WorldWideScience

Sample records for superior model fit

  1. The Model Characteristics of Physical Fitness in CrossFit

    Directory of Open Access Journals (Sweden)

    Vasilii V. Volkov

    2014-06-01

    Full Text Available The aim of the study is to work out the model characteristics of the physical fitness of CrossFit athletes based on laboratory functional testing (n=10. The analysis of the body composition was conducted using the dual-energy absorptiometry method. The morpho-functional characteristics of the heart were explored using a high-resolution ultrasound scanner. Oxygen consumption at the aerobic-anaerobic threshold and maximum oxygen consumption were determined in a step test on arm and leg cycle ergometers using a gas-analyzer. The level of the physical fitness of leg muscles in the males and females who took part in the study was satisfactory. However, it was considerably higher than the norm for untrained people. The level of the physical fitness of arm muscles was higher than the average and matched the Master of Sport of International Class standards. The productivity of the cardio-vascular system was much higher than in healthy males and females who do not work out and comparable to the standards for advanced soccer players.

  2. Evaluation of Model Fit in Cognitive Diagnosis Models

    Science.gov (United States)

    Hu, Jinxiang; Miller, M. David; Huggins-Manley, Anne Corinne; Chen, Yi-Hsin

    2016-01-01

    Cognitive diagnosis models (CDMs) estimate student ability profiles using latent attributes. Model fit to the data needs to be ascertained in order to determine whether inferences from CDMs are valid. This study investigated the usefulness of some popular model fit statistics to detect CDM fit including relative fit indices (AIC, BIC, and CAIC),…

  3. Biomedical model fitting and error analysis.

    Science.gov (United States)

    Costa, Kevin D; Kleinstein, Steven H; Hershberg, Uri

    2011-09-20

    This Teaching Resource introduces students to curve fitting and error analysis; it is the second of two lectures on developing mathematical models of biomedical systems. The first focused on identifying, extracting, and converting required constants--such as kinetic rate constants--from experimental literature. To understand how such constants are determined from experimental data, this lecture introduces the principles and practice of fitting a mathematical model to a series of measurements. We emphasize using nonlinear models for fitting nonlinear data, avoiding problems associated with linearization schemes that can distort and misrepresent the data. To help ensure proper interpretation of model parameters estimated by inverse modeling, we describe a rigorous six-step process: (i) selecting an appropriate mathematical model; (ii) defining a "figure-of-merit" function that quantifies the error between the model and data; (iii) adjusting model parameters to get a "best fit" to the data; (iv) examining the "goodness of fit" to the data; (v) determining whether a much better fit is possible; and (vi) evaluating the accuracy of the best-fit parameter values. Implementation of the computational methods is based on MATLAB, with example programs provided that can be modified for particular applications. The problem set allows students to use these programs to develop practical experience with the inverse-modeling process in the context of determining the rates of cell proliferation and death for B lymphocytes using data from BrdU-labeling experiments.

  4. Are Physical Education Majors Models for Fitness?

    Science.gov (United States)

    Kamla, James; Snyder, Ben; Tanner, Lori; Wash, Pamela

    2012-01-01

    The National Association of Sport and Physical Education (NASPE) (2002) has taken a firm stance on the importance of adequate fitness levels of physical education teachers stating that they have the responsibility to model an active lifestyle and to promote fitness behaviors. Since the NASPE declaration, national initiatives like Let's Move…

  5. Fitting Neuron Models to Spike Trains

    Science.gov (United States)

    Rossant, Cyrille; Goodman, Dan F. M.; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K.; Brette, Romain

    2011-01-01

    Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input–output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model. PMID:21415925

  6. Contrast Gain Control Model Fits Masking Data

    Science.gov (United States)

    Watson, Andrew B.; Solomon, Joshua A.; Null, Cynthia H. (Technical Monitor)

    1994-01-01

    We studied the fit of a contrast gain control model to data of Foley (JOSA 1994), consisting of thresholds for a Gabor patch masked by gratings of various orientations, or by compounds of two orientations. Our general model includes models of Foley and Teo & Heeger (IEEE 1994). Our specific model used a bank of Gabor filters with octave bandwidths at 8 orientations. Excitatory and inhibitory nonlinearities were power functions with exponents of 2.4 and 2. Inhibitory pooling was broad in orientation, but narrow in spatial frequency and space. Minkowski pooling used an exponent of 4. All of the data for observer KMF were well fit by the model. We have developed a contrast gain control model that fits masking data. Unlike Foley's, our model accepts images as inputs. Unlike Teo & Heeger's, our model did not require multiple channels for different dynamic ranges.

  7. Fitting Hidden Markov Models to Psychological Data

    Directory of Open Access Journals (Sweden)

    Ingmar Visser

    2002-01-01

    Full Text Available Markov models have been used extensively in psychology of learning. Applications of hidden Markov models are rare however. This is partially due to the fact that comprehensive statistics for model selection and model assessment are lacking in the psychological literature. We present model selection and model assessment statistics that are particularly useful in applying hidden Markov models in psychology. These statistics are presented and evaluated by simulation studies for a toy example. We compare AIC, BIC and related criteria and introduce a prediction error measure for assessing goodness-of-fit. In a simulation study, two methods of fitting equality constraints are compared. In two illustrative examples with experimental data we apply selection criteria, fit models with constraints and assess goodness-of-fit. First, data from a concept identification task is analyzed. Hidden Markov models provide a flexible approach to analyzing such data when compared to other modeling methods. Second, a novel application of hidden Markov models in implicit learning is presented. Hidden Markov models are used in this context to quantify knowledge that subjects express in an implicit learning task. This method of analyzing implicit learning data provides a comprehensive approach for addressing important theoretical issues in the field.

  8. The heterozygote superiority hypothesis for polymorphic color vision is not supported by long-term fitness data from wild neotropical monkeys.

    Science.gov (United States)

    Fedigan, Linda M; Melin, Amanda D; Addicott, John F; Kawamura, Shoji

    2014-01-01

    The leading explanatory model for the widespread occurrence of color vision polymorphism in Neotropical primates is the heterozygote superiority hypothesis, which postulates that trichromatic individuals have a fitness advantage over other phenotypes because redgreen chromatic discrimination is useful for foraging, social signaling, or predator detection. Alternative explanatory models predict that dichromatic and trichromatic phenotypes are each suited to distinct tasks. To conclusively evaluate these models, one must determine whether proposed visual advantages translate into differential fitness of trichromatic and dichromatic individuals. We tested whether color vision phenotype is a significant predictor of female fitness in a population of wild capuchins, using longterm 26 years survival and fertility data. We found no advantage to trichromats over dichromats for three fitness measures fertility rates, offspring survival and maternal survival. This finding suggests that a selective mechanism other than heterozygote advantage is operating to maintain the color vision polymorphism. We propose that attention be directed to field testing the alternative mechanisms of balancing selection proposed to explain opsin polymorphism nichedivergence, frequencydependence and mutual benefit of association. This is the first indepth, longterm study examining the effects of color vision variation on survival and reproductive success in a naturallyoccurring population of primates.

  9. The heterozygote superiority hypothesis for polymorphic color vision is not supported by long-term fitness data from wild neotropical monkeys.

    Directory of Open Access Journals (Sweden)

    Linda M Fedigan

    Full Text Available The leading explanatory model for the widespread occurrence of color vision polymorphism in Neotropical primates is the heterozygote superiority hypothesis, which postulates that trichromatic individuals have a fitness advantage over other phenotypes because redgreen chromatic discrimination is useful for foraging, social signaling, or predator detection. Alternative explanatory models predict that dichromatic and trichromatic phenotypes are each suited to distinct tasks. To conclusively evaluate these models, one must determine whether proposed visual advantages translate into differential fitness of trichromatic and dichromatic individuals. We tested whether color vision phenotype is a significant predictor of female fitness in a population of wild capuchins, using longterm 26 years survival and fertility data. We found no advantage to trichromats over dichromats for three fitness measures fertility rates, offspring survival and maternal survival. This finding suggests that a selective mechanism other than heterozygote advantage is operating to maintain the color vision polymorphism. We propose that attention be directed to field testing the alternative mechanisms of balancing selection proposed to explain opsin polymorphism nichedivergence, frequencydependence and mutual benefit of association. This is the first indepth, longterm study examining the effects of color vision variation on survival and reproductive success in a naturallyoccurring population of primates.

  10. A predictive fitness model for influenza

    Science.gov (United States)

    Łuksza, Marta; Lässig, Michael

    2014-03-01

    The seasonal human influenza A/H3N2 virus undergoes rapid evolution, which produces significant year-to-year sequence turnover in the population of circulating strains. Adaptive mutations respond to human immune challenge and occur primarily in antigenic epitopes, the antibody-binding domains of the viral surface protein haemagglutinin. Here we develop a fitness model for haemagglutinin that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a strain: adaptive epitope changes and deleterious mutations outside the epitopes. We infer both fitness components for the strains circulating in a given year, using population-genetic data of all previous strains. From fitness and frequency of each strain, we predict the frequency of its descendent strains in the following year. This fitness model maps the adaptive history of influenza A and suggests a principled method for vaccine selection. Our results call for a more comprehensive epidemiology of influenza and other fast-evolving pathogens that integrates antigenic phenotypes with other viral functions coupled by genetic linkage.

  11. Modeling and Fitting Exoplanet Transit Light Curves

    Science.gov (United States)

    Millholland, Sarah; Ruch, G. T.

    2013-01-01

    We present a numerical model along with an original fitting routine for the analysis of transiting extra-solar planet light curves. Our light curve model is unique in several ways from other available transit models, such as the analytic eclipse formulae of Mandel & Agol (2002) and Giménez (2006), the modified Eclipsing Binary Orbit Program (EBOP) model implemented in Southworth’s JKTEBOP code (Popper & Etzel 1981; Southworth et al. 2004), or the transit model developed as a part of the EXOFAST fitting suite (Eastman et al. in prep.). Our model employs Keplerian orbital dynamics about the system’s center of mass to properly account for stellar wobble and orbital eccentricity, uses a unique analytic solution derived from Kepler’s Second Law to calculate the projected distance between the centers of the star and planet, and calculates the effect of limb darkening using a simple technique that is different from the commonly used eclipse formulae. We have also devised a unique Monte Carlo style optimization routine for fitting the light curve model to observed transits. We demonstrate that, while the effect of stellar wobble on transit light curves is generally small, it becomes significant as the planet to stellar mass ratio increases and the semi-major axes of the orbits decrease. We also illustrate the appreciable effects of orbital ellipticity on the light curve and the necessity of accounting for its impacts for accurate modeling. We show that our simple limb darkening calculations are as accurate as the analytic equations of Mandel & Agol (2002). Although our Monte Carlo fitting algorithm is not as mathematically rigorous as the Markov Chain Monte Carlo based algorithms most often used to determine exoplanetary system parameters, we show that it is straightforward and returns reliable results. Finally, we show that analyses performed with our model and optimization routine compare favorably with exoplanet characterizations published by groups such as the

  12. Model-based estimation of individual fitness

    Science.gov (United States)

    Link, W.A.; Cooch, E.G.; Cam, E.

    2002-01-01

    Fitness is the currency of natural selection, a measure of the propagation rate of genotypes into future generations. Its various definitions have the common feature that they are functions of survival and fertility rates. At the individual level, the operative level for natural selection, these rates must be understood as latent features, genetically determined propensities existing at birth. This conception of rates requires that individual fitness be defined and estimated by consideration of the individual in a modelled relation to a group of similar individuals; the only alternative is to consider a sample of size one, unless a clone of identical individuals is available. We present hierarchical models describing individual heterogeneity in survival and fertility rates and allowing for associations between these rates at the individual level. We apply these models to an analysis of life histories of Kittiwakes (Rissa tridactyla ) observed at several colonies on the Brittany coast of France. We compare Bayesian estimation of the population distribution of individual fitness with estimation based on treating individual life histories in isolation, as samples of size one (e.g. McGraw & Caswell, 1996).

  13. DiskFit: a code to fit simple non-axisymmetric galaxy models either to photometric images or to kinematic maps

    CERN Document Server

    Sellwood, J A

    2015-01-01

    This posting announces public availability of version 1.2 of the DiskFit software package developed by the authors, which may be used to fit simple non-axisymmetric models either to images or to velocity fields of disk galaxies. Here we give an outline of the capability of the code and provide the link to downloading executables, the source code, and a comprehensive on-line manual. We argue that in important respects the code is superior to rotcur for fitting kinematic maps and to galfit for fitting multi-component models to photometric images.

  14. Seeing Perfectly Fitting Factor Models That Are Causally Misspecified: Understanding That Close-Fitting Models Can Be Worse

    Science.gov (United States)

    Hayduk, Leslie

    2014-01-01

    Researchers using factor analysis tend to dismiss the significant ill fit of factor models by presuming that if their factor model is close-to-fitting, it is probably close to being properly causally specified. Close fit may indeed result from a model being close to properly causally specified, but close-fitting factor models can also be seriously…

  15. Seeing Perfectly Fitting Factor Models That Are Causally Misspecified: Understanding That Close-Fitting Models Can Be Worse

    Science.gov (United States)

    Hayduk, Leslie

    2014-01-01

    Researchers using factor analysis tend to dismiss the significant ill fit of factor models by presuming that if their factor model is close-to-fitting, it is probably close to being properly causally specified. Close fit may indeed result from a model being close to properly causally specified, but close-fitting factor models can also be seriously…

  16. Evaluation of model fit in nonlinear multilevel structural equation modeling

    Directory of Open Access Journals (Sweden)

    Karin eSchermelleh-Engel

    2014-03-01

    Full Text Available Evaluating model fit in nonlinear multilevel structural equation models (MSEM presents a challenge as no adequate test statistic is available. Nevertheless, using a product indicator approach a likelihood ratio test for linear models is provided which may also be useful for nonlinear MSEM. The main problem with nonlinear models is that product variables are nonnormally distributed. Although robust test statistics have been developed for linear SEM to ensure valid results under the condition of nonnormality, they were not yet investigated for nonlinear MSEM. In a Monte Carlo study, the performance of the robust likelihood ratio test was investigated for models with single-level latent interaction effects using the unconstrained product indicator approach. As overall model fit evaluation has a potential limitation in detecting the lack of fit at a single level even for linear models, level-specific model fit evaluation was also investigated using partially saturated models. Four population models were considered: a model with interaction effects at both levels, an interaction effect at the within-group level, an interaction effect at the between-group level, and a model with no interaction effects at both levels. For these models the number of groups, predictor correlation, and model misspecification was varied. The results indicate that the robust test statistic performed sufficiently well. Advantages of level-specific model fit evaluation for the detection of model misfit are demonstrated.

  17. Evaluation of model fit in nonlinear multilevel structural equation modeling.

    Science.gov (United States)

    Schermelleh-Engel, Karin; Kerwer, Martin; Klein, Andreas G

    2014-01-01

    Evaluating model fit in nonlinear multilevel structural equation models (MSEM) presents a challenge as no adequate test statistic is available. Nevertheless, using a product indicator approach a likelihood ratio test for linear models is provided which may also be useful for nonlinear MSEM. The main problem with nonlinear models is that product variables are non-normally distributed. Although robust test statistics have been developed for linear SEM to ensure valid results under the condition of non-normality, they have not yet been investigated for nonlinear MSEM. In a Monte Carlo study, the performance of the robust likelihood ratio test was investigated for models with single-level latent interaction effects using the unconstrained product indicator approach. As overall model fit evaluation has a potential limitation in detecting the lack of fit at a single level even for linear models, level-specific model fit evaluation was also investigated using partially saturated models. Four population models were considered: a model with interaction effects at both levels, an interaction effect at the within-group level, an interaction effect at the between-group level, and a model with no interaction effects at both levels. For these models the number of groups, predictor correlation, and model misspecification was varied. The results indicate that the robust test statistic performed sufficiently well. Advantages of level-specific model fit evaluation for the detection of model misfit are demonstrated.

  18. An Investigation of Item Fit Statistics for Mixed IRT Models

    Science.gov (United States)

    Chon, Kyong Hee

    2009-01-01

    The purpose of this study was to investigate procedures for assessing model fit of IRT models for mixed format data. In this study, various IRT model combinations were fitted to data containing both dichotomous and polytomous item responses, and the suitability of the chosen model mixtures was evaluated based on a number of model fit procedures.…

  19. The best-fit universe. [cosmological models

    Science.gov (United States)

    Turner, Michael S.

    1991-01-01

    Inflation provides very strong motivation for a flat Universe, Harrison-Zel'dovich (constant-curvature) perturbations, and cold dark matter. However, there are a number of cosmological observations that conflict with the predictions of the simplest such model: one with zero cosmological constant. They include the age of the Universe, dynamical determinations of Omega, galaxy-number counts, and the apparent abundance of large-scale structure in the Universe. While the discrepancies are not yet serious enough to rule out the simplest and most well motivated model, the current data point to a best-fit model with the following parameters: Omega(sub B) approximately equal to 0.03, Omega(sub CDM) approximately equal to 0.17, Omega(sub Lambda) approximately equal to 0.8, and H(sub 0) approximately equal to 70 km/(sec x Mpc) which improves significantly the concordance with observations. While there is no good reason to expect such a value for the cosmological constant, there is no physical principle that would rule out such.

  20. The best-fit universe. [cosmological models

    Science.gov (United States)

    Turner, Michael S.

    1991-01-01

    Inflation provides very strong motivation for a flat Universe, Harrison-Zel'dovich (constant-curvature) perturbations, and cold dark matter. However, there are a number of cosmological observations that conflict with the predictions of the simplest such model: one with zero cosmological constant. They include the age of the Universe, dynamical determinations of Omega, galaxy-number counts, and the apparent abundance of large-scale structure in the Universe. While the discrepancies are not yet serious enough to rule out the simplest and most well motivated model, the current data point to a best-fit model with the following parameters: Omega(sub B) approximately equal to 0.03, Omega(sub CDM) approximately equal to 0.17, Omega(sub Lambda) approximately equal to 0.8, and H(sub 0) approximately equal to 70 km/(sec x Mpc) which improves significantly the concordance with observations. While there is no good reason to expect such a value for the cosmological constant, there is no physical principle that would rule out such.

  1. Epistasis and the Structure of Fitness Landscapes: Are Experimental Fitness Landscapes Compatible with Fisher's Geometric Model?

    Science.gov (United States)

    Blanquart, François; Bataillon, Thomas

    2016-06-01

    The fitness landscape defines the relationship between genotypes and fitness in a given environment and underlies fundamental quantities such as the distribution of selection coefficient and the magnitude and type of epistasis. A better understanding of variation in landscape structure across species and environments is thus necessary to understand and predict how populations will adapt. An increasing number of experiments investigate the properties of fitness landscapes by identifying mutations, constructing genotypes with combinations of these mutations, and measuring the fitness of these genotypes. Yet these empirical landscapes represent a very small sample of the vast space of all possible genotypes, and this sample is often biased by the protocol used to identify mutations. Here we develop a rigorous statistical framework based on Approximate Bayesian Computation to address these concerns and use this flexible framework to fit a broad class of phenotypic fitness models (including Fisher's model) to 26 empirical landscapes representing nine diverse biological systems. Despite uncertainty owing to the small size of most published empirical landscapes, the inferred landscapes have similar structure in similar biological systems. Surprisingly, goodness-of-fit tests reveal that this class of phenotypic models, which has been successful so far in interpreting experimental data, is a plausible in only three of nine biological systems. More precisely, although Fisher's model was able to explain several statistical properties of the landscapes-including the mean and SD of selection and epistasis coefficients-it was often unable to explain the full structure of fitness landscapes.

  2. Modeling the value of strategic actions in the superior colliculus

    Directory of Open Access Journals (Sweden)

    Dhushan Thevarajah

    2010-02-01

    Full Text Available In learning models of strategic game play, an agent constructs a valuation (action value over possible future choices as a function of past actions and rewards. Choices are then stochastic functions of these action values. Our goal is to uncover a neural signal that correlates with the action value posited by behavioral learning models. We measured activity from neurons in the superior colliculus (SC, a midbrain region involved in planning saccadic eye movements, in monkeys while they performed two saccade tasks. In the strategic task, monkeys competed against a computer in a saccade version of the mixed-strategy game “matching-pennies”. In the instructed task, stochastic saccades were elicited through explicit instruction rather than free choices. In both tasks, neuronal activity and behavior were shaped by past actions and rewards with more recent events exerting a larger influence. Further, SC activity predicted upcoming choices during the strategic task and upcoming reaction times during the instructed task. Finally, we found that neuronal activity in both tasks correlated with an established learning model, the Experience Weighted Attraction model of action valuation (Ho, Camerer, and Chong, 2007. Collectively, our results provide evidence that action values hypothesized by learning models are represented in the motor planning regions of the brain in a manner that could be used to select strategic actions.

