the uncertainties in the definition and quantification of the observations, which propagate through to both the emission inventories, and the measurements used for the model evaluation.

    The schemes for the atmospheric processing of black carbon that have been tested with the model are (i a simple approach considering BC as bulk aerosol and a simple treatment of the removal with fixed 70% of in-cloud black carbon concentrations scavenged by clouds and removed when rain is present and (ii a more complete description of microphysical ageing within an aerosol dynamics model, where removal is coupled to the microphysical properties of the aerosol, which results in a global average of 40% in-cloud black carbon that is scavenged in clouds and subsequently removed by rain, thus resulting in a longer atmospheric lifetime. This difference is reflected in comparisons between both sets of modelled results and the measurements. Close to the sources, both anthropogenic and vegetation fire source regions, the model results do not differ significantly, indicating that the emissions are the prevailing mechanism determining the concentrations and the choice of the aerosol scheme does not influence the levels. In more remote areas such as oceanic and polar regions the differences can be orders of magnitude, due to the differences between the two schemes. The more complete description reproduces the seasonal trend of the black carbon observations in those areas, although not always the magnitude of the signal, while the more simplified approach underestimates black carbon concentrations by orders of

  8. Sources of uncertainties in modelling Black Carbon at the global scale

    Directory of Open Access Journals (Sweden)

    F. Cavalli

    2009-11-01

    Full Text Available Our understanding of the global black carbon cycle is essentially qualitative due to uncertainties in our knowledge of the properties of black carbon. This work investigates uncertainties related to modelling black carbon: due to the use of different schemes for BC ageing and its removal rate in the global Transport-Chemistry model TM5 and due to the uncertainties in the definition and quantification of observed black carbon, which propagate through to both the emission inventories, and the measurements used for the model evaluation.

    The schemes for the atmospheric processing of black carbon that have been tested with the model are (i a simple approach considering black carbon as bulk aerosol and a simple treatment in the removal and (ii a more complete description of microphysical aging within an aerosol dynamics model, where removal is coupled to the microphysical properties of the aerosol. In the first approach a fixed 70% of black carbon is scavenged in clouds and removed when rain is present. The second leads to a global average of 40% black carbon that is scavenged in clouds and subsequently removed by rain, thus resulting in a longer lifetime. This difference is reflected in comparisons between both sets of modelled results and the measurements. Close to the sources, both anthropogenic and vegetation fire source regions, the model results do not differ significantly, showing that the emissions are the prevailing mechanism determining the concentrations and the choice of the aerosol scheme does not influence the levels. In more remote areas such as oceanic and polar regions the differences can be orders of magnitude, due to the differences between the two schemes. The more complete description reproduces the seasonal trend of the black carbon observations in those areas, although not always the magnitude of the signal, while the more simplified approach underestimates black carbon concentrations by orders of magnitude.

  9. Sources of uncertainties in modelling black carbon at the global scale

    Science.gov (United States)

    Vignati, E.; Karl, M.; Krol, M.; Wilson, J.; Stier, P.; Cavalli, F.

    2010-03-01

    Our understanding of the global black carbon (BC) cycle is essentially qualitative due to uncertainties in our knowledge of its properties. This work investigates two source of uncertainties in modelling black carbon: those due to the use of different schemes for BC ageing and its removal rate in the global Transport-Chemistry model TM5 and those due to the uncertainties in the definition and quantification of the observations, which propagate through to both the emission inventories, and the measurements used for the model evaluation. The schemes for the atmospheric processing of black carbon that have been tested with the model are (i) a simple approach considering BC as bulk aerosol and a simple treatment of the removal with fixed 70% of in-cloud black carbon concentrations scavenged by clouds and removed when rain is present and (ii) a more complete description of microphysical ageing within an aerosol dynamics model, where removal is coupled to the microphysical properties of the aerosol, which results in a global average of 40% in-cloud black carbon that is scavenged in clouds and subsequently removed by rain, thus resulting in a longer atmospheric lifetime. This difference is reflected in comparisons between both sets of modelled results and the measurements. Close to the sources, both anthropogenic and vegetation fire source regions, the model results do not differ significantly, indicating that the emissions are the prevailing mechanism determining the concentrations and the choice of the aerosol scheme does not influence the levels. In more remote areas such as oceanic and polar regions the differences can be orders of magnitude, due to the differences between the two schemes. The more complete description reproduces the seasonal trend of the black carbon observations in those areas, although not always the magnitude of the signal, while the more simplified approach underestimates black carbon concentrations by orders of magnitude. The sensitivity to wet

  10. The rainfall erosivity factor in the Czech Republic and its uncertainty

    Science.gov (United States)

    Hanel, Martin; Máca, Petr; Bašta, Petr; Vlnas, Radek; Pech, Pavel

    2016-10-01

    In the present paper, the rainfall erosivity factor (R factor) for the area of the Czech Republic is assessed. Based on 10 min data for 96 stations and corresponding R factor estimates, a number of spatial interpolation methods are applied and cross-validated. These methods include inverse distance weighting, standard, ordinary, and regression kriging with parameters estimated by the method of moments and restricted maximum likelihood, and a generalized least-squares (GLS) model. For the regression-based methods, various statistics of monthly precipitation as well as geographical indices are considered as covariates. In addition to the uncertainty originating from spatial interpolation, the uncertainty due to estimation of the rainfall kinetic energy (needed for calculation of the R factor) as well as the effect of record length and spatial coverage are also addressed. Finally, the contribution of each source of uncertainty is quantified. The average R factor for the area of the Czech Republic is 640 MJ ha-1 mm h-1, with values for the individual stations ranging between 320 and 1520 MJ ha-1 mm h-1. Among various spatial interpolation methods, the GLS model relating the R factor to the altitude, longitude, mean precipitation, and mean fraction of precipitation above the 95th percentile of monthly precipitation performed best. Application of the GLS model also reduced the uncertainty due to the record length, which is substantial when the R factor is estimated for individual sites. Our results revealed that reasonable estimates of the R factor can be obtained even from relatively short records (15-20 years), provided sufficient spatial coverage and covariates are available.

  11. Methods for Quantifying the Uncertainties of LSIT Test Parameters, Test Results, and Full-Scale Mixing Performance Using Models Developed from Scaled Test Data

    Energy Technology Data Exchange (ETDEWEB)

    Piepel, Gregory F. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Cooley, Scott K. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Kuhn, William L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Rector, David R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Heredia-Langner, Alejandro [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-05-01

    This report discusses the statistical methods for quantifying uncertainties in 1) test responses and other parameters in the Large Scale Integrated Testing (LSIT), and 2) estimates of coefficients and predictions of mixing performance from models that relate test responses to test parameters. Testing at a larger scale has been committed to by Bechtel National, Inc. and the U.S. Department of Energy (DOE) to “address uncertainties and increase confidence in the projected, full-scale mixing performance and operations” in the Waste Treatment and Immobilization Plant (WTP).

  12. Structural uncertainty in air mass factor calculation for NO2 and HCHO satellite retrievals

    Science.gov (United States)

    Lorente, Alba; Folkert Boersma, K.; Yu, Huan; Dörner, Steffen; Hilboll, Andreas; Richter, Andreas; Liu, Mengyao; Lamsal, Lok N.; Barkley, Michael; De Smedt, Isabelle; Van Roozendael, Michel; Wang, Yang; Wagner, Thomas; Beirle, Steffen; Lin, Jin-Tai; Krotkov, Nickolay; Stammes, Piet; Wang, Ping; Eskes, Henk J.; Krol, Maarten

    2017-03-01

    Air mass factor (AMF) calculation is the largest source of uncertainty in NO2 and HCHO satellite retrievals in situations with enhanced trace gas concentrations in the lower troposphere. Structural uncertainty arises when different retrieval methodologies are applied within the scientific community to the same satellite observations. Here, we address the issue of AMF structural uncertainty via a detailed comparison of AMF calculation methods that are structurally different between seven retrieval groups for measurements from the Ozone Monitoring Instrument (OMI). We estimate the escalation of structural uncertainty in every sub-step of the AMF calculation process. This goes beyond the algorithm uncertainty estimates provided in state-of-the-art retrievals, which address the theoretical propagation of uncertainties for one particular retrieval algorithm only. We find that top-of-atmosphere reflectances simulated by four radiative transfer models (RTMs) (DAK, McArtim, SCIATRAN and VLIDORT) agree within 1.5 %. We find that different retrieval groups agree well in the calculations of altitude resolved AMFs from different RTMs (to within 3 %), and in the tropospheric AMFs (to within 6 %) as long as identical ancillary data (surface albedo, terrain height, cloud parameters and trace gas profile) and cloud and aerosol correction procedures are being used. Structural uncertainty increases sharply when retrieval groups use their preference for ancillary data, cloud and aerosol correction. On average, we estimate the AMF structural uncertainty to be 42 % over polluted regions and 31 % over unpolluted regions, mostly driven by substantial differences in the a priori trace gas profiles, surface albedo and cloud parameters. Sensitivity studies for one particular algorithm indicate that different cloud correction approaches result in substantial AMF differences in polluted conditions (5 to 40 % depending on cloud fraction and cloud pressure, and 11 % on average) even for low

  13. Environmental impact and risk assessments and key factors contributing to the overall uncertainties.

    Science.gov (United States)

    Salbu, Brit

    2016-01-01

    There is a significant number of nuclear and radiological sources that have contributed, are still contributing, or have the potential to contribute to radioactive contamination of the environment in the future. To protect the environment from radioactive contamination, impact and risk assessments are performed prior to or during a release event, short or long term after deposition or prior and after implementation of countermeasures. When environmental impact and risks are assessed, however, a series of factors will contribute to the overall uncertainties. To provide environmental impact and risk assessments, information on processes, kinetics and a series of input variables is needed. Adding problems such as variability, questionable assumptions, gaps in knowledge, extrapolations and poor conceptual model structures, a series of factors are contributing to large and often unacceptable uncertainties in impact and risk assessments. Information on the source term and the release scenario is an essential starting point in impact and risk models; the source determines activity concentrations and atom ratios of radionuclides released, while the release scenario determine the physico-chemical forms of released radionuclides such as particle size distribution, structure and density. Releases will most often contain other contaminants such as metals, and due to interactions, contaminated sites should be assessed as a multiple stressor scenario. Following deposition, a series of stressors, interactions and processes will influence the ecosystem transfer of radionuclide species and thereby influence biological uptake (toxicokinetics) and responses (toxicodynamics) in exposed organisms. Due to the variety of biological species, extrapolation is frequently needed to fill gaps in knowledge e.g., from effects to no effects, from effects in one organism to others, from one stressor to mixtures. Most toxtests are, however, performed as short term exposure of adult organisms

  14. FACTOR ANALYSIS OF THE ELKINS HYPNOTIZABILITY SCALE

    Science.gov (United States)

    Elkins, Gary; Johnson, Aimee K.; Johnson, Alisa J.; Sliwinski, Jim

    2015-01-01

    Assessment of hypnotizability can provide important information for hypnosis research and practice. The Elkins Hypnotizability Scale (EHS) consists of 12 items and was developed to provide a time-efficient measure for use in both clinical and laboratory settings. The EHS has been shown to be a reliable measure with support for convergent validity with the Stanford Hypnotic Susceptibility Scale, Form C (r = .821, p < .001). The current study examined the factor structure of the EHS, which was administered to 252 adults (51.3% male; 48.7% female). Average time of administration was 25.8 minutes. Four factors selected on the basis of the best theoretical fit accounted for 63.37% of the variance. The results of this study provide an initial factor structure for the EHS. PMID:25978085

  15. Scalable multi-objective control for large scale water resources systems under uncertainty

    Science.gov (United States)

    Giuliani, Matteo; Quinn, Julianne; Herman, Jonathan; Castelletti, Andrea; Reed, Patrick

    2016-04-01

    The use of mathematical models to support the optimal management of environmental systems is rapidly expanding over the last years due to advances in scientific knowledge of the natural processes, efficiency of the optimization techniques, and availability of computational resources. However, undergoing changes in climate and society introduce additional challenges for controlling these systems, ultimately motivating the emergence of complex models to explore key causal relationships and dependencies on uncontrolled sources of variability. In this work, we contribute a novel implementation of the evolutionary multi-objective direct policy search (EMODPS) method for controlling environmental systems under uncertainty. The proposed approach combines direct policy search (DPS) with hierarchical parallelization of multi-objective evolutionary algorithms (MOEAs) and offers a threefold advantage: the DPS simulation-based optimization can be combined with any simulation model and does not add any constraint on modeled information, allowing the use of exogenous information in conditioning the decisions. Moreover, the combination of DPS and MOEAs prompts the generation or Pareto approximate set of solutions for up to 10 objectives, thus overcoming the decision biases produced by cognitive myopia, where narrow or restrictive definitions of optimality strongly limit the discovery of decision relevant alternatives. Finally, the use of large-scale MOEAs parallelization improves the ability of the designed solutions in handling the uncertainty due to severe natural variability. The proposed approach is demonstrated on a challenging water resources management problem represented by the optimal control of a network of four multipurpose water reservoirs in the Red River basin (Vietnam). As part of the medium-long term energy and food security national strategy, four large reservoirs have been constructed on the Red River tributaries, which are mainly operated for hydropower

  16. The Effects of Uncertainty in Speed-Flow Curve Parameters on a Large-Scale Model

    DEFF Research Database (Denmark)

    Manzo, Stefano; Nielsen, Otto Anker; Prato, Carlo Giacomo

    2014-01-01

    Uncertainty is inherent in transport models and prevents the use of a deterministic approach when traffic is modeled. Quantifying uncertainty thus becomes an indispensable step to produce a more informative and reliable output of transport models. In traffic assignment models, volume-delay functi......Uncertainty is inherent in transport models and prevents the use of a deterministic approach when traffic is modeled. Quantifying uncertainty thus becomes an indispensable step to produce a more informative and reliable output of transport models. In traffic assignment models, volume...... uncertainty. This aspect is evident particularly for stretches of the network with a high number of competing routes. Model sensitivity was also tested for BPR parameter uncertainty combined with link capacity uncertainty. The resultant increase in model sensitivity demonstrates even further the importance...

  17. Model parameter uncertainty analysis for an annual field-scale P loss model

    Science.gov (United States)

    Bolster, Carl H.; Vadas, Peter A.; Boykin, Debbie

    2016-08-01

    Phosphorous (P) fate and transport models are important tools for developing and evaluating conservation practices aimed at reducing P losses from agricultural fields. Because all models are simplifications of complex systems, there will exist an inherent amount of uncertainty associated with their predictions. It is therefore important that efforts be directed at identifying, quantifying, and communicating the different sources of model uncertainties. In this study, we conducted an uncertainty analysis with the Annual P Loss Estimator (APLE) model. Our analysis included calculating parameter uncertainties and confidence and prediction intervals for five internal regression equations in APLE. We also estimated uncertainties of the model input variables based on values reported in the literature. We then predicted P loss for a suite of fields under different management and climatic conditions while accounting for uncertainties in the model parameters and inputs and compared the relative contributions of these two sources of uncertainty to the overall uncertainty associated with predictions of P loss. Both the overall magnitude of the prediction uncertainties and the relative contributions of the two sources of uncertainty varied depending on management practices and field characteristics. This was due to differences in the number of model input variables and the uncertainties in the regression equations associated with each P loss pathway. Inspection of the uncertainties in the five regression equations brought attention to a previously unrecognized limitation with the equation used to partition surface-applied fertilizer P between leaching and runoff losses. As a result, an alternate equation was identified that provided similar predictions with much less uncertainty. Our results demonstrate how a thorough uncertainty and model residual analysis can be used to identify limitations with a model. Such insight can then be used to guide future data collection and model

  18. Communicating Climate Uncertainties: Challenges and Opportunities Related to Spatial Scales, Extreme Events, and the Warming 'Hiatus'

    Science.gov (United States)

    Casola, J. H.; Huber, D.

    2013-12-01

    makers can arrive at invalid conclusions from a seemingly valid scientific messages. Honest discussion of uncertainties, and recognition of the spatial and time scales associated with decision making, can work to combat this potential confusion.

  19. A scaling approach to project regional sea level rise and its uncertainties

    Directory of Open Access Journals (Sweden)

    M. Perrette

    2013-01-01

    Full Text Available Climate change causes global mean sea level to rise due to thermal expansion of seawater and loss of land ice from mountain glaciers, ice caps and ice sheets. Locally, sea level can strongly deviate from the global mean rise due to changes in wind and ocean currents. In addition, gravitational adjustments redistribute seawater away from shrinking ice masses. However, the land ice contribution to sea level rise (SLR remains very challenging to model, and comprehensive regional sea level projections, which include appropriate gravitational adjustments, are still a nascent field (Katsman et al., 2011; Slangen et al., 2011. Here, we present an alternative approach to derive regional sea level changes for a range of emission and land ice melt scenarios, combining probabilistic forecasts of a simple climate model (MAGICC6 with the new CMIP5 general circulation models. The contribution from ice sheets varies considerably depending on the assumptions for the ice sheet projections, and thus represents sizeable uncertainties for future sea level rise. However, several consistent and robust patterns emerge from our analysis: at low latitudes, especially in the Indian Ocean and Western Pacific, sea level will likely rise more than the global mean (mostly by 10–20%. Around the northeastern Atlantic and the northeastern Pacific coasts, sea level will rise less than the global average or, in some rare cases, even fall. In the northwestern Atlantic, along the American coast, a strong dynamic sea level rise is counteracted by gravitational depression due to Greenland ice melt; whether sea level will be above- or below-average will depend on the relative contribution of these two factors. Our regional sea level projections and the diagnosed uncertainties provide an improved basis for coastal impact analysis and infrastructure planning for adaptation to climate change.

  20. Sources of uncertainties in modelling black carbon at the global scale

    OpenAIRE

    2010-01-01

    Our understanding of the global black carbon (BC) cycle is essentially qualitative due to uncertainties in our knowledge of its properties. This work investigates two source of uncertainties in modelling black carbon: those due to the use of different schemes for BC ageing and its removal rate in the global Transport-Chemistry model TM5 and those due to the uncertainties in the definition and quantification of the observations, which propagate through to both the emission inventories, and the...

  1. The Effects of Uncertainty in Speed-Flow Curve Parameters on a Large-Scale Model

    DEFF Research Database (Denmark)

    Manzo, Stefano; Nielsen, Otto Anker; Prato, Carlo Giacomo

    2014-01-01

    Uncertainty is inherent in transport models and prevents the use of a deterministic approach when traffic is modeled. Quantifying uncertainty thus becomes an indispensable step to produce a more informative and reliable output of transport models. In traffic assignment models, volume-delay functi......Uncertainty is inherent in transport models and prevents the use of a deterministic approach when traffic is modeled. Quantifying uncertainty thus becomes an indispensable step to produce a more informative and reliable output of transport models. In traffic assignment models, volume...

  2. Intolerance of Uncertainty Scale: Measurement invariance among adolescent boys and girls and relationships with anxiety and risk taking.

    Science.gov (United States)

    Dekkers, Laura M S; Jansen, Brenda R J; Salemink, Elske; Huizenga, Hilde M

    2017-06-01

    Adolescence-related increases in both anxiety and risk taking may originate in variability in Intolerance of Uncertainty (IU), rendering the study of IU of importance. We therefore studied the psychometric properties of the Intolerance of Uncertainty Scale-Short version (IUS-12), including its associations with trait anxiety and risk taking, among adolescents. A sample of 879 Dutch adolescents, from diverse educational levels, and with an equal distribution of boys and girls, was classically tested. To obtain indices of IU, and self-reported trait anxiety and need for risk taking, questionnaires were administrated; to obtain an index of risk taking behavior, adolescents performed a risk taking task. Multi-group Confirmatory Factor Analyses revealed that the IUS-12 consists of a Prospective and an Inhibitory IU subscale, which are partially measurement invariant across sex. Cronbach's alphas and item-total correlations revealed that the IUS-12 and its subscales have reasonable-to-good internal consistency. Correlational analyses support convergent validity, as higher IUS-12 scores were related to, respectively, higher and lower levels of self-reported trait anxiety and need for risk taking. However, we found no relationship between IUS-12 scores and risk taking behavior, operationalized by performance on the risk taking task. A community, instead of clinical, sample was included. Also, IU was measured by a paper-and-pencil version of the IUS-12, instead of a computerized version. The IUS-12 has good psychometric properties and may be a central measure to assess IU, which enables to explain the adolescence-related increase in both anxiety and risk taking. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Final Technical Report: Quantification of Uncertainty in Extreme Scale Computations (QUEST)

    Energy Technology Data Exchange (ETDEWEB)

    Knio, Omar M. [Duke Univ., Durham, NC (United States). Dept. of Mechanical Engineering and Materials Science

    2017-06-06

    QUEST is a SciDAC Institute comprising Sandia National Laboratories, Los Alamos National Laboratory, University of Southern California, Massachusetts Institute of Technology, University of Texas at Austin, and Duke University. The mission of QUEST is to: (1) develop a broad class of uncertainty quantification (UQ) methods/tools, and (2) provide UQ expertise and software to other SciDAC projects, thereby enabling/guiding their UQ activities. The Duke effort focused on the development of algorithms and utility software for non-intrusive sparse UQ representations, and on participation in the organization of annual workshops and tutorials to disseminate UQ tools to the community, and to gather input in order to adapt approaches to the needs of SciDAC customers. In particular, fundamental developments were made in (a) multiscale stochastic preconditioners, (b) gradient-based approaches to inverse problems, (c) adaptive pseudo-spectral approximations, (d) stochastic limit cycles, and (e) sensitivity analysis tools for noisy systems. In addition, large-scale demonstrations were performed, namely in the context of ocean general circulation models.

  4. Identifying Opportunities to Reduce Uncertainty in a National-Scale Forest Carbon Accounting Model

    Science.gov (United States)

    Shaw, C. H.; Metsaranta, J. M.; Kurz, W.; Hilger, A.

    2013-12-01

    Assessing the quality of forest carbon budget models used for national and international reporting of greenhouse gas emissions is essential, but model evaluations are rarely conducted mainly because of lack of appropriate, independent ground plot data sets. Ecosystem carbon stocks for all major pools estimated from data collected for 696 ground plots from Canada's new National Forest Inventory (NFI) were used to assess plot-level carbon stocks predicted by the Carbon Budget Model of the Canadian Forest Sector 3 (CBM-CFS3) -- a model compliant with the most complex (Tier-3) approach in the reporting guidelines of the Intergovernmental Panel on Climate Change. The model is the core of Canada's National Forest Carbon Monitoring, Accounting, and Reporting System. At the landscape scale, a major portion of total uncertainty in both C stock and flux estimation is associated with biomass productivity, turnover, and soil and dead organic matter modelling parameters, which can best be further evaluated using plot-level data. Because the data collected for the ground plots were comprehensive we were able to compare carbon stock estimates for 13 pools also estimated by the CBM-CFS3 (all modelled pools excepting coarse and fine root biomass) using the classical comparison statistics of mean difference and correlation. Using a Monte Carlo approach we were able to determine the contribution of aboveground biomass, deadwood and soil pool error to modeled ecosystem total error, as well as the contribution of pools that are summed to estimate aboveground biomass, deadwood and soil, to the error of these three subtotal pools. We were also able to assess potential sources of error propagation in the computational sequence of the CBM-CFS3. Analysis of the data grouped by the 16 dominant tree species allowed us to isolate the leading species where further research would lead to the greatest reductions in uncertainty for modeling of carbon stocks using the CBM-CFS3. This analysis

  5. Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison

    Energy Technology Data Exchange (ETDEWEB)

    Prestele, Reinhard [Environmental Geography Group, Department of Earth Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1087 1081 HV Amsterdam The Netherlands; Alexander, Peter [School of GeoSciences, University of Edinburgh, Drummond Street Edinburgh EH89XP UK; Rounsevell, Mark D. A. [School of GeoSciences, University of Edinburgh, Drummond Street Edinburgh EH89XP UK; Arneth, Almut [Department Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology, Kreuzeckbahnstr. 19 82467 Garmisch-Partenkirchen Germany; Calvin, Katherine [Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park MD 20740 USA; Doelman, Jonathan [PBL Netherlands Environmental Assessment Agency, P.O. Box 303 3720 AH Bilthoven The Netherlands; Eitelberg, David A. [Environmental Geography Group, Department of Earth Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1087 1081 HV Amsterdam The Netherlands; Engström, Kerstin [Department of Geography and Ecosystem Science, Lund University, Sölvegatan 12 Lund Sweden; Fujimori, Shinichiro [Center for Social and Environmental Systems Research, National Institute for Environmental Studies, 16-2 Onogawa Tsukuba Ibaraki 305-8506 Japan; Hasegawa, Tomoko [Center for Social and Environmental Systems Research, National Institute for Environmental Studies, 16-2 Onogawa Tsukuba Ibaraki 305-8506 Japan; Havlik, Petr [Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, A-2361 Laxenburg Austria; Humpenöder, Florian [Potsdam Institute for Climate Impact Research (PIK), P.O. Box 60 12 03 14412 Potsdam Germany; Jain, Atul K. [Department of Atmospheric Sciences, University of Illinois, Urbana IL 61801 USA; Krisztin, Tamás [Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, A-2361 Laxenburg Austria; Kyle, Page [Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park MD 20740 USA; Meiyappan, Prasanth [Department of Atmospheric Sciences, University of Illinois, Urbana IL 61801 USA; Popp, Alexander [Potsdam Institute for Climate Impact Research (PIK), P.O. Box 60 12 03 14412 Potsdam Germany; Sands, Ronald D. [Resource and Rural Economics Division, Economic Research Service, US Department of Agriculture, Washington DC 20250 USA; Schaldach, Rüdiger [Center for Environmental Systems Research, University of Kassel, Wilhelmshöher Allee 47 D-34109 Kassel Germany; Schüngel, Jan [Center for Environmental Systems Research, University of Kassel, Wilhelmshöher Allee 47 D-34109 Kassel Germany; Stehfest, Elke [PBL Netherlands Environmental Assessment Agency, P.O. Box 303 3720 AH Bilthoven The Netherlands; Tabeau, Andrzej [LEI, Wageningen University and Research Centre, P.O. Box 29703 2502 LS The Hague The Netherlands; Van Meijl, Hans [LEI, Wageningen University and Research Centre, P.O. Box 29703 2502 LS The Hague The Netherlands; Van Vliet, Jasper [Environmental Geography Group, Department of Earth Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1087 1081 HV Amsterdam The Netherlands; Verburg, Peter H. [Environmental Geography Group, Department of Earth Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1087 1081 HV Amsterdam The Netherlands; Swiss Federal Research Institute WSL, Zürcherstrasse 111 CH-8903 Birmensdorf Switzerland

    2016-06-08

    Model-based global projections of future land use and land cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socio-economic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g. boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process as well as improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches and many studies ignore the uncertainty in LULC projections in assessments of

  6. Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison.

    Science.gov (United States)

    Prestele, Reinhard; Alexander, Peter; Rounsevell, Mark D A; Arneth, Almut; Calvin, Katherine; Doelman, Jonathan; Eitelberg, David A; Engström, Kerstin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Humpenöder, Florian; Jain, Atul K; Krisztin, Tamás; Kyle, Page; Meiyappan, Prasanth; Popp, Alexander; Sands, Ronald D; Schaldach, Rüdiger; Schüngel, Jan; Stehfest, Elke; Tabeau, Andrzej; Van Meijl, Hans; Van Vliet, Jasper; Verburg, Peter H

    2016-12-01

    Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC

  7. Estimating the magnitude of prediction uncertainties for field-scale P loss models

    Science.gov (United States)

    Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study, an uncertainty analysis for the Annual P Loss Estima...

  8. Model parameter uncertainty analysis for an annual field-scale phosphorus loss model

    Science.gov (United States)

    Phosphorous (P) loss models are important tools for developing and evaluating conservation practices aimed at reducing P losses from agricultural fields. All P loss models, however, have an inherent amount of uncertainty associated with them. In this study, we conducted an uncertainty analysis with ...

  9. Model parameter uncertainty analysis for annual field-scale P loss model

    Science.gov (United States)

    Phosphorous (P) loss models are important tools for developing and evaluating conservation practices aimed at reducing P losses from agricultural fields. All P loss models, however, have an inherent amount of uncertainty associated with them. In this study, we conducted an uncertainty analysis with ...

  10. Sources of uncertainties in modelling black carbon at the global scale

    NARCIS (Netherlands)

    Vignati, E.; Karl, M.; Krol, M.C.; Wilson, J.; Stier, P.; Cavalli, F.

    2010-01-01

    Our understanding of the global black carbon (BC) cycle is essentially qualitative due to uncertainties in our knowledge of its properties. This work investigates two source of uncertainties in modelling black carbon: those due to the use of different schemes for BC ageing and its removal rate in th

  11. Sources of uncertainties in modelling black carbon at the global scale

    NARCIS (Netherlands)

    Vignati, E.; Karl, M.; Krol, M.C.; Wilson, J.; Stier, P.; Cavalli, F.

    2010-01-01

    Our understanding of the global black carbon (BC) cycle is essentially qualitative due to uncertainties in our knowledge of its properties. This work investigates two source of uncertainties in modelling black carbon: those due to the use of different schemes for BC ageing and its removal rate in

  12. Large-scale determinants of diversity across Spanish forest habitats: accounting for model uncertainty in compositional and structural indicators

    Energy Technology Data Exchange (ETDEWEB)

    Martin-Quller, E.; Torras, O.; Alberdi, I.; Solana, J.; Saura, S.

    2011-07-01

    An integral understanding of forest biodiversity requires the exploration of the many aspects it comprises and of the numerous potential determinants of their distribution. The landscape ecological approach provides a necessary complement to conventional local studies that focus on individual plots or forest ownerships. However, most previous landscape studies used equally-sized cells as units of analysis to identify the factors affecting forest biodiversity distribution. Stratification of the analysis by habitats with a relatively homogeneous forest composition might be more adequate to capture the underlying patterns associated to the formation and development of a particular ensemble of interacting forest species. Here we used a landscape perspective in order to improve our understanding on the influence of large-scale explanatory factors on forest biodiversity indicators in Spanish habitats, covering a wide latitudinal and attitudinal range. We considered six forest biodiversity indicators estimated from more than 30,000 field plots in the Spanish national forest inventory, distributed in 213 forest habitats over 16 Spanish provinces. We explored biodiversity response to various environmental (climate and topography) and landscape configuration (fragmentation and shape complexity) variables through multiple linear regression models (built and assessed through the Akaike Information Criterion). In particular, we took into account the inherent model uncertainty when dealing with a complex and large set of variables, and considered different plausible models and their probability of being the best candidate for the observed data. Our results showed that compositional indicators (species richness and diversity) were mostly explained by environmental factors. Models for structural indicators (standing deadwood and stand complexity) had the worst fits and selection uncertainties, but did show significant associations with some configuration metrics. In general

  13. SFR inverse modelling Part 2. Uncertainty factors of predicted flow in deposition tunnels and uncertainty in distribution of flow paths from deposition tunnels

    Energy Technology Data Exchange (ETDEWEB)

    Holmen, Johan (Golder Associates, Uppsala (SE))

    2007-10-15

    The Swedish Nuclear Fuel and Waste Management Co (SKB) is operating the SFR repository for low- and intermediate-level nuclear waste. An update of the safety analysis of SFR was carried out by SKB as the SAFE project (Safety Assessment of Final Disposal of Operational Radioactive Waste). The aim of the project was to update the safety analysis and to produce a safety report. The safety report has been submitted to the Swedish authorities. This study is a continuation of the SAFE project, and concerns the hydrogeological modelling of the SFR repository, which was carried out as part of the SAFE project, it describes the uncertainty in the tunnel flow and distributions of flow paths from the storage tunnels. Uncertainty factors are produced for two different flow situations, corresponding to 2,000 AD (the sea covers the repository) and 4,000 AD (the sea has retreated form the repository area). Uncertainty factors are produced for the different deposition tunnels. The uncertainty factors are discussed in Chapter 2 and two lists (matrix) of uncertainty factors have been delivered as a part of this study. Flow paths are produced for two different flow situations, corresponding to 2,000 AD (the sea covers the repository) and 5,000 AD (the sea has retreated form the repository area). Flow paths from the different deposition tunnels have been simulated, considering the above discussed base case and the 60 realisation that passed all tests of this base case. The flow paths are presented and discussed in Chapter 3 and files presenting the results of the flow path analyses have been delivered as part of this study. The uncertainty factors (see Chapter 2) are not independent from the flow path data (see Chapter 3). When stochastic calculations are performed by use of a transport model and the data presented in this study is used as input to such calculations, the corresponding uncertainty factors and flow path data should be used. This study also includes a brief discussion of

  14. Scale Factor Duality for Conformal Cyclic Cosmologies

    CERN Document Server

    dS, U Camara; Sotkov, G M

    2016-01-01

    The scale factor duality is a symmetry of dilaton gravity which is known to lead to pre-big-bang cosmologies. A conformal time version of the scale factor duality (SFD) was recently implemented as a UV/IR symmetry between decelerated and accelerated phases of the post-big-bang evolution within Einstein gravity coupled to a scalar field. The problem investigated in the present paper concerns the employment of the conformal time SFD methods to the construction of pre-big-bang and cyclic extensions of these models. We demonstrate that each big-bang model gives rise to two qualitatively different pre-big-bang evolutions: a contraction/expansion SFD model and Penrose's Conformal Cyclic Cosmology (CCC). A few examples of SFD symmetric cyclic universes involving certain gauged K\\"ahler sigma models minimally coupled to Einstein gravity are studied. We also describe the specific SFD features of the thermodynamics and the conditions for validity of the generalized second law in the case of Gauss-Bonnet (GB) extension ...

  15. Scale factor duality for conformal cyclic cosmologies

    Science.gov (United States)

    Camara da Silva, U.; Alves Lima, A. L.; Sotkov, G. M.

    2016-11-01

    The scale factor duality is a symmetry of dilaton gravity which is known to lead to pre-big-bang cosmologies. A conformal time version of the scale factor duality (SFD) was recently implemented as a UV/IR symmetry between decelerated and accelerated phases of the post-big-bang evolution within Einstein gravity coupled to a scalar field. The problem investigated in the present paper concerns the employment of the conformal time SFD methods to the construction of pre-big-bang and cyclic extensions of these models. We demonstrate that each big-bang model gives rise to two qualitatively different pre-big-bang evolutions: a contraction/expansion SFD model and Penrose's Conformal Cyclic Cosmology (CCC). A few examples of SFD symmetric cyclic universes involving certain gauged Kähler sigma models minimally coupled to Einstein gravity are studied. We also describe the specific SFD features of the thermodynamics and the conditions for validity of the generalized second law in the case of Gauss-Bonnet (GB) extension of these selected CCC models.

  16. Scale factor duality for conformal cyclic cosmologies

    Energy Technology Data Exchange (ETDEWEB)

    Silva, University Camara da; Lima, A.L. Alves; Sotkov, G.M. [Departamento de Física - CCE,Universidade Federal de Espirito Santo, 29075-900, Vitoria ES (Brazil)

    2016-11-16

    The scale factor duality is a symmetry of dilaton gravity which is known to lead to pre-big-bang cosmologies. A conformal time version of the scale factor duality (SFD) was recently implemented as a UV/IR symmetry between decelerated and accelerated phases of the post-big-bang evolution within Einstein gravity coupled to a scalar field. The problem investigated in the present paper concerns the employment of the conformal time SFD methods to the construction of pre-big-bang and cyclic extensions of these models. We demonstrate that each big-bang model gives rise to two qualitatively different pre-big-bang evolutions: a contraction/expansion SFD model and Penrose’s Conformal Cyclic Cosmology (CCC). A few examples of SFD symmetric cyclic universes involving certain gauged Kähler sigma models minimally coupled to Einstein gravity are studied. We also describe the specific SFD features of the thermodynamics and the conditions for validity of the generalized second law in the case of Gauss-Bonnet (GB) extension of these selected CCC models.

  17. Evaluating uncertainty in predicting spatially variable representative elementary scales in fractured aquifers, with application to Turkey Creek Basin, Colorado

    Science.gov (United States)

    Wellman, Tristan P.; Poeter, Eileen P.

    2006-08-01

    Computational limitations and sparse field data often mandate use of continuum representation for modeling hydrologic processes in large-scale fractured aquifers. Selecting appropriate element size is of primary importance because continuum approximation is not valid for all scales. The traditional approach is to select elements by identifying a single representative elementary scale (RES) for the region of interest. Recent advances indicate RES may be spatially variable, prompting unanswered questions regarding the ability of sparse data to spatially resolve continuum equivalents in fractured aquifers. We address this uncertainty of estimating RES using two techniques. In one technique we employ data-conditioned realizations generated by sequential Gaussian simulation. For the other we develop a new approach using conditioned random walks and nonparametric bootstrapping (CRWN). We evaluate the effectiveness of each method under three fracture densities, three data sets, and two groups of RES analysis parameters. In sum, 18 separate RES analyses are evaluated, which indicate RES magnitudes may be reasonably bounded using uncertainty analysis, even for limited data sets and complex fracture structure. In addition, we conduct a field study to estimate RES magnitudes and resulting uncertainty for Turkey Creek Basin, a crystalline fractured rock aquifer located 30 km southwest of Denver, Colorado. Analyses indicate RES does not correlate to rock type or local relief in several instances but is generally lower within incised creek valleys and higher along mountain fronts. Results of this study suggest that (1) CRWN is an effective and computationally efficient method to estimate uncertainty, (2) RES predictions are well constrained using uncertainty analysis, and (3) for aquifers such as Turkey Creek Basin, spatial variability of RES is significant and complex.

  18. Bayesian methods for uncertainty factor application for derivation of reference values.

    Science.gov (United States)

    Simon, Ted W; Zhu, Yiliang; Dourson, Michael L; Beck, Nancy B

    2016-10-01

    In 2014, the National Research Council (NRC) published Review of EPA's Integrated Risk Information System (IRIS) Process that considers methods EPA uses for developing toxicity criteria for non-carcinogens. These criteria are the Reference Dose (RfD) for oral exposure and Reference Concentration (RfC) for inhalation exposure. The NRC Review suggested using Bayesian methods for application of uncertainty factors (UFs) to adjust the point of departure dose or concentration to a level considered to be without adverse effects for the human population. The NRC foresaw Bayesian methods would be potentially useful for combining toxicity data from disparate sources-high throughput assays, animal testing, and observational epidemiology. UFs represent five distinct areas for which both adjustment and consideration of uncertainty may be needed. NRC suggested UFs could be represented as Bayesian prior distributions, illustrated the use of a log-normal distribution to represent the composite UF, and combined this distribution with a log-normal distribution representing uncertainty in the point of departure (POD) to reflect the overall uncertainty. Here, we explore these suggestions and present a refinement of the methodology suggested by NRC that considers each individual UF as a distribution. From an examination of 24 evaluations from EPA's IRIS program, when individual UFs were represented using this approach, the geometric mean fold change in the value of the RfD or RfC increased from 3 to over 30, depending on the number of individual UFs used and the sophistication of the assessment. We present example calculations and recommendations for implementing the refined NRC methodology.

  19. Addressing solar modulation and long-term uncertainties in scaling secondary cosmic rays for in situ cosmogenic nuclide applications [rapid communication

    Science.gov (United States)

    Lifton, Nathaniel A.; Bieber, John W.; Clem, John M.; Duldig, Marc L.; Evenson, Paul; Humble, John E.; Pyle, Roger

    2005-10-01

    secondary cosmic ray intensities, within the uncertainties of our combined source datasets. We also estimate solar modulation variations over the last 11.4 ka from a recent physics-based sunspot number reconstruction derived from tree-ring 14C data. This approximation suggests that spallogenic nucleon scaling factors in our model for sea level and high geomagnetic latitudes can differ by up to ˜ 10%, depending on the time step over which the model sunspot numbers are averaged. The potential magnitude of this difference supports our contention that incorporating long-term solar modulation into secondary cosmic ray scaling is important. Although millennial-scale solar modulation clearly requires further study, we believe it is reasonable at present to use our S value record for scaling spallogenic nucleons during the last 11.4 ka, and the weighted mean S value for that period of 0.950 for longer exposure times. By accounting for solar modulation effects on the global variations in nucleon and muon fluxes, these models thus provide a useful framework on which to base CN production rate scaling functions.

  20. Iterative Learning Control with Forgetting Factor for Linear Distributed Parameter Systems with Uncertainty

    Directory of Open Access Journals (Sweden)

    Xisheng Dai

    2014-01-01

    Full Text Available Iterative learning control is an intelligent control algorithm which imitates human learning process. Based on this concept, this paper discussed iterative learning control problem for a class parabolic linear distributed parameter systems with uncertainty coefficients. Iterative learning control algorithm with forgetting factor is proposed and the conditions for convergence of algorithm are established. Combining the matrix theory with the basic theory of distributed parameter systems gives rigorous convergence proof of the algorithm. Finally, by using the forward difference scheme of partial differential equation to solve the problems, the simulation results are presented to illustrate the feasibility of the algorithm.

  1. Scale Factor Self-Dual Cosmological Models

    CERN Document Server

    dS, U Camara; Sotkov, G M

    2015-01-01

    We implement a conformal time scale factor duality for Friedmann-Robertson-Walker cosmological models, which is consistent with the weak energy condition. The requirement for self-duality determines the equations of state for a broad class of barotropic fluids. We study the example of a universe filled with two interacting fluids, presenting an accelerated and a decelerated period, with manifest UV/IR duality. The associated self-dual scalar field interaction turns out to coincide with the "radiation-like" modified Chaplygin gas models. We present an equivalent realization of them as gauged K\\"ahler sigma models (minimally coupled to gravity) with very specific and interrelated K\\"ahler- and super-potentials. Their applications in the description of hilltop inflation and also as quintessence models for the late universe are discussed.

  2. Uncertainty Quantification in Multi-Scale Coronary Simulations Using Multi-resolution Expansion

    Science.gov (United States)

    Tran, Justin; Schiavazzi, Daniele; Ramachandra, Abhay; Kahn, Andrew; Marsden, Alison

    2016-11-01

    Computational simulations of coronary flow can provide non-invasive information on hemodynamics that can aid in surgical planning and research on disease propagation. In this study, patient-specific geometries of the aorta and coronary arteries are constructed from CT imaging data and finite element flow simulations are carried out using the open source software SimVascular. Lumped parameter networks (LPN), consisting of circuit representations of vascular hemodynamics and coronary physiology, are used as coupled boundary conditions for the solver. The outputs of these simulations depend on a set of clinically-derived input parameters that define the geometry and boundary conditions, however their values are subjected to uncertainty. We quantify the effects of uncertainty from two sources: uncertainty in the material properties of the vessel wall and uncertainty in the lumped parameter models whose values are estimated by assimilating patient-specific clinical and literature data. We use a generalized multi-resolution chaos approach to propagate the uncertainty. The advantages of this approach lies in its ability to support inputs sampled from arbitrary distributions and its built-in adaptivity that efficiently approximates stochastic responses characterized by steep gradients.

  3. INFLUENCE OF UNCERTAINTY FACTOR ON DEVELOPMENT OF ECONOMIC CRISIS IN RUSSIA

    Directory of Open Access Journals (Sweden)

    V. A. Rudyakov

    2016-01-01

    Full Text Available Observing development of the crisis in the Russian economy, it appears that one of the reasons for the decline in the economic development is an increasing degree of uncertainty. The situation affects investment processes and multiplies itself in a growing deficiency of national income. High uncertainty blocks investments in capital-intensive and specific assets and makes economic entities transfer their resources into financial sector and, most often, outside the economy. 49 % of fixed industrial assets depreciation is an indirect proof of this situation. Depreciation of the Russian fixed assets in mining operations is 53.2 %, which includes 22.9 % of fully depreciated assets. At present, when the coefficient of renewal in this branch of ndustry is a little more than 6 and the coefficient of retirement is 0.9, the situation seems to be disastrous. There are a lot of reasons for such situation, especially in the economic sphere. One of them is that within the neoliberal ideology dominating in the economic science with its emphasis on the automatic spontaneous adaptation there is actually no place for development of recommendations for a willful increase in efficiency of adaptation to uncertainty. After all, if we consider that the market leads the entire system to the most optimum equilibrium state, a need for such development simply does not arise. The main objective of this work is to show how the uncertainty factor increases recessionary trends in the Russian economy. Applying Keynesian analysis technique and dividing all savings into investment and hoarding ones, the author proves that Russia has a very low level of adaptive efficiency which reflects long-term ability of the economy to adjust successfully to changing internal and external conditions without any detriment to the implementation of the intended targets and tasks. It is a low level of adaptive efficiency that makes the current crisis so severe. The application of different

  4. Uncertainties in turbidity-based measurements of suspended sediment load used to quantify the sediment budget on the catchment scale

    Science.gov (United States)

    de Hipt, Felix Op; Diekkrüger, Bernd; Steup, Gero; Rode, Michael

    2016-04-01

    Water-driven soil erosion, transport and deposition take place on different spatial and temporal scales. Therefore, related measurements are complex and require process understanding and a multi-method approach combining different measurement methods with soil erosion modeling. Turbidity as a surrogate measurement for suspended sediment concentration (SSC) in rivers is frequently used to overcome the disadvantages of conventional sediment measurement techniques regarding temporal resolution and continuity. The use of turbidity measurements requires a close correlation between turbidity and SSC. Depending on the number of samples collected, the measured range and the variations in the measurements, SSC-turbidity curves are subject to uncertainty. This uncertainty has to be determined in order to assess the reliability of measure-ments used to quantify catchment sediment yields and to calibrate soil erosion models. This study presents the calibration results from a sub-humid catchment in south-western Burkina Faso and investigates the related uncertainties. Daily in situ measurements of SSC manually collected at one turbidity station and the corresponding turbidity readings are used to obtain the site-specific calibration curve. The discharge is calculated based on an empirical water level-discharge relationship. The derived regression equations are used to define prediction intervals for SSC and discharge. The uncertainty of the suspended sediment load time series is influenced by the corresponding uncertainties of SSC and discharge. This study shows that the determination of uncertainty is relevant when turbidity-based measurements of suspended sediment loads are used to quantify catchment erosion and to calibrate erosion models.