  3. Curve fitting methods for solar radiation data modeling

    Energy Technology Data Exchange (ETDEWEB)

    Karim, Samsul Ariffin Abdul, E-mail: samsul-ariffin@petronas.com.my, E-mail: balbir@petronas.com.my; Singh, Balbir Singh Mahinder, E-mail: samsul-ariffin@petronas.com.my, E-mail: balbir@petronas.com.my [Department of Fundamental and Applied Sciences, Faculty of Sciences and Information Technology, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak Darul Ridzuan (Malaysia)

    2014-10-24

    This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R{sup 2}. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods.

  4. Curve fitting methods for solar radiation data modeling

    Science.gov (United States)

    Karim, Samsul Ariffin Abdul; Singh, Balbir Singh Mahinder

    2014-10-01

    This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R2. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods.

  5. A Comparison of Item Fit Statistics for Mixed IRT Models

    Science.gov (United States)

    Chon, Kyong Hee; Lee, Won-Chan; Dunbar, Stephen B.

    2010-01-01

    In this study we examined procedures for assessing model-data fit of item response theory (IRT) models for mixed format data. The model fit indices used in this study include PARSCALE's G[superscript 2], Orlando and Thissen's S-X[superscript 2] and S-G[superscript 2], and Stone's chi[superscript 2*] and G[superscript 2*]. To investigate the…

  6. Hyper-Fit: Fitting Linear Models to Multidimensional Data with Multivariate Gaussian Uncertainties

    CERN Document Server

    Robotham, A S G

    2015-01-01

    Astronomical data is often uncertain with errors that are heteroscedastic (different for each data point) and covariant between different dimensions. Assuming that a set of D-dimensional data points can be described by a (D - 1)-dimensional plane with intrinsic scatter, we derive the general likelihood function to be maximised to recover the best fitting model. Alongside the mathematical description, we also release the hyper-fit package for the R statistical language (github.com/asgr/hyper.fit) and a user-friendly web interface for online fitting (hyperfit.icrar.org). The hyper-fit package offers access to a large number of fitting routines, includes visualisation tools, and is fully documented in an extensive user manual. Most of the hyper-fit functionality is accessible via the web interface. In this paper we include applications to toy examples and to real astronomical data from the literature: the mass-size, Tully-Fisher, Fundamental Plane, and mass-spin-morphology relations. In most cases the hyper-fit ...

  7. Automated Model Fit Method for Diesel Engine Control Development

    NARCIS (Netherlands)

    Seykens, X.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.

    2014-01-01

    This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is consider

  8. Model-Free CUSUM Methods for Person Fit

    Science.gov (United States)

    Armstrong, Ronald D.; Shi, Min

    2009-01-01

    This article demonstrates the use of a new class of model-free cumulative sum (CUSUM) statistics to detect person fit given the responses to a linear test. The fundamental statistic being accumulated is the likelihood ratio of two probabilities. The detection performance of this CUSUM scheme is compared to other model-free person-fit statistics…

  9. Automated Model Fit Method for Diesel Engine Control Development

    NARCIS (Netherlands)

    Seykens, X.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.

    2014-01-01

    This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is

  10. A fitness screening model for increasing fitness assessment and research experiences in undergraduate exercise science students.

    Science.gov (United States)

    Brown, Gregory A; Lynott, Frank; Heelan, Kate A

    2008-09-01

    When students analyze and present original data they have collected, and hence have a cultivated sense of curiosity about the data, student learning is enhanced. It is often difficult to provide students an opportunity to practice their skills, use their knowledge, and gain research experiences during a typical course laboratory. This article describes a model of an out-of-classroom experience during which undergraduate exercise science students provide a free health and fitness screening to the campus community. Although some evidence of the effectiveness of this experience is presented, this is not a detailed evaluation of either the service or learning benefits of the fitness screening. Working in small learning groups in the classroom, students develop hypotheses about the health and fitness of the population to be screened. Then, as part of the health and fitness screening, participants are evaluated for muscular strength, aerobic fitness, body composition, blood pressure, physical activity, and blood cholesterol levels. Students then analyze the data collected during the screening, accept or reject their hypotheses based on statistical analyses of the data, and make in-class presentations of their findings. This learning experience has been used successfully to illustrate the levels of obesity, hypercholesterolemia, and lack of physical fitness in the campus community as well as provide an opportunity for students to use statistical procedures to analyze data. It has also provided students with an opportunity to practice fitness assessment and interpersonal skills that will enhance their future careers.

  11. topicmodels: An R Package for Fitting Topic Models

    Directory of Open Access Journals (Sweden)

    Bettina Grun

    2011-05-01

    Full Text Available Topic models allow the probabilistic modeling of term frequency occurrences in documents. The fitted model can be used to estimate the similarity between documents as well as between a set of specified keywords using an additional layer of latent variables which are referred to as topics. The R package topicmodels provides basic infrastructure for fitting topic models based on data structures from the text mining package tm. The package includes interfaces to two algorithms for fitting topic models: the variational expectation-maximization algorithm provided by David M. Blei and co-authors and an algorithm using Gibbs sampling by Xuan-Hieu Phan and co-authors.

  12. An R package for fitting age, period and cohort models

    Directory of Open Access Journals (Sweden)

    Adriano Decarli

    2014-11-01

    Full Text Available In this paper we present the R implementation of a GLIM macro which fits age-period-cohort model following Osmond and Gardner. In addition to the estimates of the corresponding model, owing to the programming capability of R as an object oriented language, methods for printing, plotting and summarizing the results are provided. Furthermore, the researcher has fully access to the output of the main function (apc which returns all the models fitted within the function. It is so possible to critically evaluate the goodness of fit of the resulting model.

  13. Robust discriminative response map fitting with constrained local models

    NARCIS (Netherlands)

    Asthana, Akshay; Zafeiriou, Stefanos; Cheng, Shiyang; Pantic, Maja

    2013-01-01

    We present a novel discriminative regression based approach for the Constrained Local Models (CLMs) framework, referred to as the Discriminative Response Map Fitting (DRMF) method, which shows impressive performance in the generic face fitting scenario. The motivation behind this approach is that, u

  14. Bayesian item fit analysis for unidimensional item response theory models.

    Science.gov (United States)

    Sinharay, Sandip

    2006-11-01

    Assessing item fit for unidimensional item response theory models for dichotomous items has always been an issue of enormous interest, but there exists no unanimously agreed item fit diagnostic for these models, and hence there is room for further investigation of the area. This paper employs the posterior predictive model-checking method, a popular Bayesian model-checking tool, to examine item fit for the above-mentioned models. An item fit plot, comparing the observed and predicted proportion-correct scores of examinees with different raw scores, is suggested. This paper also suggests how to obtain posterior predictive p-values (which are natural Bayesian p-values) for the item fit statistics of Orlando and Thissen that summarize numerically the information in the above-mentioned item fit plots. A number of simulation studies and a real data application demonstrate the effectiveness of the suggested item fit diagnostics. The suggested techniques seem to have adequate power and reasonable Type I error rate, and psychometricians will find them promising.

  15. Improved fitting of solution X-ray scattering data to macromolecular structures and structural ensembles by explicit water modeling.

    Science.gov (United States)

    Grishaev, Alexander; Guo, Liang; Irving, Thomas; Bax, Ad

    2010-11-10

    A new procedure, AXES, is introduced for fitting small-angle X-ray scattering (SAXS) data to macromolecular structures and ensembles of structures. By using explicit water models to account for the effect of solvent, and by restricting the adjustable fitting parameters to those that dominate experimental uncertainties, including sample/buffer rescaling, detector dark current, and, within a narrow range, hydration layer density, superior fits between experimental high resolution structures and SAXS data are obtained. AXES results are found to be more discriminating than standard Crysol fitting of SAXS data when evaluating poorly or incorrectly modeled protein structures. AXES results for ensembles of structures previously generated for ubiquitin show improved fits over fitting of the individual members of these ensembles, indicating these ensembles capture the dynamic behavior of proteins in solution.

  16. How Good Are Statistical Models at Approximating Complex Fitness Landscapes?

    Science.gov (United States)

    du Plessis, Louis; Leventhal, Gabriel E.; Bonhoeffer, Sebastian

    2016-01-01

    Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations. PMID:27189564

  17. How Good Are Statistical Models at Approximating Complex Fitness Landscapes?

    Science.gov (United States)

    du Plessis, Louis; Leventhal, Gabriel E; Bonhoeffer, Sebastian

    2016-09-01

    Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations.

  18. Fitting polytomous Rasch models in SAS

    DEFF Research Database (Denmark)

    Christensen, Karl Bang

    2006-01-01

    The item parameters of a polytomous Rasch model can be estimated using marginal and conditional approaches. This paper describes how this can be done in SAS (V8.2) for three item parameter estimation procedures: marginal maximum likelihood estimation, conditional maximum likelihood estimation......, and pairwise conditional estimation. The use of the procedures for extensions of the Rasch model is also discussed. The accuracy of the methods are evaluated using a simulation study....

  19. FITTING PHOTOIONIZATION MODELS TO PLANETARY NEBULAE

    Directory of Open Access Journals (Sweden)

    J. Bohigas

    2009-01-01

    Full Text Available Good to excellent photoionization models based on the Cloudy code were obtained for 13 out of 19 spectra of planetary nebulae. The two most important assumptions are that the photoionizing continuum is a Rauch model star, with gravity set by the condition that the stellar mass must be 1 M , and density is constant and determined from the observed [S II]6717/6731 ratio. The temperature and luminosity of the central star, the inner radius of the nebula and the abundance of carbon are treated as free parameters in each model run, destined to obtain the best possible t to the relative intensities of He II 4686, [O III]5007 and [N II]6584. Observed and modeled nebular temperatures derived from [N II] (6548+6584 /5755 agree within 10%, but models usually underestimate temperatures found from [O III] (4959+5007 /4363, more so when the slit does not cover the in-depth extent of the ionized region. Helium, nitrogen, oxygen, neon, sulfur and argon model abundances are uncertain at the 15%, 15%, 10%, 7%, 30% and 7% level. It is shown that neon abundance in PNe has been consistently overestimated, and an alternative ionization correction factor is recommended.

  20. An Algorithm for Optimally Fitting a Wiener Model

    Directory of Open Access Journals (Sweden)

    Lucas P. Beverlin

    2011-01-01

    Full Text Available The purpose of this work is to present a new methodology for fitting Wiener networks to datasets with a large number of variables. Wiener networks have the ability to model a wide range of data types, and their structures can yield parameters with phenomenological meaning. There are several challenges to fitting such a model: model stiffness, the nonlinear nature of a Wiener network, possible overfitting, and the large number of parameters inherent with large input sets. This work describes a methodology to overcome these challenges by using several iterative algorithms under supervised learning and fitting subsets of the parameters at a time. This methodology is applied to Wiener networks that are used to predict blood glucose concentrations. The predictions of validation sets from models fit to four subjects using this methodology yielded a higher correlation between observed and predicted observations than other algorithms, including the Gauss-Newton and Levenberg-Marquardt algorithms.

  1. Predictive models for population performance on real biological fitness landscapes.

    Science.gov (United States)

    Rowe, William; Wedge, David C; Platt, Mark; Kell, Douglas B; Knowles, Joshua

    2010-09-01

    Directed evolution, in addition to its principal application of obtaining novel biomolecules, offers significant potential as a vehicle for obtaining useful information about the topologies of biomolecular fitness landscapes. In this article, we make use of a special type of model of fitness landscapes-based on finite state machines-which can be inferred from directed evolution experiments. Importantly, the model is constructed only from the fitness data and phylogeny, not sequence or structural information, which is often absent. The model, called a landscape state machine (LSM), has already been used successfully in the evolutionary computation literature to model the landscapes of artificial optimization problems. Here, we use the method for the first time to simulate a biological fitness landscape based on experimental evaluation. We demonstrate in this study that LSMs are capable not only of representing the structure of model fitness landscapes such as NK-landscapes, but also the fitness landscape of real DNA oligomers binding to a protein (allophycocyanin), data we derived from experimental evaluations on microarrays. The LSMs prove adept at modelling the progress of evolution as a function of various controlling parameters, as validated by evaluations on the real landscapes. Specifically, the ability of the model to 'predict' optimal mutation rates and other parameters of the evolution is demonstrated. A modification to the standard LSM also proves accurate at predicting the effects of recombination on the evolution.

  2. Relative and Absolute Fit Evaluation in Cognitive Diagnosis Modeling

    Science.gov (United States)

    Chen, Jinsong; de la Torre, Jimmy; Zhang, Zao

    2013-01-01

    As with any psychometric models, the validity of inferences from cognitive diagnosis models (CDMs) determines the extent to which these models can be useful. For inferences from CDMs to be valid, it is crucial that the fit of the model to the data is ascertained. Based on a simulation study, this study investigated the sensitivity of various fit…

  3. Fitting ARMA Time Series by Structural Equation Models.

    Science.gov (United States)

    van Buuren, Stef

    1997-01-01

    This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)

  4. Critical elements on fitting the Bayesian multivariate Poisson Lognormal model

    Science.gov (United States)

    Zamzuri, Zamira Hasanah binti

    2015-10-01

    Motivated by a problem on fitting multivariate models to traffic accident data, a detailed discussion of the Multivariate Poisson Lognormal (MPL) model is presented. This paper reveals three critical elements on fitting the MPL model: the setting of initial estimates, hyperparameters and tuning parameters. These issues have not been highlighted in the literature. Based on simulation studies conducted, we have shown that to use the Univariate Poisson Model (UPM) estimates as starting values, at least 20,000 iterations are needed to obtain reliable final estimates. We also illustrated the sensitivity of the specific hyperparameter, which if it is not given extra attention, may affect the final estimates. The last issue is regarding the tuning parameters where they depend on the acceptance rate. Finally, a heuristic algorithm to fit the MPL model is presented. This acts as a guide to ensure that the model works satisfactorily given any data set.

  5. Automatic fitting of spiking neuron models to electrophysiological recordings

    Directory of Open Access Journals (Sweden)

    Cyrille Rossant

    2010-03-01

    Full Text Available Spiking models can accurately predict the spike trains produced by cortical neurons in response to somatically injected currents. Since the specific characteristics of the model depend on the neuron, a computational method is required to fit models to electrophysiological recordings. The fitting procedure can be very time consuming both in terms of computer simulations and in terms of code writing. We present algorithms to fit spiking models to electrophysiological data (time-varying input and spike trains that can run in parallel on graphics processing units (GPUs. The model fitting library is interfaced with Brian, a neural network simulator in Python. If a GPU is present it uses just-in-time compilation to translate model equations into optimized code. Arbitrary models can then be defined at script level and run on the graphics card. This tool can be used to obtain empirically validated spiking models of neurons in various systems. We demonstrate its use on public data from the INCF Quantitative Single-Neuron Modeling 2009 competition by comparing the performance of a number of neuron spiking models.

  6. HDFITS: porting the FITS data model to HDF5

    CERN Document Server

    Price, D C; Greenhill, L J

    2015-01-01

    The FITS (Flexible Image Transport System) data format has been the de facto data format for astronomy-related data products since its inception in the late 1970s. While the FITS file format is widely supported, it lacks many of the features of more modern data serialization, such as the Hierarchical Data Format (HDF5). The HDF5 file format offers considerable advantages over FITS, such as improved I/O speed and compression, but has yet to gain widespread adoption within astronomy. One of the major holdbacks is that HDF5 is not well supported by data reduction software packages and image viewers. Here, we present a comparison of FITS and HDF5 as a format for storage of astronomy datasets. We show that the underlying data model of FITS can be ported to HDF5 in a straightforward manner, and that by doing so the advantages of the HDF5 file format can be leveraged immediately. In addition, we present a software tool, fits2hdf, for converting between FITS and a new `HDFITS' format, where data are stored in HDF5 in...

  7. Fitting Equilibrium Search Models to Labour Market Data

    DEFF Research Database (Denmark)

    Bowlus, Audra J.; Kiefer, Nicholas M.; Neumann, George R.

    1996-01-01

    Specification and estimation of a Burdett-Mortensen type equilibrium search model is considered. The estimation is nonstandard. An estimation strategy asymptotically equivalent to maximum likelihood is proposed and applied. The results indicate that specifications with a small number of productiv...... of productivity types fit the data well compared to the homogeneous model....

  8. Curve Fitting And Interpolation Model Applied In Nonel Dosage Detection

    Directory of Open Access Journals (Sweden)

    Jiuling Li

    2013-06-01

    Full Text Available The Curve Fitting and Interpolation Model are applied in Nonel dosage detection in this paper firstly, and the gray of continuous explosive in the Nonel has been forecasted. Although the traditional infrared equipment establishes the relationship of explosive dosage and light intensity, but the forecast accuracy is very low. Therefore, gray prediction models based on curve fitting and interpolation are framed separately, and the deviations from the different models are compared. Simultaneously, combining on the sample library features, the cubic polynomial fitting curve of the higher precision is used to predict grays, and 5mg-28mg Nonel gray values are calculated by MATLAB. Through the predictive values, the dosage detection operations are simplified, and the defect missing rate of the Nonel are reduced. Finally, the quality of Nonel is improved.

  9. Optimisation of Ionic Models to Fit Tissue Action Potentials: Application to 3D Atrial Modelling

    Directory of Open Access Journals (Sweden)

    Amr Al Abed

    2013-01-01

    Full Text Available A 3D model of atrial electrical activity has been developed with spatially heterogeneous electrophysiological properties. The atrial geometry, reconstructed from the male Visible Human dataset, included gross anatomical features such as the central and peripheral sinoatrial node (SAN, intra-atrial connections, pulmonary veins, inferior and superior vena cava, and the coronary sinus. Membrane potentials of myocytes from spontaneously active or electrically paced in vitro rabbit cardiac tissue preparations were recorded using intracellular glass microelectrodes. Action potentials of central and peripheral SAN, right and left atrial, and pulmonary vein myocytes were each fitted using a generic ionic model having three phenomenological ionic current components: one time-dependent inward, one time-dependent outward, and one leakage current. To bridge the gap between the single-cell ionic models and the gross electrical behaviour of the 3D whole-atrial model, a simplified 2D tissue disc with heterogeneous regions was optimised to arrive at parameters for each cell type under electrotonic load. Parameters were then incorporated into the 3D atrial model, which as a result exhibited a spontaneously active SAN able to rhythmically excite the atria. The tissue-based optimisation of ionic models and the modelling process outlined are generic and applicable to image-based computer reconstruction and simulation of excitable tissue.

  10. Effects of Sample Size, Estimation Methods, and Model Specification on Structural Equation Modeling Fit Indexes.

    Science.gov (United States)

    Fan, Xitao; Wang, Lin; Thompson, Bruce

    1999-01-01

    A Monte Carlo simulation study investigated the effects on 10 structural equation modeling fit indexes of sample size, estimation method, and model specification. Some fit indexes did not appear to be comparable, and it was apparent that estimation method strongly influenced almost all fit indexes examined, especially for misspecified models. (SLD)

  11. Time-domain fitting of battery electrochemical impedance models

    Science.gov (United States)

    Alavi, S. M. M.; Birkl, C. R.; Howey, D. A.

    2015-08-01

    Electrochemical impedance spectroscopy (EIS) is an effective technique for diagnosing the behaviour of electrochemical devices such as batteries and fuel cells, usually by fitting data to an equivalent circuit model (ECM). The common approach in the laboratory is to measure the impedance spectrum of a cell in the frequency domain using a single sine sweep signal, then fit the ECM parameters in the frequency domain. This paper focuses instead on estimation of the ECM parameters directly from time-domain data. This may be advantageous for parameter estimation in practical applications such as automotive systems including battery-powered vehicles, where the data may be heavily corrupted by noise. The proposed methodology is based on the simplified refined instrumental variable for continuous-time fractional systems method ('srivcf'), provided by the Crone toolbox [1,2], combined with gradient-based optimisation to estimate the order of the fractional term in the ECM. The approach was tested first on synthetic data and then on real data measured from a 26650 lithium-ion iron phosphate cell with low-cost equipment. The resulting Nyquist plots from the time-domain fitted models match the impedance spectrum closely (much more accurately than when a Randles model is assumed), and the fitted parameters as separately determined through a laboratory potentiostat with frequency domain fitting match to within 13%.

  12. Kompaneets Model Fitting of the Orion-Eridanus Superbubble

    CERN Document Server

    Pon, Andy; Bally, John; Heiles, Carl

    2014-01-01

    Winds and supernovae from OB associations create large cavities in the interstellar medium referred to as superbubbles. The Orion molecular clouds are the nearest high mass star-forming region and have created a highly elongated, 20 degree x 45 degree, superbubble. We fit Kompaneets models to the Orion-Eridanus superbubble and find that a model where the Eridanus side of the superbubble is oriented away from the Sun provides a marginal fit. Because this model requires an unusually small scale height of 40 pc and has the superbubble inclined 35 degrees from the normal to the Galactic plane, we propose that this model should be treated as a general framework for modeling the Orion-Eridanus superbubble, with a secondary physical mechanism not included in the Kompaneets model required to fully account for the orientation and elongation of the superbubble.