  5. Dynamic Simulation, Sensitivity and Uncertainty Analysis of a Demonstration Scale Lignocellulosic Enzymatic Hydrolysis Process

    DEFF Research Database (Denmark)

    Prunescu, Remus Mihail; Sin, Gürkan

    2014-01-01

    , accounting a large number of parameters. The sensitivity analysis of model predictions with respect to model parameters is quantified by the delta mean square measure. By ranking the delta mean square, a reduced subset of parameters is found helping to identify the bottleneck of the model. The uncertainty...... to be affected by non-zero mean noise because they are determined by a Near Infrared (NIR) instrument. LHS is performed on 2 parameters: the probability of the mean value and the probability of the standard deviation for each measurement. The Monte Carlo outputs are then analyzed by linear regression......This study presents the uncertainty and sensitivity analysis of a lignocellulosic enzymatic hydrolysis model considering both model and feed parameters as sources of uncertainty. The dynamic model is parametrized for accommodating various types of biomass, and different enzymatic complexes...

  6. Scaling Factor Estimation Using an Optimized Mass Change Strategy, Part 1: Theory

    DEFF Research Database (Denmark)

    Aenlle, Manuel López; Fernández, Pelayo Fernández; Brincker, Rune

    2007-01-01

    . The scaling factors are determined using the natural frequencies and mode shapes of both the modified and the unmodified structure. However, the uncertainty on the scaling factor estimation depends on the modal analysis and the mass change strategy (number, magnitude and location of the masses) used to modify...... the dynamic behavior of the structure. In this paper, a procedure to optimize the mass change strategy is proposed, which uses the modal parameters(natural frequencies and mode shapes) of the original structure as the basic information....

  7. Anxiety sensitivity and intolerance of uncertainty as potential risk factors for cyberchondria.

    Science.gov (United States)

    Norr, Aaron M; Albanese, Brian J; Oglesby, Mary E; Allan, Nicholas P; Schmidt, Norman B

    2015-03-15

    Online medical information seeking has become an increasingly common behavior. Despite the benefits of easily accessible medical information on the Internet, researchers have identified a vicious cycle of increased physical health concerns and online medical information seeking known as "cyberchondria". Despite proposed theoretical models of cyberchondria, there is a dearth of research investigating risk factors for the development of cyberchondria. Two potential risk factors are anxiety sensitivity (AS) and intolerance of uncertainty (IU). The current study investigated the relationships among AS, IU, and cyberchondria in a large community sample. Participants (N=526) completed self-report questionnaires via online crowdsourcing. Structural equation models utilizing latent variables revealed a significant unique positive relationship between AS, as well as the IU Inhibitory lower-order factor, and cyberchondria, controlling for the effects of health anxiety. Additionally, results revealed a significant unique relationship between the IU Inhibitory factor and mistrust of medical professionals, a proposed cyberchondria-relevant construct. The cross-sectional data in the current study do not offer a true test of AS and IU as risk factors. However, establishing these unique relationships is an important step forward in the literature. The results of the current study suggest the potential importance of both AS and IU in the development of cyberchondria. Future research is needed to establish the temporal precedence of elevated AS and/or IU to determine if they are true risk factors or simply correlates of cyberchondria. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. The intolerance of uncertainty scale: measurement invariance, population heterogeneity, and its relation with worry among self-identifying White and Black respondents.

    Science.gov (United States)

    Fergus, Thomas A; Wu, Kevin D

    2013-10-01

    Although it is understood that assessment tools require evaluation using diverse samples, such evaluations are relatively rare. There are obstacles to such work, but it remains important to pursue psychometric data in broad samples. As such, we evaluated measurement invariance and population heterogeneity of two versions of a widely used measure in the anxiety literature--the Intolerance of Uncertainty Scale (IUS)--among self-identifying White (N = 1,185) and Black (N = 301) students. Data from multiple-groups confirmatory factor analysis supported the equivalence of the equal form and factor loadings of both IUS versions in White and Black respondents. However, specific IUS items functioned differently in the two groups, with more IUS items appearing biased in the full-length relative to the short-form version. Correlations between IUS factors and worry were equivalent among White and Black respondents. We discuss the implications of these results for future research.

  9. False positive and false negative radon measurement results due to uncertainties in seasonal correction factors

    Energy Technology Data Exchange (ETDEWEB)

    Cliff, K.D.; Miles, J.C.H.; Naismith, S.P. [National Radiological Protection Board, Chilton (United Kingdom)

    1994-12-31

    Data from the UK national survey of radon in 2300 homes has been re-analysed to determine the uncertainty in seasonal correction factors applied to measurements of less than 1 year. The required correction factor for each six-month result was calculated from the known annual average for the appropriate home. The seasonal correction factors derived for each month were found to be approximately log-normally distributed, with an average geometric standard deviation of 1.36. Following this initial survey, radon measurements have been made in more than 80,000 homes in southwest England to determine whether they are above the UK radon Action Level of 2000 Bq.m{sup -3}. The measurements were carried out over three months in each case using etched track detectors in two locations in each home, and the results were corrected for the average seasonal variation found in the original UK study of radon in homes. Because of the uncertainty in the seasonal correction factors, households with between 130 and 300 Bq.m{sup -3} were advised to have a second three-month measurement in a different season before deciding whether or not to take remedial action. More than 7000 homes were remonitored for this purpose. The results are analysed to show the number of false positive and false negative results that would have been reported if advice had been based solely on the initial measurement. It is shown that the present scheme results in extremely small numbers of false positive and false negative results. (author).

  10. Stochastic uncertainties and sensitivities of a regional-scale transport model of nitrate in groundwater

    NARCIS (Netherlands)

    Brink, C.v.d.; Zaadnoordijk, W.J.; Burgers, S.; Griffioen, J.

    2008-01-01

    Groundwater quality management relies more and more on models in recent years. These models are used to predict the risk of groundwater contamination for various land uses. This paper presents an assessment of uncertainties and sensitivities to input parameters for a regional model. The model had

  11. Hotspots of uncertainty in land use and land cover change projections: a global scale model comparison

    NARCIS (Netherlands)

    Prestele, Reinhard; Alexander, Peter; Rounsevell, Mark; Arneth, Almut; Calvin, Katherine; Doelman, Jonathan; Eitelberg, David; Engström, Kerstin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Humpenöder, Florian; Jain, Atul K.; Krisztin, Tamás; Kyle, Page; Meiyappan, Prasanth; Popp, Alexander; Sands, Ronald D.; Schaldach, Rüdiger; Schüngel, Jan; Stehfest, Elke; Tabeau, Andrzej; Meijl, van Hans; Vliet, van Jasper; Verburg, Peter H.

    2016-01-01

    Model-based global projections of future land use and land cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms

  12. Uncertainty propagation in up-scaling of subsoil parameters, no fixed distributions allowed

    NARCIS (Netherlands)

    Lourens, Aris; van Geer, Frans C.

    2013-01-01

    When creating numerical groundwater models, the structure and properties of the subsoil is indispensable information. Like all model data, these data are subject to uncertainty. Building a groundwater model, the available geological information, like the geological structure and parameter values, ha

  13. Scaling, propagating and mapping uncertainty in spectroscopy-derived foliar traits from the leaf to the image

    Science.gov (United States)

    Singh, A.; Serbin, S. P.; Kingdon, C.; Townsend, P. A.

    2013-12-01

    A major goal of remote sensing, and imaging spectroscopy in particular, is the development of generalizable algorithms to repeatedly and accurately map ecosystem properties such as canopy chemistry across space and time. Existing methods must therefore be tested across a range of measurement approaches to identify and overcome limits to the consistent retrieval of such properties from spectroscopic imagery. Here we illustrate a general approach for the estimation of key foliar biochemical and morphological traits from spectroscopic imagery derived from the AVIRIS instrument and the propagation of errors from the leaf to the image scale using partial least squares regression (PLSR) techniques. Our method involves the integration of three types of data representing different scales of observation: At the image scale, the images were normalized for atmospheric, illumination and BRDF effects. Spectra from field plot locations were extracted from the 51AVIRIS images and were averaged when the field plot was larger than a single pixel. At the plot level, the scaling was conducted using multiple replicates (1000) derived from the leaf-level uncertainty estimates to generate plot-level estimates with their associated uncertainties. Leaf-level estimates of foliar traits (%N, %C, %Fiber, %Cellulose, %Lignin, LMA) were scaled to the canopy based on relative species composition of each plot. Image spectra were iteratively split into 50/50 randomized calibration-validation datasets and multiple (500) trait-predictive PLSR models were generated, this time sampling from within the plot-level uncertainty distribution. This allowed the propagation of uncertainty from the leaf-level dependent variables to the plot level, and finally to models built using AVIRIS image spectra. Moreover, this method allows us to generate spatially explicit maps of uncertainty in our sampled traits. Both LMA and %N PLSR models had a R2 greater than 0.8, root mean square errors (RMSEs) for both

  14. Identification of the Uncertainties for the Calibration of the Partial Safety Factors for Load in Tidal Turbines

    Directory of Open Access Journals (Sweden)

    Gaizka Zarraonandia Simeón

    2016-03-01

    Full Text Available Tidal energy is nowadays one of the fastest growing types of marine renewable energy. In particular, Horizontal Axis Tidal Turbines (HATTs are the most advanced designs and the most appropriate for standardization. This paper presents a review of actual design criteria focusing on the identification of the uncertainties that technology developers need to address during the design process. Key environmental parameters like turbine inflow conditions or predictions of extreme values are still grey areas due to the lack of site measurements and the uncertainty in metocean model predictions. A comparison of turbulence intensity characterization using different tools and at different points in time shows the uncertainty in the prediction of this parameter. Numerical models of HATTs are still quite uncertain, often dependent on experience of the people running them. In the reliability-based calibration of partial safety factors, the uncertainties need to be reflected on the limit state formulation. This paper analyses the different types of uncertainties present in the limit state equation. These uncertainties are assessed in terms of stochastic variables in the limit state equation. In some cases, advantage can be taken from the experience from offshore wind and oil and gas industries. Tidal turbines have a mixture of the uncertainties present in both industries with regard to partial safety factor calibration.

  15. Scale factor characteristics of laser gyroscopes of different sizes

    Science.gov (United States)

    Fan, Zhenfang; Lu, Guangfeng; Hu, Shomin; Wang, Zhiguo; Luo, Hui

    2016-04-01

    The scale factor correction characteristics of two ring laser gyroscopes of different sizes are investigated systematically in this paper. The variation in the scale factor can reach 144 or 70 ppm for square gyroscopes with arm lengths of 8.4 cm or 15.6 cm, respectively, during frequency tuning. A dip in the scale factor is observed at the line center of the gain characteristic for both gyroscope sizes. When a different longitudinal mode is excited, the scale factor behavior remains the same, but the scale factor values differ slightly from those derived from geometric prediction. The scale factor tends to decrease with increasing discharge current, but the sensitivity of the scale factor to variations in the excitation decreases with increasing discharge current.

  16. Probabilistic Approach to Enable Extreme-Scale Simulations under Uncertainty and System Faults. Final Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Knio, Omar [Duke Univ., Durham, NC (United States). Dept. of Mechanical Engineering and Materials Science

    2017-05-05

    The current project develops a novel approach that uses a probabilistic description to capture the current state of knowledge about the computational solution. To effectively spread the computational effort over multiple nodes, the global computational domain is split into many subdomains. Computational uncertainty in the solution translates into uncertain boundary conditions for the equation system to be solved on those subdomains, and many independent, concurrent subdomain simulations are used to account for this bound- ary condition uncertainty. By relying on the fact that solutions on neighboring subdomains must agree with each other, a more accurate estimate for the global solution can be achieved. Statistical approaches in this update process make it possible to account for the effect of system faults in the probabilistic description of the computational solution, and the associated uncertainty is reduced through successive iterations. By combining all of these elements, the probabilistic reformulation allows splitting the computational work over very many independent tasks for good scalability, while being robust to system faults.

  17. Assessing risks for integrated water resource management: coping with uncertainty and the human factor

    Science.gov (United States)

    Polo, M. J.; Aguilar, C.; Millares, A.; Herrero, J.; Gómez-Beas, R.; Contreras, E.; Losada, M. A.

    2014-09-01

    Risk assessment for water resource planning must deal with the uncertainty associated with excess/scarcity situations and their costs. The projected actions for increasing water security usually involve an indirect "call-effect": the territory occupation/water use is increased following the achieved protection. In this work, flood and water demand in a mountainous semi-arid watershed in southern Spain are assessed by means of the stochastic simulation of extremes, when this human factor is/is not considered. The results show how not including this call-effect induced an underestimation of flood risk after protecting the floodplain of between 35 and 78 % in a 35-year planning horizon. Similarly, the pursued water availability of a new reservoir resulted in a 10-year scarcity risk increase up to 38 % when the trend of expanding the irrigated area was included in the simulations. These results highlight the need for including this interaction in the decision-making assessment.

  18. Decentralised robust stabilisation of uncertain large-scale interconnected time-delay systems with unknown upper bounds of uncertainties

    Science.gov (United States)

    Wu, Hansheng

    2016-09-01

    The problem of decentralised robust stabilisation is considered for a class of uncertain large-scale time-delay interconnected dynamical systems. In the paper, the upper bounds of delayed state perturbations, uncertainties, interconnection terms, and external disturbances are assumed to be completely unknown, and the delays are assumed to be any non-negative constants. For such a class of uncertain large-scale time-delay interconnected systems, a new method is presented whereby a class of adaptation-free decentralised local robust state feedback controllers can be constructed. In addition, it is also shown that the solutions of uncertain large-scale time-delay interconnected systems can be guaranteed to be uniformly ultimately bounded. Finally, as an application to the practical mechanical systems, some simulations of a numerical example are provided to demonstrate the validity of the theoretical results.

  19. Uncertainty quantification of fast sodium current steady-state inactivation for multi-scale models of cardiac electrophysiology.

    Science.gov (United States)

    Pathmanathan, Pras; Shotwell, Matthew S; Gavaghan, David J; Cordeiro, Jonathan M; Gray, Richard A

    2015-01-01

    Perhaps the most mature area of multi-scale systems biology is the modelling of the heart. Current models are grounded in over fifty years of research in the development of biophysically detailed models of the electrophysiology (EP) of cardiac cells, but one aspect which is inadequately addressed is the incorporation of uncertainty and physiological variability. Uncertainty quantification (UQ) is the identification and characterisation of the uncertainty in model parameters derived from experimental data, and the computation of the resultant uncertainty in model outputs. It is a necessary tool for establishing the credibility of computational models, and will likely be expected of EP models for future safety-critical clinical applications. The focus of this paper is formal UQ of one major sub-component of cardiac EP models, the steady-state inactivation of the fast sodium current, INa. To better capture average behaviour and quantify variability across cells, we have applied for the first time an 'individual-based' statistical methodology to assess voltage clamp data. Advantages of this approach over a more traditional 'population-averaged' approach are highlighted. The method was used to characterise variability amongst cells isolated from canine epi and endocardium, and this variability was then 'propagated forward' through a canine model to determine the resultant uncertainty in model predictions at different scales, such as of upstroke velocity and spiral wave dynamics. Statistically significant differences between epi and endocardial cells (greater half-inactivation and less steep slope of steady state inactivation curve for endo) was observed, and the forward propagation revealed a lack of robustness of the model to underlying variability, but also surprising robustness to variability at the tissue scale. Overall, the methodology can be used to: (i) better analyse voltage clamp data; (ii) characterise underlying population variability; (iii) investigate

  20. Mastering Uncertainty and Risk at Multiple Time Scales in the Future Electrical Grid

    Energy Technology Data Exchange (ETDEWEB)

    Chertkov, Michael [Los Alamos National Laboratory; Bent, Russell W. [Los Alamos National Laboratory; Backhaus, Scott N. [Los Alamos National Laboratory

    2012-07-10

    Today's electrical grids enjoy a relatively clean separation of spatio-temporal scales yielding a compartmentalization of grid design, optimization, control and risk assessment allowing for the use of conventional mathematical tools within each area. In contrast, the future grid will incorporate time-intermittent renewable generation, operate via faster electrical markets, and tap the latent control capability at finer grid modeling scales; creating a fundamentally new set of couplings across spatiotemporal scales and requiring revolutionary advances in mathematics techniques to bridge these scales. One example is found in decade-scale grid expansion planning in which today's algorithms assume accurate load forecasts and well-controlled generation. Incorporating intermittent renewable generation creates fluctuating network flows at the hourly time scale, inherently linking the ability of a transmission line to deliver electrical power to hourly operational decisions. New operations-based planning algorithms are required, creating new mathematical challenges. Spatio-temporal scales are also crossed when the future grid's minute-scale fluctuations in network flows (due to intermittent generation) create a disordered state upon which second-scale transient grid dynamics propagate effectively invalidating today's on-line dynamic stability analyses. Addressing this challenge requires new on-line algorithms that use large data streams from new grid sensing technologies to physically aggregate across many spatial scales to create responsive, data-driven dynamic models. Here, we sketch the mathematical foundations of these problems and potential solutions.

  1. 电子计重秤测量结果的不确定度评定%Electronic weight scale evaluation of uncertainty measurement results

    Institute of Scientific and Technical Information of China (English)

    刘海华

    2012-01-01

    This paper mainly introduces the sources uncertainty in the electronic weight scale test, calculation of each component of the standard uncertainty, and combined standard uncertainty and expanded uncertainty of the method through the actual measurement.%本文主要介绍了在电子计重秤试验过程中不确定度来源,并通过实际测量,计算各分量的标准不确定度、合成标准不确定度以及扩展不确定度的方法。

  2. Reduction of the uncertainty of the PTB vacuum pressure scale by a new large area non-rotating piston gauge

    Science.gov (United States)

    Bock, Th; Ahrendt, H.; Jousten, K.

    2009-10-01

    This paper describes the metrological characterization of a new large area piston gauge (FRS5, Furness Rosenberg Standard) installed at the vacuum metrology laboratory of the Physikalisch-Technische Bundesanstalt (PTB). The operational procedure and the uncertainty budget for pressures between 30 Pa and 11 kPa are given. Comparisons between the FRS5 and a mercury manometer, a rotary piston gauge and a force-balanced piston gauge are described. We show that the reproducibility of the calibration values of capacitance diaphragm gauges is enhanced by a factor of 6 compared with a static expansion primary standard (SE2). Improvements of the SE2 performance by reducing the number of expansions and smaller uncertainties of expansion ratios are discussed.

  3. Towards a Holistic Model for Simulating Sediment Dynamics at Watershed Scales: Partitioning of Sediment Sources and Uncertainty Quantification

    Science.gov (United States)

    Abban, Benjamin; Papanicolaou, Thanos; Cowles, Kate; Wilson, Christopher; Abaci, Ozan; Wacha, Kenneth

    2016-04-01

    The challenge remains to understand watershed sediment source dynamics for planning and evaluating mitigation measures on anthropogenic activities such as intensive agriculture, which exacerbates soil erosion from the landscape. To this end, our research aims to develop a cross-scale model, capable of simulating sediment transport from the plot scale to the watershed scale while effectively capturing the important feedback effects across the scales. Our approach combines numerical modeling with physical observations and measurements to not only provide a tool capable of mimicking cause and effect relationships, but also capable of quantifying uncertainty related to source dynamics predictions. We present herein a key component of the cross-scale model that quantifies source partitioning and the associated uncertainty. This component is based on a Bayesian un-mixing framework and is particularly useful for watersheds characterized by considerable spatiotemporal heterogeneity. The Bayesian un-mixing framework utilizes two key parameters, namely α and β, that explicitly accounts for spatial origin attributes and the time history of sediments delivered to the watershed outlet, respectively. These parameters are treated probabilistically so as to account for variability in source erosion processes, as well as the delivery times and storage of eroded material within the watershed. The use of Markov Chain Monte Carlo simulations for determining posterior probability density functions in the framework allows uncertainty in source contribution estimates to be quantified naturally as part of the solution process. We demonstrate the utility of the Bayesian un-mixing framework in a predominantly agricultural watershed in the US Midwest known as the Clear Creek Watershed, IA, which is part of the Critical Zone Observatory for Intensively Managed Landscapes (IML-CZO). Stable isotopes of Carbon and Nitrogen are used as tracers since they have been found to be appropriate for

  4. Conversion factor and uncertainty estimation for quantification of towed gamma-ray detector measurements in Tohoku coastal waters

    Science.gov (United States)

    Ohnishi, S.; Thornton, B.; Kamada, S.; Hirao, Y.; Ura, T.; Odano, N.

    2016-05-01

    Factors to convert the count rate of a NaI(Tl) scintillation detector to the concentration of radioactive cesium in marine sediments are estimated for a towed gamma-ray detector system. The response of the detector against a unit concentration of radioactive cesium is calculated by Monte Carlo radiation transport simulation considering the vertical profile of radioactive material measured in core samples. The conversion factors are acquired by integrating the contribution of each layer and are normalized by the concentration in the surface sediment layer. At the same time, the uncertainty of the conversion factors are formulated and estimated. The combined standard uncertainty of the radioactive cesium concentration by the towed gamma-ray detector is around 25 percent. The values of uncertainty, often referred to as relative root mean squat errors in other works, between sediment core sampling measurements and towed detector measurements were 16 percent in the investigation made near the Abukuma River mouth and 5.2 percent in Sendai Bay, respectively. Most of the uncertainty is due to interpolation of the conversion factors between core samples and uncertainty of the detector's burial depth. The results of the towed measurements agree well with laboratory analysed sediment samples. Also, the concentrations of radioactive cesium at the intersection of each survey line are consistent. The consistency with sampling results and between different lines' transects demonstrate the availability and reproducibility of towed gamma-ray detector system.

  5. Infrared Scales and Factorization in QCD

    CERN Document Server

    Manohar, A V

    2006-01-01

    Effective field theory methods are used to study factorization of the deep inelastic scattering cross-section. The cross-section is shown to factor in QCD, even though it does not factor in perturbation theory for some choices of the infrared regulator. Messenger modes are not required in soft-collinear effective theory for deep inelastic scattering as x -> 1.

  6. Stochastic multi-scale prediction on the apparent elastic moduli of trabecular bone considering uncertainties of biological apatite (BAp) crystallite orientation and image-based modelling.

    Science.gov (United States)

    Basaruddin, Khairul Salleh; Takano, Naoki; Nakano, Takayoshi

    2015-01-01

    An assessment of the mechanical properties of trabecular bone is important in determining the fracture risk of human bones. Many uncertainty factors contribute to the dispersion of the estimated mechanical properties of trabecular bone. This study was undertaken in order to propose a computational scheme that will be able to predict the effective apparent elastic moduli of trabecular bone considering the uncertainties that are primarily caused by image-based modelling and trabecular stiffness orientation. The effect of image-based modelling which focused on the connectivity was also investigated. A stochastic multi-scale method using a first-order perturbation-based and asymptotic homogenisation theory was applied to formulate the stochastically apparent elastic properties of trabecular bone. The effective apparent elastic modulus was predicted with the introduction of a coefficient factor to represent the variation of bone characteristics due to inter-individual differences. The mean value of the predicted effective apparent Young's modulus in principal axis was found at approximately 460 MPa for respective 15.24% of bone volume fraction, and this is in good agreement with other experimental results. The proposed method may provide a reference for the reliable evaluation of the prediction of the apparent elastic properties of trabecular bone.

  7. THE CLASSIFICATION OF UNCERTAINTY OF THE KEY FACTORS PRICING IN TOURISM SPHERE

    Directory of Open Access Journals (Sweden)

    N. Sagalakova

    2015-10-01

    Full Text Available Specific characteristics of non-productive processes in the sphere of tourism and their difference from processes of the production sphere are investigated. Features of the pricing process at the tourism enterprise are analyzed. The main problems at implementation of model of the optimum price formation of a tourism product are identified. Classification of factors of pricing at the tourism enterprise is constructed. For the comparative analysis all factors of influence on pricing process, it is possible to divide into groups on the following classification signs: controllability (controllable and uncontrollable; accessory to system (internal and external; quantification (quantitative and qualitative; stability (stable and unstable. Interpretation to the main types of uncertain parameters, which exert impact on the price of a tourism product, is given. The accounting of uncertainty of the price when forming a tourism product will allow to construct adequate forecasts on the basis of which effective decisions concerning management of the pricing process at the tourism enterprise will be made.

  8. Understanding uncertainties in non-linear population trajectories: a Bayesian semi-parametric hierarchical approach to large-scale surveys of coral cover.

    Directory of Open Access Journals (Sweden)

    Julie Vercelloni

    Full Text Available Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making.

  9. Understanding uncertainties in non-linear population trajectories: a Bayesian semi-parametric hierarchical approach to large-scale surveys of coral cover.

    Science.gov (United States)

    Vercelloni, Julie; Caley, M Julian; Kayal, Mohsen; Low-Choy, Samantha; Mengersen, Kerrie

    2014-01-01

    Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making.

  10. Accounting for global-mean warming and scaling uncertainties in climate change impact studies: application to a regulated lake system

    Directory of Open Access Journals (Sweden)

    2007-01-01

    Full Text Available A probabilistic assessment of climate change and related impacts should consider a large range of potential future climate scenarios. State-of-the-art climate models, especially coupled atmosphere-ocean general circulation models and Regional Climate Models (RCMs cannot, however, be used to simulate such a large number of scenarios. This paper presents a methodology for obtaining future climate scenarios through a simple scaling methodology. The projections of several key meteorological variables obtained from a few regional climate model runs are scaled, based on different global-mean warming projections drawn in a probability distribution of future global-mean warming. The resulting climate change scenarios are used to drive a hydrological and a water management model to analyse the potential climate change impacts on a water resources system. This methodology enables a joint quantification of the climate change impact uncertainty induced by the global-mean warming scenarios and the regional climate response. It is applied to a case study in Switzerland, a water resources system formed by three interconnected lakes located in the Jura Mountains. The system behaviour is simulated for a control period (1961–1990 and a future period (2070–2099. The potential climate change impacts are assessed through a set of impact indices related to different fields of interest (hydrology, agriculture and ecology. The results obtained show that future climate conditions will have a significant influence on the performance of the system and that the uncertainty induced by the inter-RCM variability will contribute to much of the uncertainty of the prediction of the total impact. These CSRs cover the area considered in the 2001–2004 EU funded project SWURVE.

  11. Using the Community Land Model to Assess Uncertainty in Basin Scale GRACE-Based Groundwater Estimates

    Science.gov (United States)

    Swenson, S. C.; Lawrence, D. M.

    2015-12-01

    One method for interpreting the variability in total water storage observed by GRACE is to partition the integrated GRACE measurement into its component storage reservoirs based on information provided by hydrological models. Such models, often designed to be used in couple Earth System models, simulate the stocks and fluxes of moisture through the land surface and subsurface. One application of this method attempts to isolate groundwater changes by removing modeled surface water, snow, and soil moisture changes from GRACE total water storage estimates. Human impacts on groundwater variability can be estimated by further removing model estimates of climate-driven groundwater changes. Errors in modeled water storage components directly affect the residual groundwater estimates. Here we examine the influence of model structure and process representation on soil moisture and groundwater uncertainty using the Community Land Model, with a particular focus on basins in the western U.S.

  12. Evaluation of Uncertainties in Measuring Particulate Matter Emission Factors from Atmospheric Fugitive Sources Using Optical Remote Sensing

    Science.gov (United States)

    Yuen, W.; Ma, Q.; Du, K.; Koloutsou-Vakakis, S.; Rood, M. J.

    2015-12-01

    Measurements of particulate matter (PM) emissions generated from fugitive sources are of interest in air pollution studies, since such emissions vary widely both spatially and temporally. This research focuses on determining the uncertainties in quantifying fugitive PM emission factors (EFs) generated from mobile vehicles using a vertical scanning micro-pulse lidar (MPL). The goal of this research is to identify the greatest sources of uncertainty of the applied lidar technique in determining fugitive PM EFs, and to recommend methods to reduce the uncertainties in this measurement. The MPL detects the PM plume generated by mobile fugitive sources that are carried downwind to the MPL's vertical scanning plane. Range-resolved MPL signals are measured, corrected, and converted to light extinction coefficients, through inversion of the lidar equation and calculation of the lidar ratio. In this research, both the near-end and far-end lidar equation inversion methods are considered. Range-resolved PM mass concentrations are then determined from the extinction coefficient measurements using the measured mass extinction efficiency (MEE) value, which is an intensive PM property. MEE is determined by collocated PM mass concentration and light extinction measurements, provided respectively by a DustTrak and an open-path laser transmissometer. These PM mass concentrations are then integrated with wind information, duration of plume event, and vehicle distance travelled to obtain fugitive PM EFs. To obtain the uncertainty of PM EFs, uncertainties in MPL signals, lidar ratio, MEE, and wind variation are considered. Error propagation method is applied to each of the above intermediate steps to aggregate uncertainty sources. Results include determination of uncertainties in each intermediate step, and comparison of uncertainties between the use of near-end and far-end lidar equation inversion methods.

  13. Factor Structure of the Exercise Self-Efficacy Scale

    Science.gov (United States)

    Cornick, Jessica E.

    2015-01-01

    The current study utilized exercise self-efficacy ratings from undergraduate students to assess the factor structure of the Self-Efficacy to Regulate Exercise Scale (Bandura, 1997, 2006). An exploratory factor analysis (n = 759) indicated a two-factor model solution and three separate confirmatory factor analyses (n = 1,798) supported this…

  14. Quantifying uncertainties in radar forward models through a comparison between CloudSat and SPartICus reflectivity factors

    Science.gov (United States)

    Mascio, Jeana; Mace, Gerald G.

    2017-02-01

    Interpretations of remote sensing measurements collected in sample volumes containing ice-phase hydrometeors are very sensitive to assumptions regarding the distributions of mass with ice crystal dimension, otherwise known as mass-dimensional or m-D relationships. How these microphysical characteristics vary in nature is highly uncertain, resulting in significant uncertainty in algorithms that attempt to derive bulk microphysical properties from remote sensing measurements. This uncertainty extends to radar reflectivity factors forward calculated from model output because the statistics of the actual m-D in nature is not known. To investigate the variability in m-D relationships in cirrus clouds, reflectivity factors measured by CloudSat are combined with particle size distributions (PSDs) collected by coincident in situ aircraft by using an optimal estimation-based (OE) retrieval of the m-D power law. The PSDs were collected by 12 flights of the Stratton Park Engineering Company Learjet during the Small Particles in Cirrus campaign. We find that no specific habit emerges as preferred, and instead, we find that the microphysical characteristics of ice crystal populations tend to be distributed over a continuum-defying simple categorization. With the uncertainties derived from the OE algorithm, the uncertainties in forward-modeled backscatter cross section and, in turn, radar reflectivity is calculated by using a bootstrapping technique, allowing us to infer the uncertainties in forward-modeled radar reflectivity that would be appropriately applied to remote sensing simulator algorithms.

  15. Fibroblast growth factor 21 night watch: advances and uncertainties in the field.

    Science.gov (United States)

    Kharitonenkov, A; DiMarchi, R

    2017-03-01

    Fibroblast growth factor (FGF) 21 belongs to a hormone-like subgroup within the FGF superfamily. The members of this subfamily, FGF19, FGF21 and FGF23, are characterized by their reduced binding affinity for heparin that enables them to be transported in the circulation and function in an endocrine manner. It is likely that FGF21 also acts in an autocrine and paracrine fashion, as multiple organs can produce this protein and its plasma concentration seems to be below the level necessary to induce a pharmacological effect. FGF21 signals via FGF receptors, but for efficient receptor engagement it requires a cofactor, membrane-spanning βKlotho (KLB). The regulation of glucose uptake in adipocytes was the initial biological activity ascribed to FGF21, but this hormone is now recognized to stimulate many other pathways in vitro and display multiple pharmacological effects in metabolically compromised animals and humans. Understanding of the precise physiology of FGF21 and its potential medicinal role has evolved exponentially over the last decade, yet numerous aspects remain to be defined and others are a source of debate. Here we provide a historical overview of the advances in FGF21 biology focusing on the uncertainties in the mechanism of action as well as the differing viewpoints relating to this intriguing protein.

  16. Improving estimates of surface carbon fluxes to support emissions monitoring, reporting and verification at local and regional scales: quantifying uncertainty and the effects of spatial scaling.

    Science.gov (United States)

    Gately, C.; Hutyra, L.; Wofsy, S.; Nehrkorn, T.; Sue Wing, I.

    2015-12-01

    Current approaches to quantifying surface-atmosphere fluxes of carbon often combine inventories of fossil fuel carbon emissions (ffCO2) and biosphere flux estimates with atmospheric measurements to drive forward and inverse-atmospheric modeling at high spatial and temporal resolutions (1km grids, hourly time steps have become common). Given that over 70% of total ffCO2 emissions are attributable to urban areas, accurate estimates of ffCO2 at urban scales are critical to support emissions mitigation policies at state and local levels. A successful regional or national carbon monitoring system requires a careful quantification of the uncertainties associated with estimates of both ffCO2 and biogenic carbon fluxes. Errors in the spatial distribution of ffCO2 priors used to inform atmospheric transport models can bias posterior flux estimates, and potentially provide misleading information to decision makers on the impact of policies. Most current ffCO2 priors are either too coarsely resolved in time and space, or suffer from poorly quantified errors in spatial distributions at local scales. Accurately downscaling aggregate activity data requires a careful understanding of the potentially non-linear relationships between source processes and spatial proxies. We report on ongoing work to develop an integrated, high-resolution carbon monitoring system for the Northeastern U.S., and discuss insights into the impact of spatial scaling on model uncertainty. We use a newly developed dataset of hourly surface carbon fluxes for all human and biogenic sources at 1km grid resolution for the years 2013 and 2014. To attain these spatial and temporal resolutions, ffCO2 flux estimates were subject to varying degrees of aggregation and/or downscaling depending on the native source data for each sector. We will discuss several important examples of how the choice of scaling variables and priors influences the spatial distribution CO2 and CH4 retrievals.

  17. Spatial scale effects on model parameter estimation and predictive uncertainty in ungauged basins

    CSIR Research Space (South Africa)

    Hughes, DA

    2013-06-01

    Full Text Available The most appropriate scale to use for hydrological modelling depends on the structure of the chosen model, the purpose of the results and the resolution of the available data used to quantify parameter values and provide the climatic forcing data...

  18. Modeling a production scale milk drying process: parameter estimation, uncertainty and sensitivity analysis

    DEFF Research Database (Denmark)

    Ferrari, A.; Gutierrez, S.; Sin, Gürkan

    2016-01-01

    A steady state model for a production scale milk drying process was built to help process understanding and optimization studies. It involves a spray chamber and also internal/external fluid beds. The model was subjected to a comprehensive statistical analysis for quality assurance using sensitiv...

  19. Sources of errors and uncertainties in the assessment of forest soil carbon stocks at different scales

    DEFF Research Database (Denmark)

    Vanguelova, E. I.; Bonifacio, E.; De Vos, B.

    2016-01-01

    and temporal distribution (such as soil type, topography, climate and vegetation) are needed to optimise sampling depths and numbers of samples, thereby ensuring that samples accurately reflect the distribution of SOC at a site. Furthermore, the appropriate scales related to the research question need...

  20. Aleatory Uncertainty and Scale Effects in Computational Damage Models for Failure and Fragmentation

    Science.gov (United States)

    2014-09-01

    that were generated using self-similar quantile shapes (more like the current implementation). invariant function common in geomechanics ; cf. [6...experiments. In geomechanics , it is com- mon to employ two different sets of material properties, one for the so-called laboratory scale and another for “field

  1. Towards Algorithmic Advances for Solving Stackelberg Games: Addressing Model Uncertainties and Massive Game Scale-up

    Science.gov (United States)

    2015-02-04

    Yang Runner up Best PhD thesis 2014 Rong Yang best research assistant computer science department USC 2013 Wanger Prize for Excellence in...show with a realization called COCOMO. Therefore, we presented a novel cutting-plane algorithm called BLADE to scale-up SSGs with complex adversary

  2. Adding a strategic edge to human factors/ergonomics: principles for the management of uncertainty as cornerstones for system design.

    Science.gov (United States)

    Grote, Gudela

    2014-01-01

    It is frequently lamented that human factors and ergonomics knowledge does not receive the attention and consideration that it deserves. In this paper I argue that in order to change this situation human factors/ergonomics based system design needs to be positioned as a strategic task within a conceptual framework that incorporates both business and design concerns. The management of uncertainty is presented as a viable candidate for such a framework. A case is described where human factors/ergonomics experts in a railway company have used the management of uncertainty perspective to address strategic concerns at firm level. Furthermore, system design is discussed in view of the relationship between organization and technology more broadly. System designers need to be supported in better understanding this relationship in order to cope with the uncertainties this relationship brings to the design process itself. Finally, the emphasis on uncertainty embedded in the recent surge of introducing risk management across all business sectors is suggested as another opportunity for bringing human factors and ergonomics expertise to the fore.

  3. Optimal choice of factorization scales for the description of jet production at the LHC

    Energy Technology Data Exchange (ETDEWEB)

    Martin, A.D. [Durham University, Institute for Particle Physics Phenomenology, Durham (United Kingdom); Ryskin, M.G. [Durham University, Institute for Particle Physics Phenomenology, Durham (United Kingdom); NRC ' Kurchatov Institute' , Petersburg Nuclear Physics Institute, St. Petersburg (Russian Federation)

    2017-04-15

    To obtain more precise parton distribution functions (PDFs) it is important to include data on inclusive high transverse energy jet production in the global parton analyses. These data have high statistics and the NNLO terms in the perturbative QCD (pQCD) description are now available. Our aim is to reduce the uncertainty in the comparison of the jet data with pQCD. To ensure the best convergence of the pQCD series it is important to choose the appropriate factorization scales, μ{sub F}. We show that it is possible to absorb and resum in the incoming PDFs and fragmentation function (D) an essential part of the higher α{sub s}-order corrections by determining the 'optimal' values of μ{sub F}. We emphasize that it is necessary to optimize different factorization scales for the various factors in the cross section: indeed, both of the PDFs, and also the fragmentation function, have their own optimal scale. We show how the values of these scales can be calculated for the LO (NLO) part of the pQCD prediction of the cross section based on the theoretically known NLO (NNLO) corrections. After these scales are fixed at their optimal values, the residual factorization scale dependence is much reduced. (orig.)

  4. Neutrino mass hierarchy and precision physics with medium-baseline reactors: Impact of energy-scale and flux-shape uncertainties

    Science.gov (United States)

    Capozzi, F.; Lisi, E.; Marrone, A.

    2015-11-01

    Nuclear reactors provide intense sources of electron antineutrinos, characterized by few-MeV energy E and unoscillated spectral shape Φ (E ). High-statistics observations of reactor neutrino oscillations over medium-baseline distances L ˜O (50 ) km would provide unprecedented opportunities to probe both the long-wavelength mass-mixing parameters (δ m2 and θ12) and the short-wavelength ones (Δ mee 2 and θ13), together with the subtle interference effects associated with the neutrino mass hierarchy (either normal or inverted). In a given experimental setting—here taken as in the JUNO project for definiteness—the achievable hierarchy sensitivity and parameter accuracy depend not only on the accumulated statistics but also on systematic uncertainties, which include (but are not limited to) the mass-mixing priors and the normalizations of signals and backgrounds. We examine, in addition, the effect of introducing smooth deformations of the detector energy scale, E →E'(E ), and of the reactor flux shape, Φ (E )→Φ'(E ), within reasonable error bands inspired by state-of-the-art estimates. It turns out that energy-scale and flux-shape systematics can noticeably affect the performance of a JUNO-like experiment, both on the hierarchy discrimination and on precision oscillation physics. It is shown that a significant reduction of the assumed energy-scale and flux-shape uncertainties (by, say, a factor of 2) would be highly beneficial to the physics program of medium-baseline reactor projects. Our results also shed some light on the role of the inverse-beta decay threshold, of geoneutrino backgrounds, and of matter effects in the analysis of future reactor oscillation data.

  5. Calculation of the Power Peaking Factor Using CFNN and Its Uncertainty Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Back, Ju Hyun; Kim, Dong Yeong; Yoo, Kwae Hwan; Choi, Geon Pil; Na, Man Gyun [Chosun University, Gwangju (Korea, Republic of)

    2016-05-15

    The local power density (LPD) and DNBR must be calculated in order to perform the main functions of the core protection calculator (CPC) and the core operation limit supervisory system (COLSS). CPC and COLSS play a role in the protection and monitoring systems of the optimized power reactor 1000 (OPR1000) and the advanced power reactor 1400 (APR1400). LPD should be estimated accurately to prevent fuel rods from melting. LPD at the hottest part of the core is called the power peaking factor (PPF, F{sub q} ). LPD at the hottest part of the core is more important than LPD at any other position in a reactor core. DNBR and PPF are the most important factors that must be continuously monitored from a safety aspect. The aim of the study is to calculate PPF in a reactor core by a cascaded fuzzy neural networks (CFNN) model according to operating conditions. The operation condition is reactor power, core inlet temperature, pressurizer pressure, mass flowrate, axial shape index (ASI), and variety of control rod position. The proposed CFNN model that is a PPF estimation algorithm is verified by using the nuclear and thermal data acquired from numerical simulations of OPR1000. The CFNN regression models were optimized by using the data set prepared as training data and tested by using verification data. The developed CFNN models were applied to the OPR 1000. As a result, the RMS error of the estimated PPF values is below 0.05%. In addition, their uncertainty was analyzed by a bootstrap method using 100 sampled development data sets.

  6. An indirect accuracy calibration and uncertainty evaluation method for large scale inner dimensional measurement system

    Science.gov (United States)

    Liu, Bai-Ling; Qu, Xing-Hua

    2013-10-01

    In view of present problem of low accuracy, limited range and low automaticity existing in the large-scale diameter inspection instrument, a precise measuring system (robot) was designed based on laser displacement sensor for large-scale inner diameter in this paper. Since the traditional measuring tool of the robot is expensive and hard to manufacture, an indirect calibration method is proposed. In this study, the system eccentric error is calibrated by ring gauge of laboratory. An experiment, which changes the installed order of located rods to introduce located rods' eccentric error, is designed to test whether the spindle eccentric error remains unchanged. The experiment result shows the variation of spindle's eccentricity after changing rods is within 0.02mm. Due to the spindle is an unchanged part of robot, based on Φ584 series robot calibrated by ring gauge, other series robot can be deduced combining with the length of extended arm.

  7. Scaling Factor Estimation Using Optimized Mass Change Strategy, Part 2: Experimental Results

    DEFF Research Database (Denmark)

    Fernández, Pelayo Fernández; Aenlle, Manuel López; Garcia, Luis M. Villa

    2007-01-01

    The mass change method is used to estimate the scaling factors, the uncertainty is reduced when, for each mode, the frequency shift is maximized and the changes in the mode shapes are minimized, which in turn, depends on the mass change strategy chosen to modify the dynamic behavior of the struct...... factors of a steel cantilever beam. The effect of the mass change strategy was experimentally studied by performing several modal tests in which the magnitude, the location and the number of the attached masses were changed.......The mass change method is used to estimate the scaling factors, the uncertainty is reduced when, for each mode, the frequency shift is maximized and the changes in the mode shapes are minimized, which in turn, depends on the mass change strategy chosen to modify the dynamic behavior...... of the structure. On the other hand, the aforementioned objectives are difficult to achieve for all modes simultaneously. Thus, a study of the number, magnitude and location of the masses must be performed previously to the modal tests. In this paper, the mass change method was applied to estimate the scaling...

  8. Regional-scale electric power system planning under uncertainty-A multistage interval-stochastic integer linear programming approach

    Energy Technology Data Exchange (ETDEWEB)

    Li, Y.F. [Energy and Environmental Research Center, North China Electric Power University, Beijing 102206 (China); Huang, G.H., E-mail: gordon.huang@uregina.c [Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada); College of Urban and Environmental Sciences, Peking University, Beijing 100871 (China); Li, Y.P. [College of Urban and Environmental Sciences, Peking University, Beijing 100871 (China); Xu, Y.; Chen, W.T. [Energy and Environmental Research Center, North China Electric Power University, Beijing 102206 (China)

    2010-01-15

    In this study, a multistage interval-stochastic regional-scale energy model (MIS-REM) is developed for supporting electric power system (EPS) planning under uncertainty that is based on a multistage interval-stochastic integer linear programming method. The developed MIS-REM can deal with uncertainties expressed as both probability distributions and interval values existing in energy system planning problems. Moreover, it can reflect dynamic decisions for electricity generation schemes and capacity expansions through transactions at discrete points of a multiple representative scenario set over a multistage context. It can also analyze various energy-policy scenarios that are associated with economic penalties when the regulated targets are violated. A case study is provided for demonstrating the applicability of the developed model, where renewable and non-renewable energy resources, economic concerns, and environmental requirements are integrated into a systematic optimization process. The results obtained are helpful for supporting (a) adjustment or justification of allocation patterns of regional energy resources and services, (b) formulation of local policies regarding energy consumption, economic development, and energy structure, and (c) analysis of interactions among economic cost, environmental requirement, and energy-supply security.

  9. Regional-scale electric power system planning under uncertainty. A multistage interval-stochastic integer linear programming approach

    Energy Technology Data Exchange (ETDEWEB)

    Li, Y.F.; Xu, Y.; Chen, W.T. [Energy and Environmental Research Center, North China Electric Power University, Beijing 102206 (China); Huang, G.H. [Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan (Canada); College of Urban and Environmental Sciences, Peking University, Beijing 100871 (China); Li, Y.P. [College of Urban and Environmental Sciences, Peking University, Beijing 100871 (China)

    2010-01-15

    In this study, a multistage interval-stochastic regional-scale energy model (MIS-REM) is developed for supporting electric power system (EPS) planning under uncertainty that is based on a multistage interval-stochastic integer linear programming method. The developed MIS-REM can deal with uncertainties expressed as both probability distributions and interval values existing in energy system planning problems. Moreover, it can reflect dynamic decisions for electricity generation schemes and capacity expansions through transactions at discrete points of a multiple representative scenario set over a multistage context. It can also analyze various energy-policy scenarios that are associated with economic penalties when the regulated targets are violated. A case study is provided for demonstrating the applicability of the developed model, where renewable and non-renewable energy resources, economic concerns, and environmental requirements are integrated into a systematic optimization process. The results obtained are helpful for supporting (a) adjustment or justification of allocation patterns of regional energy resources and services, (b) formulation of local policies regarding energy consumption, economic development, and energy structure, and (c) analysis of interactions among economic cost, environmental requirement, and energy-supply security. (author)

  10. Effect of Cohesion Uncertainty of Granular Materials on the Kinematics of Scaled Models of Fold-and-Thrust Belts

    Science.gov (United States)

    Nilfouroushan, F.; Pysklywec, R.; Cruden, S.

    2009-05-01

    Cohesionless or very low cohesion granular materials are widely used in analogue/physical models to simulate brittle rocks in the upper crust. Selection of materials with appropriate cohesion values in such models is important for the simulation of the dynamics of brittle rock deformation in nature. Uncertainties in the magnitude of cohesion (due to measurement errors, extrapolations at low normal stresses, or model setup) in laboratory experiments can possibly result in misinterpretation of the styles and mechanisms of deformation in natural fold-and thrust belts. We ran a series of 2-D numerical models to investigate systematically the effect of cohesion uncertainties on the evolution of models of fold-and-thrust belts. The analyses employ SOPALE, a geodynamic code based on the arbitrary Lagrangian-Eulerian (ALE) finite element method. Similar to analogue models, the material properties of sand and transparent silicone (PDMS) are used to simulate brittle and viscous behaviors of upper crustal rocks. The suite of scaled brittle and brittle-viscous numerical experiments have the same initial geometry but the cohesion value of the brittle layers is increased systematically from 0 to 100 Pa. The stress and strain distribution in different sets of models with different cohesion values are compared and analyzed. The kinematics and geometry of thrust wedges including the location and number of foreland- and hinterland- verging thrust faults, pop-up structures, tapers and topography are also explored and their sensitivity to cohesion value is discussed.

  11. Understanding and improving mitigation strategies for reducing catchment scale nutrient loads using high resolution observations and uncertainty analysis approaches

    Science.gov (United States)

    Collins, A.; Lloyd, C.; Freer, J. E.; Johnes, P.; Stirling, M.

    2012-12-01

    One of the biggest challenges in catchment water quality management is tackling the problem of reducing water pollution from agriculture whilst ensuring food security nationally. Improvements to catchment management plans are needed if we are to enhance biodiversity and maintain good ecological status in freshwater ecosystems, while producing enough food to support a growing global population. In order to plan for a more sustainable and secure future, research needs to quantify the uncertainties and understand the complexities in the source-mobilisation-delivery-impact continuum of pollution and nutrients at all scales. In the UK the Demonstration Test Catchment (DTC) project has been set up to improve water quality specifically from diffuse pollution from agriculture by enhanced high resolution monitoring and targeted mitigation experiments. The DTC project aims to detect shifts in the baseline trend of the most ecologically-significant pollutants resulting from targeted on-farm measures at field to farm scales and assessing their effects on ecosystem function. The DTC programme involves three catchments across the UK that are indicative of three different typologies and land uses. This paper will focus on the Hampshire Avon DTC, where a total of 12 parameters are monitored by bank-side stations at two sampling sites, including flow, turbidity, phosphate and nitrate concentrations at 30 min resolution. This monitoring is supported by daily resolution sampling at 5 other sites and storm sampling at all locations. Part of the DTC project aims to understand how observations of water quality within river systems at different temporal resolutions and types of monitoring strategies enable us to understand and detect changes over and above the natural variability. Baseline monitoring is currently underway and early results show that high-resolution data is essential at this sub-catchment scale to understand important process dynamics. This is critical if we are to design

  12. Demographic Correlates and Factor Structure of the Family Environment Scale.

    Science.gov (United States)

    Boake, Corwin; Salmon, Paul G.

    1983-01-01

    Factor analyzed the Family Environment Scale (FES) subscale scores of 204 families and correlated them with family demographic characteristics. The obtained factor structure showed two major factors similar to "control" and "acceptance-rejection" dimensions in previous research. Results support the FES as part of multimethod…

  13. Exploratory Factor Analysis of African Self-Consciousness Scale Scores

    Science.gov (United States)

    Bhagwat, Ranjit; Kelly, Shalonda; Lambert, Michael C.

    2012-01-01

    This study replicates and extends prior studies of the dimensionality, convergent, and external validity of African Self-Consciousness Scale scores with appropriate exploratory factor analysis methods and a large gender balanced sample (N = 348). Viable one- and two-factor solutions were cross-validated. Both first factors overlapped significantly…

  14. Geographical scenario uncertainty in generic fate and exposure factors of toxic pollutants for life-cycle impact assessment.

    Science.gov (United States)

    Huijbregts, M A J; Lundi, S; McKone, T E; van de Meent, D

    2003-05-01

    In environmental life-cycle assessments (LCA), fate and exposure factors account for the general fate and exposure properties of chemicals under generic environmental conditions by means of 'evaluative' multi-media fate and exposure box models. To assess the effect of using different generic environmental conditions, fate and exposure factors of chemicals emitted under typical conditions of (1). Western Europe, (2). Australia and (3). the United States of America were compared with the multi-media fate and exposure box model USES-LCA. Comparing the results of the three evaluative environments, it was found that the uncertainty in fate and exposure factors for ecosystems and humans due to choice of an evaluative environment, as represented by the ratio of the 97.5th and 50th percentile, is between a factor 2 and 10. Particularly, fate and exposure factors of emissions causing effects in fresh water ecosystems and effects on human health have relatively high uncertainty. This uncertainty is mainly caused by the continental difference in the average soil erosion rate, the dimensions of the fresh water and agricultural soil compartment, and the fraction of drinking water coming from ground water.

  15. Consensus Control of Complex and Multi-scale Networks with Network Uncertainty and Adversary

    Science.gov (United States)

    2015-09-02

    Applications of Large Deviations Principles, New York: Springer, (01 2013) Héctor Jasso- Fuentes , G. Yin. Advanced Criteria for controlled Markov...only Monte  Carlo  simulation or numerical approximation is possible. In addition, the calculations often require the handling of  stopping times, the...Zhang, and Q. Zhang, Applications of Two‐time‐scale Markovian Systems, Science Press, Beijing, China, 2013, vii+209  pp.  [4] H. Jasso‐ Fuentes  and G

  16. Predicted risk of cobalt deficiency in grazing sheep from a geochemical survey; communicating uncertainty with the IPCC verbal scale.

    Science.gov (United States)

    Lark, R. M.; Ander, E. L.; Cave, M. R.; Knights, K. V.; Glennon, M. M.; Scanlon, R. P.

    2014-05-01

    Deficiency or excess of certain trace elements in the soil causes problems for agriculture, including disorders of grazing ruminants. Farmers and their advisors in Ireland use index values for the concentration of total soil cobalt and manganese to identify where grazing sheep are at risk of cobalt deficiency. We used cokriging with topsoil data from a regional geochemical survey across six counties of Ireland to form local cokriging predictions of cobalt and manganese concentrations with an attendant distribution which reflects the joint uncertainty of these predictions. From this distribution we then computed conditional probabilities for different combinations of cobalt and manganese index values, and so for the corresponding inferred risk to sheep of cobalt deficiency and the appropriateness of different management interventions. The challenge is to communicate these results effectively to an audience comprising, inter alia, farmers, agronomists and veterinarians. Numerical probabilities are not generally well-understood by non-specialists. For this reason we presented our results as maps using a verbal scale to communicate the probability that a deficiency is indicated by local soil conditions, or that a particular intervention is indicated. In the light of recent research on the effectiveness of the verbal scale used by the Intergovernmental Panel on Climate Change to communicate probabilistic information we reported the geostatistical predictions as follows. First, we use the basic IPCC scale with intensifiers, but we also indicate the corresponding probabilities (as percentages) as recommended by Budescu et al. (2009). Second, we make it clear that the source of uncertainty in these predictions is the spatial variability of soil Co and Mn. The outcome under consideration is therefore that a particular soil management scenario would be indicated if the soil properties were known without error, possible uncertainty about the implications of particular soil

  17. Updating Environmental Media Concentration Limits and Uncertainty factors in the ERICA Tool

    Energy Technology Data Exchange (ETDEWEB)

    Brown, J.E.; Hosseini, A. [Norwegian Radiation Protection Authority, P.O. Box 55, N-1332 Oesteraas (Norway); Alfonso, B.; Avila, R. [Facilia AB, S-167 51 Bromma (Sweden); Beresford, N.A. [Centre for Ecology and Hydrology, CEH-Lancaster, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster LA 1 4AP (United Kingdom); Copplestone, D. [Dept. Biological and Environmental Sciences, University of Stirling, Stirling, FK9 4LA (United Kingdom)

    2014-07-01

    Tiered approaches have become a standard means of structuring information in the process of conducting environmental risk assessments. For cases involving the assessment of impacts on wildlife from ionising radiation, the ERICA integrated approach and its supporting software (The ERICA Tool) provides such a structure, splitting the system into two generic screening tiers and a third site-specific tier. The first Tier is very simple, based around Environmental Media Concentration Limits, EMCLs, and requires minimal input from the assessor. The second Tier, although still a screening tier, calculates dose rates and requires more detailed input from the assessor allowing for scrutiny and editing of default parameters in the process. A key element of Tier 2 involves the application of Uncertainty Factors, UFs. Such factors reflect our knowledge concerning probability distribution functions and provide a way of incorporating conservatism into the assessment by considering high percentile values in underlying parameters. Following its launch in 2007, there have been significant developments regarding certain components of the ERICA integrated approach. Most notably, an extended international collation of concentration ratio data has precipitated the need to update parameter values in the Tools databases. In addition, more considered guidance has been developed with regards to filling knowledge gaps in the absence of transfer data. Furthermore, the efficacy of the methods used in assigning probability distribution functions has been questioned leading to an acknowledgement from the developers that the methods were not described in enough detail nor were the justifications for applying the selected approach provided in a convincing way. This has implications for the EMCL values which are derived probabilistically using parameters including concentration ratios. Furthermore, there are implications for UF derivation that relies upon a robust consideration of underlying

  18. Factoring uncertainty into restoration modeling of in-situ leach uranium mines

    Science.gov (United States)

    Johnson, Raymond H.; Friedel, Michael J.

    2009-01-01

    Postmining restoration is one of the greatest concerns for uranium in-situ leach (ISL) mining operations. The ISL-affected aquifer needs to be returned to conditions specified in the mining permit (either premining or other specified conditions). When uranium ISL operations are completed, postmining restoration is usually achieved by injecting reducing agents into the mined zone. The objective of this process is to restore the aquifer to premining conditions by reducing the solubility of uranium and other metals in the ground water. Reactive transport modeling is a potentially useful method for simulating the effectiveness of proposed restoration techniques. While reactive transport models can be useful, they are a simplification of reality that introduces uncertainty through the model conceptualization, parameterization, and calibration processes. For this reason, quantifying the uncertainty in simulated temporal and spatial hydrogeochemistry is important for postremedial risk evaluation of metal concentrations and mobility. Quantifying the range of uncertainty in key predictions (such as uranium concentrations at a specific location) can be achieved using forward Monte Carlo or other inverse modeling techniques (trial-and-error parameter sensitivity, calibration constrained Monte Carlo). These techniques provide simulated values of metal concentrations at specified locations that can be presented as nonlinear uncertainty limits or probability density functions. Decisionmakers can use these results to better evaluate environmental risk as future metal concentrations with a limited range of possibilities, based on a scientific evaluation of uncertainty.

  19. Correlations of MMPI factor scales with measures of the five factor model of personality.

    Science.gov (United States)

    Costa, P T; Busch, C M; Zonderman, A B; McCrae, R R

    1986-01-01

    Two recent item factor analyses of the Minnesota Multiphasic Personality Inventory (MMPI) classified the resulting factors according to a conceptual scheme offered by Norman's (1963) five factor model. The present article empirically evaluates those classifications by correlating MMPI factor scales with self-report and peer rating measures of the five factor model in a sample of 153 adult men and women. Both sets of predictions were generally supported, although MMPI factors derived in a normal sample showed closer correspondences with the five normal personality dimensions. MMPI factor scales were also correlated with 18 scales measuring specific traits within the broader domains of Neuroticism, Extraversion, and Openness. The nine Costa, Zonderman, McCrae, and Williams (1985) MMPI factor scales appear to give useful global assessments of four of the five factors; other instruments are needed to provide detailed information on more specific aspects of normal personality. The use of the five factor model in routine clinical assessment is discussed.

  20. Emission-factor uncertainties in maritime transport in the Strait of Gibraltar, Spain

    Directory of Open Access Journals (Sweden)

    J. Moreno-Gutiérrez

    2012-08-01

    Full Text Available A reliable and up-to-date maritime emission inventory is essential for atmospheric scientists quantifying the impact of shipping. The objective of this study is to estimate the atmospheric emissions of SO2, NOx, CO2 and PM10 by international merchant shipping in 2007 in the Strait of Gibraltar, Spain, including the Algeciras Bay by two methods.

    Two methods (both bottom-up have been used in this study:

    1. Establishing engine power-based emission factors (g kWh−1, EPA or the mass of pollutant per work performed by the engine for each of the relevant components of the exhaust gas from diesel engines and power for each ship.

    2. Establishing fuel-based emission factors (kg emitted/t of fuel or mass of pollutant per mass of combusted fuel for each of the relevant components of the exhaust gas and a fuel-consumption inventory (IMO.

    In both methods, the means to estimate engine power and fuel-consumption inventories are the same. The exhaust from boilers and incinerators is regarded as a small contributor and excluded. In total, an estimated average of 1 389 111.05 t of CO2, 23 083.09 t of SO2, 32 005.63 t of NOx and 2972 t of PM10 were emitted from January 2007 until December 2007 by international and domestic shipping. The estimated total fuel consumption amounts to 437 405.84 t. The major differences between the estimates generated by the two methods are for NOx (16% in certain cases and CO (up to 23%.

    A total difference for all compounds of 3038 t (approximately 2% has been found between the two methods but it is not areasonable estimate of uncertainty.

    Therefore, the results for both methods may be considered acceptable because the actual uncontrolled deviations appear in the changes in emission factors that occur for a given engine with age. These deviations are often difficult to

  1. Maximum Likelihood Factor Structure of the Family Environment Scale.

    Science.gov (United States)

    Fowler, Patrick C.

    1981-01-01

    Presents the maximum likelihood factor structure of the Family Environment Scale. The first bipolar dimension, "cohesion v conflict," measures relationship-centered concerns, while the second unipolar dimension is an index of "organizational and control" activities. (Author)

  2. A broadband chip-scale optical frequency synthesizer at 2.7 × 10(-16) relative uncertainty.

    Science.gov (United States)

    Huang, Shu-Wei; Yang, Jinghui; Yu, Mingbin; McGuyer, Bart H; Kwong, Dim-Lee; Zelevinsky, Tanya; Wong, Chee Wei

    2016-04-01

    Optical frequency combs-coherent light sources that connect optical frequencies with microwave oscillations-have become the enabling tool for precision spectroscopy, optical clockwork, and attosecond physics over the past decades. Current benchmark systems are self-referenced femtosecond mode-locked lasers, but Kerr nonlinear dynamics in high-Q solid-state microresonators has recently demonstrated promising features as alternative platforms. The advance not only fosters studies of chip-scale frequency metrology but also extends the realm of optical frequency combs. We report the full stabilization of chip-scale optical frequency combs. The microcomb's two degrees of freedom, one of the comb lines and the native 18-GHz comb spacing, are simultaneously phase-locked to known optical and microwave references. Active comb spacing stabilization improves long-term stability by six orders of magnitude, reaching a record instrument-limited residual instability of [Formula: see text]. Comparing 46 nitride frequency comb lines with a fiber laser frequency comb, we demonstrate the unprecedented microcomb tooth-to-tooth relative frequency uncertainty down to 50 mHz and 2.7 × 10(-16), heralding novel solid-state applications in precision spectroscopy, coherent communications, and astronomical spectrography.

  3. A broadband chip-scale optical frequency synthesizer at 2.7 × 10−16 relative uncertainty

    Science.gov (United States)

    Huang, Shu-Wei; Yang, Jinghui; Yu, Mingbin; McGuyer, Bart H.; Kwong, Dim-Lee; Zelevinsky, Tanya; Wong, Chee Wei

    2016-01-01

    Optical frequency combs—coherent light sources that connect optical frequencies with microwave oscillations—have become the enabling tool for precision spectroscopy, optical clockwork, and attosecond physics over the past decades. Current benchmark systems are self-referenced femtosecond mode-locked lasers, but Kerr nonlinear dynamics in high-Q solid-state microresonators has recently demonstrated promising features as alternative platforms. The advance not only fosters studies of chip-scale frequency metrology but also extends the realm of optical frequency combs. We report the full stabilization of chip-scale optical frequency combs. The microcomb’s two degrees of freedom, one of the comb lines and the native 18-GHz comb spacing, are simultaneously phase-locked to known optical and microwave references. Active comb spacing stabilization improves long-term stability by six orders of magnitude, reaching a record instrument-limited residual instability of 3.6mHz/τ. Comparing 46 nitride frequency comb lines with a fiber laser frequency comb, we demonstrate the unprecedented microcomb tooth-to-tooth relative frequency uncertainty down to 50 mHz and 2.7 × 10−16, heralding novel solid-state applications in precision spectroscopy, coherent communications, and astronomical spectrography. PMID:27152341

  4. Scale Factor in Very Early Universe with the Extra Dimensions

    CERN Document Server

    Mohsenzadeh, M

    2010-01-01

    The main goal of this paper is presentation an expanding scenario of 5-dimensional space-time in the very early universe. We introduce the 5-dimensional generalized FRW metric and obtain the evolution of the bulk scale factor with space-like and time-like extra dimensions. It is shown that, additional space-like dimensions can produce an exponentially expansion for the bulk scale factor under repulsive strong gravitational force in the empty very early universe with the extra dimension.

  5. Confirmatory Factor Analysis of the Geriatric Depression Scale

    Science.gov (United States)

    Adams, Kathryn Betts; Matto, Holly C.; Sanders, Sara

    2004-01-01

    Purpose: The Geriatric Depression Scale (GDS) is widely used in clinical and research settings to screen older adults for depressive symptoms. Although several exploratory factor analytic structures have been proposed for the scale, no independent confirmation has been made available that would enable investigators to confidently identify scores…

  6. A Factor Analytic Study of the Internet Usage Scale

    Science.gov (United States)

    Monetti, David M.; Whatley, Mark A.; Hinkle, Kerry T.; Cunningham, Kerry T.; Breneiser, Jennifer E.; Kisling, Rhea

    2011-01-01

    This study developed an Internet Usage Scale (IUS) for use with adolescent populations. The IUS is a 26-item scale that measures participants' beliefs about how their Internet usage impacts their behavior. The sample for this study consisted of 947 middle school students. An exploratory factor analysis with varimax rotation was conducted on the…

  7. Bridging the gap between uncertainty analysis for complex watershed models and decision-making for watershed-scale water management

    Science.gov (United States)

    Zheng, Y.; Han, F.; Wu, B.

    2013-12-01

    Process-based, spatially distributed and dynamic models provide desirable resolutions to watershed-scale water management. However, their reliability in solving real management problems has been seriously questioned, since the model simulation usually involves significant uncertainty with complicated origins. Uncertainty analysis (UA) for complex hydrological models has been a hot topic in the past decade, and a variety of UA approaches have been developed, but mostly in a theoretical setting. Whether and how a UA could benefit real management decisions remains to be critical questions. We have conducted a series of studies to investigate the applicability of classic approaches, such as GLUE and Markov Chain Monte Carlo (MCMC) methods, in real management settings, unravel the difficulties encountered by such methods, and tailor the methods to better serve the management. Frameworks and new algorithms, such as Probabilistic Collocation Method (PCM)-based approaches, were also proposed for specific management issues. This presentation summarize our past and ongoing studies on the role of UA in real water management. Challenges and potential strategies to bridge the gap between UA for complex models and decision-making for management will be discussed. Future directions for the research in this field will also be suggested. Two common water management settings were examined. One is the Total Maximum Daily Loads (TMDLs) management for surface water quality protection. The other is integrated water resources management for watershed sustainability. For the first setting, nutrients and pesticides TMDLs in the Newport Bay Watershed (Orange Country, California, USA) were discussed. It is a highly urbanized region with a semi-arid Mediterranean climate, typical of the western U.S. For the second setting, the water resources management in the Zhangye Basin (the midstream part of Heihe Baisn, China), where the famous 'Silk Road' came through, was investigated. The Zhangye

  8. Multi-model seasonal forecast of Arctic sea-ice: forecast uncertainty at pan-Arctic and regional scales

    Science.gov (United States)

    Blanchard-Wrigglesworth, E.; Barthélemy, A.; Chevallier, M.; Cullather, R.; Fučkar, N.; Massonnet, F.; Posey, P.; Wang, W.; Zhang, J.; Ardilouze, C.; Bitz, C. M.; Vernieres, G.; Wallcraft, A.; Wang, M.

    2016-10-01

    Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or forecast post-processing (bias correction) techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

  9. Multi-model seasonal forecast of Arctic sea-ice: forecast uncertainty at pan-Arctic and regional scales

    Science.gov (United States)

    Blanchard-Wrigglesworth, E.; Barthélemy, A.; Chevallier, M.; Cullather, R.; Fučkar, N.; Massonnet, F.; Posey, P.; Wang, W.; Zhang, J.; Ardilouze, C.; Bitz, C. M.; Vernieres, G.; Wallcraft, A.; Wang, M.

    2017-08-01

    Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or forecast post-processing (bias correction) techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

  10. Confirmatory Factor Analysis of the Procrastination Assessment Scale for Students

    Directory of Open Access Journals (Sweden)

    Ronald D. Yockey

    2015-10-01

    Full Text Available The relative fit of one- and two-factor models of the Procrastination Assessment Scale for Students (PASS was investigated using confirmatory factor analysis on an ethnically diverse sample of 345 participants. The results indicated that although the two-factor model provided better fit to the data than the one-factor model, neither model provided optimal fit. However, a two-factor model which accounted for common item theme pairs used by Solomon and Rothblum in the creation of the scale provided good fit to the data. In addition, a significant difference by ethnicity was also found on the fear of failure subscale of the PASS, with Whites having significantly lower scores than Asian Americans or Latino/as. Implications of the results are discussed and recommendations made for future work with the scale.

  11. Full uncertainty quantification of N2O and NO emissions using the biogeochemical model LandscapeDNDC on site and regional scale

    Science.gov (United States)

    Haas, Edwin; Santabarbara, Ignacio; Kiese, Ralf; Butterbach-Bahl, Klaus

    2017-04-01

    Numerical simulation models are increasingly used to estimate greenhouse gas emissions at site to regional / national scale and are outlined as the most advanced methodology (Tier 3) in the framework of UNFCCC reporting. Process-based models incorporate the major processes of the carbon and nitrogen cycle of terrestrial ecosystems and are thus thought to be widely applicable at various conditions and spatial scales. Process based modelling requires high spatial resolution input data on soil properties, climate drivers and management information. The acceptance of model based inventory calculations depends on the assessment of the inventory's uncertainty (model, input data and parameter induced uncertainties). In this study we fully quantify the uncertainty in modelling soil N2O and NO emissions from arable, grassland and forest soils using the biogeochemical model LandscapeDNDC. We address model induced uncertainty (MU) by contrasting two different soil biogeochemistry modules within LandscapeDNDC. The parameter induced uncertainty (PU) was assessed by using joint parameter distributions for key parameters describing microbial C and N turnover processes as obtained by different Bayesian calibration studies for each model configuration. Input data induced uncertainty (DU) was addressed by Bayesian calibration of soil properties, climate drivers and agricultural management practices data. For the MU, DU and PU we performed several hundred simulations each to contribute to the individual uncertainty assessment. For the overall uncertainty quantification we assessed the model prediction probability, followed by sampled sets of input datasets and parameter distributions. Statistical analysis of the simulation results have been used to quantify the overall full uncertainty of the modelling approach. With this study we can contrast the variation in model results to the different sources of uncertainties for each ecosystem. Further we have been able to perform a fully

  12. Sensitivity of key factors and uncertainties in health risk assessment of benzene pollutant

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Predicting long-term potential human health risks from contaminants in the multimedia environment requires the use of models.However, there is uncertainty associated with these predictions of many parameters which can be represented by ranges or probability distributions rather than single value. Based on a case study with information from an actual site contaminated with benzene, this study describes the application of MMSOILS model to predict health risk and distributions of those predictions generated using Monte Carlo techniques. A sensitivity analysis was performed to evaluate which of the random variables are most important in producing the predicted distributions of health risks. The sensitivity analysis shows that the predicted distributions can be accurately reproduced using a small subset of the random variables. The practical implication of this analysis is the ability to distinguish between important versus unimportant random variables in terms of their sensitivity to selected endpoints. This directly translates into a reduction in data collection and modeling effort. It was demonstrated that how correlation coefficient could be used to evaluate contributions to overall uncertainty from each parameter. The integrated uncertainty analysis shows that although drinking groundwater risk is similar with inhalation air risk, uncertainties of total risk come dominantly from drinking groundwater route. Most percent of the variance of total risk comes from four random variables.

  13. Induced Land Use Emissions due to First and Second Generation Biofuels and Uncertainty in Land Use Emission Factors

    Directory of Open Access Journals (Sweden)

    Farzad Taheripour

    2013-01-01

    Full Text Available Much research has estimated induced land use changes (ILUCs and emissions for first generation biofuels. Relatively little has provided estimates for the second generation biofuels. This paper estimates ILUC emissions for the first and second generation biofuels. Estimated ILUC emissions are uncertain not only because their associated land use changes are uncertain, but also because of uncertainty in the land use emission factors (EFs. This paper also examines uncertainties related to these factors. The results suggest that converting crop residues to biofuel has no significant ILUC emissions, but that is not the case for dedicated energy crops. Use of dedicated energy crops transfers managed natural land and marginal land (cropland-pasture to crop production. Producing biogasoline from miscanthus generates the lowest land requirement among alterative pathways. The largest land requirement is associated with switchgrass. The difference is due largely to the assumed yields of switchgrass and miscanthus. The three major conclusions from uncertainty in emissions analyses are (1 inclusion or exclusion of cropland-pasture makes a huge difference; (2 changes in soil carbon sequestration due to changes in land cover vegetation play an important role; and (3 there is wide divergence among the emission factor sources, especially for dedicated crop conversion to ethanol.

  14. Factor Structure of Japanese Versions of Two Emotional Intelligence Scales

    Science.gov (United States)

    Fukuda, Eriko; Saklofske, Donald H.; Tamaoka, Katsuo; Fung, Tak Shing; Miyaoka, Yayoi; Kiyama, Sachiko

    2011-01-01

    This article reports the psychometric properties of two emotional intelligence measures translated into Japanese. Confirmatory factor analysis (CFA) was conducted to examine the factor structure of a Japanese version of the Wong and Law Emotional Intelligence Scale (WLEIS) completed by 310 Japanese university students. A second study employed CFA…

  15. The Dysfunctional Attitudes Scale: factor structure, reliability, and validity with older adults.

    Science.gov (United States)

    Floyd, M; Scogin, F; Chaplin, W F

    2004-03-01

    The Dysfunctional Attitudes Scale Form A (DAS-A), a self-report measure of depression-related attitudes, has been used in numerous depression studies. The DAS-A has a two-factor structure that has been found consistently with college student samples and clinically depressed samples of middle-aged adults, but it has not been validated with older adults. The present study examined the factor structure with a sample of 100 depressed older adults (average age = 68.19; average initial Hamilton Rating Scale for Depression [HRSD] score = 16.72) who participated in a depression treatment study. Results indicated the factor structure established with younger adults was not replicated with older adults. Furthermore, the factor structure with older adults was uncertain: a single factor structure, two-factor structure, and three-factor structure were essentially of equal validity. The uncertainty of the latent structure of the DAS-A suggests that it should be interpreted with caution whenever used with older adults.

  16. Examining the factor structure of the Multiple Sclerosis Impact Scale.

    Science.gov (United States)

    Fitzgerald, Shawn M; Li, Jian; Rumrill, Phillip D; Merchant, William; Bishop, Malachy

    2014-01-01

    The purpose of this study was to investigate the factor structure of the Multiple Sclerosis Impact Scale (MSIS-29) to assess its suitability for modeling the impact of MS on a nation-wide sample of individuals from the United States. Investigators completed a Confirmatory Factor Analysis (CFA) to examine the two-factor structure proposed by Hobart et al. [17]. Although the original MSIS-29 factor structure did not fit the data exactly, the hypothesized two-factor model was partially supported in the current data. Implications for future instrument development and rehabilitation practice are discussed.

  17. THE UNCERTAINTY AND THE RISK – REORIENTATION FACTORS OF THE INVESTMENT STRATEGIES

    Directory of Open Access Journals (Sweden)

    Halmi Mirela Camelia

    2013-03-01

    Full Text Available The Foreign Direct Investment represents one of the ways to access a foreign market and to internationalize the activities. A company that decides to become international faces a number of risks that that have to be taken into account and analyzed. These risks are associated to the complete uncertainty regarding the business’ success that comprises many risks. The economic risk is linked mainly to the macroeconomic conditions of the host country like the real structure of the interest rate as well as to exchange rate’s movements and volatility. The role of the risk’s instability is important having in view the fact that a great part of the influxes of foreign direct investments are towards emerging economies. As a result, an interesting problem that is worth being studied is the combined effect of the uncertainty and the risk on the foreign direct investment’s quantity and direction.

  18. THE UNCERTAINTY AND THE RISK – REORIENTATION FACTORS OF THE INVESTMENT STRATEGIES

    OpenAIRE

    Halmi Mirela Camelia

    2013-01-01

    The Foreign Direct Investment represents one of the ways to access a foreign market and to internationalize the activities. A company that decides to become international faces a number of risks that that have to be taken into account and analyzed. These risks are associated to the complete uncertainty regarding the business’ success that comprises many risks. The economic risk is linked mainly to the macroeconomic conditions of the host country like the real structure of the interest rate as...

  19. Data replicating the factor structure and reliability of commonly used measures of resilience: The Connor-Davidson Resilience Scale, Resilience Scale, and Scale of Protective Factors.

    Science.gov (United States)

    Madewell, A N; Ponce-Garcia, E; Martin, S E

    2016-09-01

    The data presented in this article are related to the article entitled "Assessing Resilience in Emerging Adulthood: The Resilience Scale (RS), Connor Davidson Resilience Scale (CD-RISC), and Scale of Protective Factors (SPF)" (Madewell and Ponce-Garcia, 2016) [1]. The data were collected from a sample of 451 college students from three universities located in the Southwestern region of the United States: 374 from a large public university and 67 from two smaller regional universities. The data from the three universities did not significantly differ in terms of demographics. The data represent participant responses on six measurements to include the Resilience Scale-25 (RS-25), Resilience Scale-14 (RS-14), Connor Davidson Resilience Scale-25 (CD-RISC-25), Connor Davidson Resilience Scale-10 (CD-RISC-10), Scale of Protective Factors-24 (SPF-24), and the Life Stressor Checklist Revised (LSC-R).

  20. The Large-Scale Ocean Dynamical Effect on uncertainty in the Tropical Pacific SST Warming Pattern in CMIP5 Models

    Science.gov (United States)

    Ying, Jun; Huang, Ping

    2017-04-01

    This study investigates how intermodel differences in large-scale ocean dynamics affect the tropical Pacific sea surface temperature (SST) warming (TPSW) pattern under global warming, as projected by 32 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The largest cause of intermodel TPSW pattern differences is related to the cloud-radiation feedback. After removing the effect of cloud-radiation feedback, we find that differences in ocean advection play the next largest role, explaining around 14% of the total intermodel variance in TPSW pattern. Of particular importance are differences in climatological zonal overturning circulation among the models. With the robust enhancement of ocean stratification across models, models with relatively strong climatological upwelling tend to have relatively weak SST warming in the eastern Pacific. Meanwhile, the pronounced intermodel differences in ocean overturning changes under global warming contribute little to uncertainty in the TPSW pattern. The intermodel differences in climatological zonal overturning are found to be associated with the intermodel spread in climatological SST. In most CMIP5 models, there is a common cold tongue bias associated with an overly strong overturning in the climatology simulation, implying a LaNiña-like bias in the TPSW pattern projected by the MME of the CMIP5 models. This provides further evidence for the projection that the TPSW pattern should be closer to an El Niño-like pattern than the MME projection.

  1. Uncertainty in Predicted Neighborhood-Scale Green Stormwater Infrastructure Performance Informed by field monitoring of Hydrologic Abstractions

    Science.gov (United States)

    Smalls-Mantey, L.; Jeffers, S.; Montalto, F. A.

    2013-12-01

    Human alterations to the environment provide infrastructure for housing and transportation but have drastically changed local hydrology. Excess stormwater runoff from impervious surfaces generates erosion, overburdens sewer infrastructure, and can pollute receiving bodies. Increased attention to green stormwater management controls is based on the premise that some of these issues can be mitigated by capturing or slowing the flow of stormwater. However, our ability to predict actual green infrastructure facility performance using physical or statistical methods needs additional validation, and efforts to incorporate green infrastructure controls into hydrologic models are still in their infancy stages. We use more than three years of field monitoring data to derive facility specific probability density functions characterizing the hydrologic abstractions provided by a stormwater treatment wetland, streetside bioretention facility, and a green roof. The monitoring results are normalized by impervious area treated, and incorporated into a neighborhood-scale agent model allowing probabilistic comparisons of the stormwater capture outcomes associated with alternative urban greening scenarios. Specifically, we compare the uncertainty introduced into the model by facility performance (as represented by the variability in the abstraction), to that introduced by both precipitation variability, and spatial patterns of emergence of different types of green infrastructure. The modeling results are used to update a discussion about the potential effectiveness of urban green infrastructure implementation plans.

  2. Calibration of Gyros with Temperature Dependent Scale Factors

    Science.gov (United States)

    Belur, Sheela V.; Harman, Richard

    2001-01-01

    The general problem of gyro calibration can be stated as the estimation of the scale factors, misalignments, and drift-rate biases of the gyro using the on-orbit sensor measurements. These gyro parameters have been traditionally treated as temperature-independent in the operational flight dynamics ground systems at NASA Goddard Space Flight Center (GSFC), a scenario which has been successfully applied in the gyro calibration of a large number of missions. A significant departure from this is the Microwave Anisotropy Probe (MAP) mission where, due to the high thermal variations expected during the mission phase, it is necessary to model the scale factors as functions of temperature. This paper addresses the issue of gyro calibration for the MAP gyro model using a manufacturer-supplied model of the variation of scale factors with temperature. The problem is formulated as a least squares problem and solved using the Levenberg-Marquardt algorithm in the MATLAB(R) library function NLSQ. The algorithm was tested on simulated data with Gaussian noise for the quaternions as well as the gyro rates and was found to consistently converge close to the true values. Significant improvement in accuracy was noticed due to the estimation of the temperature-dependent scale factors as against constant scale factors.

  3. INVESTIGATING THE FACTOR STRUCTURE OF THE BLOG ATTITUDE SCALE

    Directory of Open Access Journals (Sweden)

    Zahra SHAHSAVAR

    2010-10-01

    Full Text Available Due to the wide application of advanced technology in education, many attitude scales have been developed to evaluate learners’ attitudes toward educational tools. However, with the rapid development of emerging technologies, using blogs as one of the Web 2.0 tools is still in its infancy and few blog attitude scales have been developed yet. In view of this need, a lot of researchers like to design a new scale based on their conceptual and theoretical framework of their own study rather than using available scales. The present study reports the design and development of a blog attitude scale (BAS. The researchers developed a pool of items to capture the complexity of the blog attitude trait, selected 29 items in the content analysis, and assigned the scale comprising 29 items to 216 undergraduate students to explore the underlying structure of the BAS. In exploratory factor analysis, three factors were discovered: blog anxiety, blog desirability, and blog self-efficacy; 14 items were excluded. The extracted items were subjected to a confirmatory factor analysis which lent further support to the BAS underpinning structure.

  4. On the thermodynamics of scale factor dual Universes

    CERN Document Server

    Sotkov, G M; da Silva, U Camara

    2016-01-01

    The thermodynamical aspects of the conformal time scale factor duality (SFD) of cosmological models within Einstein Gravity are investigated. We derive the SFD transformations of the thermodynamical quantities describing the thermal evolution of the matter fluid and of the apparent horizon. The thermodynamical properties of the self-dual cosmological models with a modified Chaplygin gas are studied in detail. We deduce the restrictions on the equation of state parameters that allow to extend scale factor duality as a UV/IR symmetry of the cosmological models consistent with their thermodynamical behavior.

  5. Scale Development: Factors Affecting Diet, Exercise, and Stress Management (FADESM

    Directory of Open Access Journals (Sweden)

    Nitzke Susan

    2008-02-01

    Full Text Available Abstract Background The objective of this study was to develop scales measuring personal and environmental factors that affect dietary fat intake behavior, physical activity, and stress management in low-income mothers. Methods FADESM (factors affecting diet, exercise, and stress management scales were developed using the Social Cognitive Theory to measure personal (outcome expectancies, self-efficacy, emotional coping response and environmental (physical environment, social environment, situation factors affecting dietary fat intake behavior, physical activity, and stress management. Low-income African American and white mothers were recruited from the Special Supplemental Nutrition Program for Women, Infants, and Children in three counties in Michigan. In Phase one, 45 mothers completed individual cognitive interviews. Content analyses were performed. In Phase two, items modified from the cognitive interviews were administered to 216 mothers. Factor analysis and multiple indicators/multiple causes were performed. Results Results of cognitive interviews were used to revise items for the instrument that was tested in Phase two. The factor solution revealed 19 dimensions to measure personal and environmental factors affecting dietary fat intake behavior (three dimensions, physical activity (eight dimensions, and stress management (eight dimensions. Results of multiple indicators/multiple causes model showed scale invariance. Of 19 dimensions, 15 had Cronbach alpha between 0.76 and 0.94 and four were between 0.66 and 0.69. All dimensions had composite construct reliability scores between 0.74 to 0.97 and satisfactory construct and discriminant validities. Conclusion The theory-based FADESM scales have documented good validity and reliability for measuring factors affecting dietary fat intake behavior, physical activity, and stress management in low-income women. Results of this study support the use of these scales with low-income African American

  6. Modeling field-scale multiple tracer injection at a low-level waste disposal site in fractured rocks: Effect of multiscale heterogeneity and source term uncertainty on conceptual understanding of mass transfer processes

    Science.gov (United States)

    Gwo, Jin-Ping; Jardine, Philip M.; Sanford, William E.

    2005-03-01

    Multiple factors may affect the scale-up of laboratory multi-tracer injection into structured porous media to the field. Under transient flow conditions and with multiscale heterogeneities in the field, previous attempts to scale-up laboratory experiments have not answered definitely the questions about the governing mechanisms and the spatial extent of the influence of small-scale mass transfer processes such as matrix diffusion. The objective of this research is to investigate the effects of multiscale heterogeneity, mechanistic and site model conceptualization, and source term density effect on elucidating and interpreting tracer movement in the field. Tracer release and monitoring information previously obtained in a field campaign of multiple, conservative tracer injection under natural hydraulic gradients at a low-level waste disposal site in eastern Tennessee, United States, is used for the research. A suite of two-pore-domain, or fracture-matrix, groundwater flow and transport models are calibrated and used to conduct model parameter and prediction uncertainty analyses. These efforts are facilitated by a novel nested Latin-hypercube sampling technique. Our results verify, at field scale, a multiple-pore-domain, multiscale mechanistic conceptual model that was used previously to interpret only laboratory observations. The results also suggest that, integrated over the entire field site, mass flux rates attributable to small-scale mass transfer are comparable to that of field-scale solute transport. The uncertainty analyses show that fracture spacing is the most important model parameter and model prediction uncertainty is relatively higher at the interface between the preferred flow path and its parent bedrock. The comparisons of site conceptual models indicate that the effect of matrix diffusion may be confined to the immediate neighborhood of the preferential flow path. Finally, because the relatively large amount of tracer needed for field studies, it is

  7. Local Management Practices for Dealing with Change and Uncertainty: A Cross-scale Comparison of Cases in Sweden and Tanzania

    Directory of Open Access Journals (Sweden)

    Kristina Belfrage

    2004-12-01

    Full Text Available We investigated and compared management practices for dealing with uncertainty in agroecosystem dynamics in two cases of smallholder farming in different parts of the world: northeast Tanzania and east-central Sweden. Qualitative research methods were applied to map farmers' practices related to agroecosystem management. The practices are clustered according to a framework of ecosystem services relevant for agricultural production and discussed using a theoretical model of ecosystem dynamics. Almost half of the identified practices were found to be similar in both cases, with similar approaches for adjusting to and dealing with local variability and disturbance. Practices that embraced the ecological roles of wild as well as domesticated flora and fauna and the use of qualitative biological indicators are identified as tools that built insurance capital for change and enhanced the capacity to respond to changing agroecosystem dynamics. Diversification in time and space, as well as more specific practices for mitigating pest outbreaks and temporary droughts, can limit the effects of disturbance. In both Sweden and Tanzania, we identified social mechanisms for the protection of species that served important functions in the agroecosystem. We also found examples of how old practices served as a source of adaptations for dealing with new conditions and that new knowledge was adjusted to local conditions. The study shows that comparing management practices across scales and in different cultural settings can reveal insights into the capacity of farmers to adjust, respond to, and shape ecosystem dynamics. We emphasize the importance of continuous learning for developing the sustainable management of complex agroecosystems and securing agricultural production for the future.

  8. A method for the construction of strongly reduced representations of ATLAS experimental uncertainties and the application thereof to the jet energy scale

    CERN Document Server

    The ATLAS collaboration

    2015-01-01

    A method is presented for the reduction of large sets of related uncertainty sources into strongly reduced representations which retain a suitable level of correlation information for use in many cases. So long as the search or measurement is not sensitive to the details of the correlations associated with the uncertainty source, this procedure can be used to reduce the complexity of the analysis. The method provides a self-consistent means of determining whether a given analysis is sensitive to the loss of correlation information arising from the reduction procedure. The method is applied to the ATLAS Jet Energy Scale (JES) uncertainty, demonstrating that the set of 67 independent sources can be strongly reduced to form a representation constructed of 3 nuisance parameters. By forming a set of four such representations, it is shown that JES correlation information is retained or probed over the full parameter space to within an average of 1%. This procedure is expected to significantly reduce the computation...

  9. Optomechanical Analogy for Toy Cosmology with Quantized Scale Factor

    Directory of Open Access Journals (Sweden)

    Joseph A. Smiga

    2017-09-01

    Full Text Available The simplest cosmology—the Friedmann–Robertson–Walker–Lemaître (FRW model— describes a spatially homogeneous and isotropic universe where the scale factor is the only dynamical parameter. Here we consider how quantized electromagnetic fields become entangled with the scale factor in a toy version of the FRW model. A system consisting of a photon, source, and detector is described in such a universe, and we find that the detection of a redshifted photon by the detector system constrains possible scale factor superpositions. Thus, measuring the redshift of the photon is equivalent to a weak measurement of the underlying cosmology. We also consider a potential optomechanical analogy system that would enable experimental exploration of these concepts. The analogy focuses on the effects of photon redshift measurement as a quantum back-action on metric variables, where the position of a movable mirror plays the role of the scale factor. By working in the rotating frame, an effective Hubble equation can be simulated with a simple free moving mirror.

  10. Confirmatory Factor Analysis of the Work Locus of Control Scale

    Science.gov (United States)

    Oliver, Joseph E.; Jose, Paul E.; Brough, Paula

    2006-01-01

    Original formulations of the Work Locus of Control Scale (WLCS) proposed a unidimensional structure of this measure; however, more recently, evidence for a two-dimensional structure has been reported, with separate subscales for internal and external loci of control. The current study evaluates the one- and two-factor models with confirmatory…

  11. Rosenberg's Self-Esteem Scale: Two Factors or Method Effects.

    Science.gov (United States)

    Tomas, Jose M.; Oliver, Amparo

    1999-01-01

    Results of a study with 640 Spanish high school students suggest the existence of a global self-esteem factor underlying responses to Rosenberg's (M. Rosenberg, 1965) Self-Esteem Scale, although the inclusion of method effects is needed to achieve a good model fit. Method effects are associated with item wording. (SLD)

  12. Summer Student Report: ATLAS Muon Trigger Scale Factors Tools Update

    CERN Document Server

    Veeorg, Janno

    2017-01-01

    The summer student project was done in ATLAS muon trigger group. The task was to improve different tools used to provide scale factors for muon trigger. They contained many hardcoded things which were removed to make code easier to read and maintain..

  13. [Cross validity of the UCLA Loneliness Scale factorization].

    Science.gov (United States)

    Borges, Africa; Prieto, Pedro; Ricchetti, Giacinto; Hernández-Jorge, Carmen; Rodríguez-Naveiras, Elena

    2008-11-01

    Loneliness is an unpleasant experience that takes place when a person's network of social relationships is significantly deficient in quality and quantity, and it is associated with negative feelings. Loneliness is a fundamental construct that provides information about several psychological processes, especially in the clinical setting. It is well known that this construct is related to isolation and emotional loneliness. One of the most well-known psychometric instruments to measure loneliness is the revised UCLA Loneliness Scale, which has been factorized in several populations. A controversial issue related to the UCLA Loneliness Scale is its factor structure, because the test was first created based on a unidimensional structure; however, subsequent research has proved that its structure may be bipolar or even multidimensional. In the present work, the UCLA Loneliness Scale was completed by two populations: Spanish and Italian undergraduate university students. Results show a multifactorial structure in both samples. This research presents a theoretically and analytically coherent bifactorial structure.

  14. Rigorous evaluation of chemical measurement uncertainty: liquid chromatographic analysis methods using detector response factor calibration

    Science.gov (United States)

    Toman, Blaza; Nelson, Michael A.; Bedner, Mary

    2017-06-01

    Chemical measurement methods are designed to promote accurate knowledge of a measurand or system. As such, these methods often allow elicitation of latent sources of variability and correlation in experimental data. They typically implement measurement equations that support quantification of effects associated with calibration standards and other known or observed parametric variables. Additionally, multiple samples and calibrants are usually analyzed to assess accuracy of the measurement procedure and repeatability by the analyst. Thus, a realistic assessment of uncertainty for most chemical measurement methods is not purely bottom-up (based on the measurement equation) or top-down (based on the experimental design), but inherently contains elements of both. Confidence in results must be rigorously evaluated for the sources of variability in all of the bottom-up and top-down elements. This type of analysis presents unique challenges due to various statistical correlations among the outputs of measurement equations. One approach is to use a Bayesian hierarchical (BH) model which is intrinsically rigorous, thus making it a straightforward method for use with complex experimental designs, particularly when correlations among data are numerous and difficult to elucidate or explicitly quantify. In simpler cases, careful analysis using GUM Supplement 1 (MC) methods augmented with random effects meta analysis yields similar results to a full BH model analysis. In this article we describe both approaches to rigorous uncertainty evaluation using as examples measurements of 25-hydroxyvitamin D3 in solution reference materials via liquid chromatography with UV absorbance detection (LC-UV) and liquid chromatography mass spectrometric detection using isotope dilution (LC-IDMS).