  13. Ongoing Processes in a Fitness Network Model under Restricted Resources.

    Directory of Open Access Journals (Sweden)

    Takayuki Niizato

    Full Text Available In real networks, the resources that make up the nodes and edges are finite. This constraint poses a serious problem for network modeling, namely, the compatibility between robustness and efficiency. However, these concepts are generally in conflict with each other. In this study, we propose a new fitness-driven network model for finite resources. In our model, each individual has its own fitness, which it tries to increase. The main assumption in fitness-driven networks is that incomplete estimation of fitness results in a dynamical growing network. By taking into account these internal dynamics, nodes and edges emerge as a result of exchanges between finite resources. We show that our network model exhibits exponential distributions in the in- and out-degree distributions and a power law distribution of edge weights. Furthermore, our network model resolves the trade-off relationship between robustness and efficiency. Our result suggests that growing and anti-growing networks are the result of resolving the trade-off problem itself.

  14. [How to fit and interpret multilevel models using SPSS].

    Science.gov (United States)

    Pardo, Antonio; Ruiz, Miguel A; San Martín, Rafael

    2007-05-01

    Hierarchic or multilevel models are used to analyse data when cases belong to known groups and sample units are selected both from the individual level and from the group level. In this work, the multilevel models most commonly discussed in the statistic literature are described, explaining how to fit these models using the SPSS program (any version as of the 11 th ) and how to interpret the outcomes of the analysis. Five particular models are described, fitted, and interpreted: (1) one-way analysis of variance with random effects, (2) regression analysis with means-as-outcomes, (3) one-way analysis of covariance with random effects, (4) regression analysis with random coefficients, and (5) regression analysis with means- and slopes-as-outcomes. All models are explained, trying to make them understandable to researchers in health and behaviour sciences.

  15. A neutrino model fit to the CMB power spectrum

    Science.gov (United States)

    Shanks, T.; Johnson, R. W. F.; Schewtschenko, J. A.; Whitbourn, J. R.

    2014-12-01

    The standard cosmological model, Λ cold dark matter (ΛCDM), provides an excellent fit to cosmic microwave background (CMB) data. However, the model has well-known problems. For example, the cosmological constant, Λ, is fine-tuned to 1 part in 10100 and the CDM particle is not yet detected in the laboratory. Shanks previously investigated a model which assumed neither exotic particles nor a cosmological constant but instead postulated a low Hubble constant (H0) to allow a baryon density compatible with inflation and zero spatial curvature. However, recent Planck results make it more difficult to reconcile such a model with CMB power spectra. Here, we relax the previous assumptions to assess the effects of assuming three active neutrinos of mass ≈5 eV. If we assume a low H0 ≈ 45 km s-1 Mpc-1 then, compared to the previous purely baryonic model, we find a significantly improved fit to the first three peaks of the Planck power spectrum. Nevertheless, the goodness of fit is still significantly worse than for ΛCDM and would require appeal to unknown systematic effects for the fit ever to be considered acceptable. A further serious problem is that the amplitude of fluctuations is low (σ8 ≈ 0.2), making it difficult to form galaxies by the present day. This might then require seeds, perhaps from a primordial magnetic field, to be invoked for galaxy formation. These and other problems demonstrate the difficulties faced by models other than ΛCDM in fitting ever more precise cosmological data.

  16. Fuzzy Partition Models for Fitting a Set of Partitions.

    Science.gov (United States)

    Gordon, A. D.; Vichi, M.

    2001-01-01

    Describes methods for fitting a fuzzy consensus partition to a set of partitions of the same set of objects. Describes and illustrates three models defining median partitions and compares these methods to an alternative approach to obtaining a consensus fuzzy partition. Discusses interesting differences in the results. (SLD)

  17. Assessing fit in Bayesian models for spatial processes

    KAUST Repository

    Jun, M.

    2014-09-16

    © 2014 John Wiley & Sons, Ltd. Gaussian random fields are frequently used to model spatial and spatial-temporal data, particularly in geostatistical settings. As much of the attention of the statistics community has been focused on defining and estimating the mean and covariance functions of these processes, little effort has been devoted to developing goodness-of-fit tests to allow users to assess the models\\' adequacy. We describe a general goodness-of-fit test and related graphical diagnostics for assessing the fit of Bayesian Gaussian process models using pivotal discrepancy measures. Our method is applicable for both regularly and irregularly spaced observation locations on planar and spherical domains. The essential idea behind our method is to evaluate pivotal quantities defined for a realization of a Gaussian random field at parameter values drawn from the posterior distribution. Because the nominal distribution of the resulting pivotal discrepancy measures is known, it is possible to quantitatively assess model fit directly from the output of Markov chain Monte Carlo algorithms used to sample from the posterior distribution on the parameter space. We illustrate our method in a simulation study and in two applications.

  18. The Gold Medal Fitness Program: A Model for Teacher Change

    Science.gov (United States)

    Wright, Jan; Konza, Deslea; Hearne, Doug; Okely, Tony

    2008-01-01

    Background: Following the 2000 Sydney Olympics, the NSW Premier, Mr Bob Carr, launched a school-based initiative in NSW government primary schools called the "Gold Medal Fitness Program" to encourage children to be fitter and more active. The Program was introduced into schools through a model of professional development, "Quality…

  19. Application of modified vector fitting to grounding system modeling

    Energy Technology Data Exchange (ETDEWEB)

    Jimenez, D.; Camargo, M.; Herrera, J.; Torres, H. [National University of Colombia (Colombia). Research Program on Acquisition and Analysis of Signals - PAAS], Emails: dyjimeneza@unal.edu.co, mpcamargom@unal.edu.co; Vargas, M. [Siemens S.A. - Power Transmission and Distribution - Energy Services (Colombia)

    2007-07-01

    The transient behavior of grounding systems (GS) influences greatly the performance of electrical networks under fault conditions. This fact has led the authors to present an application of the Modified Vector Fitting (MVF)1 methodology based upon the frequency response of the system, in order to find a rational function approximation and an equivalent electrical network whose transient behavior is similar to the original one of the GS. The obtained network can be introduced into the EMTP/ATP program for simulating the transient behavior of the GS. The MVF technique, which is a modification of the Vector Fitting (VF) technique, allows identifying state space models from the Frequency Domain Response for both single and multiple input-output systems. In this work, the methodology is used to fit the frequency response of a grounding grid, which is computed by means of the Hybrid Electromagnetic Model (HEM), finding the relation between voltages and input currents in two points of the grid in frequency domain. The model obtained with the MVF shows a good agreement with the frequency response of the GS. Besides, the model is tested in EMTP/ATP finding a good fitting with the calculated data, which demonstrates the validity and usefulness of the MVF. (author)

  20. Raindrop size distribution: Fitting performance of common theoretical models

    Science.gov (United States)

    Adirosi, E.; Volpi, E.; Lombardo, F.; Baldini, L.

    2016-10-01

    Modelling raindrop size distribution (DSD) is a fundamental issue to connect remote sensing observations with reliable precipitation products for hydrological applications. To date, various standard probability distributions have been proposed to build DSD models. Relevant questions to ask indeed are how often and how good such models fit empirical data, given that the advances in both data availability and technology used to estimate DSDs have allowed many of the deficiencies of early analyses to be mitigated. Therefore, we present a comprehensive follow-up of a previous study on the comparison of statistical fitting of three common DSD models against 2D-Video Distrometer (2DVD) data, which are unique in that the size of individual drops is determined accurately. By maximum likelihood method, we fit models based on lognormal, gamma and Weibull distributions to more than 42.000 1-minute drop-by-drop data taken from the field campaigns of the NASA Ground Validation program of the Global Precipitation Measurement (GPM) mission. In order to check the adequacy between the models and the measured data, we investigate the goodness of fit of each distribution using the Kolmogorov-Smirnov test. Then, we apply a specific model selection technique to evaluate the relative quality of each model. Results show that the gamma distribution has the lowest KS rejection rate, while the Weibull distribution is the most frequently rejected. Ranking for each minute the statistical models that pass the KS test, it can be argued that the probability distributions whose tails are exponentially bounded, i.e. light-tailed distributions, seem to be adequate to model the natural variability of DSDs. However, in line with our previous study, we also found that frequency distributions of empirical DSDs could be heavy-tailed in a number of cases, which may result in severe uncertainty in estimating statistical moments and bulk variables.

  1. Superior accuracy of model-based radiostereometric analysis for measurement of polyethylene wear

    DEFF Research Database (Denmark)

    Stilling, M; Kold, S; de Raedt, S

    2012-01-01

    The accuracy and precision of two new methods of model-based radiostereometric analysis (RSA) were hypothesised to be superior to a plain radiograph method in the assessment of polyethylene (PE) wear.......The accuracy and precision of two new methods of model-based radiostereometric analysis (RSA) were hypothesised to be superior to a plain radiograph method in the assessment of polyethylene (PE) wear....

  2. MNP: R Package for Fitting the Multinomial Probit Model

    Directory of Open Access Journals (Sweden)

    Kosuke Imai

    2005-05-01

    Full Text Available MNP is a publicly available R package that fits the Bayesian multinomial probit model via Markov chain Monte Carlo. The multinomial probit model is often used to analyze the discrete choices made by individuals recorded in survey data. Examples where the multinomial probit model may be useful include the analysis of product choice by consumers in market research and the analysis of candidate or party choice by voters in electoral studies. The MNP software can also fit the model with different choice sets for each individual, and complete or partial individual choice orderings of the available alternatives from the choice set. The estimation is based on the efficient marginal data augmentation algorithm that is developed by Imai and van Dyk (2005.

  3. Survival model construction guided by fit and predictive strength.

    Science.gov (United States)

    Chauvel, Cécile; O'Quigley, John

    2016-10-05

    Survival model construction can be guided by goodness-of-fit techniques as well as measures of predictive strength. Here, we aim to bring together these distinct techniques within the context of a single framework. The goal is how to best characterize and code the effects of the variables, in particular time dependencies, when taken either singly or in combination with other related covariates. Simple graphical techniques can provide an immediate visual indication as to the goodness-of-fit but, in cases of departure from model assumptions, will point in the direction of a more involved and richer alternative model. These techniques appear to be intuitive. This intuition is backed up by formal theorems that underlie the process of building richer models from simpler ones. Measures of predictive strength are used in conjunction with these goodness-of-fit techniques and, again, formal theorems show that these measures can be used to help identify models closest to the unknown non-proportional hazards mechanism that we can suppose generates the observations. Illustrations from studies in breast cancer show how these tools can be of help in guiding the practical problem of efficient model construction for survival data.

  4. Supersymmetry with prejudice: Fitting the wrong model to LHC data

    Science.gov (United States)

    Allanach, B. C.; Dolan, Matthew J.

    2012-09-01

    We critically examine interpretations of hypothetical supersymmetric LHC signals, fitting to alternative wrong models of supersymmetry breaking. The signals we consider are some of the most constraining on the sparticle spectrum: invariant mass distributions with edges and endpoints from the golden decay chain q˜→qχ20(→l˜±l∓q)→χ10l+l-q. We assume a constrained minimal supersymmetric standard model (CMSSM) point to be the ‘correct’ one, but fit the signals instead with minimal gauge mediated supersymmetry breaking models (mGMSB) with a neutralino quasistable lightest supersymmetric particle, minimal anomaly mediation and large volume string compactification models. Minimal anomaly mediation and large volume scenario can be unambiguously discriminated against the CMSSM for the assumed signal and 1fb-1 of LHC data at s=14TeV. However, mGMSB would not be discriminated on the basis of the kinematic endpoints alone. The best-fit point spectra of mGMSB and CMSSM look remarkably similar, making experimental discrimination at the LHC based on the edges or Higgs properties difficult. However, using rate information for the golden chain should provide the additional separation required.

  5. Double-sigmoid model for fitting fatigue profiles in mouse fast- and slow-twitch muscle.

    Science.gov (United States)

    Cairns, S P; Robinson, D M; Loiselle, D S

    2008-07-01

    We present a curve-fitting approach that permits quantitative comparisons of fatigue profiles obtained with different stimulation protocols in isolated slow-twitch soleus and fast-twitch extensor digitorum longus (EDL) muscles of mice. Profiles from our usual stimulation protocol (125 Hz for 500 ms, evoked once every second for 100-300 s) could be fitted by single-term functions (sigmoids or exponentials) but not by a double exponential. A clearly superior fit, as confirmed by the Akaiki Information Criterion, was achieved using a double-sigmoid function. Fitting accuracy was exceptional; mean square errors were typically 0.9995. The first sigmoid (early fatigue) involved approximately 10% decline of isometric force to an intermediate plateau in both muscle types; the second sigmoid (late fatigue) involved a reduction of force to a final plateau, the decline being 83% of initial force in EDL and 63% of initial force in soleus. The maximal slope of each sigmoid was seven- to eightfold greater in EDL than in soleus. The general applicability of the model was tested by fitting profiles with a severe force loss arising from repeated tetanic stimulation evoked at different frequencies or rest periods, or with excitation via nerve terminals in soleus. Late fatigue, which was absent at 30 Hz, occurred earlier and to a greater extent at 125 than 50 Hz. The model captured small changes in rate of late fatigue for nerve terminal versus sarcolemmal stimulation. We conclude that a double-sigmoid expression is a useful and accurate model to characterize fatigue in isolated muscle preparations.

  6. Fitting and Comparison of Models of Radio Spectra

    CERN Document Server

    Nikolic, Bojan

    2009-01-01

    I describe an approach to fitting and comparison of radio spectra based on Bayesian analysis and realised using a new implementation of the nested sampling algorithm. Such an approach improves on the commonly used maximum-likelihood fitting of radio spectra by allowing objective model selection, calculation of the full probability distributions of the model parameters and provides a natural mechanism for including information other than the measured spectra through priors. In this paper I cover the theoretical background, the algorithms used and the implementation details of the computer code. I also briefly illustrate the method with some previously published data for three near-by galaxies. In forthcoming papers we will present the results of applying this analysis larger data sets, including some new observations, and the physical conclusions that can be made. The computer code as well as the overall approach described here may also be useful for analysis of other multi-chromatic broad-band observations an...

  7. Geometrical model fitting for interferometric data: GEM-FIND

    CERN Document Server

    Klotz, D; Paladini, C; Hron, J; Wachter, G

    2012-01-01

    We developed the tool GEM-FIND that allows to constrain the morphology and brightness distribution of objects. The software fits geometrical models to spectrally dispersed interferometric visibility measurements in the N-band using the Levenberg-Marquardt minimization method. Each geometrical model describes the brightness distribution of the object in the Fourier space using a set of wavelength-independent and/or wavelength-dependent parameters. In this contribution we numerically analyze the stability of our nonlinear fitting approach by applying it to sets of synthetic visibilities with statistically applied errors, answering the following questions: How stable is the parameter determination with respect to (i) the number of uv-points, (ii) the distribution of points in the uv-plane, (iii) the noise level of the observations?

  8. Atmospheric Turbulence Modeling for Aerospace Vehicles: Fractional Order Fit

    Science.gov (United States)

    Kopasakis, George (Inventor)

    2015-01-01

    An improved model for simulating atmospheric disturbances is disclosed. A scale Kolmogorov spectral may be scaled to convert the Kolmogorov spectral into a finite energy von Karman spectral and a fractional order pole-zero transfer function (TF) may be derived from the von Karman spectral. Fractional order atmospheric turbulence may be approximated with an integer order pole-zero TF fit, and the approximation may be stored in memory.

  9. The Meaning of Goodness-of-Fit Tests: Commentary on "Goodness-of-Fit Assessment of Item Response Theory Models"

    Science.gov (United States)

    Thissen, David

    2013-01-01

    In this commentary, David Thissen states that "Goodness-of-fit assessment for IRT models is maturing; it has come a long way from zero." Thissen then references prior works on "goodness of fit" in the index of Lord and Novick's (1968) classic text; Yen (1984); Drasgow, Levine, Tsien, Williams, and Mead (1995); Chen and…

  10. Supersymmetry With Prejudice: Fitting the Wrong Model to LHC Data

    CERN Document Server

    Allanach, B C

    2011-01-01

    We critically examine interpretations of hypothetical supersymmetric LHC signals, fitting to alternative wrong models of supersymmetry breaking. The signals we consider are some of the most constraining on the sparticle spectrum: invariant mass distributions with edges and end-points from the golden cascade decay chain \\tilde{q}_L -> q \\chi_2^0 (-> \\tilde{l}^{\\pm} l^{\\mp} q) -> \\chi_1^0 l^+ l^- q. We assume a CMSSM point to be the `correct' one, and fit the signals instead to minimal gauge mediated supersymmetry breaking models (mGMSB) with a neutralino quasi-stable lightest supersymmetric particle, minimal anomaly mediation (mAMSB) and large volume string compactification models (LVS). mAMSB and LVS can be unambiguously discriminated against the CMSSM for the parameter point assumed and 1 inverse femtobarn of LHC data at 14 TeV. However, mGMSB would not be discriminated on the basis of the kinematic end-points alone, and would require further, more detailed investigation. The best-fit points of mGMSB and CMS...

  11. Fitting Additive Binomial Regression Models with the R Package blm

    Directory of Open Access Journals (Sweden)

    Stephanie Kovalchik

    2013-09-01

    Full Text Available The R package blm provides functions for fitting a family of additive regression models to binary data. The included models are the binomial linear model, in which all covariates have additive effects, and the linear-expit (lexpit model, which allows some covariates to have additive effects and other covariates to have logisitc effects. Additive binomial regression is a model of event probability, and the coefficients of linear terms estimate covariate-adjusted risk differences. Thus, in contrast to logistic regression, additive binomial regression puts focus on absolute risk and risk differences. In this paper, we give an overview of the methodology we have developed to fit the binomial linear and lexpit models to binary outcomes from cohort and population-based case-control studies. We illustrate the blm packages methods for additive model estimation, diagnostics, and inference with risk association analyses of a bladder cancer nested case-control study in the NIH-AARP Diet and Health Study.

  12. Bayesian Data-Model Fit Assessment for Structural Equation Modeling

    Science.gov (United States)

    Levy, Roy

    2011-01-01

    Bayesian approaches to modeling are receiving an increasing amount of attention in the areas of model construction and estimation in factor analysis, structural equation modeling (SEM), and related latent variable models. However, model diagnostics and model criticism remain relatively understudied aspects of Bayesian SEM. This article describes…

  13. Fitting rainfall interception models to forest ecosystems of Mexico

    Science.gov (United States)

    Návar, José

    2017-05-01

    Models that accurately predict forest interception are essential both for water balance studies and for assessing watershed responses to changes in land use and the long-term climate variability. This paper compares the performance of four rainfall interception models-the sparse Gash (1995), Rutter et al. (1975), Liu (1997) and two new models (NvMxa and NvMxb)-using data from four spatially extensive, structurally diverse forest ecosystems in Mexico. Ninety-eight case studies measuring interception in tropical dry (25), arid/semi-arid (29), temperate (26), and tropical montane cloud forests (18) were compiled and analyzed. Coefficients derived from raw data or published statistical relationships were used as model input to evaluate multi-storm forest interception at the case study scale. On average empirical data showed that, tropical montane cloud, temperate, arid/semi-arid and tropical dry forests intercepted 14%, 18%, 22% and 26% of total precipitation, respectively. The models performed well in predicting interception, with mean deviations between measured and modeled interception as a function of total precipitation (ME) generally 0.66. Model fitting precision was dependent on the forest ecosystem. Arid/semi-arid forests exhibited the smallest, while tropical montane cloud forest displayed the largest ME deviations. Improved agreement between measured and modeled data requires modification of in-storm evaporation rate in the Liu; the canopy storage in the sparse Gash model; and the throughfall coefficient in the Rutter and the NvMx models. This research concludes on recommending the wide application of rainfall interception models with some caution as they provide mixed results. The extensive forest interception data source, the fitting and testing of four models, the introduction of a new model, and the availability of coefficient values for all four forest ecosystems are an important source of information and a benchmark for future investigations in this

  14. Reproduction of superior sagittal sinus animal model by bypass transplantation of biomaterial graft

    Directory of Open Access Journals (Sweden)

    Qing-yong LUO

    2011-03-01

    Full Text Available Objective To establish the beagles model of superior sagittal sinus bypass graft,and explore the feasibility of reconstruction of superior sagittal sinus with biomaterials using this model.Methods Eight adult male beagles(weight: 12.5-22.0kg were involved in the present study.The superior sagittal sinus was exposed and blocked via bone window,and then anastomosed side-to-end to the biomaterial graft under the dedicated microscope of neurosurgery surgery,expectant treatment such as anti-inflammatory was given for the animals.The digital subtraction venography(DSV and color Doppler flow imaging(CDFI of superior sagittal sinus were performed in 1,2,4 and 8 weeks after the operation.Eight weeks after the operation,all the animals were sacrificed and the material graft was examined histologically.Results The DSV and CDFI of superior sagittal sinus showed that the stomas of 2 beagles were with slight stenosis and high flow velocity,of 1 beagle with small leakage and low flow velocity,while of other 5 beagles were normal.The histological examination showed endothelial cells were growing on the graft and superior sagittal sinus,and crawling toward the lumen of graft 8 weeks after the operation.Conclusion The beagles model of superior sagittal sinus bypass graft was established successfully.The short-term effect of the model was satisfactory,while further work should be performed to determine the long-term effects.