  15. Rigorous evaluation of chemical measurement uncertainty: Liquid chromatographic analysis methods using detector response factor calibration.

    Science.gov (United States)

    Toman, Blaza; Nelson, Michael A; Bedner, Mary

    2017-06-01

    Chemical measurement methods are designed to promote accurate knowledge of a measurand or system. As such, these methods often allow elicitation of latent sources of variability and correlation in experimental data. They typically implement measurement equations that support quantification of effects associated with calibration standards and other known or observed parametric variables. Additionally, multiple samples and calibrants are usually analyzed to assess accuracy of the measurement procedure and repeatability by the analyst. Thus, a realistic assessment of uncertainty for most chemical measurement methods is not purely bottom-up (based on the measurement equation) or top-down (based on the experimental design), but inherently contains elements of both. Confidence in results must be rigorously evaluated for the sources of variability in all of the bottom-up and top-down elements. This type of analysis presents unique challenges due to various statistical correlations among the outputs of measurement equations. One approach is to use a Bayesian hierarchical (BH) model which is intrinsically rigorous, thus making it a straightforward method for use with complex experimental designs, particularly when correlations among data are numerous and difficult to elucidate or explicitly quantify. In simpler cases, careful analysis using GUM Supplement 1 (MC) methods augmented with random effects meta analysis yields similar results to a full BH model analysis. In this article we describe both approaches to rigorous uncertainty evaluation using as examples measurements of 25-hydroxyvitamin D3 in solution reference materials via liquid chromatography with UV absorbance detection (LC-UV) and liquid chromatography mass spectrometric detection using isotope dilution (LC-IDMS).

  16. Hydrogeological boundary settings in SR 97. Uncertainties in regional boundary settings and transfer of boundary conditions to site-scale models

    Energy Technology Data Exchange (ETDEWEB)

    Follin, S. [Golder Grundteknik, Uppsala (Sweden)

    1999-06-01

    The SR 97 project presents a performance assessment (PA) of the overall safety of a hypothetical deep repository at three sites in Sweden arbitrarily named Aberg, Beberg and Ceberg. One component of this PA assesses the uncertainties in the hydrogeological modelling. This study focuses on uncertainties in boundary settings (size of model domain and boundary conditions) in the regional and site-scale hydrogeological modelling of the three sites used to simulating the possible transport of radionuclides from the emplacement waste packages through the host rock to the accessible environment. Model uncertainties associated with, for instance, parameter heterogeneity and structural interpretations are addressed in other studies. This study concludes that the regional modelling of the SR 97 project addresses uncertainties in the choice of boundary conditions and size of model domain differently at each site, although the overall handling is acceptable and in accordance with common modelling practice. For example, the treatment of uncertainties with regard to the ongoing post-glacial flushing of the Baltic Shield is creditably addressed although not exhaustive from a modelling point of view. A significant contribution of the performed modelling is the study of nested numerical models, i.e., the numerical interplay between regional and site-scale numerical models. In the site-scale modelling great efforts are made to address problems associated with (i) the telescopic mesh refinement (TMR) technique with regard to the stochastic continuum approach, and (ii) the transfer of boundary conditions between variable-density flow systems and flow systems that are constrained to treat uniform density flow. This study concludes that the efforts made to handle these problems are acceptable with regards to the objectives of the SR 97 project.

  17. Factor structure of the Private Self-Consciousness Scale.

    Science.gov (United States)

    Anderson, E M; Bohon, L M; Berrigan, L P

    1996-02-01

    Several issues concerning the factors of the Private Self-Consciousness Scale (PRSC) of Fenigstein et al. (1975) are examined, including possible artifactuality and appropriate conceptualization. Findings confirm the existence of the 2 factors reported in previous research (Burnkrant & Page, 1984; Lennox, Welch, Wolfe, Zimmerman, & Dixon, 1987; Mittal & Balasubramanian, 1987; Piliavin & Charng, 1988) and suggest that these factors are substantive, not artifactual, in nature. One factor was found to be associated with mild levels of psychopathology, whereas the other was not. In addition to providing a clearer conception of the nature of these factors, our results may help to resolve apparently contradictory findings in the PRSC literature. Implications for research on self-focused attention are also discussed.

  18. Feelings about culture scales: development, factor structure, reliability, and validity.

    Science.gov (United States)

    Maffini, Cara S; Wong, Y Joel

    2015-04-01

    Although measures of cultural identity, values, and behavior exist in the multicultural psychological literature, there is currently no measure that explicitly assesses ethnic minority individuals' positive and negative affect toward culture. Therefore, we developed 2 new measures called the Feelings About Culture Scale--Ethnic Culture and Feelings About Culture Scale--Mainstream American Culture and tested their psychometric properties. In 6 studies, we piloted the measures, conducted factor analyses to clarify their factor structure, and examined reliability and validity. The factor structure revealed 2 dimensions reflecting positive and negative affect for each measure. Results provided evidence for convergent, discriminant, criterion-related, and incremental validity as well as the reliability of the scales. The Feelings About Culture Scales are the first known measures to examine both positive and negative affect toward an individual's ethnic culture and mainstream American culture. The focus on affect captures dimensions of psychological experiences that differ from cognitive and behavioral constructs often used to measure cultural orientation. These measures can serve as a valuable contribution to both research and counseling by providing insight into the nuanced affective experiences ethnic minority individuals have toward culture.

  19. Management of groundwater in-situ bioremediation system using reactive transport modelling under parametric uncertainty: field scale application

    Science.gov (United States)

    Verardo, E.; Atteia, O.; Rouvreau, L.

    2015-12-01

    In-situ bioremediation is a commonly used remediation technology to clean up the subsurface of petroleum-contaminated sites. Forecasting remedial performance (in terms of flux and mass reduction) is a challenge due to uncertainties associated with source properties and the uncertainties associated with contribution and efficiency of concentration reducing mechanisms. In this study, predictive uncertainty analysis of bio-remediation system efficiency is carried out with the null-space Monte Carlo (NSMC) method which combines the calibration solution-space parameters with the ensemble of null-space parameters, creating sets of calibration-constrained parameters for input to follow-on remedial efficiency. The first step in the NSMC methodology for uncertainty analysis is model calibration. The model calibration was conducted by matching simulated BTEX concentration to a total of 48 observations from historical data before implementation of treatment. Two different bio-remediation designs were then implemented in the calibrated model. The first consists in pumping/injection wells and the second in permeable barrier coupled with infiltration across slotted piping. The NSMC method was used to calculate 1000 calibration-constrained parameter sets for the two different models. Several variants of the method were implemented to investigate their effect on the efficiency of the NSMC method. The first variant implementation of the NSMC is based on a single calibrated model. In the second variant, models were calibrated from different initial parameter sets. NSMC calibration-constrained parameter sets were sampled from these different calibrated models. We demonstrate that in context of nonlinear model, second variant avoids to underestimate parameter uncertainty which may lead to a poor quantification of predictive uncertainty. Application of the proposed approach to manage bioremediation of groundwater in a real site shows that it is effective to provide support in

  20. UCLA Loneliness Scale (Version 3): reliability, validity, and factor structure.

    Science.gov (United States)

    Russell, D W

    1996-02-01

    In this article I evaluated the psychometric properties of the UCLA Loneliness Scale (Version 3). Using data from prior studies of college students, nurses, teachers, and the elderly, analyses of the reliability, validity, and factor structure of this new version of the UCLA Loneliness Scale were conducted. Results indicated that the measure was highly reliable, both in terms of internal consistency (coefficient alpha ranging from .89 to .94) and test-retest reliability over a 1-year period (r = .73). Convergent validity for the scale was indicated by significant correlations with other measures of loneliness. Construct validity was supported by significant relations with measures of the adequacy of the individual's interpersonal relationships, and by correlations between loneliness and measures of health and well-being. Confirmatory factor analyses indicated that a model incorporating a global bipolar loneliness factor along with two method factor reflecting direction of item wording provided a very good fit to the data across samples. Implications of these results for future measurement research on loneliness are discussed.

  1. Intolerance of Uncertainty: A Common Factor in the Treatment of Emotional Disorders

    Science.gov (United States)

    Boswell, James F.; Thompson-Hollands, Johanna; Farchione, Todd J.; Barlow, David H.

    2013-01-01

    Intolerance of uncertainty (IU) is a characteristic predominantly associated with generalized anxiety disorder (GAD); however, emerging evidence indicates that IU may be a shared element of emotional disorders. Aims This study aimed to examine IU across diagnostic categories, change in IU during transdiagnostic treatment, and the relationship between change in IU and treatment outcome. Method Patients diagnosed with heterogeneous anxiety and depressive disorders received up to 18 weeks of a transdiagnostic cognitive-behavioral therapy intervention. Patient self-reported IU and self-report and clinician-rated symptom/functioning measures were administered at pretreatment and posttreatment. Results When controlling for negative affectivity, IU correlated with measures of depressive symptoms and worry severity at pretreatment. Patients with GAD and panic disorder exhibited the highest pretreatment IU scores, yet IU scores did not differ significantly based on the presence or absence of a specific diagnosis. A significant decrease in IU was observed, and change in IU was related to reduced anxiety and depressive symptom levels at posttreatment across diagnostic categories. Discussion Change in IU can be observed across problem areas in transdiagnostic treatment and such change is correlated with treatment outcome. PMID:23381685

  2. Influence of the Factor of Uncertainty on Development and Implementation of Modern Russian Megaprojects

    Directory of Open Access Journals (Sweden)

    Inna Vasilyevna Mitrofanova

    2016-10-01

    Full Text Available The general culture of design, planning and implementation of megaprojects in Russia is underdeveloped. Commercialization of procedures of projects’ justification and the involvement of expert community hinder an objective assessment of risks and efficiency of investment projects, while the aspiration to save money at stages of scientific justifications and skilled and experimental checks, lead often to adventurous decisions and unpredictable consequences. The article’s purpose is to reveal the identification signs of modern territorial megaprojects as important tool of the state strategic management and to reveal a complex of the various risks accompanying processes of development and implementation of large investment projects. The special attention is paid to such types of risk as competence and corruption risks. On the example of modern Russian megaprojects, such as “the Ural Industrial – the Ural Polar”, construction of Olympic objects in the city of Sochi, the authors show that these risks became either the reason of megaproject’s rebranding, or led to essential excess of the actual expenses in comparison with the planned. The authors are sure that identification of possible corruption risks at a predesign stage, accounting of reputation risks, elimination of low competences risks are an important task aimed at decrease of uncertainty of final effect from implementation of the territorial complex megaproject.

  3. Wildfire Decision Making Under Uncertainty

    Science.gov (United States)

    Thompson, M.

    2013-12-01

    Decisions relating to wildfire management are subject to multiple sources of uncertainty, and are made by a broad range of individuals, across a multitude of environmental and socioeconomic contexts. In this presentation I will review progress towards identification and characterization of uncertainties and how this information can support wildfire decision-making. First, I will review a typology of uncertainties common to wildfire management, highlighting some of the more salient sources of uncertainty and how they present challenges to assessing wildfire risk. This discussion will cover the expanding role of burn probability modeling, approaches for characterizing fire effects, and the role of multi-criteria decision analysis, and will provide illustrative examples of integrated wildfire risk assessment across a variety of planning scales. Second, I will describe a related uncertainty typology that focuses on the human dimensions of wildfire management, specifically addressing how social, psychological, and institutional factors may impair cost-effective risk mitigation. This discussion will encompass decision processes before, during, and after fire events, with a specific focus on active management of complex wildfire incidents. An improved ability to characterize uncertainties faced in wildfire management could lead to improved delivery of decision support, targeted communication strategies, and ultimately to improved wildfire management outcomes.

  4. Cosmological General Relativity With Scale Factor and Dark Energy

    CERN Document Server

    Oliveira, Firmin J

    2014-01-01

    In this paper the four-dimensional space-velocity Cosmological General Relativity of Carmeli is developed by a general solution to the Einstein field equations. The metric is given in the Tolman form and the vacuum mass density is included in the energy-momentum tensor. The scale factor redshift equation is obtained, forming the basis for deriving the various redshift-distance relations of cosmological analysis. A linear equation of state dependent on the scale factor is assumed to account for the effects of an evolving dark energy in the expansion of the universe. Modeling simulations are provided for a few combinations of mass density, vacuum density and state parameter values over a sample of high redshift SNe Ia data. Also, the Carmeli cosmological model is derived as a special case of the general solution.

  5. Classification of Cosmic Scale Factor via Noether Gauge Symmetries

    CERN Document Server

    Jhangeer, Adil; Naz, Tayyaba; Iftikhar, Nazish

    2015-01-01

    In this paper, a complete classification of Friedmann-Robertson-Walker (FRW) spacetime by using approximate Noether approach is presented. Considered spacetime is discussed for three different types of universe i.e. flat, open and closed. Different forms of cosmic scale factor $a$ with respect to the nature of the universe, which posses the nontrivial Noether gauge symmetries (NGS) are reported. The perturbed Lagrangian corresponding to FRW metric in the Noether equation is used to get Noether operators. For different types of universe minimal and maximal set of Noether operators are reported. A list of Noether operators are also computed which is not only independent from the choice of the cosmic scale factor but also the choice type of universe. Further, corresponding energy type first integral of motions are also calculated.

  6. Calculating LOAEL/NOAEL uncertainty factors for wildlife species in ecological risk assessments

    Energy Technology Data Exchange (ETDEWEB)

    Suedel, B.C.; Clifford, P.A.; Ludwig, D.F. [EA Engineering, Science, and Technology, Inc., Hunt Valley, MD (United States)

    1995-12-31

    Terrestrial ecological risk assessments frequently require derivation of NOAELs or toxicity reference values (TRVS) against which to compare exposure estimates. However, much of the available information from the literature is LOAELS, not NOAELS. Lacking specific guidance, arbitrary factors of ten are sometimes employed for extrapolating NOAELs from LOAELs. In this study, the scientific literature was searched to obtain chronic and subchronic studies reporting NOAEL and LOAEL data for wildlife and laboratory species. Results to date indicate a mean conversion factor of 4.0 ({+-} 2.61 S.D.), with a minimum of 1. 6 and a maximum of 10 for 106 studies across several classes of compounds (I.e., metals, pesticides, volatiles, etc.). These data suggest that an arbitrary factor of 10 conversion factor is unnecessarily restrictive for extrapolating NOAELs from LOAELs and that a factor of 4--5 would be more realistic for deriving toxicity reference values for wildlife species. Applying less arbitrary and more realistic conversion factors in ecological risk assessments will allow for a more accurate estimate of NOAEL values for assessing risk to wildlife populations.

  7. Scale Factor Study for 1:30 Local Scour Model

    Science.gov (United States)

    2016-08-01

    Sedimentation engineering : ASCE manuals and reports on engineering practice, No. 54. Reston, VA: American Society of Civil Engineers ...Jeremy A. Sharp, Ronald E. Heath, Howard E. Park, and Tate O. McAlpin PURPOSE: This Coastal and Hydraulics Engineering Technical Note (CHETN... Engineer Research and Development Center, Vicksburg, MS. ERDC/CHL CHETN-VII-15 August 2016 8 For implementation, the scale factor was applied to the

  8. Adaptive projective synchronization with different scaling factors in networks

    Institute of Scientific and Technical Information of China (English)

    Guo Liu-Xiao; Xu Zhen-Yuan; Hu Man-Feng

    2008-01-01

    We study projective synchronization with different scaling factors (PSDF) in N coupled chaotic systems networks.By using the adaptive linear control,some sufficient criteria for the PSDF in symmetrical and asymmetrical coupled networks are separately given based on the Lyapunov function method and the left eigenvalue theory.Numerical simulations for a generalized chaotic unified system are illustrated to verify the theoretical results.

  9. ROLE OF SCALE FACTOR DURING TENSILE TESTING OF SMALL SPECIMENS

    Energy Technology Data Exchange (ETDEWEB)

    Gussev, Maxim N [ORNL; Busby, Jeremy T [ORNL; Field, Kevin G [ORNL; Sokolov, Mikhail A [ORNL; Gray, Mr. Sean [University of Michigan

    2014-01-01

    The influence of scale factor (tensile specimen geometry and dimensions) on mechanical test results was investigated for different widely used types of small specimens (SS-1, SS-2, SS-3, and SS-J3) and a set of materials. It was found that the effect of scale factor on the accurate determination of yield stress, ultimate tensile stress, and uniform elongation values was weak; however, clear systematic differences were observed and should be accounted for during interpretation of results. In contrast, total elongation values were strongly sensitive to variations in specimen geometry. Modern experimental methods like digital image correlation allow the impact of scale factor to be reduced. Using these techniques, it was shown that true stress true strain curves describing strain-hardening behavior were very close for different specimen types. The limits of miniaturization are discussed, and an ultra-miniature specimen concept was suggested and evaluated. This type of specimen, as expected, may be suitable for SEM and TEM in situ testing.

  10. Climate-driven uncertainties in modeling terrestrial gross primary production: a site level to global-scale analysis.

    Science.gov (United States)

    Barman, Rahul; Jain, Atul K; Liang, Miaoling

    2014-05-01

    We used a land surface model to quantify the causes and extents of biases in terrestrial gross primary production (GPP) due to the use of meteorological reanalysis datasets. We first calibrated the model using meteorology and eddy covariance data from 25 flux tower sites ranging from the tropics to the northern high latitudes and subsequently repeated the site simulations using two reanalysis datasets: NCEP/NCAR and CRUNCEP. The results show that at most sites, the reanalysis-driven GPP bias was significantly positive with respect to the observed meteorology-driven simulations. Notably, the absolute GPP bias was highest at the tropical evergreen tree sites, averaging up to ca. 0.45 kg C m(-2)  yr(-1) across sites (ca. 15% of site level GPP). At the northern mid-/high-latitude broadleaf deciduous and the needleleaf evergreen tree sites, the corresponding annual GPP biases were up to 20%. For the nontree sites, average annual biases of up to ca. 20-30% were simulated within savanna, grassland, and shrubland vegetation types. At the tree sites, the biases in short-wave radiation and humidity strongly influenced the GPP biases, while the nontree sites were more affected by biases in factors controlling water stress (precipitation, humidity, and air temperature). In this study, we also discuss the influence of seasonal patterns of meteorological biases on GPP. Finally, using model simulations for the global land surface, we discuss the potential impacts of site-level reanalysis-driven biases on the global estimates of GPP. In a broader context, our results can have important consequences on other terrestrial ecosystem fluxes (e.g., net primary production, net ecosystem production, energy/water fluxes) and reservoirs (e.g., soil carbon stocks). In a complementary study (Barman et al., ), we extend the present analysis for latent and sensible heat fluxes, thus consistently integrating the analysis of climate-driven uncertainties in carbon, energy, and water fluxes

  11. Jet energy scale and its systematic uncertainty in proton-proton collisions at sqrt(s)=7 TeV with ATLAS 2011 data

    CERN Document Server

    The ATLAS collaboration

    2013-01-01

    The jet energy scale (JES) and its systematic uncertainty are determined for jets measured with the ATLAS detector using proton-proton collision data with a centre-of-mass energy of sqrt(s) = 7 TeV corresponding to an integrated luminosity of 4.7 fb−1. Jets are reconstructed from topological clusters of calorimeter cells using the anti-kt algorithm with distance parameters R = 0.4 or R = 0.6, and are calibrated using Monte Carlo simulation. A residual JES correction is applied to account for differences between data and Monte Carlo. This correction and its systematic uncertainty are evaluated in bins of jet pseudorapidity and transverse momenta, for jets with calibrated transverse momenta pjet > 20 GeV and pseudorapidities |eta| 1 TeV. The calibration of forward jets is derived from dijet pT balance measurements. The resulting uncertainty reaches its largest value of 6% for low-pT jets at |eta| = 4.5. Additional JES uncertainties due to specific event topologies, such as close-by jets or selections of even...

  12. Modeling sugar cane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

    Directory of Open Access Journals (Sweden)

    A. Valade

    2014-01-01

    Full Text Available Agro-Land Surface Models (agro-LSM have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil-vegetation-atmosphere continuum. When developing agro-LSM models, a particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of Agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE-STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS' phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management or to ORCHIDEE (other ecosystem variables including biomass through distinct Monte-Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used to quantify the sensitivity of harvested

  13. Modeling sugarcane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

    Science.gov (United States)

    Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Caubel, A.; Huth, N.; Marin, F.; Martiné, J.-F.

    2014-06-01

    Agro-land surface models (agro-LSM) have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil-vegetation-atmosphere continuum. When developing agro-LSM models, particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugarcane biomass production with the agro-LSM ORCHIDEE-STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE-STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management) or to ORCHIDEE (other ecosystem variables including biomass) through distinct Monte Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte Carlo sampling method associated with the calculation of partial ranked correlation coefficients is used to quantify the sensitivity of harvested biomass to input

  14. Modeling sugar cane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

    Science.gov (United States)

    Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Huth, N.; Marin, F.; Martiné, J.-F.

    2014-01-01

    Agro-Land Surface Models (agro-LSM) have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil-vegetation-atmosphere continuum. When developing agro-LSM models, a particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of Agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE-STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS' phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management) or to ORCHIDEE (other ecosystem variables including biomass) through distinct Monte-Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used to quantify the sensitivity of harvested biomass to input

  15. Land-surface controls on afternoon precipitation diagnosed from observational data: uncertainties and confounding factors

    Directory of Open Access Journals (Sweden)

    B. P. Guillod

    2014-08-01

    Full Text Available The feedback between soil moisture and precipitation has long been a topic of interest due to its potential for improving weather and seasonal forecasts. The generally proposed mechanism assumes a control of soil moisture on precipitation via the partitioning of the surface turbulent heat fluxes, as assessed via the evaporative fraction (EF, i.e., the ratio of latent heat to the sum of latent and sensible heat, in particular under convective conditions. Our study investigates the poorly understood link between EF and precipitation by relating the before-noon EF to the frequency of afternoon precipitation over the contiguous US, through statistical analyses of multiple EF and precipitation data sets. We analyze remote-sensing data products (Global Land Evaporation: the Amsterdam Methodology (GLEAM for EF, and radar precipitation from the NEXt generation weather RADar system (NEXRAD, FLUXNET station data, and the North American Regional Reanalysis (NARR. Data sets agree on a region of positive relationship between EF and precipitation occurrence in the southwestern US. However, a region of strong positive relationship over the eastern US in NARR cannot be confirmed with observation-derived estimates (GLEAM, NEXRAD and FLUXNET. The GLEAM–NEXRAD data set combination indicates a region of positive EF–precipitation relationship in the central US. These disagreements emphasize large uncertainties in the EF data. Further analyses highlight that much of these EF–precipitation relationships could be explained by precipitation persistence alone, and it is unclear whether EF has an additional role in triggering afternoon precipitation. This also highlights the difficulties in isolating a land impact on precipitation. Regional analyses point to contrasting mechanisms over different regions. Over the eastern US, our analyses suggest that the EF–precipitation relationship in NARR is either atmospherically controlled (from precipitation persistence and

  16. Hotspots of uncertainty in land-use and land-cover change projections : a global-scale model comparison

    NARCIS (Netherlands)

    Prestele, Reinhard; Alexander, Peter; Rounsevell, Mark D A; Arneth, Almut; Calvin, Katherine; Doelman, Jonathan; Eitelberg, David A.; Engström, Kerstin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Humpenöder, Florian; Jain, Atul K.; Krisztin, Tamás; Kyle, Page; Meiyappan, Prasanth; Popp, Alexander; Sands, Ronald D.; Schaldach, Rüdiger; Schüngel, Jan; Stehfest, Elke; Tabeau, Andrzej; Van Meijl, Hans; Van Vliet, Jasper; Verburg, Peter H.

    2016-01-01

    Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms

  17. Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison

    NARCIS (Netherlands)

    Prestele, R.; Alexander, P.; Rounsevell, M.; Arneth, A.; Calvin, K.; Doelman, J.; Eitelberg, D.A.; Engström, K.; Fujimori, S.; Hasegawa, T.; Havlik, P.; Humpenöder, F.; Jain, A. K.; Krisztin, T.; Kyle, P.; Meiyappan, P.; Popp, A.; Sands, R.D.; Schaldach, R.; Schüngel, J.; Stehfest, E.; Tabeau, A.; Meijl, van H.; Vliet, van J.; Verburg, P.H.

    2016-01-01

    Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy.These projections are characterized by a high uncertainty in terms o

  18. Strategic Factor Markets Scale Free Resources and Economic Performance

    DEFF Research Database (Denmark)

    Geisler Asmussen, Christian

    2015-01-01

    This paper analyzes how scale free resources, which can be acquired by multiple firms simultaneously and deployed against one another in product market competition, will be priced in strategic factor markets, and what the consequences are for the acquiring firms' performance. Based on a game......-theoretic model, it shows how the impact of strategic factor markets on economic profits is influenced by product market rivalry, preexisting competitive (dis)advantages, and the interaction of acquired resources with those preexisting asymmetries. New insights include the result that resource suppliers will aim...... at (and largely succeed in) setting resource prices so that the acquiring firms earn negative strategic factor market profits—sacrificing some of their preexisting market power rents—by acquiring resources that they know to be overpriced....

  19. Uncertainty quantified trait predictions

    Science.gov (United States)

    Fazayeli, Farideh; Kattge, Jens; Banerjee, Arindam; Schrodt, Franziska; Reich, Peter

    2015-04-01

    Functional traits of organisms are key to understanding and predicting biodiversity and ecological change, which motivates continuous collection of traits and their integration into global databases. Such composite trait matrices are inherently sparse, severely limiting their usefulness for further analyses. On the other hand, traits are characterized by the phylogenetic trait signal, trait-trait correlations and environmental constraints, all of which provide information that could be used to statistically fill gaps. We propose the application of probabilistic models which, for the first time, utilize all three characteristics to fill gaps in trait databases and predict trait values at larger spatial scales. For this purpose we introduce BHPMF, a hierarchical Bayesian extension of Probabilistic Matrix Factorization (PMF). PMF is a machine learning technique which exploits the correlation structure of sparse matrices to impute missing entries. BHPMF additionally utilizes the taxonomic hierarchy for trait prediction. Implemented in the context of a Gibbs Sampler MCMC approach BHPMF provides uncertainty estimates for each trait prediction. We present comprehensive experimental results on the problem of plant trait prediction using the largest database of plant traits, where BHPMF shows strong empirical performance in uncertainty quantified trait prediction, outperforming the state-of-the-art based on point estimates. Further, we show that BHPMF is more accurate when it is confident, whereas the error is high when the uncertainty is high.

  20. Factor Structure of the Conflict Tactics Scale 1

    Directory of Open Access Journals (Sweden)

    Kaori Baba

    2017-07-01

    Full Text Available Background: The Conflict Tactics Scale 1 (CTS1 is a widely used self-report measure of abusive attitudes of parents towards children. The factor structure of the CTS1 still remains to be clarified. The aim of this study was to examine the factor structure of the Japanese version of the CTS1 for postpartum women in community settings. Method: The data in this study came from the Okayama and Kumamoto’s study. These were part of a larger survey using longitudinal questionnaire studies conducted in Japan from 2001 to 2002 and in 2011, respectively. In both study sites, the participant mothers were asked to fill in the CTS1 one month after delivery when they attended for check-up at the out-patient clinic. Results: A total of 1,150 questionnaires were collected, excluding the participants with missing values in the CTS1. Finally, 1,078 were included in the statistical analyses. Data of 1,078 women were divided into two parts. In the first halved sample (n=578, an exploratory factor analysis was conducted for the CTS1 items after exluding nine items with extremely low prevalence. It revealed 2-factor or 3-factor models. Then, we conducted a model comparison with the second halved sample (n=500, using confirmatory factor analysis. In terms of goodness-of-fit indeces, the 2-factor model was superior. Its subscales were Reasoning and Psycholosical Aggression. Conclusion: The 2-factor model of the CTS1 consisting of Reasoning and Psychological Aggression was superior to the 3-factor model. This is not inconsistent with the original authors’ theoretical model.

  1. Main features and possibilities of the new scale module for calculation of sensitivity and uncertainty by sampling: SAMPLER; Principlaes caracteristicas y posibilidades del nuevo modulo de SCALE 6.2 para calculo de sensibilidad e incertidumbre por muestreo: SAMPLER

    Energy Technology Data Exchange (ETDEWEB)

    Mesado, C.; Miro, R.; Barrachina, T.; Verdu, G.

    2014-07-01

    Due to the importance of calculating sensitivity and uncertainty in the calculation of field engineering, and especially in the nuclear world, it has been decided to present the main features of the new module present in the new version of SCALE 6.2 (currently beta 3 version) called SAMPLER. This module allows the calculation of uncertainty in a wide range of effective sections, neutron parameters, composition and physical parameters. However, the calculation of sensitivity is not present in the beta 3 release. Even so, this module can be helpful for participants of the proposed Benchmark by Expert Group on Uncertainty Analysis in Modelling (UAM-LWR), as well as to analysts in general. (Author)

  2. Improving the Factor Structure of Psychological Scales: The Expanded Format as an Alternative to the Likert Scale Format

    Science.gov (United States)

    Zhang, Xijuan; Savalei, Victoria

    2016-01-01

    Many psychological scales written in the Likert format include reverse worded (RW) items in order to control acquiescence bias. However, studies have shown that RW items often contaminate the factor structure of the scale by creating one or more method factors. The present study examines an alternative scale format, called the Expanded format,…

  3. Effect of Considering Sub-Grid Scale Uncertainties on the Forecasts of a High-Resolution Limited Area Ensemble Prediction System

    Science.gov (United States)

    Kim, SeHyun; Kim, Hyun Mee

    2017-03-01

    The ensemble prediction system (EPS) is widely used in research and at operation center because it can represent the uncertainty of predicted atmospheric state and provide information of probabilities. The high-resolution (so-called "convection-permitting") limited area EPS can represent the convection and turbulence related to precipitation phenomena in more detail, but it is also much sensitive to small-scale or sub-grid scale processes. The convection and turbulence are represented using physical processes in the model and model errors occur due to sub-grid scale processes that were not resolved. This study examined the effect of considering sub-grid scale uncertainties using the high-resolution limited area EPS of the Korea Meteorological Administration (KMA). The developed EPS has horizontal resolution of 3 km and 12 ensemble members. The initial and boundary conditions were provided by the global model. The Random Parameters (RP) scheme was used to represent sub-grid scale uncertainties. The EPSs with and without the RP scheme were developed and the results were compared. During the one month period of July, 2013, a significant difference was shown in the spread of 1.5 m temperature and the Root Mean Square Error and spread of 10 m zonal wind due to application of the RP scheme. For precipitation forecast, the precipitation tended to be overestimated relative to the observation when the RP scheme was applied. Moreover, the forecast became more accurate for heavy precipitations and the longer forecast lead times. For two heavy rainfall cases occurred during the research period, the higher Equitable Threat Score was observed for heavy precipitations in the system with the RP scheme compared to the one without, demonstrating consistency with the statistical results for the research period. Therefore, the predictability for heavy precipitation phenomena that affected the Korean Peninsula increases if the RP scheme is used to consider sub-grid scale uncertainties

  4. Decentralized robust guaranteed cost control for a class of interconnected singular large-scale systems with time-delay and parameter uncertainty

    Institute of Scientific and Technical Information of China (English)

    Wo Songlin; Shi Guodong; Zou Yun

    2007-01-01

    The decentralized robust guaranteed cost control problem is studied for a class ofinterconnected singular large-scale systems with time-delay and norm-bounded time-invariant parameter uncertainty under a given quadratic cost performance function. The problem that is addressed in this study is to design a decentralized robust guaranteed cost state feedback controller such that the closed-loop system is not only regular, impulse-free and stable, but also guarantees an adequate level of performance for all admissible uncertainties. A sufficient condition for the existence of the decentralized robust guaranteed cost state feedback controllers is proposed in terms of a linear matrix inequality (LMI) via LMI approach. When this condition is feasible, the desired state feedback decentralized robust guaranteed cost controller gain matrices can be obtained. Finally, an illustrative example is provided to demonstrate the effectiveness of the proposed approach.

  5. A method for the construction of strongly reduced representations of ATLAS experimental uncertainties and the application thereof to the jet energy scale

    CERN Document Server

    Boerner, Daniela; The ATLAS collaboration

    2016-01-01

    A method is presented for the reduction of large sets of related uncertainty sources into strongly reduced representations which retain a suitable level of correlation information for use in many cases. The method provides a self-consistent means of determining whether a given analysis is sensitive to the loss of correlation information arising from the reduction procedure. The method is applied to the ATLAS Jet Energy Scale (JES) uncertainty, demonstrating that the set of 60+ independent sources can be reduced to form a representation constructed of 3 nuisance parameters. By forming a set of four such representations, it is shown that JES correlation information is retained or probed over the full parameter space to within an average of 1%. This procedure is expected to significantly reduce the computational requirements placed upon early ATLAS searches in the upcoming 2015 dataset while still providing sufficient performance and correlation structure to avoid changing the analysis results.

  6. Factors affecting economies of scale in combined sewer systems.

    Science.gov (United States)

    Maurer, Max; Wolfram, Martin; Anja, Herlyn

    2010-01-01

    A generic model is introduced that represents the combined sewer infrastructure of a settlement quantitatively. A catchment area module first calculates the length and size distribution of the required sewer pipes on the basis of rain patterns, housing densities and area size. These results are fed into the sewer-cost module in order to estimate the combined sewer costs of the entire catchment area. A detailed analysis of the relevant input parameters for Swiss settlements is used to identify the influence of size on costs. The simulation results confirm that an economy of scale exists for combined sewer systems. This is the result of two main opposing cost factors: (i) increased construction costs for larger sewer systems due to larger pipes and increased rain runoff in larger settlements, and (ii) lower costs due to higher population and building densities in larger towns. In Switzerland, the more or less organically grown settlement structures and limited land availability emphasise the second factor to show an apparent economy of scale. This modelling approach proved to be a powerful tool for understanding the underlying factors affecting the cost structure for water infrastructures.

  7. Factors affecting the predictive validity of the Braden Scale.

    Science.gov (United States)

    Capobianco, M L; McDonald, D D

    1996-01-01

    This descriptive correlational study explored the predictive validity of the Braden Scale and factors affecting it A Braden score was determined within 4 hours of admission for 50 adult medical/surgical inpatients. Independent skin assessments were made three times a week and at discharge. Fourteen patients (28%) developed pressure ulcers. A Braden score cutoff of 18 or less resulted in a 71% sensitivity, 83% specificity, 63% predictive value of a positive test, and 88% predictive value of a negative test. Three of the four patients incorrectly predicted to be not at risk scored "inadequate" on the nutrition subscale. Two of the four also were underweight. Of the six patients incorrectly predicted at risk for a pressure ulcer, three had been placed on air mattresses and were receiving levothyroxine (Synthroid). This study provides further evidence of the Braden Scale's predictive validity. The results suggest that patients who are underweight or getting inadequate nutrition be considered at increased risk for pressure ulcers.

  8. Uncertainty analysis guide

    Energy Technology Data Exchange (ETDEWEB)

    Andres, T.H

    2002-05-01

    This guide applies to the estimation of uncertainty in quantities calculated by scientific, analysis and design computer programs that fall within the scope of AECL's software quality assurance (SQA) manual. The guide weaves together rational approaches from the SQA manual and three other diverse sources: (a) the CSAU (Code Scaling, Applicability, and Uncertainty) evaluation methodology; (b) the ISO Guide,for the Expression of Uncertainty in Measurement; and (c) the SVA (Systems Variability Analysis) method of risk analysis. This report describes the manner by which random and systematic uncertainties in calculated quantities can be estimated and expressed. Random uncertainty in model output can be attributed to uncertainties of inputs. The propagation of these uncertainties through a computer model can be represented in a variety of ways, including exact calculations, series approximations and Monte Carlo methods. Systematic uncertainties emerge from the development of the computer model itself, through simplifications and conservatisms, for example. These must be estimated and combined with random uncertainties to determine the combined uncertainty in a model output. This report also addresses the method by which uncertainties should be employed in code validation, in order to determine whether experiments and simulations agree, and whether or not a code satisfies the required tolerance for its application. (author)

  9. Comparison of SERPENT and SCALE methodology for LWRs transport calculations and additionally uncertainty analysis for cross-section perturbation with SAMPLER module

    Directory of Open Access Journals (Sweden)

    Labarile Antonella

    2016-01-01

    Full Text Available In nuclear safety research, the quality of the results of simulation codes is widely determined by the reactor design and safe operation, and the description of neutron transport in the reactor core is a feature of particular importance. Moreover, for the long effort that is made, there remain uncertainties in simulation results due to the neutronic data and input specification that need a huge effort to be eliminated. A realistic estimation of these uncertainties is required for finding out the reliability of the results. This explains the increasing demand in recent years for calculations in the nuclear fields with best-estimate codes that proved confidence bounds of simulation results. All this has lead to the Benchmark for Uncertainty Analysis in Modelling (UAM for Design, Operation and Safety Analysis of LWRs of the NEA. The UAM-Benchmark coupling multi-physics and multi-scale analysis using as a basis complete sets of input specifications of boiling water reactors (BWR and pressurized water reactors (PWR. In this study, the results of the transport calculations carried out using the SCALE-6.2 program (TRITON/NEWT and TRITON/KENO modules as well as Monte Carlo SERPENT code, are presented. Additionally, they have been made uncertainties calculation for a PWR 15 × 15 and a BWR 7 × 7 fuel elements, in two different configurations (with and without control rod, and two different states, Hot Full Power (HFP and Hot Zero Power (HZP, using the TSUNAMI module, which uses the Generalized Perturbation Theory (GPT, and SAMPLER, which uses stochastic sampling techniques for cross-sections perturbations. The results obtained and validated are compared with references results and similar studies presented in the exercise I-2 (Lattice Physics of UAM-Benchmark.

  10. Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians

    CERN Document Server

    Garrido, M C; Ruiz, A; 10.1613/jair.533

    2011-01-01

    This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of finite mixture models, conjugate families and factorization. Both the joint probability density of the variables and the likelihood function of the (objective or subjective) observation are approximated by a special mixture model, in such a way that any desired conditional distribution can be directly obtained without numerical integration. We have developed an extended version of the expectation maximization (EM) algorithm to estimate the parameters of mixture models from uncertain training examples (indirect observations). As a consequence, any piece of exact or uncertain information about both input and output values is consistently handled in the inference and learning stages. This ability, extremely useful in certain situations, is not found in most alternative methods. The proposed framework is formally justified from standard prob...

  11. Large-Scale Uncertainty and Error Analysis for Time-dependent Fluid/Structure Interactions in Wind Turbine Applications

    Energy Technology Data Exchange (ETDEWEB)

    Alonso, Juan J. [Stanford University; Iaccarino, Gianluca [Stanford University

    2013-08-25

    The following is the final report covering the entire period of this aforementioned grant, June 1, 2011 - May 31, 2013 for the portion of the effort corresponding to Stanford University (SU). SU has partnered with Sandia National Laboratories (PI: Mike S. Eldred) and Purdue University (PI: Dongbin Xiu) to complete this research project and this final report includes those contributions made by the members of the team at Stanford. Dr. Eldred is continuing his contributions to this project under a no-cost extension and his contributions to the overall effort will be detailed at a later time (once his effort has concluded) on a separate project submitted by Sandia National Laboratories. At Stanford, the team is made up of Profs. Alonso, Iaccarino, and Duraisamy, post-doctoral researcher Vinod Lakshminarayan, and graduate student Santiago Padron. At Sandia National Laboratories, the team includes Michael Eldred, Matt Barone, John Jakeman, and Stefan Domino, and at Purdue University, we have Prof. Dongbin Xiu as our main collaborator. The overall objective of this project was to develop a novel, comprehensive methodology for uncertainty quantification by combining stochastic expansions (nonintrusive polynomial chaos and stochastic collocation), the adjoint approach, and fusion with experimental data to account for aleatory and epistemic uncertainties from random variable, random field, and model form sources. The expected outcomes of this activity were detailed in the proposal and are repeated here to set the stage for the results that we have generated during the time period of execution of this project: 1. The rigorous determination of an error budget comprising numerical errors in physical space and statistical errors in stochastic space and its use for optimal allocation of resources; 2. A considerable increase in efficiency when performing uncertainty quantification with a large number of uncertain variables in complex non-linear multi-physics problems; 3. A

  12. Confirmatory factor analysis of the Sport Organizational Effectiveness Scale.

    Science.gov (United States)

    Karteroliotis, Konstantinos; Papadimitriou, Dimitra

    2004-08-01

    The purpose of this study was to examine the factorial validity of the 5-factor model of sport organizational effectiveness developed by Papadimitriou and Taylor. This questionnaire has 33 items which assess five composite effectiveness dimensions pertinent to the operation of sport organizations: calibre of the board and external liaisons, interest in athletes, internal procedures, long term planning, and sport science support. The multiple constituency approach was used as a theoretical framework for developing this scale. Data were obtained from respondents affiliated with 20 Greek national sport organizations with a questionnaire. Analysis indicated that the 5-factor model of effectiveness is workable in assessing the organizational performance of nonprofit sport organizations. The application of the multiple constituency approach in studying sport organizational effectiveness was also suggested.

  13. Projecting Future Land Use Changes in West Africa Driven by Climate and Socioeconomic Factors: Uncertainties and Implications for Adaptation

    Science.gov (United States)

    Wang, G.; Ahmed, K. F.; You, L.

    2015-12-01

    Land use changes constitute an important regional climate change forcing in West Africa, a region of strong land-atmosphere coupling. At the same time, climate change can be an important driver for land use, although its importance relative to the impact of socio-economic factors may vary significant from region to region. This study compares the contributions of climate change and socioeconomic development to potential future changes of agricultural land use in West Africa and examines various sources of uncertainty using a land use projection model (LandPro) that accounts for the impact of socioeconomic drivers on the demand side and the impact of climate-induced crop yield changes on the supply side. Future crop yield changes were simulated by a process-based crop model driven with future climate projections from a regional climate model, and future changes of food demand is projected using a model for policy analysis of agricultural commodities and trade. The impact of human decision-making on land use was explicitly considered through multiple "what-if" scenarios to examine the range of uncertainties in projecting future land use. Without agricultural intensification, the climate-induced decrease of crop yield together with increase of food demand are found to cause a significant increase in agricultural land use at the expense of forest and grassland by the mid-century, and the resulting land use land cover changes are found to feed back to the regional climate in a way that exacerbates the negative impact of climate on crop yield. Analysis of results from multiple decision-making scenarios suggests that human adaptation characterized by science-informed decision making to minimize land use could be very effective in many parts of the region.

  14. Factor structure of social fears: The Liebowitz Social Anxiety Scale.

    Science.gov (United States)

    Safren, S A; Heimberg, R G; Horner, K J; Juster, H R; Schneier, F R; Liebowitz, M R

    1999-01-01

    In the assessment of social anxiety, investigators often differentiate between social interactional anxiety and performance anxiety. The Liebowitz Social Anxiety Scale (LSAS), a clinician-administered measure of social anxiety and avoidance, was originally developed with separate subscales for the assessment of fear and avoidance of situations involving social interaction and performance/observation by others. Separate confirmatory factor analyses of the LSAS fear and avoidance ratings demonstrated that this two-factor model did not provide an adequate fit to the data, suggesting the need to further investigate the underlying structure of the LSAS. Separate exploratory common factor analyses of the fear and avoidance ratings yielded four similar factors for each: (1) social interaction, (2) public speaking, (3) observation by others, and (4) eating and drinking in public, which demonstrated convergent and discriminant validity with other measures of social anxiety. These findings suggest that there are four global categories of social fear assessed by the LSAS, and that while social interaction anxiety appears to be unifactorial, fear of performance/observation situations may be multifactorial.

  15. Testing the mapping between redshift and cosmic scale factor

    CERN Document Server

    Wojtak, Radosław

    2016-01-01

    The canonical redshift-scale factor relation, 1/a=1+z, is a key element in the standard LambdaCDM model of the Big Bang cosmology. Despite its fundamental role, this relation has not yet undergone any observational tests since Lemaitre and Hubble established the expansion of the Universe. It is strictly based on the assumption of the Friedmann-Lemaitre-Robertson-Walker metric describing a locally homogeneous and isotropic universe and that photons move on null geodesics of the metric. Thus any violation of this assumption, within general relativity or modified gravity, can yield a different mapping between the model redshift z=1/a-1 and the actually observed redshift z_obs, i.e. z_obs neq z. Here we perform a simple test of consistency for the standard redshift-scale factor relation by determining simultaneous observational constraints on the concordance LambdaCDM cosmological parameters and a generalized redshift mapping z=f(z_obs). Using current baryon acoustic oscillations (BAO) and Type Ia supernova (SN) ...

  16. Factors affecting paddy soil arsenic concentration in Bangladesh: prediction and uncertainty of geostatistical risk mapping.

    Science.gov (United States)

    Ahmed, Zia U; Panaullah, Golam M; DeGloria, Stephen D; Duxbury, John M

    2011-12-15

    Knowledge of the spatial correlation of soil arsenic (As) concentrations with environmental variables is needed to assess the nature and extent of the risk of As contamination from irrigation water in Bangladesh. We analyzed 263 paired groundwater and paddy soil samples covering highland (HL) and medium highland-1 (MHL-1) land types for geostatistical mapping of soil As and delineation of As contaminated areas in Tala Upazilla, Satkhira district. We also collected 74 non-rice soil samples to assess the baseline concentration of soil As for this area. The mean soil As concentrations (mg/kg) for different land types under rice and non-rice crops were: rice-MHL-1 (21.2)>rice-HL (14.1)>non-rice-MHL-1 (11.9)>non-rice-HL (7.2). Multiple regression analyses showed that irrigation water As, Fe, land elevation and years of tubewell operation are the important factors affecting the concentrations of As in HL paddy soils. Only years of tubewell operation affected As concentration in the MHL-1 paddy soils. Quantitatively similar increases in soil As above the estimated baseline-As concentration were observed for rice soils on HL and MHL-1 after 6-8 years of groundwater irrigation, implying strong retention of As added in irrigation water in both land types. Application of single geostatistical methods with secondary variables such as regression kriging (RK) and ordinary co-kriging (OCK) gave little improvement in prediction of soil As over ordinary kriging (OK). Comparing single prediction methods, kriging within strata (KWS), the combination of RK for HL and OCK for MHL-1, gave more accurate soil As predictions and showed the lowest misclassification of declaring a location "contaminated" with respect to 14.8 mg As/kg, the highest value obtained for the baseline soil As concentration. Prediction of soil As buildup over time indicated that 75% or the soils cropped to rice would contain at least 30 mg/L As by the year 2020. Copyright © 2011 Elsevier B.V. All rights reserved.

  17. Measurement uncertainty.

    Science.gov (United States)

    Bartley, David; Lidén, Göran

    2008-08-01

    The reporting of measurement uncertainty has recently undergone a major harmonization whereby characteristics of a measurement method obtained during establishment and application are combined componentwise. For example, the sometimes-pesky systematic error is included. A bias component of uncertainty can be often easily established as the uncertainty in the bias. However, beyond simply arriving at a value for uncertainty, meaning to this uncertainty if needed can sometimes be developed in terms of prediction confidence in uncertainty-based intervals covering what is to be measured. To this end, a link between concepts of accuracy and uncertainty is established through a simple yet accurate approximation to a random variable known as the non-central Student's t-distribution. Without a measureless and perpetual uncertainty, the drama of human life would be destroyed. Winston Churchill.

  18. Forest Conversion, Agricultural Transitions and the Influence of Multi-scale Market Factors in Southwest Cameroon

    Science.gov (United States)

    Ordway, E.; Lambin, E.; Asner, G. P.

    2015-12-01

    The changing structure of demand for commodities associated with food security and energy has had a startling impact on land use change in tropical forests in recent decades. Yet, the composition of conversion in the Congo basin remains a major uncertainty, particularly with regards to the scale of drivers of change. Owing to rapid expansion of production globally and longstanding historical production locally in the Congo basin, oil palm offers a lens through which to evaluate local land use decisions across a spectrum of small- to large-scales of production as well as interactions with regional and global supply chains. We examined the effect of global commodity crop expansion on land use change in Southwest Cameroon using a mixed-methods approach to integrate remote sensing, field surveys and socioeconomic data. Southwest Cameroon (2.5 Mha) has a long history of large- and small-scale agriculture, ranging from mixed crop subsistence agriculture to large monocrop plantations of oil palm, cocoa, and rubber. Trends and spatial patterns of forest conversion and agricultural transitions were analyzed from 2000-2015 using satellite imagery. We used economic, demographic and field survey datasets to assess how regional and global market factors and local commodity crop decisions affect land use patterns. Our results show that oil palm is a major commodity crop expanding in this region, and that conversion is occurring primarily through expansion by medium-scale producers and local elites. Results also indicate that global and regional supply chain dynamics influence local land use decision making. This research contributes new information on land use patterns and dynamics in the Congo basin, an understudied region. More specifically, results from this research contribute information on recent trends of oil palm expansion in Cameroon that will be used in national land use planning strategies.

  19. Collaborative Research: Quantifying the Uncertainties of Aerosol Indirect Effects and Impacts on Decadal-Scale Climate Variability in NCAR CAM5 and CESM1

    Energy Technology Data Exchange (ETDEWEB)

    Nenes, Athanasios

    2017-06-23

    The goal of this proposed project is to assess the climatic importance and sensitivity of aerosol indirect effect (AIE) to cloud and aerosol processes and feedbacks, which include organic aerosol hygroscopicity, cloud condensation nuclei (CCN) activation kinetics, Giant CCN, cloud-scale entrainment, ice nucleation in mixed-phase and cirrus clouds, and treatment of subgrid variability of vertical velocity. A key objective was to link aerosol, cloud microphysics and dynamics feedbacks in CAM5 with a suite of internally consistent and integrated parameterizations that provide the appropriate degrees of freedom to capture the various aspects of the aerosol indirect effect. The proposal integrated new parameterization elements into the cloud microphysics, moist turbulence and aerosol modules used by the NCAR Community Atmospheric Model version 5 (CAM5). The CAM5 model was then used to systematically quantify the uncertainties of aerosol indirect effects through a series of sensitivity tests with present-day and preindustrial aerosol emissions. New parameterization elements were developed as a result of these efforts, and new diagnostic tools & methodologies were also developed to quantify the impacts of aerosols on clouds and climate within fully coupled models. Observations were used to constrain key uncertainties in the aerosol-cloud links. Advanced sensitivity tools were developed and implements to probe the drivers of cloud microphysical variability with unprecedented temporal and spatial scale. All these results have been published in top and high impact journals (or are in the final stages of publication). This proposal has also supported a number of outstanding graduate students.

  20. Fatigue Damage Prognosis in FRP Composites by Combining Multi-Scale Degradation Fault Modes in an Uncertainty Bayesian Framework

    Data.gov (United States)

    National Aeronautics and Space Administration — In this work, a framework for the estimation of the fatigue damage propagation in CFRP composites is proposed. Macro-scale phenomena such as stiffness and strength...

  1. Understanding uncertainty

    CERN Document Server

    Lindley, Dennis V

    2013-01-01

    Praise for the First Edition ""...a reference for everyone who is interested in knowing and handling uncertainty.""-Journal of Applied Statistics The critically acclaimed First Edition of Understanding Uncertainty provided a study of uncertainty addressed to scholars in all fields, showing that uncertainty could be measured by probability, and that probability obeyed three basic rules that enabled uncertainty to be handled sensibly in everyday life. These ideas were extended to embrace the scientific method and to show how decisions, containing an uncertain element, could be rationally made.

  2. Research on Influential Factors Analysis and Uncertainty Evaluation About Connected Liquid Level Sensor System Online Measuring Method

    Science.gov (United States)

    Geng, L.; Liu, J.

    The accuracy of damage alarming and damage identification of bridge structural and the reliability of reliability evaluation and the fatigue life evaluation depend on the data of sensor. At present, sample calibration is only done hi the initial installation of sensors of the sensing system for long-term monitoring of the bridge and generally is not done in using. So whether the system is stable and reliable is unable to be known. In this paper, on the model of connected liquid level sensor system, value traceability approach of sensor system online measuring method is studied by the field experiment and theory research based on technical index of measurement (output displacement) proposed by output parameters of integrated deflection sensing system. Applicable connected liquid level sensor system online measuring method is established and influential factors and the uncertainty are analyzed. Finally the applicable scope of the method is obtained. This paper has made the beneficial exploration on online measurement of the instrument after the installation of the bridge health monitoring system.

  3. Impact of quality control matrix effect: application to the calculation of uncertainty of measurement in one-stage clotting factor VIII assay.

    Science.gov (United States)

    Sobas, Frédéric; Benattar, Norbert; Bellisario, Audrey; Marin, Sylvie; Nougier, Christophe; Lienhart, Anne; Négrier, Claude

    2010-07-01

    In Europe, the ISO 15 189 standard requires uncertainty of measurement to be calculated for all measurands. We calculated the analytical imprecision and bias of our factor VIII coagulometric assay method between 5 and 80 U/dl, using plasmas expected to be at 5, 30 and 80 U/dl of factor VIII. We implemented Meijer et al.'s [Clin Chem 2002; 48:1011-1015] long-term coefficient of variance, bias and also uncertainty of measurement calculations. Assessments used reference plasma diluted in severe haemophilic plasma, in immunodepleted factor VIII-deficient plasma and in bovine serum albumin. With plasmas diluted in severe haemophilic and immunodepleted factor VIII-deficient plasma, calculated uncertainty of measurement was 10% compared with 15% (i.e., 50% greater) for plasma diluted in albumin buffer or as calculated from European Concerted Action on Thrombosis consensus values. It is thus important to approximate the patient sample matrix to obtain as precise an estimation as possible of assay method uncertainty of measurement.

  4. Factor solutions of the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) in a Swedish population.

    Science.gov (United States)

    Mörtberg, Ewa; Reuterskiöld, Lena; Tillfors, Maria; Furmark, Tomas; Öst, Lars-Göran

    2017-06-01

    Culturally validated rating scales for social anxiety disorder (SAD) are of significant importance when screening for the disorder, as well as for evaluating treatment efficacy. This study examined construct validity and additional psychometric properties of two commonly used scales, the Social Phobia Scale and the Social Interaction Anxiety Scale, in a clinical SAD population (n = 180) and in a normal population (n = 614) in Sweden. Confirmatory factor analyses of previously reported factor solutions were tested but did not reveal acceptable fit. Exploratory factor analyses (EFA) of the joint structure of the scales in the total population yielded a two-factor model (performance anxiety and social interaction anxiety), whereas EFA in the clinical sample revealed a three-factor solution, a social interaction anxiety factor and two performance anxiety factors. The SPS and SIAS showed good to excellent internal consistency, and discriminated well between patients with SAD and a normal population sample. Both scales showed good convergent validity with an established measure of SAD, whereas the discriminant validity of symptoms of social anxiety and depression could not be confirmed. The optimal cut-off score for SPS and SIAS were 18 and 22 points, respectively. It is concluded that the factor structure and the additional psychometric properties of SPS and SIAS support the use of the scales for assessment in a Swedish population.

  5. Generalized uncertainty principles

    CERN Document Server

    Machluf, Ronny

    2008-01-01

    The phenomenon in the essence of classical uncertainty principles is well known since the thirties of the last century. We introduce a new phenomenon which is in the essence of a new notion that we introduce: "Generalized Uncertainty Principles". We show the relation between classical uncertainty principles and generalized uncertainty principles. We generalized "Landau-Pollak-Slepian" uncertainty principle. Our generalization relates the following two quantities and two scaling parameters: 1) The weighted time spreading $\\int_{-\\infty}^\\infty |f(x)|^2w_1(x)dx$, ($w_1(x)$ is a non-negative function). 2) The weighted frequency spreading $\\int_{-\\infty}^\\infty |\\hat{f}(\\omega)|^2w_2(\\omega)d\\omega$. 3) The time weight scale $a$, ${w_1}_a(x)=w_1(xa^{-1})$ and 4) The frequency weight scale $b$, ${w_2}_b(\\omega)=w_2(\\omega b^{-1})$. "Generalized Uncertainty Principle" is an inequality that summarizes the constraints on the relations between the two spreading quantities and two scaling parameters. For any two reason...

  6. Ambient flux-based critical values of ozone for protecting vegetation: differing spatial scales and uncertainties in risk assessment

    Science.gov (United States)

    Grünhage, L.; Krupa, S. V.; Legge, A. H.; Jäger, H.-J.

    The current European critical levels for ozone (O 3) to protect crops, natural and semi-natural vegetation and forest trees (Level I) are based on the accumulated exposure over a threshold of 40 ppb exposure index. For the revision of the 1999 UN-ECE protocol (Protocol to the 1979 Convention on Long-Range Transboundary Air Pollution to Abate Acidification, Eutrophication and Ground-Level Ozone. Gothenburg, 30 November), critical levels are partly replaced by critical cumulative stomatal uptake (critical absorbed dose or CAD). Here, we discuss possible improvements in deriving CAD. At present, the main problems with the flux approach can be attributed to uncertainties in the parameterisation of, (1) stomatal conductance, (2) non-stomatal deposition, and (3) the representativeness of species used in flux-effect studies. Although in general, the flux approach is well accepted by plant effects scientists in North America, concerted research efforts have not taken place in that direction. Furthermore, because of the differences in the approach to setting ambient air quality standards, it appears very doubtful that policy makers and air quality regulators in the US and Canada will readily accept the overall philosophy.

  7. Efficient incorporation of channel cross-section geometry uncertainty into regional and global scale flood inundation models

    NARCIS (Netherlands)

    Neal, J. C.; Odini, Nicolas; trigg, mark; Freer, Jim; garcia-pintado, javier; mason, david; Wood, Melissa; Bates, P. D.

    2015-01-01

    This paper investigates the challenge of representing structural differences in river channel cross-section geometry for regional to global scale river hydraulic models and the effect this can have on simulations of wave dynamics. Classically, channel geometry is defined using data, yet at larger

  8. Factorial Structure of the Career Decision Scale: Incremental Validity of the Five-Factor Domains

    Science.gov (United States)

    Feldt, Ronald C.; Ferry, Ashley; Bullock, Melinda; Camarotti-Carvalho, Ana; Collingwood, Melinda; Eilers, Scott; Meyer, Luke; Nurre, Emily; Woelfel, Cheryl

    2010-01-01

    For comparison of one-, three-, and four-factor structures of the Indecision scale of the Career Decision Scale, results of confirmatory factor analysis (N = 686) indicated the best fit for the three-factor structure. Multiple regression analysis results indicated incremental validity of the five-factor model for predicting dimensions of career…

  9. Factorial Structure of the Career Decision Scale: Incremental Validity of the Five-Factor Domains

    Science.gov (United States)

    Feldt, Ronald C.; Ferry, Ashley; Bullock, Melinda; Camarotti-Carvalho, Ana; Collingwood, Melinda; Eilers, Scott; Meyer, Luke; Nurre, Emily; Woelfel, Cheryl

    2010-01-01

    For comparison of one-, three-, and four-factor structures of the Indecision scale of the Career Decision Scale, results of confirmatory factor analysis (N = 686) indicated the best fit for the three-factor structure. Multiple regression analysis results indicated incremental validity of the five-factor model for predicting dimensions of career…

  10. Jet energy scale measurements and their systematic uncertainties in proton-proton collisions at $\\sqrt{s} = 13$ TeV with the ATLAS detector

    CERN Document Server

    Aaboud, Morad; ATLAS Collaboration; Abbott, Brad; Abdallah, Jalal; Abdinov, Ovsat; Abeloos, Baptiste; Abidi, Syed Haider; AbouZeid, Ossama; Abraham, Nicola; Abramowicz, Halina; Abreu, Henso; Abreu, Ricardo; Abulaiti, Yiming; Acharya, Bobby Samir; Adachi, Shunsuke; Adamczyk, Leszek; Adelman, Jahred; Adersberger, Michael; Adye, Tim; Affolder, Tony; Agatonovic-Jovin, Tatjana; Agheorghiesei, Catalin; Aguilar-Saavedra, Juan Antonio; Ahlen, Steven; Ahmadov, Faig; Aielli, Giulio; Akatsuka, Shunichi; Akerstedt, Henrik; Åkesson, Torsten Paul Ake; Akimov, Andrei; Alberghi, Gian Luigi; Albert, Justin; Albicocco, Pietro; Alconada Verzini, Maria Josefina; Aleksa, Martin; Aleksandrov, Igor; Alexa, Calin; Alexander, Gideon; Alexopoulos, Theodoros; Alhroob, Muhammad; Ali, Babar; Aliev, Malik; Alimonti, Gianluca; Alison, John; Alkire, Steven Patrick; Allbrooke, Benedict; Allen, Benjamin William; Allport, Phillip; Aloisio, Alberto; Alonso, Alejandro; Alonso, Francisco; Alpigiani, Cristiano; Alshehri, Azzah Aziz; Alstaty, Mahmoud; Alvarez Gonzalez, Barbara; Άlvarez Piqueras, Damián; Alviggi, Mariagrazia; Amadio, Brian Thomas; Amaral Coutinho, Yara; Amelung, Christoph; Amidei, Dante; Amor Dos Santos, Susana Patricia; Amorim, Antonio; Amoroso, Simone; Amundsen, Glenn; Anastopoulos, Christos; Ancu, Lucian Stefan; Andari, Nansi; Andeen, Timothy; Anders, Christoph Falk; Anders, John Kenneth; Anderson, Kelby; Andreazza, Attilio; Andrei, George Victor; Angelidakis, Stylianos; Angelozzi, Ivan; Angerami, Aaron; Anisenkov, Alexey; Anjos, Nuno; Annovi, Alberto; Antel, Claire; Antonelli, Mario; Antonov, Alexey; Antrim, Daniel Joseph; Anulli, Fabio; Aoki, Masato; Aperio Bella, Ludovica; Arabidze, Giorgi; Arai, Yasuo; Araque, Juan Pedro; Araujo Ferraz, Victor; Arce, Ayana; Ardell, Rose Elisabeth; Arduh, Francisco Anuar; Arguin, Jean-Francois; Argyropoulos, Spyridon; Arik, Metin; Armbruster, Aaron James; Armitage, Lewis James; Arnaez, Olivier; Arnold, Hannah; Arratia, Miguel; Arslan, Ozan; Artamonov, Andrei; Artoni, Giacomo; Artz, Sebastian; Asai, Shoji; Asbah, Nedaa; Ashkenazi, Adi; Asquith, Lily; Assamagan, Ketevi; Astalos, Robert; Atkinson, Markus; Atlay, Naim Bora; Augsten, Kamil; Avolio, Giuseppe; Axen, Bradley; Ayoub, Mohamad Kassem; Azuelos, Georges; Baas, Alessandra; Baca, Matthew John; Bachacou, Henri; Bachas, Konstantinos; Backes, Moritz; Backhaus, Malte; Bagnaia, Paolo; Bahrasemani, Sina; Baines, John; Bajic, Milena; Baker, Oliver Keith; Baldin, Evgenii; Balek, Petr; Balli, Fabrice; Balunas, William Keaton; Banas, Elzbieta; Banerjee, Swagato; Bannoura, Arwa A E; Barak, Liron; Barberio, Elisabetta Luigia; Barberis, Dario; Barbero, Marlon; Barillari, Teresa; Barisits, Martin-Stefan; Barklow, Timothy; Barlow, Nick; Barnes, Sarah Louise; Barnett, Bruce; Barnett, Michael; Barnovska-Blenessy, Zuzana; Baroncelli, Antonio; Barone, Gaetano; Barr, Alan; Barranco Navarro, Laura; Barreiro, Fernando; Barreiro Guimarães da Costa, João; Bartoldus, Rainer; Barton, Adam Edward; Bartos, Pavol; Basalaev, Artem; Bassalat, Ahmed; Bates, Richard; Batista, Santiago Juan; Batley, Richard; Battaglia, Marco; Bauce, Matteo; Bauer, Florian; Bawa, Harinder Singh; Beacham, James; Beattie, Michael David; Beau, Tristan; Beauchemin, Pierre-Hugues; Bechtle, Philip; Beck, Hans~Peter; Becker, Kathrin; Becker, Maurice; Beckingham, Matthew; Becot, Cyril; Beddall, Andrew; Beddall, Ayda; Bednyakov, Vadim; Bedognetti, Matteo; Bee, Christopher; Beermann, Thomas; Begalli, Marcia; Begel, Michael; Behr, Janna Katharina; Bell, Andrew Stuart; Bella, Gideon; Bellagamba, Lorenzo; Bellerive, Alain; Bellomo, Massimiliano; Belotskiy, Konstantin; Beltramello, Olga; Belyaev, Nikita; Benary, Odette; Benchekroun, Driss; Bender, Michael; Bendtz, Katarina; Benekos, Nektarios; Benhammou, Yan; Benhar Noccioli, Eleonora; Benitez, Jose; Benjamin, Douglas; Benoit, Mathieu; Bensinger, James; Bentvelsen, Stan; Beresford, Lydia; Beretta, Matteo; Berge, David; Bergeaas Kuutmann, Elin; Berger, Nicolas; Beringer, Jürg; Berlendis, Simon; Bernard, Nathan Rogers; Bernardi, Gregorio; Bernius, Catrin; Bernlochner, Florian Urs; Berry, Tracey; Berta, Peter; Bertella, Claudia; Bertoli, Gabriele; Bertolucci, Federico; Bertram, Iain Alexander; Bertsche, Carolyn; Bertsche, David; Besjes, Geert-Jan; Bessidskaia Bylund, Olga; Bessner, Martin Florian; Besson, Nathalie; Betancourt, Christopher; Bethani, Agni; Bethke, Siegfried; Bevan, Adrian John; Beyer, Julien-christopher; Bianchi, Riccardo-Maria; Biebel, Otmar; Biedermann, Dustin; Bielski, Rafal; Biesuz, Nicolo Vladi; Biglietti, Michela

    2017-01-01

    Jet energy scale measurements and their systematic uncertainties are reported for jets measured with the ATLAS detector using proton-proton collision data with a center-of-mass energy of $\\sqrt{s} = 13$ TeV, corresponding to an integrated luminosity of 3.2 fb$^{-1}$ collected during 2015 at the LHC. Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells, using the anti-$k_{t}$ algorithm with radius parameter $R = 0.4$. Jets are calibrated with a series of simulation-based corrections and in situ techniques. In situ techniques exploit the transverse momentum balance between a jet and a reference object such as a photon, $Z$ boson, or multijet system for jets with $20 0.8$) is derived from dijet $p_{T}$ balance measurements. For jets of $p_{T} = 80$ GeV, the additional uncertainty for the forward jet calibration reaches its largest value of about 2% in the range $|\\eta| > 3.5$ and in a narrow slice of $2.2 < |\\eta| < 2.4$.

  11. Predictive factors of ICU bedsores using Braden scale

    Directory of Open Access Journals (Sweden)

    Abolhasan Afkar

    2014-07-01

    Full Text Available Background: Bed sore is a major problem for inpatients in the hospital. This study was aimed to determine the predictive factors of bedsore in Intensive Care Unit (ICU. Methods: A descriptive – analytical study was conducted on 673 Intensive Care Unit (ICU inpatients of 6 selected hospitals in a period of 6 months in Guilan. The participants were selected via simple random sampling. Data were collected by the Braden Scale whose reliability and validity had breen confirmed in previous studies. Data were fed into SPSS software and analyzed using t-test, chi-square and Logistic regression. Results: The mean age of the subjects was 45.35±16.7. Incidence of bedsore was 3.6%. Dietary patterns, wear and tension were identified as predictors of bed sore after adjustment of odds ratio. Conclusion: We can properly manage the bed sore and its complications, in addition to predicting the parameters of the given model, through attention to proper nutrition, stretching the muscles and tissues of the patients in ICU. Retraining the personnel of the intensive care unit and training the patients are recommended.

  12. Characterizing uncertainties of the national-scale forest gross aboveground biomass (AGB) loss estimate: a case study of the Democratic Republic of the Congo

    Science.gov (United States)

    Tyukavina, A.; Stehman, S.; Potapov, P.; Turubanova, S.; Baccini, A.; Goetz, S. J.; Laporte, N. T.; Houghton, R. A.; Hansen, M.

    2013-12-01

    Modern remote sensing techniques enable the mapping and monitoring of aboveground biomass (AGB) carbon stocks without relying on extensive in situ measurements. The Democratic Republic of the Congo (DRC) is among the countries where a national forest inventory (NFI) has yet to be established due to a lack of infrastructure and political instability. We demonstrate a method for producing national-scale gross AGB loss estimates and quantifying uncertainty of the estimates using remotely sensed-derived forest cover loss and biomass carbon density data. Forest cover type and loss were characterized using published Landsat-based data sets and related to LIDAR-derived biomass data from the Geoscience Laser Altimeter System (GLAS). We produced two gross AGB loss estimates for the DRC for the last decade (2000-2010): a conservative estimate accounting for classification errors in the 60-m resolution FACET forest cover change product, and a maximal estimate that also took into consideration omitted change at the 30m spatial resolution. Omitted disturbances were largely related to smallholder agriculture, the detection of which is scale-dependent. The use of LIDAR data as a substitute for NFI data to estimate AGB loss based on Landsat-derived activity data was demonstrated. Comparisons of our forest cover loss and AGB estimates with published studies raise the issue of scale in forest cover change mapping and its impact on carbon stock change estimation using remotely sensed data.

  13. What factor generates greater uncertainty in predicting carbon flux for North America: climate characterization or model choice?

    Science.gov (United States)

    Dungan, J.; Wang, W.; Micaelis, A.; Nemani, R.

    2008-12-01

    Numerous efforts have begun to characterize a variety of sources of uncertainty in carbon flux estimates from both forward-modeling and inverse modeling approaches. One source of uncertainty is structural, created by the variety of approaches taken to select and characterize the most important biogeochemical processes. To begin to explore this structural uncertainty, we have used an ensemble of well-known models including CASA (Potter et al. (1993), version 2003.04.29), LPJ (Sitch et al. (2003), version 3.1.1-0.9.02), and BGC (White et al. (2000), version 5.0) with a consistent set of inputs for the period 1982-2006 for North America. Initially, the ensemble was run using input climate data interpolated from maximum, minimum and dew-point temperatures, precipitation, vapor pressure deficit, and incident daily solar radiation at stations from the National Climate Data Center's Global Summary of the Day, incorporating on average about 1900 stations. NCDC's Cooperative Summary of the Day data, available over the United States only, yielded a combined data set of approximately 9000 stations that was then used for the ensemble runs. The combined data set resulted in a significantly wetter surface than with the sparser set, resulting in noticeably larger gross primary production (GPP) estimates by models in the ensemble. Mexico and Canada remain significantly undersampled. Uncertainty due to the choice of a relatively sparse or dense station network was smaller than the structural uncertainty due to model choice.

  14. The Jet Energy Scale Uncertainty Derived from γ-jet Events for Small and Large Radius Jets and the Calibration and Performance of Variable R Jets with the ATLAS Detector

    CERN Document Server

    Kogan, Lucy

    In this thesis the jet energy scale uncertainty of small and large radius jets at the ATLAS detector is evaluated in-situ using γ-jet events. The well calibrated photon in the γ-jet events is used to probe the energy scale of the jets. The studies of the jet energy scale of small radius jets are performed using 4.7 fb−1 of data collected at √s = 7 TeV in 2011. The γ-jet methods which were developed are then adapted and applied to large radius jets, using 20.3 fb−1 of data collected at √s = 8 TeV in 2012. The new jet energy scale uncertainties are found to be ∼1 % for |η| 0.8. These uncertainties are significantly lower than the 3-6 % precision which has previously been achieved at ATLAS using track jets as a reference object. Due to the increase in precision, uncertainties due to pile-up and the topology of the jet also had to be evaluated. The total energy scale uncertainties for large radius jets are reduced by ∼1-2 % (0.5-1 %) for |η| 0.8). This reduction will be beneficial to analyses u...

  15. Strong New Evidence for Oscillation of the Cosmological Scale Factor Observed in the Large Scale Structure

    Science.gov (United States)

    Ringermacher, Harry I.; Mead, Lawrence R.

    2017-01-01

    We have analyzed SDSSIII-BOSS, DR9 galaxy number count data using 2 independent approaches, a relativistic expanding space model based on work by Ostriker and direct Fourier analysis, and found incontrovertible evidence for a scale factor oscillation at 7 Hubble-Hertz (HHz) in both methods, where we define 1 HHz as 1 cycle over 1 Hubble-time. The number count of galaxies on these scales should be relatively smooth. However, a DR9 plot of galaxy number count per 0.01 redshift bin as a function of redshift shows significant bumps to redshift 0.5. We take the SDSSIII data (about ¼ of the sky) to be a fair representation of the entire sky when using number count. Our model fits essentially all bumps at a 99.8% R-squared goodness level if and only if the 7 HHz oscillation ( plus 2nd and 3rd harmonics at 14 HHz and 21 HHz) is included. These are the same frequencies observed by us in AJ 149, 137 (2015) using SNe data. Since the SDSSIII data set only goes to redshift 0.8, only one cycle of oscillation is included compared to 2-3 in our earlier work. Thus a Fourier analysis performed on the SDSS redshift data converted to equal-time binning leaves a broadened spectrum over the range where harmonics would normally reside but nevertheless peaked at 7 HHz. A scalar field model presented in the AJ paper describes the oscillation and enters the Friedmann equations by replacing the LCDM dark matter density parameter with the scalar field density. Thus, LCDM dark matter is the median of the wave which appears to act like a fluid with a changing equation-of-state. The oscillation may be a longitudinal gravitational wave originating with the Big Bang and requiring a massive graviton. 7 HHz is consistent with a graviton mass of 10^ -32 eV.

  16. Uncertainty analysis in seismic tomography

    Science.gov (United States)

    Owoc, Bartosz; Majdański, Mariusz

    2017-04-01

    Velocity field from seismic travel time tomography depends on several factors like regularization, inversion path, model parameterization etc. The result also strongly depends on an initial velocity model and precision of travel times picking. In this research we test dependence on starting model in layered tomography and compare it with effect of picking precision. Moreover, in our analysis for manual travel times picking the uncertainty distribution is asymmetric. This effect is shifting the results toward faster velocities. For calculation we are using JIVE3D travel time tomographic code. We used data from geo-engineering and industrial scale investigations, which were collected by our team from IG PAS.

  17. Estimating Soil Organic Carbon stocks and uncertainties at the regional scale following a legacy sampling strategy - a case study from southern Belgium

    Science.gov (United States)

    Chartin, Caroline; Krüger, Inken; Goidts, Esther; Carnol, Monique; van Wesemael, Bas

    2017-04-01

    The quantification and the spatialisation of reliable SOC stocks (Mg C ha-1) and total stock (Tg C) baselines and associated uncertainties are fundamental to detect the gains or losses in SOC, and to locate sensitive areas with low SOC levels. Here, we aim to both quantify and spatialize SOC stocks at regional scale (southern Belgium) based on data from one non-design-based nor model-based sampling scheme. To this end, we developed a computation procedure based on Digital Soil Mapping techniques and stochastic simulations (Monte-Carlo) allowing the estimation of multiple (here, 10,000) independent spatialized datasets. The computation of the prediction uncertainty accounts for the errors associated to the both estimations of i) SOC stock at the pixel-related area scale and ii) parameters of the spatial model. Based on these 10,000 individuals, median SOC stocks and 90% prediction intervals were computed for each pixel, as well as total SOC stocks and their 90% prediction intervals for selected sub-areas and for the entire study area. Hence, a Generalised Additive Model (GAM) explaining 69.3 % of the SOC stock variance was calibrated and then validated (R2 = 0.64). The model overestimated low SOC stock (below 50 Mg C ha-1) and underestimated high SOC stock (especially those above 100 Mg C kg-1). A positive gradient of SOC stock occurred from the northwest to the center of Wallonia with a slight decrease on the southernmost part, correlating to the evolution of precipitation and temperature (along with elevation) and dominant land use. At the catchment scale higher SOC stocks were predicted on valley bottoms, especially for poorly drained soils under grassland. Mean predicted SOC stocks for cropland and grassland in Wallonia were of 26.58 Tg C (SD 1.52) and 43.30 Tg C (2.93), respectively. The procedure developed here allowed to predict realistic spatial patterns of SOC stocks all over agricultural lands of southern Belgium and to produce reliable statistics of total

  18. Confirmatory Factor Analysis of the Behavioral and Emotional Rating Scale-2 (BERS-2) Parent and Youth Rating Scales

    Science.gov (United States)

    Buckley, Jacquelyn A.; Ryser, Gail; Reid, Robert; Epstein, Michael H.

    2006-01-01

    We confirmed the factor structure of the Behavioral and Emotional Rating Scale-2nd Edition (BERS-2) with a normative parent and youth sample. The BERS-2, based on the Behavioral and Emotional Rating Scale (BERS), is a standardized instrument that assesses children's emotional and behavioral strengths. The original BERS was renormed to create a…

  19. Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC

    NARCIS (Netherlands)

    Ahn, S.; Korattikara, A.; Liu, N.; Rajan, S.; Welling, M.

    2015-01-01

    Despite having various attractive qualities such as high prediction accuracy and the ability to quantify uncertainty and avoid ovrfitting, Bayesian Matrix Factorization has not been widely adopted because of the prohibitive cost of inference. In this paper, we propose a scalable distributed Bayesian

  20. Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC

    NARCIS (Netherlands)

    Ahn, S.; Korattikara, A.; Liu, N.; Rajan, S.; Welling, M.

    2015-01-01

    Despite having various attractive qualities such as high prediction accuracy and the ability to quantify uncertainty and avoid ovrfitting, Bayesian Matrix Factorization has not been widely adopted because of the prohibitive cost of inference. In this paper, we propose a scalable distributed Bayesian

  1. Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

    Directory of Open Access Journals (Sweden)

    Arnaud eDechesne

    2014-12-01

    Full Text Available Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found significant diversity in the approaches used to describe and quantify spatial heterogeneity, which complicates inter-studies comparisons. However, it is clear that the presence and activity of pesticide degraders is often highly spatially variable with coefficients of variation often exceeding 50% and frequently displays nonrandom spatial patterns. A few controlling factors have tentatively been identified across pesticide classes: they include some soil characteristics (pH and some agricultural management practices (pesticide application, tillage, while other potential controlling factors have more conflicting effects depending on the site or the pesticide. Evidence demonstrating the importance of spatial heterogeneity on the fate of pesticides in soil has been difficult to obtain but modelling and experimental systems that do not include soil’s full complexity reveal that this heterogeneity must be considered to improve prediction of pesticide biodegradation rates or of leaching risks. Overall, studying the spatial heterogeneity of pesticide biodegradation is a relatively new field at the interface of agronomy, microbial ecology, and geosciences and a wealth of novel data is being collected from these different disciplinary perspectives. We make suggestions on possible avenues to take full advantage of these investigations for a better understanding and prediction of the fate of pesticides in soil.

  2. Investigating the Factor Structure of the Blog Attitude Scale

    Science.gov (United States)

    Shahsavar, Zahra; Tan, Bee Hoon; Aryadoust, S. Vahid

    2010-01-01

    Due to the wide application of advanced technology in education, many attitude scales have been developed to evaluate learners' attitudes toward educational tools. However, with the rapid development of emerging technologies, using blogs as one of the Web 2.0 tools is still in its infancy and few blog attitude scales have been developed yet.…

  3. A stochastic mathematical model to locate field hospitals under disruption uncertainty for large-scale disaster preparedness

    Directory of Open Access Journals (Sweden)

    Nezir Aydin

    2016-03-01

    Full Text Available In this study, we consider field hospital location decisions for emergency treatment points in response to large scale disasters. Specifically, we developed a two-stage stochastic model that determines the number and locations of field hospitals and the allocation of injured victims to these field hospitals. Our model considers the locations as well as the failings of the existing public hospitals while deciding on the location of field hospitals that are anticipated to be opened. The model that we developed is a variant of the P-median location model and it integrates capacity restrictions both on field hospitals that are planned to be opened and the disruptions that occur in existing public hospitals. We conducted experiments to demonstrate how the proposed model can be utilized in practice in a real life problem case scenario. Results show the effects of the failings of existing hospitals, the level of failure probability and the capacity of projected field hospitals to deal with the assessment of any given emergency treatment system’s performance. Crucially, it also specifically provides an assessment on the average distance within which a victim needs to be transferred in order to be treated properly and then from this assessment, the proportion of total satisfied demand is then calculated.

  4. Integral emission factors for methane determined using urban flux measurements and local-scale inverse models

    Science.gov (United States)

    Christen, Andreas; Johnson, Mark; Molodovskaya, Marina; Ketler, Rick; Nesic, Zoran; Crawford, Ben; Giometto, Marco; van der Laan, Mike

    2013-04-01

    The most important long-lived greenhouse gas (LLGHG) emitted during combustion of fuels is carbon dioxide (CO2), however also traces of the LLGHGs methane (CH4) and nitrous oxide (N2O) are released, the quantities of which depend largely on the conditions of the combustion process. Emission factors determine the mass of LLGHGs emitted per energy used (or kilometre driven for cars) and are key inputs for bottom-up emission modelling. Emission factors for CH4 are typically determined in the laboratory or on a test stand for a given combustion system using a small number of samples (vehicles, furnaces), yet associated with larger uncertainties when scaled to entire fleets. We propose an alternative, different approach - Can integrated emission factors be independently determined using direct micrometeorological flux measurements over an urban surface? If so, do emission factors determined from flux measurements (top-down) agree with up-scaled emission factors of relevant combustion systems (heating, vehicles) in the source area of the flux measurement? Direct flux measurements of CH4 were carried out between February and May, 2012 over a relatively densely populated, urban surface in Vancouver, Canada by means of eddy covariance (EC). The EC-system consisted of an ultrasonic anemometer (CSAT-3, Campbell Scientific Inc.) and two open-path infrared gas analyzers (Li7500 and Li7700, Licor Inc.) on a tower at 30m above the surface. The source area of the EC system is characterised by a relative homogeneous morphometry (5.3m average building height), but spatially and temporally varying emission sources, including two major intersecting arterial roads (70.000 cars drive through the 50% source area per day) and seasonal heating in predominantly single-family houses (natural gas). An inverse dispersion model (turbulent source area model), validated against large eddy simulations (LES) of the urban roughness sublayer, allows the determination of the spatial area that

  5. Modifying climate change habitat models using tree species-specific assessments of model uncertainty and life history-factors

    Science.gov (United States)

    Stephen N. Matthews; Louis R. Iverson; Anantha M. Prasad; Matthew P. Peters; Paul G. Rodewald

    2011-01-01

    Species distribution models (SDMs) to evaluate trees' potential responses to climate change are essential for developing appropriate forest management strategies. However, there is a great need to better understand these models' limitations and evaluate their uncertainties. We have previously developed statistical models of suitable habitat, based on both...

  6. Comparative chemical sensitivity between marine Australian and Northern Hemisphere ecosystems: is an uncertainty factor warranted for water-quality-guideline setting?

    Science.gov (United States)

    Hagen, Tarah G; Douglas, Richard W

    2014-05-01

    The lack of Australian species data has pragmatically led to the use of toxicological data from the Northern Hemisphere to develop water-quality guidelines. However, it is unknown whether Australian species and ecosystems are equally as sensitive and if an uncertainty factor is warranted for Australian guideline setting. In the present study, it is hypothesized that an uncertainty factor is not required. This was tested by generating species sensitivity distributions by 2 parametric methods using marine Northern Hemisphere and Australian/New Zealand data. Sufficient acute data were found for only 3 compounds: 4-chlorophenol, phenol, and ammonia. For ammonia and 4-chlorophenol, the 95% species protection levels generated with Australian and Northern Hemisphere data were essentially the same. For phenol, protection levels derived from Australian data were approximately 10-fold higher. Therefore, the derived benchmark concentration from Northern Hemisphere data should be protective. It is tentatively concluded that there is no need for an uncertainty factor when deriving water-quality guidelines for marine Australian ecosystems using Northern Hemisphere data. It is, however, noted that this is based on only 3 compounds. © 2014 SETAC.

  7. Background-independent quantization and the uncertainty principle

    Energy Technology Data Exchange (ETDEWEB)

    Hossain, Golam Mortuza; Husain, Viqar; Seahra, Sanjeev S, E-mail: ghossain@unb.c, E-mail: vhusain@unb.c, E-mail: sseahra@unb.c [Department of Mathematics and Statistics, University of New Brunswick, Fredericton, NB E3B 5A3 (Canada)

    2010-08-21

    It is shown that polymer quantization leads to a modified uncertainty principle similar to that motivated by string theory and non-commutative geometry. When applied to quantum field theory on general background spacetimes, corrections to the uncertainty principle acquire a metric dependence. For Friedmann-Robertson-Walker cosmology this translates to a scale factor dependence which gives a large effect in the early Universe.

  8. Reduced uncertainty of regional scale CLM predictions of net carbon fluxes and leaf area indices with estimated plant-specific parameters

    Science.gov (United States)

    Post, Hanna; Hendricks Franssen, Harrie-Jan; Han, Xujun; Baatz, Roland; Montzka, Carsten; Schmidt, Marius; Vereecken, Harry

    2016-04-01

    Reliable estimates of carbon fluxes and states at regional scales are required to reduce uncertainties in regional carbon balance estimates and to support decision making in environmental politics. In this work the Community Land Model version 4.5 (CLM4.5-BGC) was applied at a high spatial resolution (1 km2) for the Rur catchment in western Germany. In order to improve the model-data consistency of net ecosystem exchange (NEE) and leaf area index (LAI) for this study area, five plant functional type (PFT)-specific CLM4.5-BGC parameters were estimated with time series of half-hourly NEE data for one year in 2011/2012, using the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm, a Markov Chain Monte Carlo (MCMC) approach. The parameters were estimated separately for four different plant functional types (needleleaf evergreen temperate tree, broadleaf deciduous temperate tree, C3-grass and C3-crop) at four different sites. The four sites are located inside or close to the Rur catchment. We evaluated modeled NEE for one year in 2012/2013 with NEE measured at seven eddy covariance sites in the catchment, including the four parameter estimation sites. Modeled LAI was evaluated by means of LAI derived from remotely sensed RapidEye images of about 18 days in 2011/2012. Performance indices were based on a comparison between measurements and (i) a reference run with CLM default parameters, and (ii) a 60 instance CLM ensemble with parameters sampled from the DREAM posterior probability density functions (pdfs). The difference between the observed and simulated NEE sum reduced 23% if estimated parameters instead of default parameters were used as input. The mean absolute difference between modeled and measured LAI was reduced by 59% on average. Simulated LAI was not only improved in terms of the absolute value but in some cases also in terms of the timing (beginning of vegetation onset), which was directly related to a substantial improvement of the NEE estimates in

  9. Uncertainty theory

    CERN Document Server

    Liu, Baoding

    2015-01-01

    When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case. In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees. This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, c...

  10. Bias and Uncertainty of Critical Experiment Models with CSAS25 from SCALE4.4a for Criticality Safety Analyses On the HP J-5600 (CMODB) Workstation

    Energy Technology Data Exchange (ETDEWEB)

    Smith, R.H.; Keener, H.J.; DeClue, J.F.; Krass, A.W.; Cain, V.R.

    2001-02-01

    This report documents establishment of bias, bias trends and uncertainty for validation of the CSAS25 control module from the SCALE 4.4a computer code system for use in evaluating criticality safety of uranium systems. The 27-group ENDF/B-IV, 44-group ENDF/B-V, and 238-group ENDF/B-V cross-section libraries were used. The criticality validation calculations were performed using over 500 benchmark cases from Volumes II and IV of the ''International Handbook of Evaluated Criticality Safety Benchmark Experiments,'' published by the Nuclear Energy Agency Organization for Economic Cooperation and Development (NEA/OECD). Based on statistical analysis of the calculation results, the bias, bias trends and uncertainty of the benchmark calculations have been established for these benchmark experiments. Numerical methods for applying margins are briefly described, but the determination of appropriate correlating parameter and values for additional margin, applicable to a particular analysis, must be determined as part of process analysis. As such, this document does not specify upper subcritical limits as has been done in the past. A follow-on report will be written to assess the methods for determination of an upper safety limit in more detail, provide comparisons, and recommend a preferred method. Analysts using these results are responsible for exercising sound engineering judgment using strong technical arguments to develop a margin in k{sub eff} or other correlating parameter that is sufficiently large to ensure that conditions (calculated by this method to be subcritical by this margin) will actually be subcritical. Documentation of determination and justification of the appropriate margin in the analyst's evaluation, in conjunction with this report, will constitute the complete Validation Report in accordance with ANSI/ANS-8.1-1998, Section 4.3.6(4).

  11. Signal and Noise scaling factors in digital holography

    CERN Document Server

    Lesaffre, Max; Atlan, Michael; Gross, Michel

    2013-01-01

    An experimental study on how reconstructed image signal and noise scale with acquisition and reconstruction parameters is proposed. Monte-carlo simulation is performed to emphasize that the measured noise is shot-noise.

  12. 动态汽车衡示值误差测量结果的不确定度评定%Dynamic Truck Scale Error Value for Uncertainty Evaluation of Measurement Results

    Institute of Scientific and Technical Information of China (English)

    邢东华

    2015-01-01

    文中结合实际检定工作,根据JJF 1059.1-2012《测量不确定度评定与表示》规范要求,对动态汽车衡测量结果的不确定度进行分析评定,建立了不确定度评定的数学模型,分析了测量过程中不确定度的来源,量化不确定度分量,求出合成与扩展不确定度,其结果对动态汽车衡检定与校准工作具有一定的参考价值。[1]%Combining with the actual veriifcation work, according to the JJF1059.1-2012"measurement uncertainty evaluation and said"specification requirements, this paper analyzed and evaluated the uncertainty of measurement results of dynamic truck scale analysis evaluation, established the mathematical model of uncertainty evaluation, the source of uncertainty in measurement process is analyzed, quantitative uncertainty components, calculated the synthesis and the expanded uncertainty, the result has a certain reference value to the dynamic truck scale veriifcation and calibration work.

  13. Confirmatory Factor Analysis of the Combined Social Phobia Scale and Social Interaction Anxiety Scale: Support for a Bifactor Model

    Science.gov (United States)

    Gomez, Rapson; Watson, Shaun D.

    2017-01-01

    For the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) together, this study examined support for a bifactor model, and also the internal consistency reliability and external validity of the factors in this model. Participants (N = 526) were adults from the general community who completed the SPS and SIAS. Confirmatory factor analysis (CFA) of their ratings indicated good support for the bifactor model. For this model, the loadings for all but six items were higher on the general factor than the specific factors. The three positively worded items had negligible loadings on the general factor. The general factor explained most of the common variance in the SPS and SIAS, and demonstrated good model-based internal consistency reliability (omega hierarchical) and a strong association with fear of negative evaluation and extraversion. The practical implications of the findings for the utilization of the SPS and SIAS, and the theoretical and clinical implications for social anxiety are discussed. PMID:28210232

  14. Confirmatory Factor Analysis of the Combined Social Phobia Scale and Social Interaction Anxiety Scale: Support for a Bifactor Model.

    Science.gov (United States)

    Gomez, Rapson; Watson, Shaun D

    2017-01-01

    For the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) together, this study examined support for a bifactor model, and also the internal consistency reliability and external validity of the factors in this model. Participants (N = 526) were adults from the general community who completed the SPS and SIAS. Confirmatory factor analysis (CFA) of their ratings indicated good support for the bifactor model. For this model, the loadings for all but six items were higher on the general factor than the specific factors. The three positively worded items had negligible loadings on the general factor. The general factor explained most of the common variance in the SPS and SIAS, and demonstrated good model-based internal consistency reliability (omega hierarchical) and a strong association with fear of negative evaluation and extraversion. The practical implications of the findings for the utilization of the SPS and SIAS, and the theoretical and clinical implications for social anxiety are discussed.

  15. Meteorological uncertainty and rainfall downscaling

    Directory of Open Access Journals (Sweden)

    J. von Hardenberg

    2007-05-01

    Full Text Available We explore the sources of forecast uncertainty in a mixed dynamical-stochastic ensemble prediction chain for small-scale precipitation, suitable for hydrological applications. To this end, we apply the stochastic downscaling method RainFARM to each member of ensemble limited-area forecasts provided by the COSMO-LEPS system. Aim of the work is to quantitatively compare the relative weights of the meteorological uncertainty associated with large-scale synoptic conditions (represented by the ensemble of dynamical forecasts and of the uncertainty due to small-scale processes (represented by the set of fields generated by stochastic downscaling. We show that, in current operational configurations, small- and large-scale uncertainties have roughly the same weight. These results can be used to pinpoint the specific components of the prediction chain where a better estimate of forecast uncertainty is needed.