  15. Broadband distortion modeling in Lyman-$\\alpha$ forest BAO fitting

    CERN Document Server

    Blomqvist, Michael; Bautista, Julian E; Ariño, Andreu; Busca, Nicolás G; Miralda-Escudé, Jordi; Slosar, Anže; Font-Ribera, Andreu; Margala, Daniel; Schneider, Donald P; Vazquez, Jose A

    2015-01-01

    In recent years, the Lyman-$\\alpha$ absorption observed in the spectra of high-redshift quasars has been used as a tracer of large-scale structure by means of the three-dimensional Lyman-$\\alpha$ forest auto-correlation function at redshift $z\\simeq 2.3$, but the need to fit the quasar continuum in every absorption spectrum introduces a broadband distortion that is difficult to correct and causes a systematic error for measuring any broadband properties. We describe a $k$-space model for this broadband distortion based on a multiplicative correction to the power spectrum of the transmitted flux fraction that suppresses power on scales corresponding to the typical length of a Lyman-$\\alpha$ forest spectrum. Implementing the distortion model in fits for the baryon acoustic oscillation (BAO) peak position in the Lyman-$\\alpha$ forest auto-correlation, we find that the fitting method recovers the input values of the linear bias parameter $b_{F}$ and the redshift-space distortion parameter $\\beta_{F}$ for mock dat...

  16. Assessing the fit of the Dysphoric Arousal model across two nationally representative epidemiological surveys: The Australian NSMHWB and the United States NESARC

    DEFF Research Database (Denmark)

    Armour, C.; Carragher, N.; Elhai, J. D.

    2013-01-01

    samples. Results revealed that the Dysphoric Arousal model provided superior fit to the data compared to the alternative models. In conclusion, these findings suggest that items D1-D3 (sleeping difficulties; irritability; concentration difficulties) represent a separate, fifth factor within PTSD's latent...

  17. Chempy: A flexible chemical evolution model for abundance fitting

    Science.gov (United States)

    Rybizki, J.; Just, A.; Rix, H.-W.; Fouesneau, M.

    2017-02-01

    Chempy models Galactic chemical evolution (GCE); it is a parametrized open one-zone model within a Bayesian framework. A Chempy model is specified by a set of 5-10 parameters that describe the effective galaxy evolution along with the stellar and star-formation physics: e.g. the star-formation history (SFH), the feedback efficiency, the stellar initial mass function (IMF) and the incidence of supernova of type Ia (SN Ia). Chempy can sample the posterior probability distribution in the full model parameter space and test data-model matches for different nucleosynthetic yield sets, performing essentially as a chemical evolution fitting tool. Chempy can be used to confront predictions from stellar nucleosynthesis with complex abundance data sets and to refine the physical processes governing the chemical evolution of stellar systems.

  18. When the model fits the frame: the impact of regulatory fit on efficacy appraisal and persuasion in health communication.

    Science.gov (United States)

    Bosone, Lucia; Martinez, Frédéric; Kalampalikis, Nikos

    2015-04-01

    In health-promotional campaigns, positive and negative role models can be deployed to illustrate the benefits or costs of certain behaviors. The main purpose of this article is to investigate why, how, and when exposure to role models strengthens the persuasiveness of a message, according to regulatory fit theory. We argue that exposure to a positive versus a negative model activates individuals' goals toward promotion rather than prevention. By means of two experiments, we demonstrate that high levels of persuasion occur when a message advertising healthy dietary habits offers a regulatory fit between its framing and the described role model. Our data also establish that the effects of such internal regulatory fit by vicarious experience depend on individuals' perceptions of response-efficacy and self-efficacy. Our findings constitute a significant theoretical complement to previous research on regulatory fit and contain valuable practical implications for health-promotional campaigns. © 2015 by the Society for Personality and Social Psychology, Inc.

  19. Fitting Latent Cluster Models for Networks with latentnet

    Directory of Open Access Journals (Sweden)

    Pavel N. Krivitsky

    2007-12-01

    Full Text Available latentnet is a package to fit and evaluate statistical latent position and cluster models for networks. Hoff, Raftery, and Handcock (2002 suggested an approach to modeling networks based on positing the existence of an latent space of characteristics of the actors. Relationships form as a function of distances between these characteristics as well as functions of observed dyadic level covariates. In latentnet social distances are represented in a Euclidean space. It also includes a variant of the extension of the latent position model to allow for clustering of the positions developed in Handcock, Raftery, and Tantrum (2007.The package implements Bayesian inference for the models based on an Markov chain Monte Carlo algorithm. It can also compute maximum likelihood estimates for the latent position model and a two-stage maximum likelihood method for the latent position cluster model. For latent position cluster models, the package provides a Bayesian way of assessing how many groups there are, and thus whether or not there is any clustering (since if the preferred number of groups is 1, there is little evidence for clustering. It also estimates which cluster each actor belongs to. These estimates are probabilistic, and provide the probability of each actor belonging to each cluster. It computes four types of point estimates for the coefficients and positions: maximum likelihood estimate, posterior mean, posterior mode and the estimator which minimizes Kullback-Leibler divergence from the posterior. You can assess the goodness-of-fit of the model via posterior predictive checks. It has a function to simulate networks from a latent position or latent position cluster model.

  20. Rapid world modeling: Fitting range data to geometric primitives

    Energy Technology Data Exchange (ETDEWEB)

    Feddema, J.; Little, C.

    1996-12-31

    For the past seven years, Sandia National Laboratories has been active in the development of robotic systems to help remediate DOE`s waste sites and decommissioned facilities. Some of these facilities have high levels of radioactivity which prevent manual clean-up. Tele-operated and autonomous robotic systems have been envisioned as the only suitable means of removing the radioactive elements. World modeling is defined as the process of creating a numerical geometric model of a real world environment or workspace. This model is often used in robotics to plan robot motions which perform a task while avoiding obstacles. In many applications where the world model does not exist ahead of time, structured lighting, laser range finders, and even acoustical sensors have been used to create three dimensional maps of the environment. These maps consist of thousands of range points which are difficult to handle and interpret. This paper presents a least squares technique for fitting range data to planar and quadric surfaces, including cylinders and ellipsoids. Once fit to these primitive surfaces, the amount of data associated with a surface is greatly reduced up to three orders of magnitude, thus allowing for more rapid handling and analysis of world data.

  1. Direct model fitting to combine dithered ACS images

    CERN Document Server

    Mahmoudian, Haniyeh

    2013-01-01

    The information lost in images of undersampled CCD cameras can be recovered with the technique of `dithering'. A number of subexposures is taken with sub-pixel shifts in order to record structures on scales smaller than a pixel. The standard method to combine such exposures, `Drizzle', averages after reversing the displacements, including rotations and distortions. More sophisticated methods are available to produce, e.g., Nyquist sampled representations of band-limited inputs. While the combined images produced by these methods can be of high quality, their use as input for forward-modelling techniques in gravitational lensing is still not optimal, because the residual artefacts still affect the modelling results in unpredictable ways. In this paper we argue for an overall modelling approach that takes into account the dithering and the lensing without the intermediate product of a combined image. As one building block we introduce an alternative approach to combine dithered images by direct model fitting wi...

  2. A Commentary on the Relationship between Model Fit and Saturated Path Models in Structural Equation Modeling Applications

    Science.gov (United States)

    Raykov, Tenko; Lee, Chun-Lung; Marcoulides, George A.; Chang, Chi

    2013-01-01

    The relationship between saturated path-analysis models and their fit to data is revisited. It is demonstrated that a saturated model need not fit perfectly or even well a given data set when fit to the raw data is examined, a criterion currently frequently overlooked by researchers utilizing path analysis modeling techniques. The potential of…

  3. Issues in Evaluating Model Fit With Missing Data

    Science.gov (United States)

    Davey, Adam

    2005-01-01

    Effects of incomplete data on fit indexes remain relatively unexplored. We evaluate a wide set of fit indexes (?[squared], root mean squared error of appproximation, Normed Fit Index [NFI], Tucker-Lewis Index, comparative fit index, gamma-hat, and McDonald's Centrality Index) varying conditions of sample size (100-1,000 in increments of 50),…

  4. Assessing Model Data Fit of Unidimensional Item Response Theory Models in Simulated Data

    Science.gov (United States)

    Kose, Ibrahim Alper

    2014-01-01

    The purpose of this paper is to give an example of how to assess the model-data fit of unidimensional IRT models in simulated data. Also, the present research aims to explain the importance of fit and the consequences of misfit by using simulated data sets. Responses of 1000 examinees to a dichotomously scoring 20 item test were simulated with 25…

  5. A person-fit index for polytomous Rasch models, latent class models, and their mixture generalizations

    NARCIS (Netherlands)

    von Davier, M; Molenaar, IW

    2003-01-01

    A normally distributed person-fit index is proposed for detecting aberrant response patterns in latent class models and mixture distribution IRT models for dichotomous and polytomous data. This article extends previous work on the null distribution of person-fit indices for the dichotomous Rasch mod

  6. Mechanical Response of Polycarbonate with Strength Model Fits

    Science.gov (United States)

    2012-02-01

    is used as free -parameter to improve the quality of the fit. ̇ is the strain rate and ?̇? is the reference strain rate for which 1/s was used...experimental data. Table 3. ZA model parameters. Bo= 0.006715948 1/K B1= 0.00009503 1/K Bpa = 550 MPa Bopa= 48 MPa ωa= -8 ▬ ωb= -0.01 ▬ β= 0.5...Hybrid Hard/Ductile All-Plastic-and Glass-Plastic-Based Composites ; ARL-TR-3155; U.S. Army Research Laboratory: Aberdeen Proving Ground, MD, February

  7. An NCME Instructional Module on Item-Fit Statistics for Item Response Theory Models

    Science.gov (United States)

    Ames, Allison J.; Penfield, Randall D.

    2015-01-01

    Drawing valid inferences from item response theory (IRT) models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. This instructional module provides an overview of methods used for evaluating the fit of IRT models. Upon completing…

  8. Cavity approach for modeling and fitting polymer stretching

    CERN Document Server

    Massucci, Francesco Alessandro; Vicente, Conrad J Pérez

    2014-01-01

    The mechanical properties of molecules are today captured by single molecule manipulation experiments, so that polymer features are tested at a nanometric scale. Yet devising mathematical models to get further insight beyond the commonly studied force--elongation relation is typically hard. Here we draw from techniques developed in the context of disordered systems to solve models for single and double--stranded DNA stretching in the limit of a long polymeric chain. Since we directly derive the marginals for the molecule local orientation, our approach allows us to readily calculate the experimental elongation as well as other observables at wish. As an example, we evaluate the correlation length as a function of the stretching force. Furthermore, we are able to fit successfully our solution to real experimental data. Although the model is admittedly phenomenological, our findings are very sound. For single--stranded DNA our solution yields the correct (monomer) scale and, yet more importantly, the right pers...

  9. Empirical fitness models for hepatitis C virus immunogen design

    Science.gov (United States)

    Hart, Gregory R.; Ferguson, Andrew L.

    2015-12-01

    Hepatitis C virus (HCV) afflicts 170 million people worldwide, 2%-3% of the global population, and kills 350 000 each year. Prophylactic vaccination offers the most realistic and cost effective hope of controlling this epidemic in the developing world where expensive drug therapies are not available. Despite 20 years of research, the high mutability of the virus and lack of knowledge of what constitutes effective immune responses have impeded development of an effective vaccine. Coupling data mining of sequence databases with spin glass models from statistical physics, we have developed a computational approach to translate clinical sequence databases into empirical fitness landscapes quantifying the replicative capacity of the virus as a function of its amino acid sequence. These landscapes explicitly connect viral genotype to phenotypic fitness, and reveal vulnerable immunological targets within the viral proteome that can be exploited to rationally design vaccine immunogens. We have recovered the empirical fitness landscape for the HCV RNA-dependent RNA polymerase (protein NS5B) responsible for viral genome replication, and validated the predictions of our model by demonstrating excellent accord with experimental measurements and clinical observations. We have used our landscapes to perform exhaustive in silico screening of 16.8 million T-cell immunogen candidates to identify 86 optimal formulations. By reducing the search space of immunogen candidates by over five orders of magnitude, our approach can offer valuable savings in time, expense, and labor for experimental vaccine development and accelerate the search for a HCV vaccine. Abbreviations: HCV—hepatitis C virus, HLA—human leukocyte antigen, CTL—cytotoxic T lymphocyte, NS5B—nonstructural protein 5B, MSA—multiple sequence alignment, PEG-IFN—pegylated interferon.

  10. THE SUPERIORITY OF EMPIRICAL BAYES ESTIMATION OF PARAMETERS IN PARTITIONED NORMAL LINEAR MODEL

    Institute of Scientific and Technical Information of China (English)

    Zhang Weiping; Wei Laisheng

    2008-01-01

    In this article, the empirical Bayes (EB) estimators are constructed for the estimable functions of the parameters in partitioned normal linear model. The superiorities of the EB estimators over ordinary least-squares (LS) estimator are investigated under mean square error matrix (MSEM) criterion.

  11. Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS

    Science.gov (United States)

    Bolker, Benjamin M.; Gardner, Beth; Maunder, Mark; Berg, Casper W.; Brooks, Mollie; Comita, Liza; Crone, Elizabeth; Cubaynes, Sarah; Davies, Trevor; de Valpine, Perry; Ford, Jessica; Gimenez, Olivier; Kéry, Marc; Kim, Eun Jung; Lennert-Cody, Cleridy; Magunsson, Arni; Martell, Steve; Nash, John; Nielson, Anders; Regentz, Jim; Skaug, Hans; Zipkin, Elise

    2013-01-01

    1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. 2. R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. 3. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. 4. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data.

  12. Nested by design: model fitting and interpretation in a mixed model era

    National Research Council Canada - National Science Library

    Schielzeth, Holger; Nakagawa, Shinichi; Freckleton, Robert

    2013-01-01

    ...‐effects models offer a powerful framework to do so. Nested effects can usually be fitted using the syntax for crossed effects in mixed models, provided that the coding reflects implicit nesting...

  13. Robust goodness-of-fit tests for AR(p) models based on L1-norm fitting

    Institute of Scientific and Technical Information of China (English)

    蒋建成; 郑忠国

    1999-01-01

    A robustified residual autocorrelation is defined based on L1-regression. Under very general conditions,the asymptotic distribution of the robust residual autocorrelation is obtained. A robustified portmanteau statistic is then constructed which can be used in checking the goodness-of-fit of AR(p) models when using L1-norm fitting. Empirical results show that L1-norm estimators and the proposed portmanteau statistic are robust against outliers, error distributions, and accuracy for a given finite sample.

  14. A neutrino model fit to the CMB power spectrum

    CERN Document Server

    Shanks, T; Schewtschenko, J A; Whitbourn, J R

    2014-01-01

    The current standard cosmological model, LCDM, provides an excellent fit to the WMAP and Planck CMB data. However, the model has well known problems. For example, the cosmological constant is fine tuned to 1 part in 10^100 and the cold dark matter (CDM) particle is not yet detected in the laboratory. Here we seek an alternative model to LCDM which makes minimal assumptions about new physics. This is based on previous work by Shanks who investigated a model which assumed neither exotic particles nor a cosmological constant but instead postulated a low Hubble constant (H_0) to help allow a baryon density which was compatible with an inflationary model with zero spatial curvature. However, the recent Planck results make it more difficult to reconcile such a model with the cosmic microwave background (CMB) temperature fluctuations. Here we relax the previous assumptions to assess the effects of assuming standard model neutrinos of moderate mass (~5eV) but with no CDM and no cosmological constant. If we assume a l...

  15. [A study of coordinates transform iterative fitting method to extract bio-impedance model parameters bio-impedance model parameters].

    Science.gov (United States)

    Zhou, Liming; Yang, Yuxing; Yuan, Shiying

    2006-02-01

    A new algorithm, the coordinates transform iterative optimizing method based on the least square curve fitting model, is presented. This arithmetic is used for extracting the bio-impedance model parameters. It is superior to other methods, for example, its speed of the convergence is quicker, and its calculating precision is higher. The objective to extract the model parameters, such as Ri, Re, Cm and alpha, has been realized rapidly and accurately. With the aim at lowering the power consumption, decreasing the price and improving the price-to-performance ratio, a practical bio-impedance measure system with double CPUs has been built. It can be drawn from the preliminary results that the intracellular resistance Ri increased largely with an increase in working load during sitting, which reflects the ischemic change of lower limbs.

  16. 3D Building Model Fitting Using A New Kinetic Framework

    CERN Document Server

    Brédif, Mathieu; Pierrot-Deseilligny, Marc; Maître, Henri

    2008-01-01

    We describe a new approach to fit the polyhedron describing a 3D building model to the point cloud of a Digital Elevation Model (DEM). We introduce a new kinetic framework that hides to its user the combinatorial complexity of determining or maintaining the polyhedron topology, allowing the design of a simple variational optimization. This new kinetic framework allows the manipulation of a bounded polyhedron with simple faces by specifying the target plane equations of each of its faces. It proceeds by evolving continuously from the polyhedron defined by its initial topology and its initial plane equations to a polyhedron that is as topologically close as possible to the initial polyhedron but with the new plane equations. This kinetic framework handles internally the necessary topological changes that may be required to keep the faces simple and the polyhedron bounded. For each intermediate configurations where the polyhedron looses the simplicity of its faces or its boundedness, the simplest topological mod...

  17. The FIT Model - Fuel-cycle Integration and Tradeoffs

    Energy Technology Data Exchange (ETDEWEB)

    Steven J. Piet; Nick R. Soelberg; Samuel E. Bays; Candido Pereira; Layne F. Pincock; Eric L. Shaber; Meliisa C Teague; Gregory M Teske; Kurt G Vedros

    2010-09-01

    All mass streams from fuel separation and fabrication are products that must meet some set of product criteria – fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the “system losses study” team that developed it [Shropshire2009, Piet2010] are an initial step by the FCR&D program toward a global analysis that accounts for the requirements and capabilities of each component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R&D needs and set longer-term goals. The question originally posed to the “system losses study” was the cost of separation, fuel fabrication, waste management, etc. versus the separation efficiency. In other words, are the costs associated with marginal reductions in separations losses (or improvements in product recovery) justified by the gains in the performance of other systems? We have learned that that is the wrong question. The right question is: how does one adjust the compositions and quantities of all mass streams, given uncertain product criteria, to balance competing objectives including cost? FIT is a method to analyze different fuel cycles using common bases to determine how chemical performance changes in one part of a fuel cycle (say used fuel cooling times or separation efficiencies) affect other parts of the fuel cycle. FIT estimates impurities in fuel and waste via a rough estimate of physics and mass balance for a set of technologies. If feasibility is an issue for a set, as it is for “minimum fuel treatment” approaches such as melt refining and AIROX, it can help to make an estimate of how performances would have to change to achieve feasibility.

  18. The FIT Model - Fuel-cycle Integration and Tradeoffs

    Energy Technology Data Exchange (ETDEWEB)

    Steven J. Piet; Nick R. Soelberg; Samuel E. Bays; Candido Pereira; Layne F. Pincock; Eric L. Shaber; Meliisa C Teague; Gregory M Teske; Kurt G Vedros

    2010-09-01

    All mass streams from fuel separation and fabrication are products that must meet some set of product criteria – fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the “system losses study” team that developed it [Shropshire2009, Piet2010] are an initial step by the FCR&D program toward a global analysis that accounts for the requirements and capabilities of each component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R&D needs and set longer-term goals. The question originally posed to the “system losses study” was the cost of separation, fuel fabrication, waste management, etc. versus the separation efficiency. In other words, are the costs associated with marginal reductions in separations losses (or improvements in product recovery) justified by the gains in the performance of other systems? We have learned that that is the wrong question. The right question is: how does one adjust the compositions and quantities of all mass streams, given uncertain product criteria, to balance competing objectives including cost? FIT is a method to analyze different fuel cycles using common bases to determine how chemical performance changes in one part of a fuel cycle (say used fuel cooling times or separation efficiencies) affect other parts of the fuel cycle. FIT estimates impurities in fuel and waste via a rough estimate of physics and mass balance for a set of technologies. If feasibility is an issue for a set, as it is for “minimum fuel treatment” approaches such as melt refining and AIROX, it can help to make an estimate of how performances would have to change to achieve feasibility.