  16. PIV uncertainty propagation

    Science.gov (United States)

    Sciacchitano, Andrea; Wieneke, Bernhard

    2016-08-01

    This paper discusses the propagation of the instantaneous uncertainty of PIV measurements to statistical and instantaneous quantities of interest derived from the velocity field. The expression of the uncertainty of vorticity, velocity divergence, mean value and Reynolds stresses is derived. It is shown that the uncertainty of vorticity and velocity divergence requires the knowledge of the spatial correlation between the error of the x and y particle image displacement, which depends upon the measurement spatial resolution. The uncertainty of statistical quantities is often dominated by the random uncertainty due to the finite sample size and decreases with the square root of the effective number of independent samples. Monte Carlo simulations are conducted to assess the accuracy of the uncertainty propagation formulae. Furthermore, three experimental assessments are carried out. In the first experiment, a turntable is used to simulate a rigid rotation flow field. The estimated uncertainty of the vorticity is compared with the actual vorticity error root-mean-square, with differences between the two quantities within 5-10% for different interrogation window sizes and overlap factors. A turbulent jet flow is investigated in the second experimental assessment. The reference velocity, which is used to compute the reference value of the instantaneous flow properties of interest, is obtained with an auxiliary PIV system, which features a higher dynamic range than the measurement system. Finally, the uncertainty quantification of statistical quantities is assessed via PIV measurements in a cavity flow. The comparison between estimated uncertainty and actual error demonstrates the accuracy of the proposed uncertainty propagation methodology.

  17. Error analysis and compensation research of scale factor for MEMS gyroscope

    Science.gov (United States)

    Liu, Chang-zheng; Wang, Xiangjun; Tang, Qi-jian

    2014-11-01

    In dynamic condition, scale factor has been one of the main errors for MEMS (micro electromechanical system) gyroscopes. This paper, based on one kind of gyroscope in the airborne optoelectronic pod, studies the variation law of the scale factor and its compensation under different environment temperature and operating speed, and then puts forward to the method of combination of ambient temperature and actual angular velocity when compensating the MEMS gyroscope's scale factor error. Test result demonstrates that the scale factor error can be effectively suppressed, and compared with compensation method only based on temperature or angular velocity separately, this new method is easy practical and presents better performance.

  18. A confirmatory factor analysis of the Self-Directed Learning Readiness Scale.

    Science.gov (United States)

    Williams, Brett; Brown, Ted

    2013-12-01

    The Self-Directed Learning Readiness Scale measures readiness for self-directed learning among undergraduate healthcare students. While several exploratory factor analyses and one confirmatory factor analysis have examined the psychometric properties of the Self-Directed Learning Readiness Scale, questions have been raised regarding the underlying latent constructs being measured. The objective of this study was to determine the best-fitting Self-Directed Learning Readiness Scale factorial structure among three models published in the literature. Data from the three-factor 40-item Self-Directed Learning Readiness Scale completed by 233 undergraduate paramedic students from four Australian universities (response rate of 26%) were analyzed using maximum likelihood confirmatory factor analysis. Comparison of model fit from the 40-item version was undertaken with the previously documented four-factor 36-item and three-factor 29-item Self-Directed Learning Readiness Scales. The model fit indices of the three one-factor congeneric models with maximum likelihood analysis demonstrate that the 40-item Self-Directed Learning Readiness Scale does not fit the data well. The best fitting model was the four-factor 36-item Self-Directed Learning Readiness Scale followed by the three-factor 29-item models. The confirmatory factor analysis results did not support the overall construct validity of the original 40-item Self-Directed Learning Readiness Scale. © 2013 Wiley Publishing Asia Pty Ltd.

  19. Factor Structure of the Student-Teacher Relationship Scale for Norwegian School-Age Children Explored with Confirmatory Factor Analysis

    Science.gov (United States)

    Drugli, May Britt; Hjemdal, Odin

    2013-01-01

    The validity of the Student-Teacher Relationship Scale (STRS) was examined in a national sample of 863 Norwegian schoolchildren in grades 1-7 (aged 6-13). The original factor structure of the STRS was tested by confirmatory factor analysis (CFA). The CFA results did not support the original three-factor structure of the STRS. Subsequent CFA of the…

  20. Uncertainty evaluation of EnPIs in industrial applications as a key factor in setting improvement actions

    Science.gov (United States)

    D'Emilia, G.; Di Gasbarro, D.; Gaspari, A.; Natale, E.

    2015-11-01

    A methodology is proposed assuming high-level Energy Performance Indicators (EnPIs) uncertainty as quantitative indicator of the evolution of an Energy Management System (EMS). Motivations leading to the selection of the EnPIs, uncertainty evaluation techniques and criteria supporting decision-making are discussed, in order to plan and pursue reliable measures for energy performance improvement. In this paper, problems, priorities, operative possibilities and reachable improvement limits are examined, starting from the measurement uncertainty assessment. Two different industrial cases are analysed with reference to the following aspects: absence/presence of energy management policy and action plans; responsibility level for the energy issues; employees’ training and motivation in respect of the energy problems; absence/presence of adequate infrastructures for monitoring and sharing of energy information; level of standardization and integration of methods and procedures linked to the energy activities; economic and financial resources for the improvement of energy efficiency. A critic and comparative analysis of the obtained results is realized. The methodology, experimentally validated, allows developing useful considerations for effective, realistic and economically feasible improvement plans, depending on the specific situation. Recursive application of the methodology allows getting reliable and resolved assessment of the EMS status, also in dynamic industrial contexts.

  1. A two-step combination of top-down and bottom-up fire emission estimates at regional and global scales: strengths and main uncertainties

    Science.gov (United States)

    Sofiev, Mikhail; Soares, Joana; Kouznetsov, Rostislav; Vira, Julius; Prank, Marje

    2016-04-01

    Top-down emission estimation via inverse dispersion modelling is used for various problems, where bottom-up approaches are difficult or highly uncertain. One of such areas is the estimation of emission from wild-land fires. In combination with dispersion modelling, satellite and/or in-situ observations can, in principle, be used to efficiently constrain the emission values. This is the main strength of the approach: the a-priori values of the emission factors (based on laboratory studies) are refined for real-life situations using the inverse-modelling technique. However, the approach also has major uncertainties, which are illustrated here with a few examples of the Integrated System for wild-land Fires (IS4FIRES). IS4FIRES generates the smoke emission and injection profile from MODIS and SEVIRI active-fire radiative energy observations. The emission calculation includes two steps: (i) initial top-down calibration of emission factors via inverse dispersion problem solution that is made once using training dataset from the past, (ii) application of the obtained emission coefficients to individual-fire radiative energy observations, thus leading to bottom-up emission compilation. For such a procedure, the major classes of uncertainties include: (i) imperfect information on fires, (ii) simplifications in the fire description, (iii) inaccuracies in the smoke observations and modelling, (iv) inaccuracies of the inverse problem solution. Using examples of the fire seasons 2010 in Russia, 2012 in Eurasia, 2007 in Australia, etc, it is pointed out that the top-down system calibration performed for a limited number of comparatively moderate cases (often the best-observed ones) may lead to errors in application to extreme events. For instance, the total emission of 2010 Russian fires is likely to be over-estimated by up to 50% if the calibration is based on the season 2006 and fire description is simplified. Longer calibration period and more sophisticated parameterization

  2. Transcultural Factors in Hypnotizability Scales: Limits and Prospects.

    Science.gov (United States)

    Champigny, Claire M; Raz, Amir

    2015-10-01

    Hypnotic suggestibility--loosely termed hypnotizability--is difficult to assess across cultures. Investigators often use translated research instruments to guide their inquiry in disparate geographic locations. Present-day hypnosis researchers rely heavily on two primary scales that are more than half a century old: the Stanford Hypnotic Susceptibility Scale: Form C (SHSS:C) (Weitzenhoffer & Hilgard, 1959) and the Harvard Group Scale of Hypnotic Susceptibility: Form A (HGSHS:A) (Shor & Orne, 1962). Scholars typically translate these scales to measure hypnotizability transculturally. This approach, however, operates under the specious assumption that the concept of hypnotizability is largely monolithic or universal across cultures. Whereas translations likely conserve the linguistic content, they may arguably imply different cultural meanings and historical subtexts. Whereas social scientists acknowledge the importance of qualitative and phenomenological accounts in the study of altered consciousness, including suggestibility, researchers interested in hypnotizability consider the impact of findings from anthropology and ethnography too little. Clinicians and scholars of hypnosis would stand to benefit from incorporating the insights afforded by transcultural research in the overarching investigation of a concept as nuanced as hypnotizability.

  3. Scale Bias as a Factor in Mood Adjective Checklists.

    Science.gov (United States)

    Campbell, J. F.; Tiller, Dale K.

    1987-01-01

    A visual analogue mood scale was developed that included an option indicating subjects didn't understand the meaning of an adjective in an item. The item content significantly affected responses, raising questions about the adequacy of recently proposed affective taxonomies that were based on restricted samples of emotion-descriptive adjectives.…

  4. Revisiting the Leadership Scale for Sport: Examining Factor Structure Through Exploratory Structural Equation Modeling.

    Science.gov (United States)

    Chiu, Weisheng; Rodriguez, Fernando M; Won, Doyeon

    2016-10-01

    This study examines the factor structure of the shortened version of the Leadership Scale for Sport, through a survey of 201 collegiate swimmers at National Collegiate Athletic Association Division II and III institutions, using both exploratory structural equation modeling and confirmatory factor analysis. Both exploratory structural equation modeling and confirmatory factor analysis showed that a five-factor solution fit the data adequately. The sizes of factor loadings on target factors substantially differed between the confirmatory factor analysis and exploratory structural equation modeling solutions. In addition, the inter-correlations between factors of the Leadership Scale for Sport and the correlations with athletes' satisfaction were found to be inflated in the confirmatory factor analysis solution. Overall, the findings provide evidence of the factorial validity of the shortened Leadership Scale for Sport.

  5. Radio-astrochronology of the Agrio Formation (Neuquén Basin, Argentina) to reduce the uncertainties of the geological time scale in Early Cretaceous times

    Science.gov (United States)

    Martinez, Mathieu; Beatriz, Aguirre-Urreta; Marina, Lescano; Julieta, Omarini; Maisa, Tunik; Thomas, Frederichs; Anna-Leah, Nickl; Heiko, Pälike

    2017-04-01

    Important discrepancies between the numerical ages stated by the Geological Time Scale 2016 and radio-astrochronological works have been reported in the last years (Aguirre-Urreta et al., 2015; Martinez et al., 2015; Ogg et al., 2016). Large uncertainties notably exist for the Valanginian-Hauterivian stages for which the recently provided timescales are still debated. Here, we present an astronomical calibration for the Agrio Formation (Neuquén Basin, Argentina) to better constraint the durations of the Valanginian and the Hauterivian stages. The formation is divided into a lower and an upper member (called Pilmatué and Agua de la Mula members, respectively) composed of marl-limestone alternations deposited in a semi-pelagic to outer ramp environment and related to an orbital forcing (Sagasti, 2005). A rapidly (Elsevier B.V., 243 pp. Sagasti, G., 2005. Hemipelagic record of orbitally-induced dilution cycles in Lower Cretaceous sediments of the Neuquén Basin, in Veiga, G.D., Spaletti, L.A., Howell, J.A. and Schwarz E. (Eds.). The Neuquén Basin, Argentina: A Case Study in Sequence Stratigraphy and Basin Dynamics. Geological Society, London, Special Publications 252, 231-250.

  6. Neutrino mass hierarchy and precision physics with medium-baseline reactors: impact of energy-scale and flux-shape uncertainties

    CERN Document Server

    Capozzi, F; Marrone, A

    2015-01-01

    Nuclear reactors provide intense sources of electron antineutrinos, characterized by few-MeV energy E and unoscillated spectral shape Phi(E). High-statistics observations of reactor neutrino oscillations over medium-baseline distances L ~ O(50) km would provide unprecedented opportunities to probe both the long-wavelength mass-mixing parameters (delta m^2 and theta_12) and the short-wavelength ones (Delta m^2 and theta_13), together with the subtle interference effects associated to the neutrino mass hierarchy (either normal or inverted). In a given experimental setting - here taken as in the JUNO project for definiteness - the achievable hierarchy sensitivity and parameter accuracy depend not only on the accumulated statistics but also on systematic uncertainties, which include (but are not limited to) the mass-mixing priors and the normalizations of signals and backgrounds. We examine, in addition, the effect of introducing smooth deformations of the detector energy scale, E -> E'(E), and of the reactor flu...

  7. Activated sludge model 2d calibration with full-scale WWTP data: comparing model parameter identifiability with influent and operational uncertainty.

    Science.gov (United States)

    Machado, Vinicius Cunha; Lafuente, Javier; Baeza, Juan Antonio

    2014-07-01

    The present work developed a model for the description of a full-scale wastewater treatment plant (WWTP) (Manresa, Catalonia, Spain) for further plant upgrades based on the systematic parameter calibration of the activated sludge model 2d (ASM2d) using a methodology based on the Fisher information matrix. The influent was characterized for the application of the ASM2d and the confidence interval of the calibrated parameters was also assessed. No expert knowledge was necessary for model calibration and a huge available plant database was converted into more useful information. The effect of the influent and operating variables on the model fit was also studied using these variables as calibrating parameters and keeping the ASM2d kinetic and stoichiometric parameters, which traditionally are the calibration parameters, at their default values. Such an "inversion" of the traditional way of model fitting allowed evaluating the sensitivity of the main model outputs regarding the influent and the operating variables changes. This new approach is able to evaluate the capacity of the operational variables used by the WWTP feedback control loops to overcome external disturbances in the influent and kinetic/stoichiometric model parameters uncertainties. In addition, the study of the influence of operating variables on the model outputs provides useful information to select input and output variables in decentralized control structures.

  8. Demand Uncertainty

    DEFF Research Database (Denmark)

    Nguyen, Daniel Xuyen

    This paper presents a model of trade that explains why firms wait to export and why many exporters fail. Firms face uncertain demands that are only realized after the firm enters the destination. The model retools the timing of uncertainty resolution found in productivity heterogeneity models...... in untested destinations. The option to forecast demands causes firms to delay exporting in order to gather more information about foreign demand. Third, since uncertainty is resolved after entry, many firms enter a destination and then exit after learning that they cannot profit. This prediction reconciles...

  9. Piecewise compensation for the nonlinear error of fiber-optic gyroscope scale factor

    Science.gov (United States)

    Zhang, Yonggang; Wu, Xunfeng; Yuan, Shun; Wu, Lei

    2013-08-01

    Fiber-Optic Gyroscope (FOG) scale factor nonlinear error will result in errors in Strapdown Inertial Navigation System (SINS). In order to reduce nonlinear error of FOG scale factor in SINS, a compensation method is proposed in this paper based on curve piecewise fitting of FOG output. Firstly, reasons which can result in FOG scale factor error are introduced and the definition of nonlinear degree is provided. Then we introduce the method to divide the output range of FOG into several small pieces, and curve fitting is performed in each output range of FOG to obtain scale factor parameter. Different scale factor parameters of FOG are used in different pieces to improve FOG output precision. These parameters are identified by using three-axis turntable, and nonlinear error of FOG scale factor can be reduced. Finally, three-axis swing experiment of SINS verifies that the proposed method can reduce attitude output errors of SINS by compensating the nonlinear error of FOG scale factor and improve the precision of navigation. The results of experiments also demonstrate that the compensation scheme is easy to implement. It can effectively compensate the nonlinear error of FOG scale factor with slightly increased computation complexity. This method can be used in inertial technology based on FOG to improve precision.

  10. A Factor Analysis of the Future Use of English Scale

    OpenAIRE

    Jean-Pierre, Joseph Richard; 上原, 寿和子; Uehara, Suwako

    2013-01-01

    Since 2003 when Irie summarized the research into the motivationsof Japanese university learners into two principal orientations,career and contact, two important trends have been identified inJapanese society, (a) the increasingly important role that English isperceived to play in Japanese business and (b) the struggles ofgraduates to find successful employment. This paper reports onthe development of a 50-item psychometric scale, FUES 2.0, tomeasure future use of English. The participants i...

  11. Emission Factor from Small Scale Tropical Peat Combustion

    Science.gov (United States)

    Setyawati, W.; Damanhuri, E.; Lestari, P.; Dewi, K.

    2017-03-01

    Peatfire in Indonesia recently had become an important issue regarding its global warming impact of green house gases emitted. Emission factor is one of important variables to determine total emission of carbon released by peatfire. But currently there were only a few studies about Indonesian peat fire emission factors. The previous studies of Indonesian peat fire emission factor reported the results from a very limited number of samples and during smoldering combustion stages only. Therefore this study attempts to quantify carbon dioxide (CO2) and methane (CH4) emission factors from laboratory peat combustion based on higher number of samples and taken both of combustion stages (flaming and smoldering) into consideration. Peats were sampled from five different districts in Pontianak, West Kalimantan. Ultimate analysis showed that pure peat composed of relatively high carbon content (52.85 - 59.43% dry basis). Laboratory experiments were carried out by burning small amout of peats in a mini furnace and measuring their CO2 and CH4 emission concentration during flaming and smoldering. CO2, CO and CH4 average emission factors and their related average MCE for flaming were found to be 2,088 ± 21 g/kg (n = 17), 3.104 ± 7.173 g/kg (n = 17), 0.143 ± 0.132 g/kg (n = 17) and 0.998 ± 0.005 (n = 17), respectively, while for smoldering were 1,831 ± 131 g/kg (n = 17), 138 ± 72 g/kg (n = 17), 17 ± 12 g/kg (n = 17) and 0.894 ± 0.055 g/kg (n = 17), respectively. This emission factors based on the laboratory combustion experiment can be conveniently used to estimate CO2 and CH4 emission from Indonesian peat fire. Equation models to correlate between MCE and emission factors for both flaming and smoldering were developed. MCE and CO2 emission factor during flaming was relatively higher than smoldering. On the contrary, CO and CH4 emission factors were relatively smaller during flaming than smoldering.

  12. Confirmatory factor analysis of the portuguese Depression Anxiety Stress Scales-21

    OpenAIRE

    Apóstolo,João Luís Alves; Tanner,Barry Allen; Arfken,Cynthia Lee

    2012-01-01

    To determine which of three published models best characterizes the factor structure of the Portuguese version of the Depression Anxiety Stress Scales-21 and to assess its validity and reliability. Confirmatory factor analysis of Depression Anxiety and Stress Scale-21 for 1,297 adult, primary care outpatients (66.7% female, Mage = 48.57 years) comparing 3 models. The relationship between the Depression Anxiety Stress Scales-21 and the Positive and Negative Affect Schedule was analyzed. The co...

  13. Market uncertainty; Markedsusikkerhet

    Energy Technology Data Exchange (ETDEWEB)

    Doorman, Gerard; Holtan, Jon Anders; Mo, Birger; Groenli, Helle; Haaland, Magnar; Grinden, Bjoern

    1997-04-10

    In Norway, the project ``Market uncertainty`` has been in progress for over two years and resulted in increased skill in the use of the Grid System Operation Model. This report classifies some of the factors which lead to uncertainties in the electric power market. It has been examined whether these factors should be, or can be, modelled in the available simulation models. Some of the factors have been further considered and methods of modelling the associated uncertainties have been examined. It is concluded that (1) There is a need for automatic simulation of several scenarios in the model, and these scenarios should incorporate probability parameters, (2) At first it is most important that one can handle uncertainties in fuel prices and demand, (3) Market uncertainty which is due to irrational behaviour should be dealt with in a separate model. The difference between real and simulated prices should be analysed and modelled with a time series model, (4) Risk should be included in the Vansimtap model by way of feedback from simulations, (5) The marginal values of stored water as calculated by means of the various methods in use should be compared systematically. 9 refs., 16 figs., 5 tabs.

  14. Calibration uncertainty

    DEFF Research Database (Denmark)

    Heydorn, Kaj; Anglov, Thomas

    2002-01-01

    Methods recommended by the International Standardization Organisation and Eurachem are not satisfactory for the correct estimation of calibration uncertainty. A novel approach is introduced and tested on actual calibration data for the determination of Pb by ICP-AES. The improved calibration unce...

  15. Application of XSUSA with aleatoric and epistemic uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Gallner, Lucia; Klein, Markus; Krzykacz-Hausmann, Bernard; Pautz, Andreas; Velkov, Kiril; Zwermann, Winfried [Gesellschaft fuer Anlagen- und Reaktorsicherheit (GRS) mbH, Garching (Germany). Forschungszentrum

    2012-11-01

    When performing sampling based uncertainty and sensitivity analyses for neutron transport problems with the Monte Carlo method, two kinds of uncertainties have to be considered, namely aleatoric uncertainties arising from the stochastic nature of the simulation procedure, and epistemic uncertainties arising from an incomplete knowledge of the values of input parameters. To determine the influence of the epistemic uncertainties alone, the sample calculations from epistemic sampling can traditionally be performed with a very large number of histories such that the aleatoric uncertainties become negligible and the total uncertainty practically only comes from the influence of the epistemic uncertainties. This procedure may be CPU time intensive. In the present paper, a method was applied which uses heavily reduced numbers of particle histories in each sample calculation, and, nevertheless, is able to largely eliminate the aleatoric uncertainty contribution introduced to the output. Applying this approach, sampling based uncertainty and sensitivity analyses with nuclear covariance data were performed with the XSUSA code and KENO-Va from the SCALE 6 system as Monte Carlo transport solver, for an international criticality benchmark. Equivalent uncertainty and sensitivity results were obtained as compared to the traditional method of using very large numbers of histories in each sample calculation. Thereby, computing times could be reduced by factors of the magnitude of 100. The use of multi-group nuclear data is no restriction, i.e. the described method can also be applied when using continuous energy nuclear data. The method can equally well be used for analyses with a Monte Carlo transport solver and epistemic uncertainties from other sources, like manufacturing tolerances. So far, the method was applied to stand-alone Monte Carlo criticality calculations; currently, investigations are being performed with calculations coupling Monte Carlo transport with depletion

  16. Factors influencing uncertainties of in vivo bone lead measurement using a (109)Cd K X-ray fluorescence clover leaf geometry detector system.

    Science.gov (United States)

    Behinaein, Sepideh; Chettle, David R; Marro, Leonora; Malowany, Morie; Fisher, Mandy; Fleming, David E B; Healey, Norm; Inskip, Mike; Arbuckle, Tye E; McNeill, Fiona E

    2014-12-01

    A (109)Cd K X-ray fluorescence (KXRF) measurement system consisting of four detectors in clover-leaf geometry is a non-invasive, low-radiation-dose method of measuring bone lead concentration. Its high precision in estimating the bone lead content makes it a promising tool for the determination of the low levels of lead currently found in the general population. After developing the clover-leaf geometry system, the system was used for the first time in a major survey in 2008 to measure the lead levels of 497 smelter employees (an occupationally exposed group with high lead levels). Since the delivered effective dose of the bone lead system in clover-leaf geometry is small (on the order of nSv), the technique can be used to measure the bone lead of sensitive populations such as the elderly and children. This detector system was used from 2009 to 2011, in a pilot study that measured the bone lead concentration of 263 environmentally exposed individuals (termed the EG group) residing in Toronto, Ontario, Canada. In this paper, the factors that influence uncertainties in lead content in tibia (cortical bone) and calcaneus (trabecular bone) are discussed based on gender, age, and body mass index (BMI) by using analysis of variance (ANOVA) and multiple linear regression models. Results from the two study groups (the EG group versus the occupationally exposed smelter employees) are compared where appropriate (i.e. for males older than 20). Results from univariate analyses showed that females have higher tibia uncertainty compared to males. We observed significant differences for both calcaneus and tibia uncertainty measures (p < 0.0005) among different age groups, where the uncertainties were highest in the lowest age group (<11 years). Lastly, and perhaps most significantly, we found that the product of source activity and measurement time influenced the precision of measurements greatly, and that this factor alone could account for the higher uncertainties observed for

  17. Sensitivity and uncertainty analysis

    CERN Document Server

    Cacuci, Dan G; Navon, Ionel Michael

    2005-01-01

    As computer-assisted modeling and analysis of physical processes have continued to grow and diversify, sensitivity and uncertainty analyses have become indispensable scientific tools. Sensitivity and Uncertainty Analysis. Volume I: Theory focused on the mathematical underpinnings of two important methods for such analyses: the Adjoint Sensitivity Analysis Procedure and the Global Adjoint Sensitivity Analysis Procedure. This volume concentrates on the practical aspects of performing these analyses for large-scale systems. The applications addressed include two-phase flow problems, a radiative c

  18. Examination of factor structure for the consumers' responses to the Value Consciousness Scale.

    Science.gov (United States)

    Conrad, C A; Williams, J R

    2000-12-01

    The psychometric properties of the Value Consciousness Scale developed by Lichtenstein, Netemeyer, and Burton in 1990 were examined in a retail grocery study (N = 497). Original assessment of scale properties was undertaken using two convenience samples in a nonretail setting and additional scale performance has been documented by the scale authors. This study furthers previous research by (1) examining performance on the items in the retail grocery setting and (2) utilizing an appropriately rigorous sampling procedure. A confirmatory factor analysis indicated that the Value Consciousness Scale does not exhibit unidimensional properties, and one must be cautious if this scale is used in applications of market segmentation until further clarification can be provided.

  19. Scaling of Gene Expression with Transcription-Factor Fugacity

    Science.gov (United States)

    Weinert, Franz M.; Brewster, Robert C.; Rydenfelt, Mattias; Phillips, Rob; Kegel, Willem K.

    2015-01-01

    The proteins associated with gene regulation are often shared between multiple pathways simultaneously. By way of contrast, models in regulatory biology often assume these pathways act independently. We demonstrate a framework for calculating the change in gene expression for the interacting case by decoupling repressor occupancy across the cell from the gene of interest by way of a chemical potential. The details of the interacting regulatory architecture are encompassed in an effective concentration, and thus, a single scaling function describes a collection of gene expression data from diverse regulatory situations and collapses it onto a single master curve. PMID:25554908

  20. Scaling of gene expression with transcription-factor fugacity.

    Science.gov (United States)

    Weinert, Franz M; Brewster, Robert C; Rydenfelt, Mattias; Phillips, Rob; Kegel, Willem K

    2014-12-19

    The proteins associated with gene regulation are often shared between multiple pathways simultaneously. By way of contrast, models in regulatory biology often assume these pathways act independently. We demonstrate a framework for calculating the change in gene expression for the interacting case by decoupling repressor occupancy across the cell from the gene of interest by way of a chemical potential. The details of the interacting regulatory architecture are encompassed in an effective concentration, and thus, a single scaling function describes a collection of gene expression data from diverse regulatory situations and collapses it onto a single master curve.

  1. Identification of the underlying factor structure of the Derriford Appearance Scale 24.

    Science.gov (United States)

    Moss, Timothy P; Lawson, Victoria; White, Paul

    2015-01-01

    Background. The Derriford Appearance Scale24 (DAS24) is a widely used measure of distress and dysfunction in relation to self-consciousness of appearance. It has been used in clinical and research settings, and translated into numerous European and Asian languages. Hitherto, no study has conducted an analysis to determine the underlying factor structure of the scale. Methods. A large (n = 1,265) sample of community and hospital patients with a visible difference were recruited face to face or by post, and completed the DAS24. Results. A two factor solution was generated. An evaluation of the congruence of the factor solutions on each of the the hospital and the community samples using Tucker's Coefficient of Congruence (rc = .979) and confirmatory factor analysis, which demonstrated a consistent factor structure. A main factor, general self consciousness (GSC), was represented by 18 items. Six items comprised a second factor, sexual and body self-consciousness (SBSC). The SBSC scale demonstrated greater sensitivity and specificity in identifying distress for sexually significant areas of the body. Discussion. The factor structure of the DAS24 facilitates a more nuanced interpretation of scores using this scale. Two conceptually and statistically coherent sub-scales were identified. The SBSC sub-scale offers a means of identifying distress and dysfunction around sexually significant areas of the body not previously possible with this scale.

  2. Identification of the underlying factor structure of the Derriford Appearance Scale 24

    Directory of Open Access Journals (Sweden)

    Timothy P. Moss

    2015-07-01

    Full Text Available Background. The Derriford Appearance Scale24 (DAS24 is a widely used measure of distress and dysfunction in relation to self-consciousness of appearance. It has been used in clinical and research settings, and translated into numerous European and Asian languages. Hitherto, no study has conducted an analysis to determine the underlying factor structure of the scale.Methods. A large (n = 1,265 sample of community and hospital patients with a visible difference were recruited face to face or by post, and completed the DAS24.Results. A two factor solution was generated. An evaluation of the congruence of the factor solutions on each of the the hospital and the community samples using Tucker’s Coefficient of Congruence (rc = .979 and confirmatory factor analysis, which demonstrated a consistent factor structure. A main factor, general self consciousness (GSC, was represented by 18 items. Six items comprised a second factor, sexual and body self-consciousness (SBSC. The SBSC scale demonstrated greater sensitivity and specificity in identifying distress for sexually significant areas of the body.Discussion. The factor structure of the DAS24 facilitates a more nuanced interpretation of scores using this scale. Two conceptually and statistically coherent sub-scales were identified. The SBSC sub-scale offers a means of identifying distress and dysfunction around sexually significant areas of the body not previously possible with this scale.

  3. Confirmatory Factor Analysis of the Scales for Diagnosing Attention Deficit Hyperactivity Disorder (SCALES)

    Science.gov (United States)

    Ryser, Gail R.; Campbell, Hilary L.; Miller, Brian K.

    2010-01-01

    The diagnostic criteria for attention deficit hyperactivity disorder have evolved over time with current versions of the "Diagnostic and Statistical Manual", (4th edition), text revision, ("DSM-IV-TR") suggesting that two constellations of symptoms may be present alone or in combination. The SCALES instrument for diagnosing attention deficit…

  4. Confirmatory Factor Analysis of the Scales for Diagnosing Attention Deficit Hyperactivity Disorder (SCALES)

    Science.gov (United States)

    Ryser, Gail R.; Campbell, Hilary L.; Miller, Brian K.

    2010-01-01

    The diagnostic criteria for attention deficit hyperactivity disorder have evolved over time with current versions of the "Diagnostic and Statistical Manual", (4th edition), text revision, ("DSM-IV-TR") suggesting that two constellations of symptoms may be present alone or in combination. The SCALES instrument for diagnosing attention deficit…

  5. Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

    DEFF Research Database (Denmark)

    Dechesne, Arnaud; Badawi, N.; Aamand, Jens;

    2014-01-01

    Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we criti...

  6. Factorization in large-scale many-body calculations

    CERN Document Server

    Johnson, Calvin W; Krastev, Plamen G

    2013-01-01

    One approach for solving interacting many-fermion systems is the configuration-interaction method, also sometimes called the interacting shell model, where one finds eigenvalues of the Hamiltonian in a many-body basis of Slater determinants (antisymmeterized products of single-particle wavefunctions). The resulting Hamiltonian matrix is typically very sparse, but for large systems the nonzero matrix elements can nonetheless require terabytes or more of storage. An alternate algorithm, applicable to a broad class of systems with symmetry, in our case rotational invariance, is to exactly factorize both the basis and the interaction using additive/multiplicative quantum numbers; such an algorithm can reduce the storage requirements by an order of magnitude or more. We discuss factorization in general as well as in the context of a specific configuration-interaction code, BIGSTICK, which runs both on serial and parallel machines.

  7. Confirmatory factor analysis of the Portuguese Depression Anxiety Stress Scales-21.

    Science.gov (United States)

    Apóstolo, João Luís Alves; Tanner, Barry Allen; Arfken, Cynthia Lee

    2012-01-01

    To determine which of three published models best characterizes the factor structure of the Portuguese version of the Depression Anxiety Stress Scales-21 and to assess its validity and reliability. Confirmatory factor analysis of Depression Anxiety and Stress Scale-21 for 1,297 adult, primary care outpatients (66.7% female, Mage = 48.57 years) comparing 3 models. The relationship between the Depression Anxiety Stress Scales-21 and the Positive and Negative Affect Schedule was analyzed. The correlated 3-factor model fit the data best. The scale demonstrated good internal consistency, with alpha scores of the subscales ranging from 0.836 to 0.897. Correlation with the Positive and Negative Affect Schedule was positive and moderate with the negative affect scale; it was negative and limited with the positive affect. These findings support the correlated 3-factor structure. The test demonstrated adequate reliability and construct validity, which supports its use for screening in primary care settings with Portuguese speakers.

  8. Online self-compensation for enhanced the scale factor stability of a micromachined gyroscope

    Energy Technology Data Exchange (ETDEWEB)

    Zhou Bin; Zhang Rong; Chen Zhiyong [Department of Precision Instrument, Tsinghua University, Beijing, 100084 (China)], E-mail: zhoubin98@tsinghua.org.cn

    2009-09-01

    In this paper, an online self-compensation control scheme for micromachined gyroscope has been presented to eliminate the scale factor drift due to temperature influence. Firstly, the error sources of scale factor have been analyzed. According the analysis results, a novel control scheme which contains three loops has been proposed: a phase-locked loop of driving mode is to drive the proof mass oscillation in its' resonant frequency, an AGC loop of driving mode is to keep a constant value of the drive amplitude, an additional scale factor error online detection and cancellation loop is to keep the scale factor stable. A digital hardware prototype has been implemented to perform the precision loop control and self-compensation loop. Scale factor of the gyroscope has been measured in a temperature-controlled turntable. Experiment results show that the scale factor drift is -3.5% to 5.2% over the temperature range of -45 deg. C to +80 deg. C without the self-compensation loop, while the scale factor drift decrease to -0.009% to 0.15% after the self-compensation loop is applied.

  9. Dimensionality of the Chinese Dyadic Adjustment Scale Based on Confirmatory Factor Analyses

    Science.gov (United States)

    Shek, Daniel T. L.; Cheung, C. K.

    2008-01-01

    Based on the responses of 1,501 Chinese married adults to the Chinese version of the Dyadic Adjustment Scale (C-DAS), confirmatory factor analyses showed that four factors were abstracted from the C-DAS (Dyadic Consensus, Dyadic Cohesion, Dyadic Satisfaction and Affectional Expression) and these four primary factors were subsumed under a…

  10. Factor Structure of the Wechsler Intelligence Scale for Children--Fourth Edition among Referred Students

    Science.gov (United States)

    Watkins, Marley W.; Wilson, Sharise M.; Kotz, Kasey M.; Carbone, Maria C.; Babula, Teresa

    2006-01-01

    Factor analysis was applied to the Wechsler Intelligence Scale for Children--Fourth Edition (WISC-IV) scores of 432 Pennsylvania students referred for evaluation for special education services to determine the factor structure of the WISC-IV with this population. A first-order, four-factor oblique solution that mirrored that found in the WISC-IV…

  11. Examination of the Factor Structure and Concurrent Validity of the Langer Mindfulness/Mindlessness Scale

    Science.gov (United States)

    Haigh, Emily A. P.; Moore, Michael T.; Kashdan, Todd B.; Fresco, David M.

    2011-01-01

    Langer's theory of mindfulness proposes that a mindful person seeks out and produces novelty, is attentive to context, and is flexible in thought and behavior. In three independent studies, the factor structure of the Langer Mindfulness/Mindlessness Scale was examined. Confirmatory factor analysis failed to replicate the four-factor model and a…

  12. Managing risk and uncertainty

    OpenAIRE

    Coulson-Thomas, Colin

    2015-01-01

    Examines risk management and contemporary issues concerning risk governance from a board perspective, including risk tolerance, innovation, insurance, balancing risks and other factors, risk and strategies of diversification or focus, increasing flexibility to cope with uncertainty, periodic planning versus intelligent steering, and limiting downside risks and adverse consequences.

  13. Handling uncertainty

    DEFF Research Database (Denmark)

    Jønsson, Jesper Bosse; Fold, Niels

    2009-01-01

    Small-scale mining supports the livelihoods of several hundred thousand rural households in Africa. Nonetheless, the understanding of the organizational dynamics of small-scale miners' activities is modest. The paper outlines the small-scale mining codes in Tanzania and contrasts them to prevalen...

  14. Failure probability under parameter uncertainty.

    Science.gov (United States)

    Gerrard, R; Tsanakas, A

    2011-05-01

    In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location-scale families (including the log-normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications. © 2010 Society for Risk Analysis.

  15. Reliability and factor validity of a Farsi version of The Positive and Negative Perfectionism Scale.

    Science.gov (United States)

    Besharat, Mohammad Ali

    2009-08-01

    This study investigated reliability and factor validity of a Farsi version of the Positive and Negative Perfectionism Scale in 606 undergraduate students (257 men, 349 women) from the University of Tehran. All participants were asked to complete the scale, along with the General Health Questionnaire (Goldberg, 1972) and the Coopersmith Self-Esteem Inventory (Coopersmith, 1967). Findings indicated good internal consistency, test-retest reliability, and construct validity of the two-factor structure of the Farsi version of the Positive and Negative Perfectionism Scale. These factors were similar to the factors found in previous studies and were accordingly labeled Positive Perfectionism and Negative Perfectionism. The results provide evidence for applicability of the scale and its cross-cultural validity.

  16. TMFA: A FORTRAN Program for Three-Mode Factor Analysis and Individual Differences Multidimensional Scaling.

    Science.gov (United States)

    Redfield, Joel

    1978-01-01

    TMFA, a FORTRAN program for three-mode factor analysis and individual-differences multidimensional scaling, is described. Program features include a variety of input options, extensive preprocessing of input data, and several alternative methods of analysis. (Author)

  17. The Aggression-Submission-Conventionalism Scale: Testing a New Three Factor Measure of Authoritarianism

    Directory of Open Access Journals (Sweden)

    Philip T. Dunwoody

    2016-08-01

    Full Text Available Altemeyer’s (1981 Right-Wing Authoritarianism scale is the most popular authoritarianism measure today. However, the use of a unidimensional scale to measure a three factor construct and an apparent tautology between items and predictive criteria have garnered criticism. Revisions take one of two main approaches: either they simplify the construct to be unidimensional and create new items or they retain Altemeyer’s three factor theory and alter Altemeyer‘s original items to produce a three factor scale. We combine these two approaches by retaining Altemeyer’s three factor theory while creating new items. Our new measure, the Aggression-Submission-Conventionalism (ASC scale, allows for a test of Altemeyer’s theory divorced of the original items. The ASC scale was designed to maximize discriminant validity while creating less tautological and more politically and religiously neutral items. A total of 649 participants in three convenience samples from the United States completed surveys showing the ASC scale to have good reliability and validity. The ASC scale was found to have similar predictive validity to other three factor scales but superior discriminant validity. Most importantly, we found a clear contribution of all three factors in predicting ethnocentrism, political intolerance, and anti-democratic attitudes. Authoritarian aggression emerged as the most important and consistent predictor with submission and conventionalism effects dependent upon the criterion. The ASC subscales all added unique variance above current unidimensional measures, with aggression consistently adding the most variance. Our findings support Altemeyer’s three factor theory and show that unidimensional measures fail to capture the nuances of our ASC scale.

  18. Factor Structure and Short Form of the Miville-Guzman Universality-Diversity Scale.

    Science.gov (United States)

    Fuertes, Jairo N.; Miville, Marie L.; Mohr, Jonathan J.; Sedlacek, William E.; Gretchen, Denise

    2000-01-01

    Examines the factor structure of the Miville-Guzman Universality-Diversity Scale (M-GUDS) and presents a short form of the scale (M-GUDS-S). Findings suggest that the M-GUDS-S measures Universal-Diverse Orientation as a multidimensional construct with three distinct domains: behavioral, emotional, and cognitive. (Contains 21 references and 3…

  19. Macroecological factors explain large-scale spatial population patterns of ancient agriculturalists

    NARCIS (Netherlands)

    Xu, C.; Chen, B.; Abades, S.; Reino, L.; Teng, S.; Ljungqvist, F.C.; Huang, Z.Y.X.; Liu, X.

    2015-01-01

    Aim: It has been well demonstrated that the large-scale distribution patterns of numerous species are driven by similar macroecological factors. However, understanding of this topic remains limited when applied to our own species. Here we take a large-scale look at ancient agriculturalist population

  20. Spider diversity in cereal fields: comparing factors at local, landscape and regional scales

    NARCIS (Netherlands)

    Clough, Y.; Kruess, A.; Kleijn, D.; Tscharntke, T.

    2005-01-01

    Aim Factors acting at various scales may affect biodiversity, demanding analyses at multiple spatial scales in order to understand how community richness is determined. Here, we adopted a hierarchical approach to test the contribution of region, landscape heterogeneity, local management (organic vs.

  1. Demand Uncertainty

    DEFF Research Database (Denmark)

    Nguyen, Daniel Xuyen

    This paper presents a model of trade that explains why firms wait to export and why many exporters fail. Firms face uncertain demands that are only realized after the firm enters the destination. The model retools the timing of uncertainty resolution found in productivity heterogeneity models...... the high rate of exit seen in the first years of exporting. Finally, when faced with multiple countries in which to export, some firms will choose to sequentially export in order to slowly learn more about its chances for success in untested markets....

  2. Spatially varying relationships between land-cover change and driving factors at multiple sampling scales.

    Science.gov (United States)

    Du, Shihong; Wang, Qiao; Guo, Luo

    2014-05-01

    Modeling the relationships between environment, human activity, and natural conditions is very important for understanding human-environment interactions. This study aims at examining how these relationships vary over spatial sampling scales and investigating the spatially varying relationships between land-cover changes and driving factors, as well as the variations in the relationships at different sampling scales in the Tibetan Autonomous Prefecture of Qinghai Province, P.R. China. Regular sampling methods are used first to generate eight sets of data points at different scales, and then the values for land-cover changes and the factors are extracted for these data points. Geographically weighted regression (GWR) model is applied to analyze the relationships between land-cover changes and the factors at different sampling scales. The results indicate that the influences of the factors (e.g. the signs, significances, and values of coefficients) change greatly over different sampling scales; similarly, for different types of land-cover changes, the contributions of the factors also vary. Generally, roads, rivers, and lakes contribute greatly to land-cover changes, while villages, temples, and elevations contribute less. A possible reason is that the densities of roads, rivers, and lakes is much greater than those of villages and temples, and the populations in temples and villages are too small to have much effect on land-cover changes. The results demonstrate that the sampling scales have an important influence on the relationships between land-cover change and the factors.

  3. Effective dose scaling factors for use with cascade impactor sampling data in tenorm inhalation exposures.

    Science.gov (United States)

    Kim, Kwang Pyo; Wu, Chang-Yu; Birky, Brian K; Bolch, Wesley E

    2005-10-01

    When assessing the effective dose to workers following radio-aerosol inhalation exposures, significant reductions in dose uncertainty can be achieved through direct measurement of the particle-size distribution. The University of Washington Mark III cascade impactor is one such air sampling device that permits the user to determine aerosol mass and radioactivity concentrations as a function of particle size within eight different size intervals (each corresponding to a different impactor stage or end filter). Traditionally, dose assessments made using the LUDEP code or other internal dosimetry software utilize this air sampling information by assigning the radioactivity measured at each stage as concentrated at a single representative size central to the size interval. In this study, we explore more realistic assumptions that the measured radioactivity distributes uniformly, linearly increases, or linearly decreases across the particle size interval for each impactor stage. The concept of an effective dose scaling factor, SF(E), is thus introduced whereby (1) the former approach can be used (which requires less computational effort using the LUDEP code), and (2) the resulting values of effective dose per stage can then be rescaled to values appropriate to a linear radioactivity distribution per stage. For a majority of (238)U-series radionuclides, particle size ranges, and absorption classes, differences in these two approaches are less than 10%, and thus no corrections in effective dose per particle stage are needed. Significant corrections, however, were noted in select cases. For uniform or linearly decreasing radioactivity distributions, end-filter particles (0.03 to 0.35 microm) of type F, M, or S radionuclides were assigned values of SF(E) ranging from 1.15 to 1.44, while 3(rd) stage particles (4.5 to 12 microm) of type M and S radionuclides were assigned values of SF(E) ranging from 1.11 to 1.53. When the cascade impactor measurements indicate a linear

  4. Uncertainty analysis

    Energy Technology Data Exchange (ETDEWEB)

    Thomas, R.E.

    1982-03-01

    An evaluation is made of the suitability of analytical and statistical sampling methods for making uncertainty analyses. The adjoint method is found to be well-suited for obtaining sensitivity coefficients for computer programs involving large numbers of equations and input parameters. For this purpose the Latin Hypercube Sampling method is found to be inferior to conventional experimental designs. The Latin hypercube method can be used to estimate output probability density functions, but requires supplementary rank transformations followed by stepwise regression to obtain uncertainty information on individual input parameters. A simple Cork and Bottle problem is used to illustrate the efficiency of the adjoint method relative to certain statistical sampling methods. For linear models of the form Ax=b it is shown that a complete adjoint sensitivity analysis can be made without formulating and solving the adjoint problem. This can be done either by using a special type of statistical sampling or by reformulating the primal problem and using suitable linear programming software.

  5. Initial revision of Chinese version of parents' perception of uncertainty scale%中文版疾病不确定感父母量表的初步修订

    Institute of Scientific and Technical Information of China (English)

    麦嘉轩; 谢婉花; 马春花; 邓叶青; 戴黎黎

    2013-01-01

    Objective To translate Parents' Perception of Uncertainty Scale (PPUS) into Chinese,analyze and selected items,and then test the reliability and validity of the Chinese version of PPUS initially.Methods 210 parents of hospitalized children were recruited for the investigation.Frequency analysis,dispersion degree analysis,correlation analysis and so on were applied to analyze and select items.Internal consistency test,Pearson correlation analysis and exploratory factor analysis etc.were applied to test reliability and validity of the scale.Results The final Chinese version of PPUS contained 28 items.The Cronbach α and parity split-half reliability coefficients were 0.844 and 0.835; The Cronbach α coefficient of 4 dimensions ranged from 0.537 to 0.770.The item-total scale correlation coefficient ranged from 0.300 to 0.737.Item-dimension correlation coefficients ranged from 0.376 to 0.762.Item-other dimension correlation coefficients ranged from 0.028 to 0.514.Dimension-total scale correlation coefficients ranged from 0.480 to 0.863 and those between dimensions ranged from 0.226 to 0.536.In the content validity assessed by experts,I-CVI ranged from 0.75 to 1.00,S-CVI/Ave was 0.928.Four-factor model was performed in the principal component analysis and they explained for 41.401% variances.The maximum factor loading of all items were higher than 0.3,and most of items had adequate loadings in related dimensions.Conclusions Chinese version of PPUS had appropriate reliability and validity as an assessment tool for parental uncertainty in illness of hospitalized children' parents.%目的 翻译英文版疾病不确定感父母量表(parents' perception of uncertainty scale,PPUS)并进行条目分析和筛选,初步检验量表修订后的信效度.方法 翻译PPUS,抽取210例住院患儿的父母进行调查.运用频数分析法、离散程度法、相关系数法等多种方法进行条目分析和筛选;用内部一致性检验、Pearson相关分析和探索性

  6. A Global Analysis of the Strange Vector and Axial Form Factors of the Nucleon and their Uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Schaub, John [New Mexico State Univ., Las Cruces, NM (United States); Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)

    2010-07-01

    We studied the strange contributions to the elastic vector and axial form factors of the nucleon using all available elastic electroweak scattering data. Specifically, we combine elastic nu-p and nubar-p scattering cross-section data from the Brookhaven E734 experiment with elastic ep and quasi-elastic ed and e-4He scattering parity-violating asymmetry data from the SAMPLE, HAPPEx, PVA4 and G0 experiments. We not only determined these form factors at individual values of momentum-transfer (Q2), as other groups have done recently, but also fit the Q2-dependence of these form factors using simple functional forms. I present an overview of the G0 backward-angle experiment as well as the results of these fits using existing data, along with some expectations of how we can improve our knowledge of these form factors if the MicroBooNE collaboration completes their experiment.