  19. An experimentally informed evolutionary model improves phylogenetic fit to divergent lactamase homologs.

    Science.gov (United States)

    Bloom, Jesse D

    2014-10-01

    Phylogenetic analyses of molecular data require a quantitative model for how sequences evolve. Traditionally, the details of the site-specific selection that governs sequence evolution are not known a priori, making it challenging to create evolutionary models that adequately capture the heterogeneity of selection at different sites. However, recent advances in high-throughput experiments have made it possible to quantify the effects of all single mutations on gene function. I have previously shown that such high-throughput experiments can be combined with knowledge of underlying mutation rates to create a parameter-free evolutionary model that describes the phylogeny of influenza nucleoprotein far better than commonly used existing models. Here, I extend this work by showing that published experimental data on TEM-1 beta-lactamase (Firnberg E, Labonte JW, Gray JJ, Ostermeier M. 2014. A comprehensive, high-resolution map of a gene's fitness landscape. Mol Biol Evol. 31:1581-1592) can be combined with a few mutation rate parameters to create an evolutionary model that describes beta-lactamase phylogenies much better than most common existing models. This experimentally informed evolutionary model is superior even for homologs that are substantially diverged (about 35% divergence at the protein level) from the TEM-1 parent that was the subject of the experimental study. These results suggest that experimental measurements can inform phylogenetic evolutionary models that are applicable to homologs that span a substantial range of sequence divergence.

  20. Direct model fitting to combine dithered ACS images

    Science.gov (United States)

    Mahmoudian, H.; Wucknitz, O.

    2013-08-01

    The information lost in images of undersampled CCD cameras can be recovered with the technique of "dithering". A number of subexposures is taken with sub-pixel shifts in order to record structures on scales smaller than a pixel. The standard method to combine such exposures, "Drizzle", averages after reversing the displacements, including rotations and distortions. More sophisticated methods are available to produce, e.g., Nyquist sampled representations of band-limited inputs. While the combined images produced by these methods can be of high quality, their use as input for forward-modelling techniques in gravitational lensing is still not optimal, because the residual artefacts still affect the modelling results in unpredictable ways. In this paper we argue for an overall modelling approach that takes into account the dithering and the lensing without the intermediate product of a combined image. As one building block we introduce an alternative approach to combine dithered images by direct model fitting with a least-squares approach including a regularization constraint. We present tests with simulated and real data that show the quality of the results. The additional effects of gravitational lensing and the convolution with an instrumental point spread function can be included in a natural way, avoiding the possible systematic errors of previous procedures.

  1. Modeling Percentile Rank of Cardiorespiratory Fitness Across the Lifespan

    Science.gov (United States)

    Graves, Rasinio S.; Mahnken, Jonathan D.; Perea, Rodrigo D.; Billinger, Sandra A.; Vidoni, Eric D.

    2016-01-01

    Purpose The purpose of this investigation was to create an equation for continuous percentile rank of maximal oxygen consumption (VO2 max) from ages 20 to 99. Methods We used a two-staged modeling approach with existing normative data from the American College of Sports Medicine for VO2 max. First, we estimated intercept and slope parameters for each decade of life as a logistic function. We then modeled change in intercept and slope as functions of age (stage two) using weighted least squares regression. The resulting equations were used to predict fitness percentile rank based on age, sex, and VO2 max, and included estimates for individuals beyond 79 years old. Results We created a continuous, sex specific model of VO2 max percentile rank across the lifespan. Conclusions Percentile ranking of VO2 max can be made continuous and account for adults aged 20 to 99 with reasonable accuracy, improving the utility of this normalization procedure in practical and research settings, particularly in aging populations. PMID:26778922

  2. Methodical fitting for mathematical models of rubber-like materials

    Science.gov (United States)

    Destrade, Michel; Saccomandi, Giuseppe; Sgura, Ivonne

    2017-02-01

    A great variety of models can describe the nonlinear response of rubber to uniaxial tension. Yet an in-depth understanding of the successive stages of large extension is still lacking. We show that the response can be broken down in three steps, which we delineate by relying on a simple formatting of the data, the so-called Mooney plot transform. First, the small-to-moderate regime, where the polymeric chains unfold easily and the Mooney plot is almost linear. Second, the strain-hardening regime, where blobs of bundled chains unfold to stiffen the response in correspondence to the `upturn' of the Mooney plot. Third, the limiting-chain regime, with a sharp stiffening occurring as the chains extend towards their limit. We provide strain-energy functions with terms accounting for each stage that (i) give an accurate local and then global fitting of the data; (ii) are consistent with weak nonlinear elasticity theory and (iii) can be interpreted in the framework of statistical mechanics. We apply our method to Treloar's classical experimental data and also to some more recent data. Our method not only provides models that describe the experimental data with a very low quantitative relative error, but also shows that the theory of nonlinear elasticity is much more robust that seemed at first sight.

  3. A cautionary note on the use of information fit indexes in covariance structure modeling with means

    NARCIS (Netherlands)

    Wicherts, J.M.; Dolan, C.V.

    2004-01-01

    Information fit indexes such as Akaike Information Criterion, Consistent Akaike Information Criterion, Bayesian Information Criterion, and the expected cross validation index can be valuable in assessing the relative fit of structural equation models that differ regarding restrictiveness. In cases i

  4. A Simulated Annealing based Optimization Algorithm for Automatic Variogram Model Fitting

    Science.gov (United States)

    Soltani-Mohammadi, Saeed; Safa, Mohammad

    2016-09-01

    Fitting a theoretical model to an experimental variogram is an important issue in geostatistical studies because if the variogram model parameters are tainted with uncertainty, the latter will spread in the results of estimations and simulations. Although the most popular fitting method is fitting by eye, in some cases use is made of the automatic fitting method on the basis of putting together the geostatistical principles and optimization techniques to: 1) provide a basic model to improve fitting by eye, 2) fit a model to a large number of experimental variograms in a short time, and 3) incorporate the variogram related uncertainty in the model fitting. Effort has been made in this paper to improve the quality of the fitted model by improving the popular objective function (weighted least squares) in the automatic fitting. Also, since the variogram model function (£) and number of structures (m) too affect the model quality, a program has been provided in the MATLAB software that can present optimum nested variogram models using the simulated annealing method. Finally, to select the most desirable model from among the single/multi-structured fitted models, use has been made of the cross-validation method, and the best model has been introduced to the user as the output. In order to check the capability of the proposed objective function and the procedure, 3 case studies have been presented.

  5. A quantitative confidence signal detection model: 1. Fitting psychometric functions.

    Science.gov (United States)

    Yi, Yongwoo; Merfeld, Daniel M

    2016-04-01

    Perceptual thresholds are commonly assayed in the laboratory and clinic. When precision and accuracy are required, thresholds are quantified by fitting a psychometric function to forced-choice data. The primary shortcoming of this approach is that it typically requires 100 trials or more to yield accurate (i.e., small bias) and precise (i.e., small variance) psychometric parameter estimates. We show that confidence probability judgments combined with a model of confidence can yield psychometric parameter estimates that are markedly more precise and/or markedly more efficient than conventional methods. Specifically, both human data and simulations show that including confidence probability judgments for just 20 trials can yield psychometric parameter estimates that match the precision of those obtained from 100 trials using conventional analyses. Such an efficiency advantage would be especially beneficial for tasks (e.g., taste, smell, and vestibular assays) that require more than a few seconds for each trial, but this potential benefit could accrue for many other tasks. Copyright © 2016 the American Physiological Society.

  6. RNA virus evolution via a fitness-space model

    Energy Technology Data Exchange (ETDEWEB)

    Tsimring, L.S.; Levine, H. [Institute for Nonlinear Science, University of California, San Diego, La Jolla, California 92093-0402 (United States); Kessler, D.A. [Department of Physics, Bar-Ilan University, Ramat Gan 52900 (Israel)

    1996-06-01

    We present a mean-field theory for the evolution of RNA virus populations. The theory operates with a distribution of the population in a one-dimensional fitness space, and is valid for sufficiently smooth fitness landscapes. Our approach explains naturally the recent experimental observation [I. S. Novella {ital et} {ital al}., Proc. Natl. Acad. Sci. U.S.A. {bold 92}, 5841{endash}5844 (1995)] of two distinct stages in the growth of virus fitness. {copyright} {ital 1995 The American Physical Society.}

  7. Fitness voter model: Damped oscillations and anomalous consensus

    Science.gov (United States)

    Woolcock, Anthony; Connaughton, Colm; Merali, Yasmin; Vazquez, Federico

    2017-09-01

    We study the dynamics of opinion formation in a heterogeneous voter model on a complete graph, in which each agent is endowed with an integer fitness parameter k ≥0 , in addition to its + or - opinion state. The evolution of the distribution of k -values and the opinion dynamics are coupled together, so as to allow the system to dynamically develop heterogeneity and memory in a simple way. When two agents with different opinions interact, their k -values are compared, and with probability p the agent with the lower value adopts the opinion of the one with the higher value, while with probability 1 -p the opposite happens. The agent that keeps its opinion (winning agent) increments its k -value by one. We study the dynamics of the system in the entire 0 ≤p ≤1 range and compare with the case p =1 /2 , in which opinions are decoupled from the k -values and the dynamics is equivalent to that of the standard voter model. When 0 ≤p mean consensus time τ appears to grow logarithmically with the number of agents N , and it is greatly decreased relative to the linear behavior τ ˜N found in the standard voter model. When 1 /2

    model, although it still scales linearly with N . The p =1 case is special, with a relaxation to coexistence that scales as t-2.73 and a consensus time that scales as τ ˜Nβ , with β ≃1.45 .

  8. Convergence, Admissibility, and Fit of Alternative Confirmatory Factor Analysis Models for MTMM Data

    Science.gov (United States)

    Lance, Charles E.; Fan, Yi

    2016-01-01

    We compared six different analytic models for multitrait-multimethod (MTMM) data in terms of convergence, admissibility, and model fit to 258 samples of previously reported data. Two well-known models, the correlated trait-correlated method (CTCM) and the correlated trait-correlated uniqueness (CTCU) models, were fit for reference purposes in…

  9. Convergence, Admissibility, and Fit of Alternative Confirmatory Factor Analysis Models for MTMM Data

    Science.gov (United States)

    Lance, Charles E.; Fan, Yi

    2016-01-01

    We compared six different analytic models for multitrait-multimethod (MTMM) data in terms of convergence, admissibility, and model fit to 258 samples of previously reported data. Two well-known models, the correlated trait-correlated method (CTCM) and the correlated trait-correlated uniqueness (CTCU) models, were fit for reference purposes in…

  10. An Application of M[subscript 2] Statistic to Evaluate the Fit of Cognitive Diagnostic Models

    Science.gov (United States)

    Liu, Yanlou; Tian, Wei; Xin, Tao

    2016-01-01

    The fit of cognitive diagnostic models (CDMs) to response data needs to be evaluated, since CDMs might yield misleading results when they do not fit the data well. Limited-information statistic M[subscript 2] and the associated root mean square error of approximation (RMSEA[subscript 2]) in item factor analysis were extended to evaluate the fit of…

  11. Superior Effects of Eccentric to Concentric Knee Extensor Resistance Training on Physical Fitness, Insulin Sensitivity and Lipid Profiles of Elderly Men

    Science.gov (United States)

    Chen, Trevor Chung-Ching; Tseng, Wei-Chin; Huang, Guan-Ling; Chen, Hsin-Lian; Tseng, Kuo-Wei; Nosaka, Kazunori

    2017-01-01

    It has been reported that eccentric training of knee extensors is effective for improving blood insulin sensitivity and lipid profiles to a greater extent than concentric training in young women. However, it is not known whether this is also the case for elderly individuals. Thus, the present study tested the hypothesis that eccentric training of the knee extensors would improve physical function and health parameters (e.g., blood lipid profiles) of older adults better than concentric training. Healthy elderly men (60–76 years) were assigned to either eccentric training or concentric training group (n = 13/group), and performed 30–60 eccentric or concentric contractions of knee extensors once a week. The intensity was progressively increased over 12 weeks from 10 to 100% of maximal concentric strength for eccentric training and from 50 to 100% for concentric training. Outcome measures were taken before and 4 days after the training period. The results showed that no sings of muscle damage were observed after any sessions. Functional physical fitness (e.g., 30-s chair stand) and maximal concentric contraction strength of the knee extensors increased greater (P ≤ 0.05) after eccentric training than concentric training. Homeostasis model assessment, oral glucose tolerance test and whole blood glycosylated hemoglobin showed improvement of insulin sensitivity only after eccentric training (P ≤ 0.05). Greater (P ≤ 0.05) decreases in fasting triacylglycerols, total, and low-density lipoprotein cholesterols were evident after eccentric training than concentric training, and high-density lipoprotein cholesterols increased only after eccentric training. These results support the hypothesis and suggest that it is better to focus on eccentric contractions in exercise medicine. PMID:28443029

  12. Superior Effects of Eccentric to Concentric Knee Extensor Resistance Training on Physical Fitness, Insulin Sensitivity and Lipid Profiles of Elderly Men.

    Science.gov (United States)

    Chen, Trevor Chung-Ching; Tseng, Wei-Chin; Huang, Guan-Ling; Chen, Hsin-Lian; Tseng, Kuo-Wei; Nosaka, Kazunori

    2017-01-01

    It has been reported that eccentric training of knee extensors is effective for improving blood insulin sensitivity and lipid profiles to a greater extent than concentric training in young women. However, it is not known whether this is also the case for elderly individuals. Thus, the present study tested the hypothesis that eccentric training of the knee extensors would improve physical function and health parameters (e.g., blood lipid profiles) of older adults better than concentric training. Healthy elderly men (60-76 years) were assigned to either eccentric training or concentric training group (n = 13/group), and performed 30-60 eccentric or concentric contractions of knee extensors once a week. The intensity was progressively increased over 12 weeks from 10 to 100% of maximal concentric strength for eccentric training and from 50 to 100% for concentric training. Outcome measures were taken before and 4 days after the training period. The results showed that no sings of muscle damage were observed after any sessions. Functional physical fitness (e.g., 30-s chair stand) and maximal concentric contraction strength of the knee extensors increased greater (P ≤ 0.05) after eccentric training than concentric training. Homeostasis model assessment, oral glucose tolerance test and whole blood glycosylated hemoglobin showed improvement of insulin sensitivity only after eccentric training (P ≤ 0.05). Greater (P ≤ 0.05) decreases in fasting triacylglycerols, total, and low-density lipoprotein cholesterols were evident after eccentric training than concentric training, and high-density lipoprotein cholesterols increased only after eccentric training. These results support the hypothesis and suggest that it is better to focus on eccentric contractions in exercise medicine.

  13. Keratoconus, cross-link-induction, comparison between fitting exponential function and a fitting equation obtained by a mathematical model.

    Science.gov (United States)

    Albanese, A; Urso, R; Bianciardi, L; Rigato, M; Battisti, E

    2009-11-01

    With reference to experimental data in the literature, we present a model consisting of two elastic elements, conceived to simulate resistance to stretching, at constant velocity of elongation, of corneal tissue affected by keratoconus, treated with riboflavin and ultraviolet irradiation to induce cross-linking. The function describing model behaviour adapted to stress and strain values. It was found that the Young's moduli of the two elastic elements increased in cross-linked tissues and that cross-linking treatment therefore increased corneal rigidity. It is recognized that this observation is substantially in line with the conclusion reported in the literature, obtained using an exponential fitting function. It is observed, however, that the latter function implies a condition of non-zero stresses without strain, and does not provide interpretative insights for lack of any biomechanical basis. Above all, the function fits a singular trend, inexplicably claimed to be viscoelastic, with surprising perfection. In any case, using the reported data, the study demonstrates that a fitting equation obtained by a modelling approach not only shows the evident efficacy of the treatment, but also provides orientations for studying modifications induced in cross-linked fibres.

  14. Satellite image blind restoration based on surface fitting and multivariate model

    Institute of Scientific and Technical Information of China (English)

    CHEN Xin-bing; YANG Shi-zhi; WANG Xian-hua; QIAO Yan-li

    2009-01-01

    Owing to the blurring effect from atmosphere and camera system in the satellite imaging a blind image restoration algo-rithm is proposed which includes the modulation transfer function (MTF) estimation and the image restoration. In the MTF estimation stage, based on every degradation process of satellite imaging-chain, a combined parametric model of MTF is given and used to fit the surface of normalized logarithmic amplitude spectrum of degraded image. In the image restoration stage, a maximum a posteriori (MAP) based edge-preserving image restoration method is presented which introduces multivariate Laplacian model to characterize the prior distribution of wavelet coefficients of original image. During the image restoration, in order to avoid solving high nonlinear equations, optimization transfer algorithm is adopted to decom-pose the image restoration procedure into two simple steps: Landweber iteration and wavelet thresholding denoising. In the numerical experiment, the satellite image restoration results from SPOT-5 and high resolution camera (HR) of China & Brazil earth resource satellite (CBERS-02B) ane compared, and the proposed algorithm is superior in the image edge preservation and noise inhibition.

  15. Regularization Methods for Fitting Linear Models with Small Sample Sizes: Fitting the Lasso Estimator Using R

    Science.gov (United States)

    Finch, W. Holmes; Finch, Maria E. Hernandez

    2016-01-01

    Researchers and data analysts are sometimes faced with the problem of very small samples, where the number of variables approaches or exceeds the overall sample size; i.e. high dimensional data. In such cases, standard statistical models such as regression or analysis of variance cannot be used, either because the resulting parameter estimates…

  16. Regularization Methods for Fitting Linear Models with Small Sample Sizes: Fitting the Lasso Estimator Using R

    Directory of Open Access Journals (Sweden)

    W. Holmes Finch

    2016-05-01

    Full Text Available Researchers and data analysts are sometimes faced with the problem of very small samples, where the number of variables approaches or exceeds the overall sample size; i.e. high dimensional data. In such cases, standard statistical models such as regression or analysis of variance cannot be used, either because the resulting parameter estimates exhibit very high variance and can therefore not be trusted, or because the statistical algorithm cannot converge on parameter estimates at all. There exist an alternative set of model estimation procedures, known collectively as regularization methods, which can be used in such circumstances, and which have been shown through simulation research to yield accurate parameter estimates. The purpose of this paper is to describe, for those unfamiliar with them, the most popular of these regularization methods, the lasso, and to demonstrate its use on an actual high dimensional dataset involving adults with autism, using the R software language. Results of analyses involving relating measures of executive functioning with a full scale intelligence test score are presented, and implications of using these models are discussed.

  17. Fitting Item Response Theory Models to Two Personality Inventories: Issues and Insights.

    Science.gov (United States)

    Chernyshenko, Oleksandr S.; Stark, Stephen; Chan, Kim-Yin; Drasgow, Fritz; Williams, Bruce

    2001-01-01

    Compared the fit of several Item Response Theory (IRT) models to two personality assessment instruments using data from 13,059 individuals responding to one instrument and 1,770 individuals responding to the other. Two- and three-parameter logistic models fit some scales reasonably well, but not others, and the graded response model generally did…

  18. A fitted neoprene garment to cover dressings in swine models.

    Science.gov (United States)

    Mino, Matthew J; Mauskar, Neil A; Matt, Sara E; Pavlovich, Anna R; Prindeze, Nicholas J; Moffatt, Lauren T; Shupp, Jeffrey W

    2012-12-17

    Domesticated porcine species are commonly used in studies of wound healing, owing to similarities between porcine skin and human skin. Such studies often involve wound dressings, and keeping these dressings intact on the animal can be a challenge. The authors describe a novel and simple technique for constructing a fitted neoprene garment for pigs that covers dressings and maintains their integrity during experiments.

  19. The FITS model office ergonomics program: a model for best practice.

    Science.gov (United States)

    Chim, Justine M Y

    2014-01-01

    An effective office ergonomics program can predict positive results in reducing musculoskeletal injury rates, enhancing productivity, and improving staff well-being and job satisfaction. Its objective is to provide a systematic solution to manage the potential risk of musculoskeletal disorders among computer users in an office setting. A FITS Model office ergonomics program is developed. The FITS Model Office Ergonomics Program has been developed which draws on the legislative requirements for promoting the health and safety of workers using computers for extended periods as well as previous research findings. The Model is developed according to the practical industrial knowledge in ergonomics, occupational health and safety management, and human resources management in Hong Kong and overseas. This paper proposes a comprehensive office ergonomics program, the FITS Model, which considers (1) Furniture Evaluation and Selection; (2) Individual Workstation Assessment; (3) Training and Education; (4) Stretching Exercises and Rest Break as elements of an effective program. An experienced ergonomics practitioner should be included in the program design and implementation. Through the FITS Model Office Ergonomics Program, the risk of musculoskeletal disorders among computer users can be eliminated or minimized, and workplace health and safety and employees' wellness enhanced.