  7. The impact of variation in scaling factors on the estimation of internal dose metrics: a case study using bromodichloromethane (BDCM)

    Science.gov (United States)

    Many physiologically based pharmacokinetic (PBPK) models include values for metabolic rate parameters extrapolated from in vitro metabolism studies using scaling factors such as mg of microsomal protein per gram of liver (MPPGL) and liver mass (FVL). Variation in scaling factor ...

  8. A measurement of the calorimeter response to single hadrons and determination of the jet energy scale uncertainty using LHC Run-1 pp-collision data with the ATLAS detector

    Science.gov (United States)

    Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Verzini, M. J. Alconada; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alstaty, M.; Gonzalez, B. Alvarez; Piqueras, D. Álvarez; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Coutinho, Y. Amaral; Amelung, C.; Amidei, D.; Santos, S. P. Amor Dos; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Anulli, F.; Aoki, M.; Bella, L. Aperio; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Navarro, L. Barranco; Barreiro, F.; da Costa, J. Barreiro Guimarães; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Noccioli, E. Benhar; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Kuutmann, E. Bergeaas; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bylund, O. Bessidskaia; Bessner, M.; Besson, N.; Betancourt, C.; Bethke, S.; Bevan, A. J.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; De Mendizabal, J. Bilbao; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Sola, J. D. Bossio; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Madden, W. D. Breaden; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; de Renstrom, P. A. Bruckman; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Bruni, L. S.

    2017-01-01

    A measurement of the calorimeter response to isolated charged hadrons in the ATLAS detector at the LHC is presented. This measurement is performed with 3.2 nb^{-1} of proton-proton collision data at √{s}=7 TeV from 2010 and 0.1 nb^{-1} of data at √{s}=8 TeV from 2012. A number of aspects of the calorimeter response to isolated hadrons are explored. After accounting for energy deposited by neutral particles, there is a 5% discrepancy in the modelling, using various sets of Geant4 hadronic physics models, of the calorimeter response to isolated charged hadrons in the central calorimeter region. The description of the response to anti-protons at low momenta is found to be improved with respect to previous analyses. The electromagnetic and hadronic calorimeters are also examined separately, and the detector simulation is found to describe the response in the hadronic calorimeter well. The jet energy scale uncertainty and correlations in scale between jets of different momenta and pseudorapidity are derived based on these studies. The uncertainty is 2-5% for jets with transverse momenta above 2 TeV, where this method provides the jet energy scale uncertainty for ATLAS.

  9. Jet energy scale and its systematic uncertainty for jets produced in proton-proton collisions at sqrt(s) = 7 TeV and measured with the ATLAS detector

    CERN Document Server

    The ATLAS collaboration

    2010-01-01

    The first determination of the jet energy scale (JES) and the evaluation of its systematic uncertainty for inclusive jets measured in the ATLAS detector from proton-proton collisions at sqrt(s) = 7 TeV are described. The energy scale of jets measured in the ATLAS calorimeters is calibrated on average to the hadronic scale using a method based on a simulated Monte Carlo QCD jets sample. This Monte Carlo simulation has been validated with data collected by the ATLAS detector at sqrt(s) = 900 GeV and sqrt(s) = 7 TeV. The energy contribution of multiple proton-proton interactions to calorimeter jets is not accounted for in the current JES calibration; it is included as a separate contribution to the systematic uncertainty, and it is shown to contribute less than 2%. The JES systematic uncertainty is evaluated by comparing the nominal results to Monte Carlo simulations using alternative detector configurations, alternative hadronic shower and physics models, and by comparing the relative response of jets across ps...

  10. A measurement of the calorimeter response to single hadrons and determination of the jet energy scale uncertainty using LHC Run-1 pp-collision data with the ATLAS detector.

    Science.gov (United States)

    Aaboud, M; Aad, G; Abbott, B; Abdallah, J; Abdinov, O; Abeloos, B; Aben, R; AbouZeid, O S; Abraham, N L; Abramowicz, H; Abreu, H; Abreu, R; Abulaiti, Y; Acharya, B S; Adamczyk, L; Adams, D L; Adelman, J; Adomeit, S; Adye, T; Affolder, A A; Agatonovic-Jovin, T; Agricola, J; Aguilar-Saavedra, J A; Ahlen, S P; Ahmadov, F; Aielli, G; Akerstedt, H; Åkesson, T P A; Akimov, A V; Alberghi, G L; Albert, J; Albrand, S; Verzini, M J Alconada; Aleksa, M; Aleksandrov, I N; Alexa, C; Alexander, G; Alexopoulos, T; Alhroob, M; Ali, B; Aliev, M; Alimonti, G; Alison, J; Alkire, S P; Allbrooke, B M M; Allen, B W; Allport, P P; Aloisio, A; Alonso, A; Alonso, F; Alpigiani, C; Alstaty, M; Gonzalez, B Alvarez; Piqueras, D Álvarez; Alviggi, M G; Amadio, B T; Amako, K; Coutinho, Y Amaral; Amelung, C; Amidei, D; Santos, S P Amor Dos; Amorim, A; Amoroso, S; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anders, J K; Anderson, K J; Andreazza, A; Andrei, V; Angelidakis, S; Angelozzi, I; Anger, P; Angerami, A; Anghinolfi, F; Anisenkov, A V; Anjos, N; Annovi, A; Antel, C; Antonelli, M; Antonov, A; Anulli, F; Aoki, M; Bella, L Aperio; Arabidze, G; Arai, Y; Araque, J P; Arce, A T H; Arduh, F A; Arguin, J-F; Argyropoulos, S; Arik, M; Armbruster, A J; Armitage, L J; Arnaez, O; Arnold, H; Arratia, M; Arslan, O; Artamonov, A; Artoni, G; Artz, S; Asai, S; Asbah, N; Ashkenazi, A; Åsman, B; Asquith, L; Assamagan, K; Astalos, R; Atkinson, M; Atlay, N B; Augsten, K; Avolio, G; Axen, B; Ayoub, M K; Azuelos, G; Baak, M A; Baas, A E; Baca, M J; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Bagiacchi, P; Bagnaia, P; Bai, Y; Baines, J T; Baker, O K; Baldin, E M; Balek, P; Balestri, T; Balli, F; Balunas, W K; Banas, E; Banerjee, Sw; Bannoura, A A E; Barak, L; Barberio, E L; Barberis, D; Barbero, M; Barillari, T; Barisits, M-S; Barklow, T; Barlow, N; Barnes, S L; Barnett, B M; Barnett, R M; Barnovska-Blenessy, Z; Baroncelli, A; Barone, G; Barr, A J; Navarro, L Barranco; Barreiro, F; da Costa, J Barreiro Guimarães; Bartoldus, R; Barton, A E; Bartos, P; Basalaev, A; Bassalat, A; Bates, R L; Batista, S J; Batley, J R; Battaglia, M; Bauce, M; Bauer, F; Bawa, H S; Beacham, J B; Beattie, M D; Beau, T; Beauchemin, P H; Bechtle, P; Beck, H P; Becker, K; Becker, M; Beckingham, M; Becot, C; Beddall, A J; Beddall, A; Bednyakov, V A; Bedognetti, M; Bee, C P; Beemster, L J; Beermann, T A; Begel, M; Behr, J K; Belanger-Champagne, C; Bell, A S; Bella, G; Bellagamba, L; Bellerive, A; Bellomo, M; Belotskiy, K; Beltramello, O; Belyaev, N L; Benary, O; Benchekroun, D; Bender, M; Bendtz, K; Benekos, N; Benhammou, Y; Noccioli, E Benhar; Benitez, J; Benjamin, D P; Bensinger, J R; Bentvelsen, S; Beresford, L; Beretta, M; Berge, D; Kuutmann, E Bergeaas; Berger, N; Beringer, J; Berlendis, S; Bernard, N R; Bernius, C; Bernlochner, F U; Berry, T; Berta, P; Bertella, C; Bertoli, G; Bertolucci, F; Bertram, I A; Bertsche, C; Bertsche, D; Besjes, G J; Bylund, O Bessidskaia; Bessner, M; Besson, N; 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Van Der Deijl, P C; van der Graaf, H; van Eldik, N; van Gemmeren, P; Van Nieuwkoop, J; van Vulpen, I; van Woerden, M C; Vanadia, M; Vandelli, W; Vanguri, R; Vaniachine, A; Vankov, P; Vardanyan, G; Vari, R; Varnes, E W; Varol, T; Varouchas, D; Vartapetian, A; Varvell, K E; Vasquez, J G; Vazeille, F; Schroeder, T Vazquez; Veatch, J; Veeraraghavan, V; Veloce, L M; Veloso, F; Veneziano, S; Ventura, A; Venturi, M; Venturi, N; Venturini, A; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, J C; Vest, A; Vetterli, M C; Viazlo, O; Vichou, I; Vickey, T; Boeriu, O E Vickey; Viehhauser, G H A; Viel, S; Vigani, L; Villa, M; Perez, M Villaplana; Vilucchi, E; Vincter, M G; Vinogradov, V B; Vittori, C; Vivarelli, I; Vlachos, S; Vlasak, M; Vogel, M; Vokac, P; Volpi, G; Volpi, M; von der Schmitt, H; von Toerne, E; Vorobel, V; Vorobev, K; Vos, M; Voss, R; Vossebeld, J H; Vranjes, N; Milosavljevic, M Vranjes; Vrba, V; Vreeswijk, M; Vuillermet, R; Vukotic, I; Vykydal, Z; Wagner, P; Wagner, W; Wahlberg, H; Wahrmund, S; Wakabayashi, J; Walder, J; Walker, R; Walkowiak, W; Wallangen, V; Wang, C; Wang, C; Wang, F; Wang, H; Wang, H; Wang, J; Wang, J; Wang, K; Wang, R; Wang, S M; Wang, T; Wang, T; Wang, W; Wang, X; Wanotayaroj, C; Warburton, A; Ward, C P; Wardrope, D R; Washbrook, A; Watkins, P M; Watson, A T; Watson, M F; Watts, G; Watts, S; Waugh, B M; Webb, S; Weber, M S; Weber, S W; Webster, J S; Weidberg, A R; Weinert, B; Weingarten, J; Weiser, C; Weits, H; Wells, P S; Wenaus, T; Wengler, T; Wenig, S; Wermes, N; Werner, M; Werner, M D; Werner, P; Wessels, M; Wetter, J; Whalen, K; Whallon, N L; Wharton, A M; White, A; White, M J; White, R; Whiteson, D; Wickens, F J; Wiedenmann, W; Wielers, M; Wienemann, P; Wiglesworth, C; Wiik-Fuchs, L A M; Wildauer, A; Wilk, F; Wilkens, H G; Williams, H H; Williams, S; Willis, C; Willocq, S; Wilson, J A; Wingerter-Seez, I; Winklmeier, F; Winston, O J; Winter, B T; Wittgen, M; Wittkowski, J; Wolf, T M H; Wolter, M W; Wolters, H; Worm, S D; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wu, M; Wu, M; Wu, S L; Wu, X; Wu, Y; Wyatt, T R; Wynne, B M; Xella, S; Xu, D; Xu, L; Yabsley, B; Yacoob, S; Yamaguchi, D; Yamaguchi, Y; Yamamoto, A; Yamamoto, S; Yamanaka, T; Yamauchi, K; Yamazaki, Y; Yan, Z; Yang, H; Yang, H; Yang, Y; Yang, Z; Yao, W-M; Yap, Y C; Yasu, Y; Yatsenko, E; Wong, K H Yau; Ye, J; Ye, S; Yeletskikh, I; Yen, A L; Yildirim, E; Yorita, K; Yoshida, R; Yoshihara, K; Young, C; Young, C J S; Youssef, S; Yu, D R; Yu, J; Yu, J M; Yu, J; Yuan, L; Yuen, S P Y; Yusuff, I; Zabinski, B; Zaidan, R; Zaitsev, A M; Zakharchuk, N; Zalieckas, J; Zaman, A; Zambito, S; Zanello, L; Zanzi, D; Zeitnitz, C; Zeman, M; Zemla, A; Zeng, J C; Zeng, Q; Zengel, K; Zenin, O; Ženiš, T; Zerwas, D; Zhang, D; Zhang, F; Zhang, G; Zhang, H; Zhang, J; Zhang, L; Zhang, R; Zhang, R; Zhang, X; Zhang, Z; Zhao, X; Zhao, Y; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, C; Zhou, L; Zhou, L; Zhou, M; Zhou, N; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhukov, K; Zibell, A; Zieminska, D; Zimine, N I; Zimmermann, C; Zimmermann, S; Zinonos, Z; Zinser, M; Ziolkowski, M; Živković, L; Zobernig, G; Zoccoli, A; Nedden, M Zur; Zwalinski, L

    2017-01-01

    A measurement of the calorimeter response to isolated charged hadrons in the ATLAS detector at the LHC is presented. This measurement is performed with 3.2 nb[Formula: see text] of proton-proton collision data at [Formula: see text] [Formula: see text] from 2010 and 0.1 nb[Formula: see text] of data at [Formula: see text] [Formula: see text] from 2012. A number of aspects of the calorimeter response to isolated hadrons are explored. After accounting for energy deposited by neutral particles, there is a 5% discrepancy in the modelling, using various sets of Geant4 hadronic physics models, of the calorimeter response to isolated charged hadrons in the central calorimeter region. The description of the response to anti-protons at low momenta is found to be improved with respect to previous analyses. The electromagnetic and hadronic calorimeters are also examined separately, and the detector simulation is found to describe the response in the hadronic calorimeter well. The jet energy scale uncertainty and correlations in scale between jets of different momenta and pseudorapidity are derived based on these studies. The uncertainty is 2-5% for jets with transverse momenta above 2 [Formula: see text], where this method provides the jet energy scale uncertainty for ATLAS.

  11. Perception of Environmental Risk Factors Scale for the primary school students

    Directory of Open Access Journals (Sweden)

    Nilüfer Özabacı

    2016-07-01

    Full Text Available The purpose of this study was to develop a scale to determine the effect of perception of environmental risk factors on primary school students. The participants of this study were 409 students of both low and high socio-economic level from 2 primary schools in Gaziantep. Confirmatory factor analysis and path analysis were used for scale development study. As a result of the analysis, it has been determined that the scale has a structure composed of six subscales and 55 items. Subscales of the scale are; perceptions of in school experience, perceptions of oneself, perceptions of family attitudes, perceptions of family interactions, perceptions of problems within the family, perceptions of the nearest living area. Cronbach Alpha for the scale was found to be .85.

  12. Factor Structure and Psychometric Properties of the Injection Phobia Scale-Anxiety

    Science.gov (United States)

    Olatunji, Bunmi O.; Sawchuk, Craig N.; Moretz, Melanie W.; David, Bieke; Armstrong, Thomas; Ciesielski, Bethany G.

    2010-01-01

    The present investigation examined the factor structure and psychometric properties of the Injection Phobia Scale-Anxiety (IPS-Anx). Principal components analysis of IPS-Anx items in Study 1 (n = 498) revealed a 2-factor structure consisting of Distal Fear and Contact Fear. However, CFA results in Study 2 (n = 567) suggest that a 1-factor…

  13. Development and Validation of a Coping with Discrimination Scale: Factor Structure, Reliability, and Validity

    Science.gov (United States)

    Wei, Meifen; Alvarez, Alvin N.; Ku, Tsun-Yao; Russell, Daniel W.; Bonett, Douglas G.

    2010-01-01

    Four studies were conducted to develop and validate the Coping With Discrimination Scale (CDS). In Study 1, an exploratory factor analysis (N = 328) identified 5 factors: Education/Advocacy, Internalization, Drug and Alcohol Use, Resistance, and Detachment, with internal consistency reliability estimates ranging from 0.72 to 0.90. In Study 2, a…

  14. Factor Structure of the Family Environment Scale: Effects of Social Desirability.

    Science.gov (United States)

    Fowler, Patrick C.

    1982-01-01

    Presented for 64 subjects a replication of the Family Environment Scale's maximum likelihood factor structure for which the two-factor, Varimax-rotated solution was found to be stable when the correlations among the subscales were corrected for the effects of social desirability response bias. (Author)

  15. Developing Multidimensional Likert Scales Using Item Factor Analysis: The Case of Four-Point Items

    Science.gov (United States)

    Asún, Rodrigo A.; Rdz-Navarro, Karina; Alvarado, Jesús M.

    2016-01-01

    This study compares the performance of two approaches in analysing four-point Likert rating scales with a factorial model: the classical factor analysis (FA) and the item factor analysis (IFA). For FA, maximum likelihood and weighted least squares estimations using Pearson correlation matrices among items are compared. For IFA, diagonally weighted…

  16. Factor Structure and Psychometric Properties of the Injection Phobia Scale-Anxiety

    Science.gov (United States)

    Olatunji, Bunmi O.; Sawchuk, Craig N.; Moretz, Melanie W.; David, Bieke; Armstrong, Thomas; Ciesielski, Bethany G.

    2010-01-01

    The present investigation examined the factor structure and psychometric properties of the Injection Phobia Scale-Anxiety (IPS-Anx). Principal components analysis of IPS-Anx items in Study 1 (n = 498) revealed a 2-factor structure consisting of Distal Fear and Contact Fear. However, CFA results in Study 2 (n = 567) suggest that a 1-factor…

  17. Children's Perception of Interparental Conflict Scale (CPIC): Factor Structure and Invariance across Adolescents and Emerging Adults

    Science.gov (United States)

    Moura, Octavio; dos Santos, Rute Andrade; Rocha, Magda; Matos, Paula Mena

    2010-01-01

    The Children's Perception of Interparental Conflict Scale (CPIC) is based on the cognitive-contextual framework for understanding interparental conflict. This study investigates the factor validity and the invariance of two factor models of CPIC within a sample of Portuguese adolescents and emerging adults (14 to 25 years old; N = 677). At the…

  18. The Three Domains of Disgust Scale: Factor Structure, Psychometric Properties, and Conceptual Limitations

    Science.gov (United States)

    Olatunji, Bunmi O.; Adams, Thomas; Ciesielski, Bethany; David, Bieke; Sarawgi, Shivali; Broman-Fulks, Joshua

    2012-01-01

    This investigation examined the measurement properties of the Three Domains of Disgust Scale (TDDS). Principal components analysis in Study 1 (n = 206) revealed three factors of Pathogen, Sexual, and Moral Disgust that demonstrated excellent reliability, including test-retest over 12 weeks. Confirmatory factor analyses in Study 2 (n = 406)…

  19. Confirming the Factor Structure of the Cognitive Test Anxiety Scale: Comparing the Utility of Three Solutions

    Science.gov (United States)

    Cassady, Jerrell C.; Finch, W. Holmes

    2014-01-01

    This study validated the factor structure of a popular assessment of learner's cognitive test anxiety. Following recent findings in a study with Argentinean students' use of the Spanish version of the Cognitive Test Anxiety Scale (CTAS), this study tested the factor structure using data from 742 students who completed the original English version…

  20. Factor Structure of the Acute Stress Disorder Scale in a Sample of Hurricane Katrina Evacuees

    Science.gov (United States)

    Edmondson, Donald; Mills, Mary Alice; Park, Crystal L.

    2010-01-01

    Acute stress disorder (ASD) is a poorly understood and controversial diagnosis (A. G. Harvey & R. A. Bryant, 2002). The present study used confirmatory factor analysis (CFA) to test the factor structure of the most widely used self-report measure of ASD, the Acute Stress Disorder Scale (R. A. Bryant, M. L. Moulds, & R. M. Guthrie, 2000),…

  1. The Three Domains of Disgust Scale: Factor Structure, Psychometric Properties, and Conceptual Limitations

    Science.gov (United States)

    Olatunji, Bunmi O.; Adams, Thomas; Ciesielski, Bethany; David, Bieke; Sarawgi, Shivali; Broman-Fulks, Joshua

    2012-01-01

    This investigation examined the measurement properties of the Three Domains of Disgust Scale (TDDS). Principal components analysis in Study 1 (n = 206) revealed three factors of Pathogen, Sexual, and Moral Disgust that demonstrated excellent reliability, including test-retest over 12 weeks. Confirmatory factor analyses in Study 2 (n = 406)…

  2. Factor Structure of the Rorschach Prognostic Rating Scale and Its Relation to Therapeutic Outcome

    Science.gov (United States)

    Auerbach, Stephen M.; Edinger, Jack D.

    1976-01-01

    This study evaluated the factor structure of the Rorschach Prognostic Rating Scale (RPRS) in order to: (a) test the assumption that the RPRS represents a unitary response system and (b) determine the efficacy of employing population specific factor scores as predictors of therapy outcome. (Author/NG)

  3. Confirming the Three-Factor Structure of the Disgust Scale-Revised in Eight Countries

    NARCIS (Netherlands)

    Olatunji, Bunmi O.; Moretz, Melanie W.; Mckay, Dean; Bjorklund, Fredrik; de Jong, Peter J.; Haidt, Jonathan; Hursti, Timo J.; Imada, Sumio; Koller, Silvia; Mancini, Francesco; Page, Andrew C.; Schienle, Anne

    2009-01-01

    The current study evaluates the factor structure of the Disgust Scale-Revised (DS-R) in eight countries: Australia, Brazil, Germany, Italy, Japan, the Netherlands, Sweden, and the United States (N = 2,606). Confirmatory factor analysis is used to compare two different models of the DS-R and to inves

  4. Factor Structure Analysis of the Schutte Self-Report Emotional Intelligence Scale on International Students

    Science.gov (United States)

    Ng, Kok-Mun; Wang, Chuang; Kim, Do-Hong; Bodenhorn, Nancy

    2010-01-01

    The authors investigated the factor structure of the Schutte Self-Report Emotional Intelligence (SSREI) scale on international students. Via confirmatory factor analysis, the authors tested the fit of the models reported by Schutte et al. and five other studies to data from 640 international students in the United States. Results show that…

  5. Evaluation of accuracy and uncertainty of ELISA assays for the determination of interleukin-4, interleukin-5, interferon-gamma and tumor necrosis factor-alpha

    DEFF Research Database (Denmark)

    Borg, Lone; Kristiansen, Jesper; Christensen, Jytte M

    2002-01-01

    . However, models for establishing the traceability and uncertainty of immunoassay results are lacking. Sandwich enzyme-linked immunosorbent assays (ELISAs) were developed for determination of the human cytokines interleukin-4 (IL-4), interleukin-5 (IL-5), interferon-y (IFN-gamma) and tumor necrosis factor......) of the assessed ELISAs was found to be in the range of 11-18%, except for IL-5 where RSDA increased at decreasing concentrations. The LOD was 0.12 microg/l, 0.0077 microg/l, 0.0069 microg/l and 0.0063 microg/l for IL-4, IL-5, IFN-gamma and TNF-alpha, respectively. Traceability to the WHO IS was established...

  6. GENDER DIFFERENTIALS IN FACTORS AFFECTING PERFORMANCE OF SMALL-SCALE ENTERPRISES IN LAGOS STATE – NIGERIA

    Directory of Open Access Journals (Sweden)

    Yusuff Olabisi Sherifat

    2013-05-01

    Full Text Available There is a lack of empirical data segregation on factors affecting gender as the variable of interest. However, previous research had indicated several factors that affect business performances among small-scale enterprise owners. Using feminist theory and a descriptive survey research design, data were collected from fifty (50 small-scale enterprise owners that were purposively chosen across the study area. The findings show that the factors that were significant for female were significantly different from male. For female small scale enterprise owners, marital status (64% Age of Children (68%, Role Model/ advisors (58% were significant factors that affect their business performance. For male small-scale enterprise owners, Friends (70%, a lack of Government support (80%, inability to display innovativeness (78% and Risk-Taking (84% were significant for male. Lack of availability of capital and finances were significant for the two. Other factors that affect performance include friends, inadequate training and business location. Adequate knowledge of factors that affect gender enterprise performance will go a long way in alleviating these problems. Small-scale enterprises should be supported for poverty alleviation, especially among women and for the nation’s economic development

  7. Scale-model charge-transfer technique for measuring enhancement factors

    Science.gov (United States)

    Kositsky, J.; Nanevicz, J. E.

    1991-01-01

    Determination of aircraft electric field enhancement factors is crucial when using airborne field mill (ABFM) systems to accurately measure electric fields aloft. SRI used the scale model charge transfer technique to determine enhancement factors of several canonical shapes and a scale model Learjet 36A. The measured values for the canonical shapes agreed with known analytic solutions within about 6 percent. The laboratory determined enhancement factors for the aircraft were compared with those derived from in-flight data gathered by a Learjet 36A outfitted with eight field mills. The values agreed to within experimental error (approx. 15 percent).

  8. Using Multilevel Factor Analysis with Clustered Data: Investigating the Factor Structure of the Positive Values Scale

    Science.gov (United States)

    Huang, Francis L.; Cornell, Dewey G.

    2016-01-01

    Advances in multilevel modeling techniques now make it possible to investigate the psychometric properties of instruments using clustered data. Factor models that overlook the clustering effect can lead to underestimated standard errors, incorrect parameter estimates, and model fit indices. In addition, factor structures may differ depending on…

  9. Factor structure of the private self-consciousness scale: role of item wording.

    Science.gov (United States)

    Ben-Artzi, Elisheva

    2003-12-01

    In 3 studies, I have tested the structure of different phrasing versions of the Private Self-Consciousness Scale (PrSC; Fenigstein, Scheier, & Buss, 1975) using exploratory and confirmatory factor-analytic methods and examined their predictive validity. For the original version of the PrSC, a 2-factorial model similar to Nystedt and Ljungberg's (2002) solution was found to best fit the data. When all scale items included extreme rate of occurrence words such as always, a single-factor solution emerged. Finally, when all words reflecting rate of occurrence were removed, again a 2-factor structure emerged, although different in item composition from that of the original version. In addition, different patterns of association emerged between the PrSC factors and depression and self-esteem for the extreme and neutral versions. I discuss the importance of reconceptualizing self-consciousness and the need for a new, theoretically based scale for self-consciousness.

  10. The five-factor model of the Positive and Negative Syndrome Scale - I : Confirmatory factor analysis fails to confirm 25 published five-factor solutions

    NARCIS (Netherlands)

    van der Gaag, Mark; Cuijpers, Anke; Hoffman, Tonko; Remijsen, Mila; Hijman, Ron; de Haan, Lieuwe; van Meijel, Berno; van Harten, Peter N.; Valmaggia, Lucia; de Hert, Marc; Wiersma, Durk

    2006-01-01

    Objective: The aim of this study was to test the goodness-of-fit of all previously published five-factor models of the Positive and Negative Syndrome Scale (PANSS). Methods: We used confirmatory factor analysis (CFA) with a large data set (N = 5769). Results: The different subsamples were tested for

  11. Testing the Scale Dependence of the Scale Factor $\\sigma_{eff}$ in Double Dijet Production at the LHC

    CERN Document Server

    Domdey, Svend; Wiedemann, Urs Achim

    2010-01-01

    The scale factor σ eff is the effective cross section used to characterize the measured rate of inclusive double dijet production in high energy hadron collisions. It is sensitive to the two-parton distributions in the hadronic projectile. In principle, the scale factor depends on the center of mass energy and on the minimal transverse energy of the jets contributing to the double dijet cross section. Here, we point out that proton-proton collisions at the LHC will provide for the first time experimental access to these scale dependences in a logarithmically wide, nominally perturbative kinematic range of minimal transverse energy between 10 GeV and 100 GeV. This constrains the dependence of two-parton distribution functions on parton momentum fractions and parton localization in impact parameter space. Novel information is to be expected about the transverse growth of hadronic distribution functions in the range of semi-hard Bjorken x (0.001 < x < 0.1) and high resolution Q^2. We discuss to what exten...

  12. Testing the scale dependence of the scale factor {sigma}{sub eff} in double dijet production at the LHC

    Energy Technology Data Exchange (ETDEWEB)

    Domdey, Svend [Institut fuer Theoretische Physik, Heidelberg (Germany); Theory Division, CERN, Department of Physics, Geneve 23 (Switzerland); Pirner, Hans-Juergen [Institut fuer Theoretische Physik, Heidelberg (Germany); Wiedemann, Urs Achim [Theory Division, CERN, Department of Physics, Geneve 23 (Switzerland)

    2010-01-15

    The scale factor {sigma}{sub eff} is the effective cross section used to characterize the measured rate of inclusive double dijet production in high-energy hadron collisions. It is sensitive to the two-parton distributions in the hadronic projectile. In principle, the scale factor depends on the center of mass energy and on the minimal transverse energy E{sub T,min} of the jets contributing to the double dijet cross section. Here, we point out that proton-proton collisions at the LHC will provide for the first time experimental access to these scale dependences in a logarithmically wide, nominally perturbative kinematic range 10

  13. The factor structure underlying three self-report multicultural counseling competence scales.

    Science.gov (United States)

    Constantine, Madonna G; Gloria, Alberta M; Ladany, Nicholas

    2002-11-01

    This study examined the extent to which 3 self-report multicultural scales were measuring the predominant 3-factor conceptualization of multicultural counseling competence as consisting of multicultural attitudes/beliefs, knowledge, and skills. Results of a confirmatory factor analysis revealed that the 3-factor model was not fully supported. An exploratory factor analysis identified a 2-factor structure (i.e., self-perceived multicultural counseling skills and multicultural counseling attitudes/beliefs) underlying these instruments. Implications of the findings for clinical practice, training, and research are discussed.

  14. Benchmarking observational uncertainties for hydrology (Invited)

    Science.gov (United States)

    McMillan, H. K.; Krueger, T.; Freer, J. E.; Westerberg, I.

    2013-12-01

    There is a pressing need for authoritative and concise information on the expected error distributions and magnitudes in hydrological data, to understand its information content. Many studies have discussed how to incorporate uncertainty information into model calibration and implementation, and shown how model results can be biased if uncertainty is not appropriately characterised. However, it is not always possible (for example due to financial or time constraints) to make detailed studies of uncertainty for every research study. Instead, we propose that the hydrological community could benefit greatly from sharing information on likely uncertainty characteristics and the main factors that control the resulting magnitude. In this presentation, we review the current knowledge of uncertainty for a number of key hydrological variables: rainfall, flow and water quality (suspended solids, nitrogen, phosphorus). We collated information on the specifics of the data measurement (data type, temporal and spatial resolution), error characteristics measured (e.g. standard error, confidence bounds) and error magnitude. Our results were primarily split by data type. Rainfall uncertainty was controlled most strongly by spatial scale, flow uncertainty was controlled by flow state (low, high) and gauging method. Water quality presented a more complex picture with many component errors. For all variables, it was easy to find examples where relative error magnitude exceeded 40%. We discuss some of the recent developments in hydrology which increase the need for guidance on typical error magnitudes, in particular when doing comparative/regionalisation and multi-objective analysis. Increased sharing of data, comparisons between multiple catchments, and storage in national/international databases can mean that data-users are far removed from data collection, but require good uncertainty information to reduce bias in comparisons or catchment regionalisation studies. Recently it has

  15. Comparing the factor structure of the Wisconsin Schizotypy Scales and the Schizotypal Personality Questionnaire.

    Science.gov (United States)

    Gross, Georgina M; Mellin, Juliann; Silvia, Paul J; Barrantes-Vidal, Neus; Kwapil, Thomas R

    2014-10-01

    Schizotypy is a multidimensional construct that captures the expression of schizophrenic symptoms and impairment from subclinical levels to full-blown psychosis. The present study examined the comparability of the factor structure of 2 leading psychometric measures of schizotypy: the Wisconsin Schizotypy Scales (WSS) and the Schizotypal Personality Questionnaire (SPQ). Both the SPQ and WSS purportedly capture the multidimensional structure of schizotypy; however, whether they are measuring comparable factors has not been empirically demonstrated. This study provided support for a 2-factor model with positive and negative factors underlying the WSS; however, contrary to previous findings, the best fit for the SPQ was for a 4-factor model using confirmatory factor analysis, and a 2-factor model using exploratory factor analysis. The WSS factors were relatively distinct, whereas those underlying the SPQ showed high overlap. The WSS positive and SPQ cognitive-perceptual factors appeared to tap comparable constructs. However, the WSS negative and SPQ interpersonal factors appeared to tap somewhat different constructs based on their correlation and their patterns of associations with other schizotypy dimensions and the Five-Factor Model-suggesting that the SPQ interpersonal factor may not adequately tap negative or deficit schizotypy. Although the SPQ offers the advantage over the WSS of having a disorganization factor, it is not clear that this SPQ factor is actually distinct from positive schizotypy. Existing measures should be used with caution and new measures based on a priori theories are necessary to further understand the factor structure of schizotypy.

  16. Impact of discharge data uncertainty on nutrient load uncertainty

    Science.gov (United States)

    Westerberg, Ida; Gustavsson, Hanna; Sonesten, Lars

    2016-04-01

    Uncertainty in the rating-curve model of the stage-discharge relationship leads to uncertainty in discharge time series. These uncertainties in turn affect many other analyses based on discharge data, such as nutrient load estimations. It is important to understand how large the impact of discharge data uncertainty is on such analyses, since they are often used as the basis to take important environmental management decisions. In the Baltic Sea basin, nutrient load estimates from river mouths are a central information basis for managing and reducing eutrophication in the Baltic Sea. In this study we investigated rating curve uncertainty and its propagation to discharge data uncertainty and thereafter to uncertainty in the load of phosphorous and nitrogen for twelve Swedish river mouths. We estimated rating curve uncertainty using the Voting Point method, which accounts for random and epistemic errors in the stage-discharge relation and allows drawing multiple rating-curve realisations consistent with the total uncertainty. We sampled 40,000 rating curves, and for each sampled curve we calculated a discharge time series from 15-minute water level data for the period 2005-2014. Each discharge time series was then aggregated to daily scale and used to calculate the load of phosphorous and nitrogen from linearly interpolated monthly water samples, following the currently used methodology for load estimation. Finally the yearly load estimates were calculated and we thus obtained distributions with 40,000 load realisations per year - one for each rating curve. We analysed how the rating curve uncertainty propagated to the discharge time series at different temporal resolutions, and its impact on the yearly load estimates. Two shorter periods of daily water quality sampling around the spring flood peak allowed a comparison of load uncertainty magnitudes resulting from discharge data with those resulting from the monthly water quality sampling.

  17. An inter-battery factor analysis of the comrey personality scales and the 16 personality factor questionnaire

    Directory of Open Access Journals (Sweden)

    Gideon P. de Bruin

    2000-06-01

    Full Text Available The scores of 700 Afrikaans-speaking university students on the Comrey Personality Scales and the 16 Personality Factor Questionnaire were subjected to an inter-battery factor analysis. This technique uses only the correlations between two sets of variables and reveals only the factors that they have in common. Three of the Big Five personality factors were revealed, namely Extroversion, Neuroticism and Conscientiousness. However, the Conscientiousness factor contained a relatively strong unsocialised component and in this regard it is similar to Eysencks Psychoticism factor. The results support the construct validity of the Comrey Personality Scales and the 16 Personality Factor Questionnaire. Implications for personality questionnaire design and validation are discussed. OpsommingDie tellings van 700 Afrikaanssprekende universiteitstudente vir die Comrey Persoonlikheidskale en die 16 Per- soonlikheidsfaktorvraelys is aan 'n interbattery-faktorontleding onderwerp. Hierdie tegniek gebruik slegs die korrelasies tussen twee stelle veranderlikes en ontbloot slegs faktore wat die twee stelle veranderlikes gemeen het. Drie van die faktore van die vyfFaktormodel is blootgele, naamlik Ekstroversie, Neurotisisme en Konsensieusheid. Die Konsensieusheidsfaktor het ook n relatief sterk ongesosialiseerdheidskomponent ingesluit en in hierdie sin is dit soortgelyk aan Eysenck se Psigotisisme faktor. Die resultate ondersteun die konstrukgeldigheid van die Comrey Persoonlikheidskale en die 16 Persoonlikheidsfaktorvraelys. Implikasies vir die ontwerp en validering van persoonlikheidstoetse word bespreek.

  18. Uncertainty in Air Quality Modeling.

    Science.gov (United States)

    Fox, Douglas G.

    1984-01-01

    arises because individual realizations of the concentrations are different from the average concentrations. The average square difference allows quantification of this fact. Viewed in this framework, uncertainty is related to the variance of concentration fluctuations and the integral time scale of the turbulent flow.How can the uncertainty be communicated to decision makers? There was concern expressed by a third subgroup that non-technical people would have little understanding of quantified uncertainty. This places an increased burden on modelers to ensure that their efforts are useful. Similarly, decision makers will need to educate themselves and accept the challenge of decision making with quantified uncertainty.

  19. Scale-factor variations due to wavelength-dependent optical losses in fiber optic gyros

    Science.gov (United States)

    Hammond, James A.

    1996-11-01

    Most sources of optical loss in a fiber optic gyro (FOG) depend on wavelength. Because of the broadband sources used in interferometric FOGs, these losses result in an effective shift of mean wavelength of the light producing the interference signal. For some signal processing methods, these wavelength variations produce proportional changes in the IFOG scale factor. Using well documented approximations, losses are calculated and plotted versus wavelength. A discussion of the qualitative effects on scale factor is presented and expected mean wavelength variations are computed using a representative approximation of the spectrum of a FOG source. The types of losses considered include: fiber-fiber or fiber-wave guide misalignments; microbend losses, bending losses and mode diameter mismatches. Preliminary results indicate that scale factor variations caused by such losses will contribute significantly to the total scale factor thermal sensitivity for some FOG designs. While closed loop operation results in a scale factor with fundamentally low sensitivity to variations in optical losses, most implementations are sensitive to changes in mean wavelength, thus the effects discussed here should be considered when designing high performance IFOGs and their electronics.

  20. Scale-dependent factors affecting North American river otter distribution in the midwest

    Science.gov (United States)

    Jeffress, Mackenzie R.; Paukert, C.P.; Whittier, Joanna B.; Sandercock, B.K.; Gipson, P.S.

    2011-01-01

    The North American river otter (Lontra canadensis) is recovering from near extirpation throughout much of its range. Although reintroductions, trapping regulations and habitat improvements have led to the reestablishment of river otters in the Midwest, little is known about how their distribution is influenced by local- and landscape-scale habitat. We conducted river otter sign surveys from Jan. to Apr. in 2008 and 2009 in eastern Kansas to assess how local- and landscape-scale habitat factors affect river otter occupancy. We surveyed three to nine 400-m stretches of stream and reservoir shorelines for 110 sites and measured local-scale variables (e.g., stream order, land cover types) within a 100 m buffer of the survey site and landscape-scale variables (e.g., road density, land cover types) for Hydrological Unit Code 14 watersheds. We then used occupancy models that account for the probability of detection to estimate occupancy as a function of these covariates using Program PRESENCE. The best-fitting model indicated river otter occupancy increased with the proportion of woodland cover and decreased with the proportion of cropland and grassland cover at the local scale. Occupancy also increased with decreased shoreline diversity, waterbody density and stream density at the landscape scale. Occupancy was not affected by land cover or human disturbance at the landscape scale. Understanding the factors and scale important to river otter occurrence will be useful in identifying areas for management and continued restoration. ?? 2011, American Midland Naturalist.

  1. Factor Structure and Reliability of the Revised Conflict Tactics Scales' (CTS2) 10-Factor Model in a Community-Based Female Sample

    Science.gov (United States)

    Yun, Sung Hyun

    2011-01-01

    The present study investigated the factor structure and reliability of the revised Conflict Tactics Scales' (CTS2) 10-factor model in a community-based female sample (N = 261). The underlying factor structure of the 10-factor model was tested by the confirmatory multiple group factor analysis, which demonstrated complex factor cross-loadings…

  2. Genome-scale reconstruction of the sigma factor network in Escherichia coli: topology and functional states

    DEFF Research Database (Denmark)

    Cho, Byung-Kwan; Kim, Donghyuk; Knight, Eric M.

    2014-01-01

    to transcription units (TUs), representing an increase of more than 300% over what has been previously reported. The reconstructed network was used to investigate competition between alternative sigma-factors (the sigma(70) and sigma(38) regulons), confirming the competition model of sigma substitution......Background: At the beginning of the transcription process, the RNA polymerase (RNAP) core enzyme requires a sigma-factor to recognize the genomic location at which the process initiates. Although the crucial role of sigma-factors has long been appreciated and characterized for many individual...... promoters, we do not yet have a genome-scale assessment of their function. Results: Using multiple genome-scale measurements, we elucidated the network of s-factor and promoter interactions in Escherichia coli. The reconstructed network includes 4,724 sigma-factor-specific promoters corresponding...

  3. Factor structure of the De Jong Gierveld loneliness scale in Spanish elderly adults

    Directory of Open Access Journals (Sweden)

    José Buz

    2014-05-01

    Full Text Available Loneliness is an important component in the measurement of subjective well-being of elderly adults. The most influential instrument in Europe is the 11-item de Jong Gierveld loneliness scale (DJGLS; de Jong Gierveld and Kamphuis, 1985. The aim of this study was to examine, throughout factorial techniques, the internal structure the Spanish version of the DJGLS. Data were gathered from 328 community-dwelling elderly adults (M = 75.53, Range: 60-99 years. The factor analysis techniques revealed that the scale was essentially unidimensional (RMR = .088, AGFI = .970, NFI = .966. Reliability was .91. Neither substantive nor statistical reasons were found to consider the existence of a second factor. Our findings also revealed some psychometric problems in the measurement of the social and emotional aspects of loneliness. Emphasis is placed on the need to improve the scale and bear in mind the differences between collectivist and individualist cultures in the use of scales measuring well-being.

  4. Scale-Free Relationships between Social and Landscape Factors in Urban Systems

    Directory of Open Access Journals (Sweden)

    Chunzhu Wei

    2017-01-01

    anthropogenic and natural factors. Moreover, this scale-free behavior of landscape–social relationships challenges the traditional modifiable area unit problem, and provides mechanistic insight into the conflicts and compatibilities between human activities and human-induced land use change.

  5. Comparison of One-, Two-, and Three-Factor Models of Personal Resiliency Using the Resiliency Scales for Children and Adolescents

    Science.gov (United States)

    Prince-Embury, Sandra; Courville, Troy

    2008-01-01

    This article examines the scale structure of the Resiliency Scales for Children and Adolescents (RSCA). Confirmatory factor analysis reveals that a three-factor model is a better fit than one- or two-factor models for the normative sample. These findings lend support to the construct validity of the RSCA. The three-factor model is discussed as a…

  6. [Development of the sense of agency scale and its factor structure].

    Science.gov (United States)

    Asai, Tomohisa; Takano, Keisuke; Sugimori, Eriko; Tanno, Yoshihiko

    2009-12-01

    A "sense of agency" involves a contemporaneous experience that the "self" causes the actions performed by the "self" (i.e., "I am the one who causes my actions"). This may comprise the main component of self-consciousness. The present research focuses on the development of a questionnaire to investigate the subjective aspects of a sense of agency. We selected items from the extant relevant measures and from previous empirical studies, and conducted four longitudinal surveys with additional scales. Statistical computations confirmed the validity and reliability of the Sense of Agency Scale (SOAS), consisting of seventeen items involving three factors. Furthermore, the results indicated that these three factors might be organized hierarchically, with each factor showing a unique relationship with emotional or social traits. This novel finding, emerging from the Sense of Agency Scale, would have been difficult to obtain via traditional empirical studies.

  7. Scale Factor Determination of Micro-Machined Angular Rate Sensors Without a Turntable

    Institute of Scientific and Technical Information of China (English)

    Gaisser Alexander; GAO Zhongyu; ZHOU Bin; ZHANG Rong; CHEN Zhiyong

    2006-01-01

    This paper presents a digital readout system to detect small capacitive signals of a micro-machined angular rate sensor. The flexible parameter adjustment ability and the computation speed of the digital signal processor were used to develop a new calibration procedure to determine the scale factor of a gyroscope without a turntable. The force of gravity was used to deflect the movable masses in the sensor, which resulted in a corresponding angular rate input. The gyroscope scale factor was then measured without a turntable. Test results show a maximum deviation of about 1.2% with respect to the scale factor determined on a turntable with the accuracy independent of the manufacturing process and property variations. The calibration method in combination with the improved readout electronics can minimize the calibration procedure and, thus, reduce the manufacturing costs.

  8. Control factors and scale analysis of annual river water, sediments and carbon transport in China

    Science.gov (United States)

    Song, Chunlin; Wang, Genxu; Sun, Xiangyang; Chang, Ruiying; Mao, Tianxu

    2016-05-01

    Under the context of dramatic human disturbances on river system, the processes that control the transport of water, sediment, and carbon from river basins to coastal seas are not completely understood. Here we performed a quantitative synthesis for 121 sites across China to find control factors of annual river exports (Rc: runoff coefficient; TSSC: total suspended sediment concentration; TSSL: total suspended sediment loads; TOCL: total organic carbon loads) at different spatial scales. The results indicated that human activities such as dam construction and vegetation restoration might have a greater influence than climate on the transport of river sediment and carbon, although climate was a major driver of Rc. Multiple spatial scale analyses indicated that Rc increased from the small to medium scale by 20% and then decreased at the sizable scale by 20%. TSSC decreased from the small to sizeable scale but increase from the sizeable to large scales; however, TSSL significantly decreased from small (768 g·m‑2·a‑1) to medium spatial scale basins (258 g·m‑2·a‑1), and TOCL decreased from the medium to large scale. Our results will improve the understanding of water, sediment and carbon transport processes and contribute better water and land resources management strategies from different spatial scales.