  20. An accurate halo model for fitting non-linear cosmological power spectra and baryonic feedback models

    CERN Document Server

    Mead, Alexander; Heymans, Catherine; Joudaki, Shahab; Heavens, Alan

    2015-01-01

    We present an optimised variant of the halo model, designed to produce accurate matter power spectra well into the non-linear regime for a wide range of cosmological models. To do this, we introduce physically-motivated free parameters into the halo-model formalism and fit these to data from high-resolution N-body simulations. For a variety of $\\Lambda$CDM and $w$CDM models the halo-model power is accurate to $\\simeq 5$ per cent for $k\\leq 10h\\,\\mathrm{Mpc}^{-1}$ and $z\\leq 2$. We compare our results with recent revisions of the popular HALOFIT model and show that our predictions are more accurate. An advantage of our new halo model is that it can be adapted to account for the effects of baryonic feedback on the power spectrum. We demonstrate this by fitting the halo model to power spectra from the OWLS hydrodynamical simulation suite via parameters that govern halo internal structure. We are able to fit all feedback models investigated at the 5 per cent level using only two free parameters, and we place limi...

  1. Modelling population dynamics model formulation, fitting and assessment using state-space methods

    CERN Document Server

    Newman, K B; Morgan, B J T; King, R; Borchers, D L; Cole, D J; Besbeas, P; Gimenez, O; Thomas, L

    2014-01-01

    This book gives a unifying framework for estimating the abundance of open populations: populations subject to births, deaths and movement, given imperfect measurements or samples of the populations.  The focus is primarily on populations of vertebrates for which dynamics are typically modelled within the framework of an annual cycle, and for which stochastic variability in the demographic processes is usually modest. Discrete-time models are developed in which animals can be assigned to discrete states such as age class, gender, maturity,  population (within a metapopulation), or species (for multi-species models). The book goes well beyond estimation of abundance, allowing inference on underlying population processes such as birth or recruitment, survival and movement. This requires the formulation and fitting of population dynamics models.  The resulting fitted models yield both estimates of abundance and estimates of parameters characterizing the underlying processes.  

  2. A Model of the Superior Colliculus Predicts Fixation Locations during Scene Viewing and Visual Search.

    Science.gov (United States)

    Adeli, Hossein; Vitu, Françoise; Zelinsky, Gregory J

    2017-02-08

    Modern computational models of attention predict fixations using saliency maps and target maps, which prioritize locations for fixation based on feature contrast and target goals, respectively. But whereas many such models are biologically plausible, none have looked to the oculomotor system for design constraints or parameter specification. Conversely, although most models of saccade programming are tightly coupled to underlying neurophysiology, none have been tested using real-world stimuli and tasks. We combined the strengths of these two approaches in MASC, a model of attention in the superior colliculus (SC) that captures known neurophysiological constraints on saccade programming. We show that MASC predicted the fixation locations of humans freely viewing naturalistic scenes and performing exemplar and categorical search tasks, a breadth achieved by no other existing model. Moreover, it did this as well or better than its more specialized state-of-the-art competitors. MASC's predictive success stems from its inclusion of high-level but core principles of SC organization: an over-representation of foveal information, size-invariant population codes, cascaded population averaging over distorted visual and motor maps, and competition between motor point images for saccade programming, all of which cause further modulation of priority (attention) after projection of saliency and target maps to the SC. Only by incorporating these organizing brain principles into our models can we fully understand the transformation of complex visual information into the saccade programs underlying movements of overt attention. With MASC, a theoretical footing now exists to generate and test computationally explicit predictions of behavioral and neural responses in visually complex real-world contexts.SIGNIFICANCE STATEMENT The superior colliculus (SC) performs a visual-to-motor transformation vital to overt attention, but existing SC models cannot predict saccades to visually

  3. Inhibition drives configural superiority of illusory Gestalt: Combined behavioral and drift-diffusion model evidence.

    Science.gov (United States)

    Nie, Qi-Yang; Maurer, Mara; Müller, Hermann J; Conci, Markus

    2016-05-01

    Illusory Kanizsa figures demonstrate that a perceptually completed whole is more than the sum of its composite parts. In the current study, we explored part/whole relationships in object completion using the configural superiority effect (CSE) with illusory figures (Pomerantz & Portillo, 2011). In particular, we investigated to which extent the CSE is modulated by closure in target and distractor configurations. Our results demonstrated a typical CSE, with detection of a configural whole being more efficient than the detection of a corresponding part-level target. Moreover, the CSE was more pronounced when grouped objects were presented in distractors rather than in the target. A follow-up experiment systematically manipulated closure in whole target or, respectively, distractor configurations. The results revealed the effect of closure to be again stronger in distractor, rather than in target configurations, suggesting that closure primarily affects the inhibition of distractors, and to a lesser extent the selection of the target. In addition, a drift-diffusion model analysis of our data revealed that efficient distractor inhibition expedites the rate of evidence accumulation, with closure in distractors particularly speeding the drift toward the decision boundary. In sum, our findings demonstrate that the CSE in Kanizsa figures derives primarily from the inhibition of closed distractor objects, rather than being driven by a conspicuous target configuration. Altogether, these results support a fundamental role of inhibition in driving configural superiority effects in visual search.

  4. Modeling the minimal newborn's intersubjective mind: the visuotopic-somatotopic alignment hypothesis in the superior colliculus.

    Directory of Open Access Journals (Sweden)

    Alexandre Pitti

    Full Text Available The question whether newborns possess inborn social skills is a long debate in developmental psychology. Fetal behavioral and anatomical observations show evidences for the control of eye movements and facial behaviors during the third trimester of pregnancy whereas specific sub-cortical areas, like the superior colliculus (SC and the striatum appear to be functionally mature to support these behaviors. These observations suggest that the newborn is potentially mature for developing minimal social skills. In this manuscript, we propose that the mechanism of sensory alignment observed in SC is particularly important for enabling the social skills observed at birth such as facial preference and facial mimicry. In a computational simulation of the maturing superior colliculus connected to a simulated facial tissue of a fetus, we model how the incoming tactile information is used to direct visual attention toward faces. We suggest that the unisensory superficial visual layer (eye-centered and the deep somatopic layer (face-centered in SC are combined into an intermediate layer for visuo-tactile integration and that multimodal alignment in this third layer allows newborns to have a sensitivity to configuration of eyes and mouth. We show that the visual and tactile maps align through a Hebbian learning stage and and strengthen their synaptic links from each other into the intermediate layer. It results that the global network produces some emergent properties such as sensitivity toward the spatial configuration of face-like patterns and the detection of eyes and mouth movement.

  5. A New Finite Interval Lifetime Distribution Model for Fitting Bathtub-Shaped Failure Rate Curve

    Directory of Open Access Journals (Sweden)

    Xiaohong Wang

    2015-01-01

    Full Text Available This paper raised a new four-parameter fitting model to describe bathtub curve, which is widely used in research on components’ life analysis, then gave explanation of model parameters, and provided parameter estimation method as well as application examples utilizing some well-known lifetime data. By comparative analysis between the new model and some existing bathtub curve fitting model, we can find that the new fitting model is very convenient and its parameters are clear; moreover, this model is of universal applicability which is not only suitable for bathtub-shaped failure rate curves but also applicable for the constant, increasing, and decreasing failure rate curves.

  6. Fitting Multilevel Models with Ordinal Outcomes: Performance of Alternative Specifications and Methods of Estimation

    Science.gov (United States)

    Bauer, Daniel J.; Sterba, Sonya K.

    2011-01-01

    Previous research has compared methods of estimation for fitting multilevel models to binary data, but there are reasons to believe that the results will not always generalize to the ordinal case. This article thus evaluates (a) whether and when fitting multilevel linear models to ordinal outcome data is justified and (b) which estimator to employ…

  7. A Cautionary Note on the Use of Information Fit Indexes in Covariance Structure Modeling with Means

    Science.gov (United States)

    Wicherts, Jelte M.; Dolan, Conor V.

    2004-01-01

    Information fit indexes such as Akaike Information Criterion, Consistent Akaike Information Criterion, Bayesian Information Criterion, and the expected cross validation index can be valuable in assessing the relative fit of structural equation models that differ regarding restrictiveness. In cases in which models without mean restrictions (i.e.,…

  8. Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.

    Science.gov (United States)

    DeCarlo, Lawrence T

    2003-02-01

    The recent addition of aprocedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.

  9. Effect of Correlations Between Model Parameters and Nuisance Parameters When Model Parameters are Fit to Data

    CERN Document Server

    Roe, Byron

    2013-01-01

    The effect of correlations between model parameters and nuisance parameters is discussed, in the context of fitting model parameters to data. Modifications to the usual $\\chi^2$ method are required. Fake data studies, as used at present, will not be optimum. Problems will occur for applications of the Maltoni-Schwetz \\cite{ms} theorem. Neutrino oscillations are used as examples, but the problems discussed here are general ones, which are often not addressed.

  10. Refractive Index of Humid Air in the Infrared: Model Fits

    CERN Document Server

    Mathar, R J

    2006-01-01

    The theory of summation of electromagnetic line transitions is used to tabulate the Taylor expansion of the refractive index of humid air over the basic independent parameters (temperature, pressure, humidity, wavelength) in five separate infrared regions from the H to the Q band at a fixed percentage of Carbon Dioxide. These are least-squares fits to raw, highly resolved spectra for a set of temperatures from 10 to 25 C, a set of pressures from 500 to 1023 hPa, and a set of relative humidities from 5 to 60%. These choices reflect the prospective application to characterize ambient air at mountain altitudes of astronomical telescopes.

  11. The Thorny Relation Between Measurement Quality and Fit Index Cutoffs in Latent Variable Models.

    Science.gov (United States)

    McNeish, Daniel; An, Ji; Hancock, Gregory R

    2017-03-02

    Latent variable modeling is a popular and flexible statistical framework. Concomitant with fitting latent variable models is assessment of how well the theoretical model fits the observed data. Although firm cutoffs for these fit indexes are often cited, recent statistical proofs and simulations have shown that these fit indexes are highly susceptible to measurement quality. For instance, a root mean square error of approximation (RMSEA) value of 0.06 (conventionally thought to indicate good fit) can actually indicate poor fit with poor measurement quality (e.g., standardized factors loadings of around 0.40). Conversely, an RMSEA value of 0.20 (conventionally thought to indicate very poor fit) can indicate acceptable fit with very high measurement quality (standardized factor loadings around 0.90). Despite the wide-ranging effect on applications of latent variable models, the high level of technical detail involved with this phenomenon has curtailed the exposure of these important findings to empirical researchers who are employing these methods. This article briefly reviews these methodological studies in minimal technical detail and provides a demonstration to easily quantify the large influence measurement quality has on fit index values and how greatly the cutoffs would change if they were derived under an alternative level of measurement quality. Recommendations for best practice are also discussed.

  12. Identifying best-fitting inputs in health-economic model calibration: a Pareto frontier approach.

    Science.gov (United States)

    Enns, Eva A; Cipriano, Lauren E; Simons, Cyrena T; Kong, Chung Yin

    2015-02-01

    To identify best-fitting input sets using model calibration, individual calibration target fits are often combined into a single goodness-of-fit (GOF) measure using a set of weights. Decisions in the calibration process, such as which weights to use, influence which sets of model inputs are identified as best-fitting, potentially leading to different health economic conclusions. We present an alternative approach to identifying best-fitting input sets based on the concept of Pareto-optimality. A set of model inputs is on the Pareto frontier if no other input set simultaneously fits all calibration targets as well or better. We demonstrate the Pareto frontier approach in the calibration of 2 models: a simple, illustrative Markov model and a previously published cost-effectiveness model of transcatheter aortic valve replacement (TAVR). For each model, we compare the input sets on the Pareto frontier to an equal number of best-fitting input sets according to 2 possible weighted-sum GOF scoring systems, and we compare the health economic conclusions arising from these different definitions of best-fitting. For the simple model, outcomes evaluated over the best-fitting input sets according to the 2 weighted-sum GOF schemes were virtually nonoverlapping on the cost-effectiveness plane and resulted in very different incremental cost-effectiveness ratios ($79,300 [95% CI 72,500-87,600] v. $139,700 [95% CI 79,900-182,800] per quality-adjusted life-year [QALY] gained). Input sets on the Pareto frontier spanned both regions ($79,000 [95% CI 64,900-156,200] per QALY gained). The TAVR model yielded similar results. Choices in generating a summary GOF score may result in different health economic conclusions. The Pareto frontier approach eliminates the need to make these choices by using an intuitive and transparent notion of optimality as the basis for identifying best-fitting input sets. © The Author(s) 2014.

  13. Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

    Science.gov (United States)

    Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O’Brien, Katherine R.

    2017-01-01

    When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

  14. The issue of statistical power for overall model fit in evaluating structural equation models

    Directory of Open Access Journals (Sweden)

    Richard HERMIDA

    2015-06-01

    Full Text Available Statistical power is an important concept for psychological research. However, examining the power of a structural equation model (SEM is rare in practice. This article provides an accessible review of the concept of statistical power for the Root Mean Square Error of Approximation (RMSEA index of overall model fit in structural equation modeling. By way of example, we examine the current state of power in the literature by reviewing studies in top Industrial-Organizational (I/O Psychology journals using SEMs. Results indicate that in many studies, power is very low, which implies acceptance of invalid models. Additionally, we examined methodological situations which may have an influence on statistical power of SEMs. Results showed that power varies significantly as a function of model type and whether or not the model is the main model for the study. Finally, results indicated that power is significantly related to model fit statistics used in evaluating SEMs. The results from this quantitative review imply that researchers should be more vigilant with respect to power in structural equation modeling. We therefore conclude by offering methodological best practices to increase confidence in the interpretation of structural equation modeling results with respect to statistical power issues.

  15. Envelope: interactive software for modeling and fitting complex isotope distributions

    Directory of Open Access Journals (Sweden)

    Sykes Michael T

    2008-10-01

    Full Text Available Abstract Background An important aspect of proteomic mass spectrometry involves quantifying and interpreting the isotope distributions arising from mixtures of macromolecules with different isotope labeling patterns. These patterns can be quite complex, in particular with in vivo metabolic labeling experiments producing fractional atomic labeling or fractional residue labeling of peptides or other macromolecules. In general, it can be difficult to distinguish the contributions of species with different labeling patterns to an experimental spectrum and difficult to calculate a theoretical isotope distribution to fit such data. There is a need for interactive and user-friendly software that can calculate and fit the entire isotope distribution of a complex mixture while comparing these calculations with experimental data and extracting the contributions from the differently labeled species. Results Envelope has been developed to be user-friendly while still being as flexible and powerful as possible. Envelope can simultaneously calculate the isotope distributions for any number of different labeling patterns for a given peptide or oligonucleotide, while automatically summing these into a single overall isotope distribution. Envelope can handle fractional or complete atom or residue-based labeling, and the contribution from each different user-defined labeling pattern is clearly illustrated in the interactive display and is individually adjustable. At present, Envelope supports labeling with 2H, 13C, and 15N, and supports adjustments for baseline correction, an instrument accuracy offset in the m/z domain, and peak width. Furthermore, Envelope can display experimental data superimposed on calculated isotope distributions, and calculate a least-squares goodness of fit between the two. All of this information is displayed on the screen in a single graphical user interface. Envelope supports high-quality output of experimental and calculated

  16. Assessing Fit of Cognitive Diagnostic Models: A Case Study

    Science.gov (United States)

    Sinharay, Sandip; Almond, Russell G.

    2007-01-01

    A cognitive diagnostic model uses information from educational experts to describe the relationships between item performances and posited proficiencies. When the cognitive relationships can be described using a fully Bayesian model, Bayesian model checking procedures become available. Checking models tied to cognitive theory of the domains…

  17. Model Fitting Versus Curve Fitting: A Model of Renormalization Provides a Better Account of Age Aftereffects Than a Model of Local Repulsion.

    Science.gov (United States)

    O'Neil, Sean F; Mac, Amy; Rhodes, Gillian; Webster, Michael A

    2015-12-01

    Recently, we proposed that the aftereffects of adapting to facial age are consistent with a renormalization of the perceived age (e.g., so that after adapting to a younger or older age, all ages appear slightly older or younger, respectively). This conclusion has been challenged by arguing that the aftereffects can also be accounted for by an alternative model based on repulsion (in which facial ages above or below the adapting age are biased away from the adaptor). However, we show here that this challenge was based on allowing the fitted functions to take on values which are implausible and incompatible across the different adapting conditions. When the fits are constrained or interpreted in terms of standard assumptions about normalization and repulsion, then the two analyses both agree in pointing to a pattern of renormalization in age aftereffects.

  18. Action potential generation in an anatomically constrained model of medial superior olive axons.

    Science.gov (United States)

    Lehnert, Simon; Ford, Marc C; Alexandrova, Olga; Hellmundt, Franziska; Felmy, Felix; Grothe, Benedikt; Leibold, Christian

    2014-04-09

    Neurons in the medial superior olive (MSO) encode interaural time differences (ITDs) with sustained firing rates of >100 Hz. They are able to generate such high firing rates for several hundred milliseconds despite their extremely low-input resistances of only few megaohms and high synaptic conductances in vivo. The biophysical mechanisms by which these leaky neurons maintain their excitability are not understood. Since action potentials (APs) are usually assumed to be generated in the axon initial segment (AIS), we analyzed anatomical data of proximal MSO axons in Mongolian gerbils and found that the axon diameter is <1 μm and the internode length is ∼100 μm. Using a morphologically constrained computational model of the MSO axon, we show that these thin axons facilitate the excitability of the AIS. However, for ongoing high rates of synaptic inputs the model generates a substantial fraction of APs in its nodes of Ranvier. These distally initiated APs are mediated by a spatial gradient of sodium channel inactivation and a strong somatic current sink. The model also predicts that distal AP initiation increases the dynamic range of the rate code for ITDs.

  19. Covariance Structure Model Fit Testing under Missing Data: An Application of the Supplemented EM Algorithm

    Science.gov (United States)

    Cai, Li; Lee, Taehun

    2009-01-01

    We apply the Supplemented EM algorithm (Meng & Rubin, 1991) to address a chronic problem with the "two-stage" fitting of covariance structure models in the presence of ignorable missing data: the lack of an asymptotically chi-square distributed goodness-of-fit statistic. We show that the Supplemented EM algorithm provides a…

  20. Behavior-based network management: a unique model-based approach to implementing cyber superiority

    Science.gov (United States)

    Seng, Jocelyn M.

    2016-05-01

    Behavior-Based Network Management (BBNM) is a technological and strategic approach to mastering the identification and assessment of network behavior, whether human-driven or machine-generated. Recognizing that all five U.S. Air Force (USAF) mission areas rely on the cyber domain to support, enhance and execute their tasks, BBNM is designed to elevate awareness and improve the ability to better understand the degree of reliance placed upon a digital capability and the operational risk.2 Thus, the objective of BBNM is to provide a holistic view of the digital battle space to better assess the effects of security, monitoring, provisioning, utilization management, allocation to support mission sustainment and change control. Leveraging advances in conceptual modeling made possible by a novel advancement in software design and implementation known as Vector Relational Data Modeling (VRDM™), the BBNM approach entails creating a network simulation in which meaning can be inferred and used to manage network behavior according to policy, such as quickly detecting and countering malicious behavior. Initial research configurations have yielded executable BBNM models as combinations of conceptualized behavior within a network management simulation that includes only concepts of threats and definitions of "good" behavior. A proof of concept assessment called "Lab Rat," was designed to demonstrate the simplicity of network modeling and the ability to perform adaptation. The model was tested on real world threat data and demonstrated adaptive and inferential learning behavior. Preliminary results indicate this is a viable approach towards achieving cyber superiority in today's volatile, uncertain, complex and ambiguous (VUCA) environment.

  1. A model for programmatic assessment fit for purpose.

    NARCIS (Netherlands)

    Vleuten, C.P.M. van der; Schuwirth, L.W.; Driessen, E.W.; Dijkstra, J.; Tigelaar, D.; Baartman, L.K.; Tartwijk, J. van

    2012-01-01

    We propose a model for programmatic assessment in action, which simultaneously optimises assessment for learning and assessment for decision making about learner progress. This model is based on a set of assessment principles that are interpreted from empirical research. It specifies cycles of train

  2. Fitting a Stochastic Model for Golden-Ten

    NARCIS (Netherlands)

    de Vos, J.C.; van der Genugten, B.B.

    1996-01-01

    Golden-Ten is an observation game in which players try to predict the outcome of the motion of a ball rolling down the surface of a drum.This paper describes the motion of the ball as a stochastic model, based on a deterministic, mechanical model.To this end, the motion is split into several stages,

  3. Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits

    Science.gov (United States)

    Kopasakis, George

    2015-01-01

    Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.