  9. FACTOR ANALYSIS OF A SOCIAL SKILLS SCALE FOR HIGH SCHOOL STUDENTS.

    Science.gov (United States)

    Wang, H-Y; Lin, C-K

    2015-10-01

    The objective of this study was to develop a social skills scale for high school students in Taiwan. This study adopted stratified random sampling. A total of 1,729 high school students were included. The students ranged in age from 16 to 18 years. A Social Skills Scale was developed for this study and was designed for classroom teachers to fill out. The test-retest reliability of this scale was tested by Pearson's correlation coefficient. Exploratory factor analysis was used to determine construct validity. The Social Skills Scale had good overall test-retest reliability of .92, and the internal consistency of the five subscales was above .90. The results of the factor analysis showed that the Social Skills Scale covered the five domains of classroom learning skills, communication skills, individual initiative skills, interaction skills, and job-related social skills, and the five factors explained 68.34% of the variance. Thus, the Social Skills Scale had good reliability and validity and would be applicable to and could be promoted for use in schools.

  10. 参数不确定离散广义大系统的保性能控制%Guaranteed Cost Control for Discrete-time Singular Large-scale Systems with Parameter Uncertainty

    Institute of Scientific and Technical Information of China (English)

    沃松林; 史国栋; 邹云

    2005-01-01

    The problem of optimal guaranteed cost control for discrete-time singular large-scale systems with a quadratic cost function is considered in this paper. The system under discussion is subject to norm bounded time-invariant parameter uncertainty in all the matrices of model. The problem we address is to design a state feedback controller such that the closed-loop system not only is robustly stable but also guarantees an adequate level of performance for all admissible uncertainties. A sufficient condition for the existence of guaranteed cost controllers is presented in terms of linear matrix inequalities (LMIs), and a desired state feedback controller is obtained via convex optimization. An illustrative example is given to demonstrate the effectiveness of the proposed approach.

  11. Reliability of the factor structure of the Multidimensional Scale of Interpersonal Reactivity (EMRI

    Directory of Open Access Journals (Sweden)

    Nilton S. Formiga

    2013-10-01

    Full Text Available This study aims to check the internal consistency and factor structure evaluative of the empathy scale in a high school and college sample in the state of Minas Gerais. The instruments that measure empathy can be easily found, however, of the existing, just multidimensional scale of interpersonal reactivity (Emri is the theoretical framework that has far more and better organized, and the scale that is most commonly used to assess this construct. Participated 488 subjects, male and female, with ages from 14-54 years old, distributed in primary and college levels in Patrocínio-MG composed this study sample. The subjects answered the Multidimensional Scale of Interpersonal Reactivity and socio-demographic data. From an equation analysis and structural modeling were observed psychometric indicators that assured the structural consistency of the scale, promoting in the security of the measure theoretical construct of empathy.

  12. Factor structure of a multidimensional gender identity scale in a sample of Chinese elementary school children.

    Science.gov (United States)

    Yu, Lu; Xie, Dong; Shek, Daniel T L

    2012-01-01

    This study examined the factor structure of a scale based on the four-dimensional gender identity model (Egan and Perry, 2001) in 726 Chinese elementary school students. Exploratory factor analyses suggested a three-factor model, two of which corresponded to "Felt Pressure" and "Intergroup Bias" in the original model. The third factor "Gender Compatibility" appeared to be a combination of "Gender Typicality" and "Gender Contentment" in the original model. Follow-up confirmatory factor analysis (CFA) indicated that, relative to the initial four-factor structure, the three-factor model fits the current Chinese sample better. These results are discussed in light of cross-cultural similarities and differences in development of gender identity.

  13. Factor Structure of a Multidimensional Gender Identity Scale in a Sample of Chinese Elementary School Children

    Directory of Open Access Journals (Sweden)

    Lu Yu

    2012-01-01

    Full Text Available This study examined the factor structure of a scale based on the four-dimensional gender identity model (Egan and Perry, 2001 in 726 Chinese elementary school students. Exploratory factor analyses suggested a three-factor model, two of which corresponded to “Felt Pressure” and “Intergroup Bias” in the original model. The third factor “Gender Compatibility” appeared to be a combination of “Gender Typicality” and “Gender Contentment” in the original model. Follow-up confirmatory factor analysis (CFA indicated that, relative to the initial four-factor structure, the three-factor model fits the current Chinese sample better. These results are discussed in light of cross-cultural similarities and differences in development of gender identity.

  14. Climate model uncertainty vs. conceptual geological uncertainty in hydrological modeling

    Directory of Open Access Journals (Sweden)

    T. O. Sonnenborg

    2015-04-01

    Full Text Available Projections of climate change impact are associated with a cascade of uncertainties including CO2 emission scenario, climate model, downscaling and impact model. The relative importance of the individual uncertainty sources is expected to depend on several factors including the quantity that is projected. In the present study the impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Each projection of future climate is a result of a GCM-RCM model combination (from the ENSEMBLES project forced by the same CO2 scenario (A1B. The changes from the reference period (1991–2010 to the future period (2081–2100 in projected hydrological variables are evaluated and the effects of geological model and climate model uncertainties are quantified. The results show that uncertainty propagation is context dependent. While the geological conceptualization is the dominating uncertainty source for projection of travel time and capture zones, the uncertainty on the climate models is more important for groundwater hydraulic heads and stream flow.

  15. First Spanish version of the Memorial Delirium Assessment Scale: psychometric properties, responsiveness, and factor loadings.

    Science.gov (United States)

    Noguera, Antonio; Carvajal, Ana; Alonso-Babarro, Alberto; Chisholm, Gary; Bruera, Eduardo; Centeno, Carlos

    2014-01-01

    The Memorial Delirium Assessment Scale (MDAS) is a reliable and validated instrument with which to assess delirium. However, MDAS responsiveness has only been investigated in an indirect way. Also, neurobehavioral and global cognitive factors seem to be the MDAS main factor loads. The primary objective of this study was to evaluate MDAS responsiveness and analyze individual factors on this scale. The secondary objective was to confirm concurrent validity and reliability of the Spanish version of the MDAS. The translation-back translation method was used to obtain the Spanish version of the MDAS. Delirium diagnosis was determined by the clinical Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision criteria and with the Confusion Assessment Method. Responsiveness and factor loadings were determined with the Delirium Rating Scale-Revised-98, the Mini-Mental State Examination (MMSE), and the MDAS at baseline (0 hours) and at 72 hours. Variation in the scores of the Delirium Rating Scale-Revised-98 shows a correlation of r = 0.93, with variation in MDAS scores at P < 0.001. Variation in MMSE scores shows a correlation of r = -0.84, with variation in MDAS scores at P = 0.015. Factor I, neurobehavioral (reduced awareness, reduced attention, perceptual disturbance, delusions, altered psychomotor activity, and sleep-wake cycle disturbance), correlated moderately with the MMSE at -0.56. Factor II, global cognitive (disorientation, short-term memory impairment, impaired digit span, and disorganized thinking), correlated strongly with the MMSE at -0.81. Factor II was significantly more reliable than Factor I, rho = 0.7, P = 0.01. The high responsiveness confirms the value of the MDAS for ongoing delirium assessment. Two differentiated factor loadings point to a potential future need for MDAS subscales. Copyright © 2014 U.S. Cancer Pain Relief Committee. All rights reserved.

  16. Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale

    Directory of Open Access Journals (Sweden)

    Leandro F. Malloy-Diniz

    2017-04-01

    Full Text Available Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale.Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a urgency, (b lack of premeditation; (c lack of perseverance; (d sensation seeking. In the present study 384 participants (278 women and 106 men, who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis.Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach’s alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory.Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS.

  17. Feature analysis of the scale factor variation on a constant rate biased ring laser gyro

    Institute of Scientific and Technical Information of China (English)

    Shiqiao Qin; Zongsheng Huang; Xingshu Wang

    2007-01-01

    Scale factor of a constant rate biased ring laser gyro (RLG) is studied both theoretically and experimentally.By analyzing experimental data, we find that there are three main terms contributing to the scale factor deviation. One of them is independent of time, the second varies linearly with time and the third varies exponentially with time. Theoretical analyses show that the first term is caused by experimental setup,the second and the third are caused by un-uniform thermal expension and cavity loss variation of the RLG.

  18. Factor Analysis of the Omega Scale: A Scale Designed To Measure the Attitudes of College Students toward Their Own Deaths and the Disposition of Their Bodies.

    Science.gov (United States)

    Staik, Irene M.

    A study was undertaken to provide a factor analysis of the Omega Scale, a 25-item, Likert-type scale developed in 1984 to assess attitudes toward death and funerals and other body disposition practices. The Omega Scale was administered to 250 students enrolled in introductory psychology classes at two higher education institutions in Alabama.…

  19. Uncertainty in geological and hydrogeological data

    Directory of Open Access Journals (Sweden)

    B. Nilsson

    2007-09-01

    Full Text Available Uncertainty in conceptual model structure and in environmental data is of essential interest when dealing with uncertainty in water resources management. To make quantification of uncertainty possible is it necessary to identify and characterise the uncertainty in geological and hydrogeological data. This paper discusses a range of available techniques to describe the uncertainty related to geological model structure and scale of support. Literature examples on uncertainty in hydrogeological variables such as saturated hydraulic conductivity, specific yield, specific storage, effective porosity and dispersivity are given. Field data usually have a spatial and temporal scale of support that is different from the one on which numerical models for water resources management operate. Uncertainty in hydrogeological data variables is characterised and assessed within the methodological framework of the HarmoniRiB classification.

  20. Biophysical and Socioeconomic Factors Associated with Forest Transitions at Multiple Spatial and Temporal Scales

    Directory of Open Access Journals (Sweden)

    Charles B. Yackulic

    2011-09-01

    Full Text Available Forest transitions (FT occur when socioeconomic development leads to a shift from net deforestation to reforestation; these dynamics have been observed in multiple countries across the globe, including the island of Puerto Rico in the Caribbean. Starting in the 1950s, Puerto Rico transitioned from an agrarian to a manufacturing and service economy reliant on food imports, leading to extensive reforestation. In recent years, however, net reforestation has leveled off. Here we examine the drivers of forest transition in Puerto Rico from 1977 to 2000 at two subnational, nested spatial scales (municipality and barrio and over two time periods (1977-1991 and 1991-2000. This study builds on previous work by considering the social and biophysical factors that influence both reforestation and deforestation at multiple spatial and temporal scales. By doing so within one analysis, this study offers a comprehensive understanding of the relative importance of various social and biophysical factors for forest transitions and the scales at which they are manifest. Biophysical factors considered in these analyses included slope, soil quality, and land-cover in the surrounding landscape. We also considered per capita income, population density, and the extent of protected areas as potential factors associated with forest change. Our results show that, in the 1977-1991 period, biophysical factors that exhibit variation at municipality scales (~100 km² were more important predictors of forest change than socioeconomic factors. In this period, forest dynamics were driven primarily by abandonment of less productive, steep agricultural land in the western, central part of the island. These factors had less predictive power at the smaller barrio scale (~10 km² relative to the larger municipality scale during this time period. The relative importance of socioeconomic variables for deforestation, however, increased over time as development pressures on available land

  1. Study on the accuracy factors of large-scale photogrammetry system

    Science.gov (United States)

    Wang, Jun; Dong, Mingli; Lu, Naiguang

    2011-05-01

    In photogrammetry system, the Base-Distance Ratio, the Image Scale, and the Image Standard Error, which construct the network strength of the system, are the main accuracy factors. In this paper, the normal and convergent network configurations of the photogrammetry are studied and the Network Strength, which presents the strength and accuracy of the camera station network, is expressed with the accuracy factors mentioned above. In order to verify the validation of this expression, the large-scale 3D reference field is designed and used to test the effects of these accuracy factors. The experimental results show that the relationship between the accuracy and the factors is consistent with the expression. These conclusions will guide the photogrammetric work to reduce the system errors.

  2. The Obsessive Compulsive Cocaine Scale: assessment of factor structure, reliability, and validity.

    Science.gov (United States)

    Jardin, Bianca F; Larowe, Steven D; Hall, Brian J; Malcolm, Robert J

    2011-12-01

    The present study assessed the factor structure, reliability, test retest, convergent validity, and predictive validity of the Obsessive Compulsive Cocaine Scale (OCCS), a newly developed questionnaire adapted from the Obsessive Compulsive Drinking Scale (OCDS). The questionnaire was administered to 189 cocaine-dependent individuals participating in two medication treatment trials for cocaine dependence. Confirmatory factor analysis of this measure revealed that it primarily assesses two factors, obsessions and compulsions. In addition, the data provided strong support for the internal consistency, test-retest reliability, predictive validity, and convergent validity of this two-factor measure. Overall, the data provide support for the psychometric strength of a modified version of the OCDS specifically designed to assess obsessive and compulsive cocaine use among those with cocaine dependence. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. Factor analysis of the hospital anxiety and depression scale among a Huntington's disease population

    DEFF Research Database (Denmark)

    Dale, Maria; Maltby, John; Martucci, Rossana

    2015-01-01

    INTRODUCTION: Depression and anxiety are common in Huntington's disease, a genetic neurodegenerative disorder. There is a need for measurement tools of mood to be validated within a Huntington's disease population. The current study aimed to analyze the factor structure of the Hospital Anxiety......, with two group factors, comprising four depression and four anxiety items, provided the best fit of the data. The salience of loadings on the bifactor model suggested that loadings were high on the general factor (accounting for 64% of the variance) and low on the group factors (21% for anxiety and 15......% for depression). CONCLUSIONS: The findings suggest that eight items from the scale perform well among the sample. Consistent with recent developments in modeling the Hospital Anxiety and Depression Scale, a bifactor interpretation for an eight-item version outperformed other extant models. Our findings provide...

  4. Factor and item response theory analysis of the Protean and Boundaryless Career Attitude Scales

    Directory of Open Access Journals (Sweden)

    Gideon P. de Bruin

    2010-12-01

    Full Text Available Orientation: The concepts of the Protean Career and the Boundaryless Career show potential as frameworks for research and practice in the contemporary world of work. Briscoe, Hall and DeMuth (2006 developed the Protean and Boundaryless Career Attitude Scales, which consist of the Self-Directed Career Management, Values Driven, Boundaryless Mindset and Mobility Preference subscales. However, the standardisation and replication studies conducted by Briscoe et al., left some questions unanswered in terms of the psychometric properties of the subscales.Research purpose: This study examines the psychometric properties of the Protean and Boundaryless Career Attitude Scales with the aim of clarifying the structure of the scales, examining the quality of the items and evaluating the measurement precision of the scales.Research design, approach and method: Responses of adults to the items of the Protean and Boundaryless Career Attitude Scales were analysed with factor analytic and Rasch item response model techniques.Main findings: Factor and Rasch analyses revealed that three of the four postulated dimensions were replicated, but the Values Driven dimension split into two factors. Misfitting items were identified and sources of their misfit were uncovered. The Rasch analysis showed that three of the four subscales provide most of their psychometric information at the lower ends of their respective latent traits (where relatively few persons are located. Hence, the trait estimates of persons with low scores are more precise than those of persons with high scores.Practical/managerial implications: Overall, the quality of the Protean and Boundaryless Career Attitude Scales is satisfactory, but some aspects that may be improved are identified. Researchers may use at least three of the four subscales with confidence, but more work is possibly needed on the Values Driven subscale.Contribution/value-add: The study provides researchers with information on the

  5. Factor Structure of the Wechsler Intelligence Scale for Children: Fourth Edition in Children with ADHD.

    Science.gov (United States)

    Thaler, Nicholas S; Barchard, Kimberly A; Parke, Elyse; Jones, W Paul; Etcoff, Lewis M; Allen, Daniel N

    2015-12-01

    Recent evidence suggests that the factor structure of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is better explained by a five-factor model rather than the four-factor model in the standardization sample. The current study examined the WISC-IV's factor structure in a sample of children with ADHD. Participants included 314 children and adolescents who were diagnosed with ADHD. Confirmatory factor analysis was conducted on the 10 core subtests of the WISC-IV, and three models were examined including two based on Cattell-Horn-Carroll (CHC) theory. A five-factor model consisting of Gc, Gf, Gv, Gsm, and Gs factors provided the best fit for the data. The Perceptual Reasoning factor identified in the original four-factor model split into the two CHC factors, Gf and Gv, and cross-loaded the Symbol Search subtest onto the Gv factor. A five-factor model based on CHC theory provided superior fit for the WISC-IV in children with ADHD, as has been found with the standardization sample. © The Author(s) 2012.

  6. Strategies for Application of Isotopic Uncertainties in Burnup Credit

    Energy Technology Data Exchange (ETDEWEB)

    Gauld, I.C.

    2002-12-23

    Uncertainties in the predicted isotopic concentrations in spent nuclear fuel represent one of the largest sources of overall uncertainty in criticality calculations that use burnup credit. The methods used to propagate the uncertainties in the calculated nuclide concentrations to the uncertainty in the predicted neutron multiplication factor (k{sub eff}) of the system can have a significant effect on the uncertainty in the safety margin in criticality calculations and ultimately affect the potential capacity of spent fuel transport and storage casks employing burnup credit. Methods that can provide a more accurate and realistic estimate of the uncertainty may enable increased spent fuel cask capacity and fewer casks needing to be transported, thereby reducing regulatory burden on licensee while maintaining safety for transporting spent fuel. This report surveys several different best-estimate strategies for considering the effects of nuclide uncertainties in burnup-credit analyses. The potential benefits of these strategies are illustrated for a prototypical burnup-credit cask design. The subcritical margin estimated using best-estimate methods is discussed in comparison to the margin estimated using conventional bounding methods of uncertainty propagation. To quantify the comparison, each of the strategies for estimating uncertainty has been performed using a common database of spent fuel isotopic assay measurements for pressurized-light-water reactor fuels and predicted nuclide concentrations obtained using the current version of the SCALE code system. The experimental database applied in this study has been significantly expanded to include new high-enrichment and high-burnup spent fuel assay data recently published for a wide range of important burnup-credit actinides and fission products. Expanded rare earth fission-product measurements performed at the Khlopin Radium Institute in Russia that contain the only known publicly-available measurement for {sup 103

  7. Strategies for Application of Isotopic Uncertainties in Burnup Credit

    Energy Technology Data Exchange (ETDEWEB)

    Gauld, I.C.

    2002-12-23

    Uncertainties in the predicted isotopic concentrations in spent nuclear fuel represent one of the largest sources of overall uncertainty in criticality calculations that use burnup credit. The methods used to propagate the uncertainties in the calculated nuclide concentrations to the uncertainty in the predicted neutron multiplication factor (k{sub eff}) of the system can have a significant effect on the uncertainty in the safety margin in criticality calculations and ultimately affect the potential capacity of spent fuel transport and storage casks employing burnup credit. Methods that can provide a more accurate and realistic estimate of the uncertainty may enable increased spent fuel cask capacity and fewer casks needing to be transported, thereby reducing regulatory burden on licensee while maintaining safety for transporting spent fuel. This report surveys several different best-estimate strategies for considering the effects of nuclide uncertainties in burnup-credit analyses. The potential benefits of these strategies are illustrated for a prototypical burnup-credit cask design. The subcritical margin estimated using best-estimate methods is discussed in comparison to the margin estimated using conventional bounding methods of uncertainty propagation. To quantify the comparison, each of the strategies for estimating uncertainty has been performed using a common database of spent fuel isotopic assay measurements for pressurized-light-water reactor fuels and predicted nuclide concentrations obtained using the current version of the SCALE code system. The experimental database applied in this study has been significantly expanded to include new high-enrichment and high-burnup spent fuel assay data recently published for a wide range of important burnup-credit actinides and fission products. Expanded rare earth fission-product measurements performed at the Khlopin Radium Institute in Russia that contain the only known publicly-available measurement for {sup 103

  8. Evaluation of psychological factors in orthodontic patients with TMD as applied to the "TMJ Scale".

    Science.gov (United States)

    Yamaguchi, Daisuke; Motegi, Etsuko; Nomura, Mayumi; Narimiya, Yukie; Katsumura, Sakura; Miyazaki, Haruyo; Kaji, Hatsuhiko; Watanabe, Kazuya; Yamaguchi, Hideharu

    2002-05-01

    Physical and psychological evaluation have been required for TMD patients whose problems are multi dimensional. The questionnaire named the "TMJ Scale" was created to differentiate subjective TMD symptoms of patients. The purpose of this study was to clarify the reliability of the TMJ Scale for Japanese orthodontic patients with TMD and to differentiate the symptoms. Fifty orthodontic patients (average age 21y4m) with a chief complaint of TMD symptoms were compared with thirty patients (average age 21y1m) without TMD symptoms. The results were as follows: female patients in the symptom group in particular showed a higher degree of stress due to the chronic pain and abnormalities than those in the non-symptom group. Significant differences were observed in Pain Report, Joint Dysfunction and Global Scale at the 0.1% significant level, in Non-TM Disorder, Psychological Factor and Chronicity at the 1% level, and in Palpation Pain and Perceived Malocclusion at the 5% level in females. Few psychological problems were observed in male patients in the symptom group. Significant differences were observed in Range of Motion limitation at the 5% level in males. The differences in the psychological factors between male and female patients were clarified by using the TMJ Scale. These findings suggested that it was useful to differentiate the multiple symptoms, especially the psychological factors, by using the TMJ Scale for orthodontic patients with TMD.

  9. Confirmatory factor analysis of the Appraisal of Self-Care Agency Scale - Revised 1

    Science.gov (United States)

    Stacciarini, Thaís Santos Guerra; Pace, Ana Emilia

    2017-01-01

    ABSTRACT Objective: to analyze the factor structure of the Appraisal of Self-Care Agency Scale-Revised (ASAS-R), adapted for Brazil. Method: methodological study conducted with 150 individuals with diabetes mellitus cared for by the Family Health Strategy, most of whom are elderly with low educational levels. The test of the hypothesis concerning the confirmatory factor composition of the ASAS-R was performed using latent variables structural equations. Results: the model’s goodness-of-fit indexes were satisfactory (χ2 = 259.19; χ2/g.l = 2.97, p < 0.001; GFI = 0.85; RMR = 0.07; RMSEA = 0.09); the factor loads were greater than 0.40; and most item-to-factor-correlations presented moderate to strong magnitude (0.34 to 0.58); total alpha value was 0.74, while the alpha of the three factors were 0.69, 0.38 and 0.69, respectively. Conclusion: the scale’s factor structure presented satisfactory validity and reliability results, with the exception of one factor. Application of this scale to samples of the general population is desirable in order to strengthen analyses of internal consistency and the dimensionality of the factor structure. This study is expected to contribute to further studies addressing the self-care agency construct and the development of the ASAS-R. PMID:28146182

  10. Confirmatory Factor Analytical Study of the Revised Developmental Work Personality Scale

    Science.gov (United States)

    Wong, Alex W. K.; O'Sullivan, Deirdre; Strauser, David R.

    2012-01-01

    This study investigated psychometric properties of the Revised Developmental Work Personality Scale (RDWPS). Results yielded a 14-item three-factor model that aligns with the original DWPS and fits the data very well. RDWPS scores were useful in predicting the resolution of Erikson's fourth stage of development, indicating construct validity.…

  11. Scale construction and evaluation in practice : A review of factor analysis versus item response theory applications

    NARCIS (Netherlands)

    Ten Holt, J.C.; van Duijn, M.A.J.; Boomsma, A.

    2010-01-01

    In scale construction and evaluation, factor analysis (FA) and item response theory (IRT) are two methods frequently used to determine whether a set of items reliably measures a latent variable. In a review of 41 published studies we examined which methodology – FA or IRT – was used, and what resear

  12. Validity of the Quality of School Life Scale: A Primary and Second-Order Factor Analysis.

    Science.gov (United States)

    Johnson, William L.; Johnson, Annabel M.

    1993-01-01

    Primary and second-order principal components analyses were performed on the Quality of School Life Scale (QSL), a measure of elementary school climate, for responses of 141 fourth through sixth graders. Findings suggest three general factors, but item composition of subscales differs somewhat from that proposed by the QSL's developers. (SLD)

  13. General Factor Loadings and Specific Effects of the Differential Ability Scales, Second Edition Composites

    Science.gov (United States)

    Maynard, Jennifer L.; Floyd, Randy G.; Acklie, Teresa J.; Houston, Lawrence, III

    2011-01-01

    The purpose of this study was to investigate the "g" loadings and specific effects of the core and diagnostic composite scores from the Differential Abilities Scales, Second Edition (DAS-II; Elliott, 2007a). Scores from a subset of the DAS-II standardization sample for ages 3:6 to 17:11 were submitted to principal factor analysis. Four composites,…

  14. Societal Factors Impacting Child Welfare: Validating the Perceptions of Child Welfare Scale

    Science.gov (United States)

    Auerbach, Charles; Zeitlin, Wendy; Augsberger, Astraea; McGowan, Brenda G.; Claiborne, Nancy; Lawrence, Catherine K.

    2015-01-01

    Objective: This research examines the psychometric properties of the Perceptions of Child Welfare Scale (PCWS). This instrument is designed to assess child welfare workers' understanding of how society views their role and their work. Methods: Confirmatory factor analysis (CFA) was utilized to analyze data on 538 child welfare workers. Results:…

  15. The Factor Structure of Preschool Learning Behaviors Scale Scores in Peruvian Children

    Science.gov (United States)

    Hahn, Kathryn R.; Schaefer, Barbara A.; Merino, Cesar; Worrell, Frank C.

    2009-01-01

    The factor structure of the Escala de Conductas de Aprendizaje Preescolar (ECAP), a Spanish translation of the Preschool Learning Behaviors Scale (PLBS), was examined in this study. Children aged 2 to 6 years (N = 328) enrolled in public and private preschools in the Republic of Peru were rated by classroom teachers on the frequency of observable,…

  16. General Factor Loadings and Specific Effects of the Differential Ability Scales, Second Edition Composites

    Science.gov (United States)

    Maynard, Jennifer L.; Floyd, Randy G.; Acklie, Teresa J.; Houston, Lawrence, III

    2011-01-01

    The purpose of this study was to investigate the "g" loadings and specific effects of the core and diagnostic composite scores from the Differential Abilities Scales, Second Edition (DAS-II; Elliott, 2007a). Scores from a subset of the DAS-II standardization sample for ages 3:6 to 17:11 were submitted to principal factor analysis. Four…

  17. Assessing Disharmony and Disaffection in Intimate Relationships: Revision of the Marital Satisfaction Inventory Factor Scales

    Science.gov (United States)

    Herrington, Rachael L.; Mitchell, Alexandra E.; Castellani, Angela M.; Joseph, Jana I.; Snyder, Douglas K.; Gleaves, David H.

    2008-01-01

    Previous research has identified 2 broad components of distress in intimate relationships: overt conflict, or "disharmony", and emotional distance, or "disaffection". Using confirmatory factor analysis, the authors derived 2 broadband scales of disharmony and disaffection from the Marital Satisfaction Inventory-Revised (D. K. Snyder, 1997),…

  18. Dimensionality of the Chinese Positive Youth Development Scale: Confirmatory Factor Analyses

    Science.gov (United States)

    Shek, Daniel T. L.; Ma, Cecilia M. S.

    2010-01-01

    This paper examines the dimensionality and factorial invariance of the Chinese Positive Youth Development Scale (CPYDS) using multigroup confirmatory factor analyses (MCFA). Secondary 1 students (N = 5,649) responded to the CPYDS in the context of a positive youth development program. Results showed that there are 15 basic dimensions of the CPYDS…

  19. Scale factor correction for Gaussian beam truncation in second moment beam radius measurements

    Science.gov (United States)

    Hofer, Lucas R.; Dragone, Rocco V.; MacGregor, Andrew D.

    2017-04-01

    Charged-couple devices (CCD) and complementary metal oxide semiconductor (CMOS) image sensors, in conjunction with the second moment radius analysis method, are effective tools for determining the radius of a laser beam. However, the second moment method heavily weights sensor noise, which must be dealt with using a thresholding algorithm and a software aperture. While these noise reduction methods lower the random error due to noise, they simultaneously generate systematic error by truncating the Gaussian beam's edges. A scale factor that is invariant to beam ellipticity and corrects for the truncation of the Gaussian beam due to thresholding and the software aperture has been derived. In particular, simulations showed an order of magnitude reduction in measured beam radius error when using the scale factor-irrespective of beam ellipticity-and further testing with real beam data demonstrated that radii corrected by the scale factor are independent of the noise reduction parameters. Thus, through use of the scale factor, the accuracy of beam radius measurements made with a CCD or CMOS sensor and the second moment are significantly improved.

  20. Factors affecting Small-Scale Coffee Production in Githunguri District, Kenya

    Directory of Open Access Journals (Sweden)

    Margaret Njeri Gathura

    2013-09-01

    Full Text Available This study was carried out to determine the factors affecting small scale coffee production in Kenya. The establishments under study were small-scale coffee farms in Githunguri District.It was to determine whether marketing factors, finances, government policies and physical and human resources affect coffee production in Githunguri District. Primary sources included use of questionnaires, observation and interviews. Secondary sources included desk research, library research on journals, text books and factory publications. The target population was over 700,000 small-scale coffee producers in Kenya out of which the accessible population of 10,000 producers drawn from Githunguri District in Kiambu County was selected which a sample size of 120 respondents was sampled. Stratified sampling technique was employed to compare views among coffee producers from the various coffee societies in the area. Data analysis was both qualitative and quantitative using descriptive statistics. Data presentation was in form of tables to help interpret findings and generate conclusions that aided solutions to identified problems. The research established that marketing factors, finances, government policies and physical and human resources greatly affected coffee production. The study recommended that the government should encourage coffee production by formulating favorable marketing factors and other policies and provide finances to small scale coffee producers. Producers on the other hand should strive to provide conducive working environment to their workers so as to sustain them in their farms. This will help to improve coffee yields and quality.

  1. The Factor Structure of Preschool Learning Behaviors Scale Scores in Peruvian Children

    Science.gov (United States)

    Hahn, Kathryn R.; Schaefer, Barbara A.; Merino, Cesar; Worrell, Frank C.

    2009-01-01

    The factor structure of the Escala de Conductas de Aprendizaje Preescolar (ECAP), a Spanish translation of the Preschool Learning Behaviors Scale (PLBS), was examined in this study. Children aged 2 to 6 years (N = 328) enrolled in public and private preschools in the Republic of Peru were rated by classroom teachers on the frequency of observable,…

  2. Construction of a scale for assessing at work psychosocial risk factors in professors

    Directory of Open Access Journals (Sweden)

    Sara Unda

    2016-05-01

    Full Text Available The aim of this study was to create a valid and reliable instrument to measure psychosocial risk factorsat work in Mexican professors. A 66-item scale with 5 response choices was built. In order to validate thescale, it was administered to 500 public professors at Mexico city, aged between 21 an 76, 331 males and168 females, belonging to nine higher education schools. Statistical analyses were made to know the itemdiscriminant power, reliability, and factor structure. The scale rendered five factors: perceived inequity,difficult students, perceived insecurity, academic overload, and lack of resources at the workplace. Thescales had a Cronbach´s alpha between .75 and 92. As a conclusion, the scale fulfills the requirements ofreliability and validity in a population of professors.

  3. Potential Application Of Radionuclide Scaling Factors To High Level Waste Characterization

    Energy Technology Data Exchange (ETDEWEB)

    Reboul, S. H. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2013-09-30

    Production sources, radiological properties, relative solubilities in waste, and laboratory analysis techniques for the forty-five radionuclides identified in Hanford's Waste Treatment and Immobilization Plant (WTP) Feed Acceptance Data Quality Objectives (DQO) document are addressed in this report. Based on Savannah River Site (SRS) experience and waste characteristics, thirteen of the radionuclides are judged to be candidates for potential scaling in High Level Waste (HLW) based on the concentrations of other radionuclides as determined through laboratory measurements. The thirteen radionuclides conducive to potential scaling are: Ni-59, Zr-93, Nb-93m, Cd-113m, Sn-121m, Sn-126, Cs-135, Sm-151, Ra-226, Ra-228, Ac-227, Pa-231, and Th-229. The ability to scale radionuclides is useful from two primary perspectives: 1) it provides a means of checking the radionuclide concentrations that have been determined by laboratory analysis; and 2) it provides a means of estimating radionuclide concentrations in the absence of a laboratory analysis technique or when a complex laboratory analysis technique fails. Along with the rationale for identifying and applying the potential scaling factors, this report also provides examples of using the scaling factors to estimate concentrations of radionuclides in current SRS waste and into the future. Also included in the report are examples of independent laboratory analysis techniques that can be used to check results of key radionuclide analyses. Effective utilization of radionuclide scaling factors requires understanding of the applicable production sources and the chemistry of the waste. As such, the potential scaling approaches identified in this report should be assessed from the perspective of the Hanford waste before reaching a decision regarding WTP applicability.

  4. Various Types of Five Dimensional Warp Factor and Effective Planck Scale

    CERN Document Server

    Ito, M

    2002-01-01

    Based on the assumption that the warp factor of four dimensional spacetime and the one of fifth dimension are tied through a parameter $\\alpha$, we consider five dimensional gravity with a 3-brane coupled to a bulk scalar field. For arbitrary value of $\\alpha$, the form of the warp factor is implicitly determined by hypergeometric function. Concretely, we show that the warp factor becomes explicit form for appropriate value of $\\alpha$, and study the relation between four dimensional effective Planck scale and the brane tension. This setup allows the possibility of extending the diversity of brane world.

  5. Factor analysis of the Career Decision Scale on South African high school students.

    Science.gov (United States)

    Watson, M B; Foxcroft, C D; Stead, G B

    1991-12-01

    A factor analytic study of the Career Decision Scale-High School version of Hartman and Hartman on 312 white South African adolescents from Grades 11 and 12 was undertaken. A simple two-factor structure emerged which accounted for 47.36% of the total variance in the scores. These results support the use of the version as a differential measure of career indecision and indicate that the number and structure of factors can change across populations. The implications of these results for research in South Africa are considered.

  6. Importance of proper scaling of aerobic power when relating to cardiometabolic risk factors in children

    DEFF Research Database (Denmark)

    McMurray, Robert; Hosick ‎, Peter; Bugge, Anna

    2011-01-01

    BACKGROUND: The relationship between cardiometabolic risk factors (CMRF) and aerobic power (VO(2max)) scaled as mL O(2) per kilogram body mass is controversial because mass includes both fat and fat-free mass, and fat mass is independently associated with the CMRF. AIM: To examine common units used...... to scale VO(2max) and their relationships to mean blood pressure (MBP), total cholesterol (TC), HDL cholesterol, triglycerides (TG), insulin resistance (HOMA-IR) and cumulative risk score (z-score). SUBJECTS: 1784, 8-18 year-old youths, 938 girls and 886 boys. METHODS: Fasting blood samples were obtained....... VO(2max) was estimated in mL/min from cycle ergometry and scaled to body mass (kg), fat free mass (kg(FFM)), body surface area (m(2)), height (cm) and allometric (mL/kg(0.67)/min). RESULTS: Unadjusted correlations between CMRF and many of the scaled VO(2max) units were significant (p

  7. Vibrational frequency scale factors for density functional theory and the polarization consistent basis sets.

    Science.gov (United States)

    Laury, Marie L; Carlson, Matthew J; Wilson, Angela K

    2012-11-15

    Calculated harmonic vibrational frequencies systematically deviate from experimental vibrational frequencies. The observed deviation can be corrected by applying a scale factor. Scale factors for: (i) harmonic vibrational frequencies [categorized into low (1000 cm(-1))], (ii) vibrational contributions to enthalpy and entropy, and (iii) zero-point vibrational energies (ZPVEs) have been determined for widely used density functionals in combination with polarization consistent basis sets (pc-n, n = 0,1,2,3,4). The density functionals include pure functionals (BP86, BPW91, BLYP, HCTH93, PBEPBE), hybrid functionals with Hartree-Fock exchange (B3LYP, B3P86, B3PW91, PBE1PBE, mPW1K, BH&HLYP), hybrid meta functionals with the kinetic energy density gradient (M05, M06, M05-2X, M06-2X), a double hybrid functional with Møller-Plesset correlation (B2GP-PLYP), and a dispersion corrected functional (B97-D). The experimental frequencies for calibration were from 41 organic molecules and the ZPVEs for comparison were from 24 small molecules (diatomics, triatomics). For this family of basis sets, the scale factors for each property are more dependent on the functional selection than on basis set level, and thus allow for a suggested scale factor for each density functional when employing polarization consistent basis sets (pc-n, n = 1,2,3,4). A separate scale factor is recommended when the un-polarized basis set, pc-0, is used in combination with the density functionals.

  8. Acquired experience on organizing 3D S.UN.COP: international course to support nuclear license by user training in the areas of scaling, uncertainty, and 3D thermal-hydraulics/neutron-kinetics coupled codes

    Energy Technology Data Exchange (ETDEWEB)

    Petruzzi, Alessandro; D' Auria, Francesco [University of Pisa, San Piero a Grado (Italy). Nuclear Research Group San Piero a Grado (GRNSPG); Galetti, Regina, E-mail: regina@cnen.gov.b [National Commission for Nuclear Energy (CNEN), Rio de Janeiro, RJ (Brazil); Bajs, Tomislav [University of Zagreb (Croatia). Fac. of Electrical Engineering and Computing. Dept. of Power Systems; Reventos, Francesc [Technical University of Catalonia, Barcelona (Spain). Dept. of Physics and Nuclear Engineering

    2011-07-01

    Thermal-hydraulic system computer codes are extensively used worldwide for analysis of nuclear facilities by utilities, regulatory bodies, nuclear power plant designers, vendors, and research organizations. Computer code user represents a source of uncertainty that may significantly affect the results of system code calculations. Code user training and qualification represent an effective means for reducing the variation of results caused by the application of the codes by different users. This paper describes the experience in applying a systematic approach to training code users who, upon completion of the training, should be able to perform calculations making the best possible use of the capabilities of best estimate codes. In addition, this paper presents the organization and the main features of the 3D S.UN.COP (scaling, uncertainty, and 3D coupled code calculations) seminars during which particular emphasis is given to practical applications in connection with the licensing process of best estimate plus uncertainty methodologies, showing the designer, utility and regulatory approaches. (author)

  9. Factor structure of Bech's version of the Brief Psychiatric Rating Scale in Brazilian patients

    Directory of Open Access Journals (Sweden)

    J.A.S. Crippa

    2002-10-01

    Full Text Available The objective of the present study was to evaluate the factor structure of Bech's version of the Brief Psychiatric Rating Scale (BPRS, translated into Portuguese. The BPRS was administered to a heterogeneous group of psychiatric inpatients (N = 98 and outpatients (N = 62 in a University Hospital. Each patient was evaluated from one to eight times. The interval between consecutive interviews was one week for the inpatients and one month for the outpatients. The results were submitted to factorial analysis. The internal consistency of the total scale and of each factor was also estimated. Factorial analysis followed by normalized orthogonal rotation (Varimax yielded four factors: Withdrawal-Retardation, Thinking Disorder, Anxious-Depression and Activation. Internal consistency measured by Cronbach's alpha coefficient ranged from 0.766 to 0.879. The data show that the factor structure of the present instrument is similar to that of the American version of the BPRS which contains 18 items, except for the absence of the fifth factor of the latter scale, Hostile-Suspiciousness.

  10. Factor Structure and Psychometric Properties of the Work-Family Balance Scale in an Urban Chinese Sample

    Science.gov (United States)

    Zhang, Huiping; Yip, Paul S. F.; Chi, Peilian; Chan, Kinsun; Cheung, Yee Tak; Zhang, Xiulan

    2012-01-01

    The purpose of this study was to explore the factor structure of the Work-Family Balance Scale (WFBS) and examine its reliability and validity in use in the urban Chinese population. The scale was validated using a sample of 605 urban Chinese residents from 7 cities. Exploratory factor analysis identified two factors: work-family conflict and…

  11. The Skin Picking Impact Scale: Factor structure, validity and development of a short version.

    Science.gov (United States)

    Snorrason, Ivar; Olafsson, Ragnar P; Flessner, Christopher A; Keuthen, Nancy J; Franklin, Martin E; Woods, Douglas W

    2013-08-01

    In the present study, we examined the psychometric properties of the Skin Picking Impact Scale (SPIS; Keuthen, Deckersbach, Wilhelm et al., 2001), a 10 item self-report questionnaire designed to assess the psychosocial impact of skin picking disorder (SPD). Participants were 650 individuals who met criteria for SPD in an online survey. Exploratory and confirmatory factor analyses demonstrated a unitary factor structure with high internal consistency (α = 0.94). Consequently, we constructed an abbreviated 4-item version that retained good internal consistency (α = 0.87) and a robust factor structure. Both the short and the full versions demonstrated discriminant and convergent/concurrent validity. In conclusion, the findings indicate that both versions are psychometrically sound measures of SPD related psychosocial impact; however, some potential limitations of the full scale are discussed.

  12. Analysis on the restriction factors of the green building scale promotion based on DEMATEL

    Science.gov (United States)

    Wenxia, Hong; Zhenyao, Jiang; Zhao, Yang

    2017-03-01

    In order to promote the large-scale development of the green building in our country, DEMATEL method was used to classify influence factors of green building development into three parts, including green building market, green technology and macro economy. Through the DEMATEL model, the interaction mechanism of each part was analyzed. The mutual influence degree of each barrier factor that affects the green building promotion was quantitatively analysed and key factors for the development of green building in China were also finally determined. In addition, some implementation strategies of promoting green building scale development in our country were put forward. This research will show important reference value and practical value for making policies of the green building promotion.

  13. Evaluation of Critical Success Factors For Successful Six Sigma Implementation in Indian Medium Scale Automotive Enterprises

    Directory of Open Access Journals (Sweden)

    Rajeshkumar U. Sambhe,

    2011-03-01

    Full Text Available Large scale organisations are expecting high quality products from their suppliers those are owners of SMEs’. In today scenario, many Indian SMEs’ operate their processes at the two to three sigma quality levels. So there is Six Sigma implementation needs and have been attracting much attention. Consequently, a good design ethodology for implementation of Six Sigma in manufacturing products as well as that of services is needed. The purpose of this paper is to propose and evaluation of critical success factors for successful Six Sigma implementation in medium scale automotive industries in India. The proposed method centers on critical success factors which enables the industries in the initial stage to focus on those factors which needs more concentration and it supports for successful mplementation without investing on expensive consultation

  14. Optimal investment timing and investment scale decision making under uncertainty%不确定条件下最优投资时机和最优投资规模决策

    Institute of Scientific and Technical Information of China (English)

    阳军; 孟卫东; 熊维勤

    2012-01-01

    运用实物期权理论,通过求解不变产出和可变产出条件下企业最优投资时机和最优投资规模的解析表达式,比较研究了两种不同条件下同时选择最优投资时机和最优投资规模的决策问题.研究表明,不确定性增大了企业的等待价值,企业将推迟投资,增大投资规模;最优投资规模仅与预期市场需求的不确定性相关,与反映市场需求的某一个实现值的大小无关;可变产出条件下,企业具有更大的投资临界值和更大的投资规模.不确定性降低了企业产能利用率,导致了过度投资的存在;同时,在可变产出条件下企业的产能利用率更低.%In the investment decision making, the enterprise focuses not only on investment timing choice, but on investment scale choice as well. Based on real options theory, by solving the analytical expression of optimal investment timing and optimal scale under the condition of fixed output and variable output, the paper studies comparatively the decision making in simultaneously selecting the optimal investment timing and optimal investment scale. The study shows that the uncertainty increases the expectation waiting value, thus the enterprise will postpone the investment and increase the investment scale. The paper also illustrates that the investment scale is associated with the uncertainty of expected market demand but not associated with a certain size of earned value, which reflects the market demand. Under the condition of variable output, the enterprise has greater investment critical value and larger investment scale. The uncertainty decreases the enterprise's capacity utilization, resulting in the existence of over-investment. Meanwhile the enterprise's capacity utilization is lower under the condition of variable output.

  15. Confirmatory Factor Analysis of the French Version of the Anticipatory and Consummatory Interpersonal Pleasure Scale

    Directory of Open Access Journals (Sweden)

    Joséphine Chaix

    2017-07-01

    Full Text Available The Anticipatory and Consummatory Interpersonal Pleasure Scale (ACIPS, a measure specifically designed to assess hedonic capacity for social and interpersonal pleasure, was used to evaluate the presence of social anhedonia in patients as well as the general population. The first goal of this study was to validate the structure of the French version of the ACIPS. The second objective was to verify whether a one, two or three factor solution is most appropriate for the ACIPS scale. The French version of the ACIPS was tested on 263 French-speaking pre-graduate students or professional volunteers. For the confirmatory factor analysis, data were treated as categorical ordinal and all the models were estimated using a robust weighted least squares estimator with adjustments for the mean and variance. Three models were estimated. A one-factor model representing a general undifferentiated “pleasure” latent construct was first tested on the 17 ACIPS items. A two-factor model distinguishing anticipatory-pleasure and consummatory-pleasure was tested next. Finally, a three-factor model including subdomains of intimate social interactions, group social interactions, and social bonding was tested. The one and two-factor models showed a somewhat poor fit to the data. However, the goodness of fit of the three factor model was adequate. These results suggest that individuals who enjoyed interaction in one of these three subdomains were more likely to enjoy doing so in the two other domains. However, on the basis of the comparison between the one and three factor models, these three types of interactions may not be considered as indistinguishable. Rather, they represent distinct and theoretically meaningful dimensions. These results show the French version of the ACIPS is a useful and valid scale to measure the capacity of savoring different kinds of social relationships.

  16. Factor analysis of the Hospital Anxiety and Depression Scale from a large cancer population.

    Science.gov (United States)

    Smith, Adam B; Selby, Peter J; Velikova, Galina; Stark, Dan; Wright, E Penny; Gould, Ann; Cull, Ann

    2002-06-01

    The Hospital Anxiety and Depression Scale (HADS) is widely used as a tool for assessing psychological distress in patients and non-clinical groups. Previous studies have demonstrated conflicting results regarding the factor structure of the questionnaire for different groups of patients, and the general population. This study investigated the factor structure of the HADS in a large heterogeneous cancer population of 1474 patients. It also sought to investig