  4. Fitting the Two-Higgs-Doublet model of type II

    CERN Document Server

    Eberhardt, Otto

    2014-01-01

    We present the current status of the Two-Higgs-Doublet model of type II. Taking into account all available relevant information, we exclude at $95$% CL sizeable deviations of the so-called alignment limit, in which all couplings of the light CP-even Higgs boson $h$ are Standard-Model-like. While we can set a lower limit of $240$ GeV on the mass of the pseudoscalar Higgs boson at $95$% CL, the mass of the heavy CP-even Higgs boson $H$ can be even lighter than $200$ GeV. The strong constraints on the model parameters also set limits on the triple Higgs couplings: the $hhh$ coupling in the Two-Higgs-Doublet model of type II cannot be larger than in the Standard Model, while the $hhH$ coupling can maximally be $2.5$ times the size of the Standard Model $hhh$ coupling, assuming an $H$ mass below $1$ TeV. The selection of benchmark scenarios which maximize specific effects within the allowed regions for further collider studies is illustrated for the $H$ branching fraction to fermions and gauge bosons. As an exampl...

  5. A model of the medial superior olive explains spatiotemporal features of local field potentials.

    Science.gov (United States)

    Goldwyn, Joshua H; Mc Laughlin, Myles; Verschooten, Eric; Joris, Philip X; Rinzel, John

    2014-08-27

    Local field potentials are important indicators of in vivo neural activity. Sustained, phase-locked, sound-evoked extracellular fields in the mammalian auditory brainstem, known as the auditory neurophonic, reflect the activity of neurons in the medial superior olive (MSO). We develop a biophysically based model of the neurophonic that accounts for features of in vivo extracellular recordings in the cat auditory brainstem. By making plausible idealizations regarding the spatial symmetry of MSO neurons and the temporal synchrony of their afferent inputs, we reduce the challenging problem of computing extracellular potentials in a 3D volume conductor to a one-dimensional problem. We find that postsynaptic currents in bipolar MSO neuron models generate extracellular voltage responses that strikingly resemble in vivo recordings. Simulations reproduce distinctive spatiotemporal features of the in vivo neurophonic response to monaural pure tones: large oscillations (hundreds of microvolts to millivolts), broad spatial reach (millimeter scale), and a dipole-like spatial profile. We also explain how somatic inhibition and the relative timing of bilateral excitation may shape the spatial profile of the neurophonic. We observe in simulations, and find supporting evidence in in vivo data, that coincident excitatory inputs on both dendrites lead to a drastically reduced spatial reach of the neurophonic. This outcome surprises because coincident inputs are thought to evoke maximal firing rates in MSO neurons, and it reconciles previously puzzling evoked potential results in humans and animals. The success of our model, which has no axon or spike-generating sodium currents, suggests that MSO spikes do not contribute appreciably to the neurophonic.

  6. Superior model for fault tolerance computation in designing nano-sized circuit systems

    Energy Technology Data Exchange (ETDEWEB)

    Singh, N. S. S., E-mail: narinderjit@petronas.com.my; Muthuvalu, M. S., E-mail: msmuthuvalu@gmail.com [Fundamental and Applied Sciences Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak (Malaysia); Asirvadam, V. S., E-mail: vijanth-sagayan@petronas.com.my [Electrical and Electronics Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak (Malaysia)

    2014-10-24

    As CMOS technology scales nano-metrically, reliability turns out to be a decisive subject in the design methodology of nano-sized circuit systems. As a result, several computational approaches have been developed to compute and evaluate reliability of desired nano-electronic circuits. The process of computing reliability becomes very troublesome and time consuming as the computational complexity build ups with the desired circuit size. Therefore, being able to measure reliability instantly and superiorly is fast becoming necessary in designing modern logic integrated circuits. For this purpose, the paper firstly looks into the development of an automated reliability evaluation tool based on the generalization of Probabilistic Gate Model (PGM) and Boolean Difference-based Error Calculator (BDEC) models. The Matlab-based tool allows users to significantly speed-up the task of reliability analysis for very large number of nano-electronic circuits. Secondly, by using the developed automated tool, the paper explores into a comparative study involving reliability computation and evaluation by PGM and, BDEC models for different implementations of same functionality circuits. Based on the reliability analysis, BDEC gives exact and transparent reliability measures, but as the complexity of the same functionality circuits with respect to gate error increases, reliability measure by BDEC tends to be lower than the reliability measure by PGM. The lesser reliability measure by BDEC is well explained in this paper using distribution of different signal input patterns overtime for same functionality circuits. Simulation results conclude that the reliability measure by BDEC depends not only on faulty gates but it also depends on circuit topology, probability of input signals being one or zero and also probability of error on signal lines.

  7. SPSS macros to compare any two fitted values from a regression model.

    Science.gov (United States)

    Weaver, Bruce; Dubois, Sacha

    2012-12-01

    In regression models with first-order terms only, the coefficient for a given variable is typically interpreted as the change in the fitted value of Y for a one-unit increase in that variable, with all other variables held constant. Therefore, each regression coefficient represents the difference between two fitted values of Y. But the coefficients represent only a fraction of the possible fitted value comparisons that might be of interest to researchers. For many fitted value comparisons that are not captured by any of the regression coefficients, common statistical software packages do not provide the standard errors needed to compute confidence intervals or carry out statistical tests-particularly in more complex models that include interactions, polynomial terms, or regression splines. We describe two SPSS macros that implement a matrix algebra method for comparing any two fitted values from a regression model. The !OLScomp and !MLEcomp macros are for use with models fitted via ordinary least squares and maximum likelihood estimation, respectively. The output from the macros includes the standard error of the difference between the two fitted values, a 95% confidence interval for the difference, and a corresponding statistical test with its p-value.

  8. Using proper regression methods for fitting the Langmuir model to sorption data

    Science.gov (United States)

    The Langmuir model, originally developed for the study of gas sorption to surfaces, is one of the most commonly used models for fitting phosphorus sorption data. There are good theoretical reasons, however, against applying this model to describe P sorption to soils. Nevertheless, the Langmuir model...

  9. Efficient parallel Levenberg-Marquardt model fitting towards real-time automated parametric imaging microscopy.

    Science.gov (United States)

    Zhu, Xiang; Zhang, Dianwen

    2013-01-01

    We present a fast, accurate and robust parallel Levenberg-Marquardt minimization optimizer, GPU-LMFit, which is implemented on graphics processing unit for high performance scalable parallel model fitting processing. GPU-LMFit can provide a dramatic speed-up in massive model fitting analyses to enable real-time automated pixel-wise parametric imaging microscopy. We demonstrate the performance of GPU-LMFit for the applications in superresolution localization microscopy and fluorescence lifetime imaging microscopy.

  10. Efficient Parallel Levenberg-Marquardt Model Fitting towards Real-Time Automated Parametric Imaging Microscopy

    OpenAIRE

    Xiang Zhu; Dianwen Zhang

    2013-01-01

    We present a fast, accurate and robust parallel Levenberg-Marquardt minimization optimizer, GPU-LMFit, which is implemented on graphics processing unit for high performance scalable parallel model fitting processing. GPU-LMFit can provide a dramatic speed-up in massive model fitting analyses to enable real-time automated pixel-wise parametric imaging microscopy. We demonstrate the performance of GPU-LMFit for the applications in superresolution localization microscopy and fluorescence lifetim...

  11. The empirical likelihood goodness-of-fit test for regression model

    Institute of Scientific and Technical Information of China (English)

    Li-xing ZHU; Yong-song QIN; Wang-li XU

    2007-01-01

    Goodness-of-fit test for regression modes has received much attention in literature. In this paper, empirical likelihood (EL) goodness-of-fit tests for regression models including classical parametric and autoregressive (AR) time series models are proposed. Unlike the existing locally smoothing and globally smoothing methodologies, the new method has the advantage that the tests are self-scale invariant and that the asymptotic null distribution is chi-squared. Simulations are carried out to illustrate the methodology.

  12. A fitness model for the Italian Interbank Money Market

    CERN Document Server

    De Masi, G; Iori, G

    2006-01-01

    We use the theory of complex networks in order to quantitatively characterize the formation of communities in a particular financial market. The system is composed by different banks exchanging on a daily basis loans and debts of liquidity. Through topological analysis and by means of a model of network growth we can determine the formation of different group of banks characterized by different business strategy. The model based on Pareto's Law makes no use of growth or preferential attachment and it reproduces correctly all the various statistical properties of the system. We believe that this network modeling of the market could be an efficient way to evaluate the impact of different policies in the market of liquidity.

  13. Fitness model for the Italian interbank money market

    Science.gov (United States)

    de Masi, G.; Iori, G.; Caldarelli, G.

    2006-12-01

    We use the theory of complex networks in order to quantitatively characterize the formation of communities in a particular financial market. The system is composed by different banks exchanging on a daily basis loans and debts of liquidity. Through topological analysis and by means of a model of network growth we can determine the formation of different group of banks characterized by different business strategy. The model based on Pareto’s law makes no use of growth or preferential attachment and it reproduces correctly all the various statistical properties of the system. We believe that this network modeling of the market could be an efficient way to evaluate the impact of different policies in the market of liquidity.

  14. A no-scale inflationary model to fit them all

    Energy Technology Data Exchange (ETDEWEB)

    Ellis, John [Theoretical Particle Physics and Cosmology Group, Department of Physics, King' s College London, WC2R 2LS London (United Kingdom); García, Marcos A.G.; Olive, Keith A. [William I. Fine Theoretical Physics Institute, School of Physics and Astronomy, University of Minnesota, 116 Church Street SE, Minneapolis, MN 55455 (United States); Nanopoulos, Dimitri V., E-mail: john.ellis@cern.ch, E-mail: garciagarcia@physics.umn.edu, E-mail: dimitri@physics.tamu.edu, E-mail: olive@physics.umn.edu [George P. and Cynthia W. Mitchell Institute for Fundamental Physics and Astronomy, Texas A and M University, College Station, 77843 Texas (United States)

    2014-08-01

    The magnitude of B-mode polarization in the cosmic microwave background as measured by BICEP2 favours models of chaotic inflation with a quadratic m{sup 2} φ{sup 2}/2 potential, whereas data from the Planck satellite favour a small value of the tensor-to-scalar perturbation ratio r that is highly consistent with the Starobinsky R +R{sup 2} model. Reality may lie somewhere between these two scenarios. In this paper we propose a minimal two-field no-scale supergravity model that interpolates between quadratic and Starobinsky-like inflation as limiting cases, while retaining the successful prediction n{sub s} ≅ 0.96.

  15. Fitness model for the Italian interbank money market.

    Science.gov (United States)

    De Masi, G; Iori, G; Caldarelli, G

    2006-12-01

    We use the theory of complex networks in order to quantitatively characterize the formation of communities in a particular financial market. The system is composed by different banks exchanging on a daily basis loans and debts of liquidity. Through topological analysis and by means of a model of network growth we can determine the formation of different group of banks characterized by different business strategy. The model based on Pareto's law makes no use of growth or preferential attachment and it reproduces correctly all the various statistical properties of the system. We believe that this network modeling of the market could be an efficient way to evaluate the impact of different policies in the market of liquidity.

  16. BOUSSINESQ MODELLING OF NEARSHORE WAVES UNDER BODY FITTED COORDINATE

    Institute of Scientific and Technical Information of China (English)

    FANG Ke-zhao; ZOU Zhi-li; LIU Zhong-bo; YIN Ji-wei

    2012-01-01

    A set of nonlinear Boussinesq equations with fully nonlinearity property is solved numerically in generalized coordinates,to develop a Boussinesq-type wave model in dealing with irregular computation boundaries in complex nearshore regions and to facilitate the grid refinements in simulations.The governing equations expressed in contravariant components of velocity vectors under curv ilinear coordinates are derived and a high order finite difference scheme on a staggered grid is employed for the numerical implementation.The developed model is used to simulate nearshore wave propagations under curvilinear coordinates,the numerical results are compared against analytical or experimental data with a good agreement.

  17. Information Theoretic Tools for Parameter Fitting in Coarse Grained Models

    KAUST Repository

    Kalligiannaki, Evangelia

    2015-01-07

    We study the application of information theoretic tools for model reduction in the case of systems driven by stochastic dynamics out of equilibrium. The model/dimension reduction is considered by proposing parametrized coarse grained dynamics and finding the optimal parameter set for which the relative entropy rate with respect to the atomistic dynamics is minimized. The minimization problem leads to a generalization of the force matching methods to non equilibrium systems. A multiplicative noise example reveals the importance of the diffusion coefficient in the optimization problem.

  18. Design of spatial experiments: Model fitting and prediction

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, V.V.

    1996-03-01

    The main objective of the paper is to describe and develop model oriented methods and algorithms for the design of spatial experiments. Unlike many other publications in this area, the approach proposed here is essentially based on the ideas of convex design theory.

  19. Reducing uncertainty based on model fitness: Application to a ...

    African Journals Online (AJOL)

    2015-01-07

    Jan 7, 2015 ... 2Hydrology and Water Quality, Agricultural and Biological Engineering ... This general methodology is applied to a reservoir model of the Okavango ... Global sensitivity and uncertainty analysis (GSA/UA) system- ... and weighing risks between decisions (Saltelli et al., 2008). ...... resources and support.

  20. On assessing model fit for distribution-free longitudinal models under missing data.

    Science.gov (United States)

    Wu, P; Tu, X M; Kowalski, J

    2014-01-15

    The generalized estimating equation (GEE), a distribution-free, or semi-parametric, approach for modeling longitudinal data, is used in a wide range of behavioral, psychotherapy, pharmaceutical drug safety, and healthcare-related research studies. Most popular methods for assessing model fit are based on the likelihood function for parametric models, rendering them inappropriate for distribution-free GEE. One rare exception is a score statistic initially proposed by Tsiatis for logistic regression (1980) and later extended by Barnhart and Willamson to GEE (1998). Because GEE only provides valid inference under the missing completely at random assumption and missing values arising in most longitudinal studies do not follow such a restricted mechanism, this GEE-based score test has very limited applications in practice. We propose extensions of this goodness-of-fit test to address missing data under the missing at random assumption, a more realistic model that applies to most studies in practice. We examine the performance of the proposed tests using simulated data and demonstrate the utilities of such tests with data from a real study on geriatric depression and associated medical comorbidities.

  1. Superiority of Classification Tree versus Cluster, Fuzzy and Discriminant Models in a Heartbeat Classification System.

    Directory of Open Access Journals (Sweden)

    Vessela Krasteva

    Full Text Available This study presents a 2-stage heartbeat classifier of supraventricular (SVB and ventricular (VB beats. Stage 1 makes computationally-efficient classification of SVB-beats, using simple correlation threshold criterion for finding close match with a predominant normal (reference beat template. The non-matched beats are next subjected to measurement of 20 basic features, tracking the beat and reference template morphology and RR-variability for subsequent refined classification in SVB or VB-class by Stage 2. Four linear classifiers are compared: cluster, fuzzy, linear discriminant analysis (LDA and classification tree (CT, all subjected to iterative training for selection of the optimal feature space among extended 210-sized set, embodying interactive second-order effects between 20 independent features. The optimization process minimizes at equal weight the false positives in SVB-class and false negatives in VB-class. The training with European ST-T, AHA, MIT-BIH Supraventricular Arrhythmia databases found the best performance settings of all classification models: Cluster (30 features, Fuzzy (72 features, LDA (142 coefficients, CT (221 decision nodes with top-3 best scored features: normalized current RR-interval, higher/lower frequency content ratio, beat-to-template correlation. Unbiased test-validation with MIT-BIH Arrhythmia database rates the classifiers in descending order of their specificity for SVB-class: CT (99.9%, LDA (99.6%, Cluster (99.5%, Fuzzy (99.4%; sensitivity for ventricular ectopic beats as part from VB-class (commonly reported in published beat-classification studies: CT (96.7%, Fuzzy (94.4%, LDA (94.2%, Cluster (92.4%; positive predictivity: CT (99.2%, Cluster (93.6%, LDA (93.0%, Fuzzy (92.4%. CT has superior accuracy by 0.3-6.8% points, with the advantage for easy model complexity configuration by pruning the tree consisted of easy interpretable 'if-then' rules.

  2. Goodness-of-fit tests in mixed models

    KAUST Repository

    Claeskens, Gerda

    2009-05-12

    Mixed models, with both random and fixed effects, are most often estimated on the assumption that the random effects are normally distributed. In this paper we propose several formal tests of the hypothesis that the random effects and/or errors are normally distributed. Most of the proposed methods can be extended to generalized linear models where tests for non-normal distributions are of interest. Our tests are nonparametric in the sense that they are designed to detect virtually any alternative to normality. In case of rejection of the null hypothesis, the nonparametric estimation method that is used to construct a test provides an estimator of the alternative distribution. © 2009 Sociedad de Estadística e Investigación Operativa.

  3. Network growth models: A behavioural basis for attachment proportional to fitness

    Science.gov (United States)

    Bell, Michael; Perera, Supun; Piraveenan, Mahendrarajah; Bliemer, Michiel; Latty, Tanya; Reid, Chris

    2017-01-01

    Several growth models have been proposed in the literature for scale-free complex networks, with a range of fitness-based attachment models gaining prominence recently. However, the processes by which such fitness-based attachment behaviour can arise are less well understood, making it difficult to compare the relative merits of such models. This paper analyses an evolutionary mechanism that would give rise to a fitness-based attachment process. In particular, it is proven by analytical and numerical methods that in homogeneous networks, the minimisation of maximum exposure to node unfitness leads to attachment probabilities that are proportional to node fitness. This result is then extended to heterogeneous networks, with supply chain networks being used as an example. PMID:28205599

  4. Structural model of in-group dynamic of 6-10 years old boys’ motor fitness

    Directory of Open Access Journals (Sweden)

    Ivashchenko O.V.

    2015-10-01

    Full Text Available Purpose: to determine structural model of in-group dynamic of 6-10 years old boys’ motor fitness. Material: in the research 6 years old boys (n=48, 7 years old (n=45, 8 years old (n=60, 9 years’ age (n=47 and10 years’ age (n=40 participated. We carried out analysis of factorial model of schoolchildren’s motor fitness. Results: we received information for taking decisions in monitoring of physical education. This information is also necessary for working out of effective programs of children’s and adolescents’ physical training. We determined model of motor fitness and specified informative tests for pedagogic control in every age group. In factorial model of boys’ motor fitness the following factor is the most significant: for 6 years - complex development of motor skills; for 7 years - also complex development of motor skills; for 8 years - strength and coordination; for 9 years - complex development of motor skills; for 10 years - complex development of motor skills. Conclusions: In factorial model of 6-10 years old boys’ motor fitness the most significant are backbone and shoulder joints’ mobility, complex manifestation of motor skills, motor coordination. The most informative tests for assessment of different age boys’ motor fitness have been determined.

  5. Adaptation in tunably rugged fitness landscapes: the rough Mount Fuji model.

    Science.gov (United States)

    Neidhart, Johannes; Szendro, Ivan G; Krug, Joachim

    2014-10-01

    Much of the current theory of adaptation is based on Gillespie's mutational landscape model (MLM), which assumes that the fitness values of genotypes linked by single mutational steps are independent random variables. On the other hand, a growing body of empirical evidence shows that real fitness landscapes, while possessing a considerable amount of ruggedness, are smoother than predicted by the MLM. In the present article we propose and analyze a simple fitness landscape model with tunable ruggedness based on the rough Mount Fuji (RMF) model originally introduced by Aita et al. in the context of protein evolution. We provide a comprehensive collection of results pertaining to the topographical structure of RMF landscapes, including explicit formulas for the expected number of local fitness maxima, the location of the global peak, and the fitness correlation function. The statistics of single and multiple adaptive steps on the RMF landscape are explored mainly through simulations, and the results are compared to the known behavior in the MLM model. Finally, we show that the RMF model can explain the large number of second-step mutations observed on a highly fit first-step background in a recent evolution experiment with a microvirid bacteriophage.

  6. Gfitter - Revisiting the global electroweak fit of the Standard Model and beyond

    Energy Technology Data Exchange (ETDEWEB)

    Flaecher, H.; Hoecker, A. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Goebel, M. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)]|[Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany)]|[Hamburg Univ. (Germany). Inst. fuer Experimentalphysik; Haller, J. [Hamburg Univ. (Germany). Inst. fuer Experimentalphysik; Moenig, K.; Stelzer, J. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)]|[Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany)

    2008-11-15

    The global fit of the Standard Model to electroweak precision data, routinely performed by the LEP electroweak working group and others, demonstrated impressively the predictive power of electroweak unification and quantum loop corrections. We have revisited this fit in view of (i) the development of the new generic fitting package, Gfitter, allowing flexible and efficient model testing in high-energy physics, (ii) the insertion of constraints from direct Higgs searches at LEP and the Tevatron, and (iii) a more thorough statistical interpretation of the results. Gfitter is a modular fitting toolkit, which features predictive theoretical models as independent plugins, and a statistical analysis of the fit results using toy Monte Carlo techniques. The state-of-the-art electroweak Standard Model is fully implemented, as well as generic extensions to it. Theoretical uncertainties are explicitly included in the fit through scale parameters varying within given error ranges. This paper introduces the Gfitter project, and presents state-of-the-art results for the global electroweak fit in the Standard Model, and for a model with an extended Higgs sector (2HDM). Numerical and graphical results for fits with and without including the constraints from the direct Higgs searches at LEP and Tevatron are given. Perspectives for future colliders are analysed and discussed. Including the direct Higgs searches, we find M{sub H}=116.4{sup +18.3}{sub -1.3} GeV, and the 2{sigma} and 3{sigma} allowed regions [114,145] GeV and [[113,168] and [180,225

  7. Model independent analysis of dark energy I: Supernova fitting result

    CERN Document Server

    Gong, Y

    2004-01-01

    The nature of dark energy is a mystery to us. This paper uses the supernova data to explore the property of dark energy by some model independent methods. We first Talyor expanded the scale factor $a(t)$ to find out the deceleration parameter $q_0<0$. This result just invokes the Robertson-Walker metric. Then we discuss several different parameterizations used in the literature. We find that $\\Omega_{\\rm DE0}$ is almost less than -1 at $1\\sigma$ level. We also find that the transition redshift from deceleration phase to acceleration phase is $z_{\\rm T}\\sim 0.3$.

  8. Comparative model accuracy of a data-fitted generalized Aw-Rascle-Zhang model

    CERN Document Server

    Fan, Shimao; Seibold, Benjamin

    2013-01-01

    The Aw-Rascle-Zhang (ARZ) model can be interpreted as a generalization of the Lighthill-Whitham-Richards (LWR) model, possessing a family of fundamental diagram curves, each of which represents a class of drivers with a different empty road velocity. A weakness of this approach is that different drivers possess vastly different densities at which traffic flow stagnates. This drawback can be overcome by modifying the pressure relation in the ARZ model, leading to the generalized Aw-Rascle-Zhang (GARZ) model. We present an approach to determine the parameter functions of the GARZ model from fundamental diagram measurement data. The predictive accuracy of the resulting data-fitted GARZ model is compared to other traffic models by means of a three-detector test setup, employing two types of data: vehicle trajectory data, and sensor data. This work also considers the extension of the ARZ and the GARZ models to models with a relaxation term, and conducts an investigation of the optimal relaxation time.

  9. Assessing Fit of Alternative Unidimensional Polytomous IRT Models Using Posterior Predictive Model Checking.

    Science.gov (United States)

    Li, Tongyun; Xie, Chao; Jiao, Hong

    2016-05-30

    This article explored the application of the posterior predictive model checking (PPMC) method in assessing fit for unidimensional polytomous item response theory (IRT) models, specifically the divide-by-total models (e.g., the generalized partial credit model). Previous research has primarily focused on using PPMC in model checking for unidimensional and multidimensional IRT models for dichotomous data, and has paid little attention to polytomous models. A Monte Carlo simulation was conducted to investigate the performance of PPMC in detecting different sources of misfit for the partial credit model family. Results showed that the PPMC method, in combination with appropriate discrepancy measures, had adequate power in detecting different sources of misfit for the partial credit model family. Global odds ratio and item total correlation exhibited specific patterns in detecting the absence of the slope parameter, whereas Yen's Q1 was found to be promising in the detection of misfit caused by the constant category intersection parameter constraint across items. (PsycINFO Database Record

  10. Are Fit Indices Biased in Favor of Bi-Factor Models in Cognitive Ability Research?: A Comparison of Fit in Correlated Factors, Higher-Order, and Bi-Factor Models via Monte Carlo Simulations

    Directory of Open Access Journals (Sweden)

    Grant B. Morgan

    2015-02-01

    Full Text Available Bi-factor confirmatory factor models have been influential in research on cognitive abilities because they often better fit the data than correlated factors and higher-order models. They also instantiate a perspective that differs from that offered by other models. Motivated by previous work that hypothesized an inherent statistical bias of fit indices favoring the bi-factor model, we compared the fit of correlated factors, higher-order, and bi-factor models via Monte Carlo methods. When data were sampled from a true bi-factor structure, each of the approximate fit indices was more likely than not to identify the bi-factor solution as the best fitting. When samples were selected from a true multiple correlated factors structure, approximate fit indices were more likely overall to identify the correlated factors solution as the best fitting. In contrast, when samples were generated from a true higher-order structure, approximate fit indices tended to identify the bi-factor solution as best fitting. There was extensive overlap of fit values across the models regardless of true structure. Although one model may fit a given dataset best relative to the other models, each of the models tended to fit the data well in absolute terms. Given this variability, models must also be judged on substantive and conceptual grounds.

  11. Revisiting a Statistical Shortcoming When Fitting the Langmuir Model to Sorption Data

    Science.gov (United States)

    The Langmuir model is commonly used for describing sorption behavior of reactive solutes to surfaces. Fitting the Langmuir model to sorption data requires either the use of nonlinear regression or, alternatively, linear regression using one of the linearized versions of the model. Statistical limit...

  12. A simple model of group selection that cannot be analyzed with inclusive fitness

    NARCIS (Netherlands)

    M. van Veelen; S. Luo; B. Simon

    2014-01-01

    A widespread claim in evolutionary theory is that every group selection model can be recast in terms of inclusive fitness. Although there are interesting classes of group selection models for which this is possible, we show that it is not true in general. With a simple set of group selection models,

  13. Blood Pool Segmentation Results in Superior Virtual Cardiac Models than Myocardial Segmentation for 3D Printing.

    Science.gov (United States)

    Farooqi, Kanwal M; Lengua, Carlos Gonzalez; Weinberg, Alan D; Nielsen, James C; Sanz, Javier

    2016-08-01

    The method of cardiac magnetic resonance (CMR) three-dimensional (3D) image acquisition and post-processing which should be used to create optimal virtual models for 3D printing has not been studied systematically. Patients (n = 19) who had undergone CMR including both 3D balanced steady-state free precession (bSSFP) imaging and contrast-enhanced magnetic resonance angiography (MRA) were retrospectively identified. Post-processing for the creation of virtual 3D models involved using both myocardial (MS) and blood pool (BP) segmentation, resulting in four groups: Group 1-bSSFP/MS, Group 2-bSSFP/BP, Group 3-MRA/MS and Group 4-MRA/BP. The models created were assessed by two raters for overall quality (1-poor; 2-good; 3-excellent) and ability to identify predefined vessels (1-5: superior vena cava, inferior vena cava, main pulmonary artery, ascending aorta and at least one pulmonary vein). A total of 76 virtual models were created from 19 patient CMR datasets. The mean overall quality scores for Raters 1/2 were 1.63 ± 0.50/1.26 ± 0.45 for Group 1, 2.12 ± 0.50/2.26 ± 0.73 for Group 2, 1.74 ± 0.56/1.53 ± 0.61 for Group 3 and 2.26 ± 0.65/2.68 ± 0.48 for Group 4. The numbers of identified vessels for Raters 1/2 were 4.11 ± 1.32/4.05 ± 1.31 for Group 1, 4.90 ± 0.46/4.95 ± 0.23 for Group 2, 4.32 ± 1.00/4.47 ± 0.84 for Group 3 and 4.74 ± 0.56/4.63 ± 0.49 for Group 4. Models created using BP segmentation (Groups 2 and 4) received significantly higher ratings than those created using MS for both overall quality and number of vessels visualized (p printed on desktop 3D printers with good quality and accurate representation of the virtual 3D models. We recommend using BP segmentation with either MRA or bSSFP source datasets to create virtual 3D models for 3D printing. Desktop 3D printers can offer good quality printed models with accurate representation of anatomic detail.

  14. Development of a program to fit data to a new logistic model for microbial growth.

    Science.gov (United States)

    Fujikawa, Hiroshi; Kano, Yoshihiro

    2009-06-01

    Recently we developed a mathematical model for microbial growth in food. The model successfully predicted microbial growth at various patterns of temperature. In this study, we developed a program to fit data to the model with a spread sheet program, Microsoft Excel. Users can instantly get curves fitted to the model by inputting growth data and choosing the slope portion of a curve. The program also could estimate growth parameters including the rate constant of growth and the lag period. This program would be a useful tool for analyzing growth data and further predicting microbial growth.

  15. ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks

    Directory of Open Access Journals (Sweden)

    David R. Hunter

    2008-12-01

    Full Text Available We describe some of the capabilities of the ergm package and the statistical theory underlying it. This package contains tools for accomplishing three important, and inter-related, tasks involving exponential-family random graph models (ERGMs: estimation, simulation, and goodness of fit. More precisely, ergm has the capability of approximating a maximum likelihood estimator for an ERGM given a network data set; simulating new network data sets from a fitted ERGM using Markov chain Monte Carlo; and assessing how well a fitted ERGM does at capturing characteristics of a particular network data set.

  16. Efficient fitting of multiplanet Keplerian models to radial velocity and astrometry data

    CERN Document Server

    Howard, J T Wright A W

    2009-01-01

    We describe a technique for solving for the orbital elements of multiple planets from radial velocity (RV) and/or astrometric data taken with 1 m/s and microarcsecond precision, appropriate for efforts to detect Earth-massed planets in their stars' habitable zones, such as NASA's proposed Space Interferometry Mission. We include details of calculating analytic derivatives for use in the Levenberg-Marquardt (LM) algorithm for the problems of fitting RV and astrometric data separately and jointly. We also explicate the general method of separating the linear and nonlinear components of a model fit in the context of an LM fit, show how explicit derivatives can be calculated in such a model, and demonstrate the speed up and convergence improvements of such a scheme in the case of a five-planet fit to published radial velocity data for 55 Cnc.

  17. Spin models inferred from patient data faithfully describe HIV fitness landscapes and enable rational vaccine design

    CERN Document Server

    Shekhar, Karthik; Ferguson, Andrew L; Barton, John P; Kardar, Mehran; Chakraborty, Arup K

    2013-01-01

    Mutational escape from vaccine induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of non-equilibrium viral evolution driven by patient-specific immune responses, and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory \\'{a} la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our f...

  18. Spin models inferred from patient-derived viral sequence data faithfully describe HIV fitness landscapes

    Science.gov (United States)

    Shekhar, Karthik; Ruberman, Claire F.; Ferguson, Andrew L.; Barton, John P.; Kardar, Mehran; Chakraborty, Arup K.

    2013-12-01

    Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses.

  19. Facilitating superior chronic disease management through a knowledge-based systems development model.

    Science.gov (United States)

    Wickramasinghe, Nilmini S; Goldberg, Steve

    2008-01-01

    To date, the adoption and diffusion of technology-enabled solutions to deliver better healthcare has been slow. There are many reasons for this. One of the most significant is that the existing methodologies that are normally used in general for Information and Communications Technology (ICT) implementations tend to be less successful in a healthcare context. This paper describes a knowledge-based adaptive mapping to realisation methodology to traverse successfully from idea to realisation rapidly and without compromising rigour so that success ensues. It is discussed in connection with trying to implement superior ICT-enabled approaches to facilitate superior Chronic Disease Management (CDM).

  20. Note: curve fit models for atomic force microscopy cantilever calibration in water.

    Science.gov (United States)

    Kennedy, Scott J; Cole, Daniel G; Clark, Robert L

    2011-11-01

    Atomic force microscopy stiffness calibrations performed on commercial instruments using the thermal noise method on the same cantilever in both air and water can vary by as much as 20% when a simple harmonic oscillator model and white noise are used in curve fitting. In this note, several fitting strategies are described that reduce this difference to about 11%. © 2011 American Institute of Physics

  1. Empirical models of Total Electron Content based on functional fitting over Taiwan during geomagnetic quiet condition

    Directory of Open Access Journals (Sweden)

    Y. Kakinami

    2009-08-01

    Full Text Available Empirical models of Total Electron Content (TEC based on functional fitting over Taiwan (120° E, 24° N have been constructed using data of the Global Positioning System (GPS from 1998 to 2007 during geomagnetically quiet condition (Dst>−30 nT. The models provide TEC as functions of local time (LT, day of year (DOY and the solar activity (F, which are represented by 1–162 days mean of F10.7 and EUV. Other models based on median values have been also constructed and compared with the models based on the functional fitting. Under same values of F parameter, the models based on the functional fitting show better accuracy than those based on the median values in all cases. The functional fitting model using daily EUV is the most accurate with 9.2 TECu of root mean square error (RMS than the 15-days running median with 10.4 TECu RMS and the model of International Reference Ionosphere 2007 (IRI2007 with 14.7 TECu RMS. IRI2007 overestimates TEC when the solar activity is low, and underestimates TEC when the solar activity is high. Though average of 81 days centered running mean of F10.7 and daily F10.7 is often used as indicator of EUV, our result suggests that average of F10.7 mean from 1 to 54 day prior and current day is better than the average of 81 days centered running mean for reproduction of TEC. This paper is for the first time comparing the median based model with the functional fitting model. Results indicate the functional fitting model yielding a better performance than the median based one. Meanwhile we find that the EUV radiation is essential to derive an optimal TEC.

  2. Is Model Fitting Necessary for Model-Based fMRI?

    Directory of Open Access Journals (Sweden)

    Robert C Wilson

    2015-06-01

    Full Text Available Model-based analysis of fMRI data is an important tool for investigating the computational role of different brain regions. With this method, theoretical models of behavior can be leveraged to find the brain structures underlying variables from specific algorithms, such as prediction errors in reinforcement learning. One potential weakness with this approach is that models often have free parameters and thus the results of the analysis may depend on how these free parameters are set. In this work we asked whether this hypothetical weakness is a problem in practice. We first developed general closed-form expressions for the relationship between results of fMRI analyses using different regressors, e.g., one corresponding to the true process underlying the measured data and one a model-derived approximation of the true generative regressor. Then, as a specific test case, we examined the sensitivity of model-based fMRI to the learning rate parameter in reinforcement learning, both in theory and in two previously-published datasets. We found that even gross errors in the learning rate lead to only minute changes in the neural results. Our findings thus suggest that precise model fitting is not always necessary for model-based fMRI. They also highlight the difficulty in using fMRI data for arbitrating between different models or model parameters. While these specific results pertain only to the effect of learning rate in simple reinforcement learning models, we provide a template for testing for effects of different parameters in other models.

  3. Is Model Fitting Necessary for Model-Based fMRI?

    Science.gov (United States)

    Wilson, Robert C; Niv, Yael

    2015-06-01

    Model-based analysis of fMRI data is an important tool for investigating the computational role of different brain regions. With this method, theoretical models of behavior can be leveraged to find the brain structures underlying variables from specific algorithms, such as prediction errors in reinforcement learning. One potential weakness with this approach is that models often have free parameters and thus the results of the analysis may depend on how these free parameters are set. In this work we asked whether this hypothetical weakness is a problem in practice. We first developed general closed-form expressions for the relationship between results of fMRI analyses using different regressors, e.g., one corresponding to the true process underlying the measured data and one a model-derived approximation of the true generative regressor. Then, as a specific test case, we examined the sensitivity of model-based fMRI to the learning rate parameter in reinforcement learning, both in theory and in two previously-published datasets. We found that even gross errors in the learning rate lead to only minute changes in the neural results. Our findings thus suggest that precise model fitting is not always necessary for model-based fMRI. They also highlight the difficulty in using fMRI data for arbitrating between different models or model parameters. While these specific results pertain only to the effect of learning rate in simple reinforcement learning models, we provide a template for testing for effects of different parameters in other models.

  4. Unifying distance-based goodness-of-fit indicators for hydrologic model assessment

    Science.gov (United States)

    Cheng, Qinbo; Reinhardt-Imjela, Christian; Chen, Xi; Schulte, Achim

    2014-05-01

    The goodness-of-fit indicator, i.e. efficiency criterion, is very important for model calibration. However, recently the knowledge about the goodness-of-fit indicators is all empirical and lacks a theoretical support. Based on the likelihood theory, a unified distance-based goodness-of-fit indicator termed BC-GED model is proposed, which uses the Box-Cox (BC) transformation to remove the heteroscedasticity of model errors and the generalized error distribution (GED) with zero-mean to fit the distribution of model errors after BC. The BC-GED model can unify all recent distance-based goodness-of-fit indicators, and reveals the mean square error (MSE) and the mean absolute error (MAE) that are widely used goodness-of-fit indicators imply statistic assumptions that the model errors follow the Gaussian distribution and the Laplace distribution with zero-mean, respectively. The empirical knowledge about goodness-of-fit indicators can be also easily interpreted by BC-GED model, e.g. the sensitivity to high flow of the goodness-of-fit indicators with large power of model errors results from the low probability of large model error in the assumed distribution of these indicators. In order to assess the effect of the parameters (i.e. the BC transformation parameter λ and the GED kurtosis coefficient β also termed the power of model errors) of BC-GED model on hydrologic model calibration, six cases of BC-GED model were applied in Baocun watershed (East China) with SWAT-WB-VSA model. Comparison of the inferred model parameters and model simulation results among the six indicators demonstrates these indicators can be clearly separated two classes by the GED kurtosis β: β >1 and β ≤ 1. SWAT-WB-VSA calibrated by the class β >1 of distance-based goodness-of-fit indicators captures high flow very well and mimics the baseflow very badly, but it calibrated by the class β ≤ 1 mimics the baseflow very well, because first the larger value of β, the greater emphasis is put on

  5. Soft X-ray spectral fits of Geminga with model neutron star atmospheres

    Science.gov (United States)

    Meyer, R. D.; Pavlov, G. G.; Meszaros, P.

    1994-01-01

    The spectrum of the soft X-ray pulsar Geminga consists of two components, a softer one which can be interpreted as thermal-like radiation from the surface of the neutron star, and a harder one interpreted as radiation from a polar cap heated by relativistic particles. We have fitted the soft spectrum using a detailed magnetized hydrogen atmosphere model. The fitting parameters are the hydrogen column density, the effective temperature T(sub eff), the gravitational redshift z, and the distance to radius ratio, for different values of the magnetic field B. The best fits for this model are obtained when B less than or approximately 1 x 10(exp 12) G and z lies on the upper boundary of the explored range (z = 0.45). The values of T(sub eff) approximately = (2-3) x 10(exp 5) K are a factor of 2-3 times lower than the value of T(sub eff) obtained for blackbody fits with the same z. The lower T(sub eff) increases the compatibility with some proposed schemes for fast neutrino cooling of neutron stars (NSs) by the direct Urca process or by exotic matter, but conventional cooling cannot be excluded. The hydrogen atmosphere fits also imply a smaller distance to Geminga than that inferred from a blackbody fit. An accurate evaluation of the distance would require a better knowledge of the ROSAT Position Sensitive Proportional Counter (PSPC) response to the low-energy region of the incident spectrum. Our modeling of the soft component with a cooler magnetized atmosphere also implies that the hard-component fit requires a characteristic temperature which is higher (by a factor of approximately 2-3) and a surface area which is smaller (by a factor of 10(exp 3), compared to previous blackbody fits.

  6. Finite population size effects in quasispecies models with single-peak fitness landscape

    Science.gov (United States)

    Saakian, David B.; Deem, Michael W.; Hu, Chin-Kun

    2012-04-01

    We consider finite population size effects for Crow-Kimura and Eigen quasispecies models with single-peak fitness landscape. We formulate accurately the iteration procedure for the finite population models, then derive the Hamilton-Jacobi equation (HJE) to describe the dynamic of the probability distribution. The steady-state solution of HJE gives the variance of the mean fitness. Our results are useful for understanding the population sizes of viruses in which the infinite population models can give reliable results for biological evolution problems.

  7. Fit of different linear models to the lactation curve of Italian water buffalo

    Directory of Open Access Journals (Sweden)

    N.P.P. Macciotta

    2010-01-01

    Full Text Available Mathematical modelling of lactation curve by suitable functions of time, widely used in the dairy cattle industry, can represent also for buffaloes a fundamental tool for management and breeding decision, where average curves are considered, and for genetic evaluation by random regression models, where individual patterns are fitted.

  8. A fungal growth model fitted to carbon-limited dynamics of Rhizoctonia solani

    NARCIS (Netherlands)

    Jeger, M.J.; Lamour, A.; Gilligan, C.A.; Otten, W.

    2008-01-01

    Here, a quasi-steady-state approximation was used to simplify a mathematical model for fungal growth in carbon-limiting systems, and this was fitted to growth dynamics of the soil-borne plant pathogen and saprotroph Rhizoctonia solani. The model identified a criterion for invasion into

  9. An Assessment of the Nonparametric Approach for Evaluating the Fit of Item Response Models

    Science.gov (United States)

    Liang, Tie; Wells, Craig S.; Hambleton, Ronald K.

    2014-01-01

    As item response theory has been more widely applied, investigating the fit of a parametric model becomes an important part of the measurement process. There is a lack of promising solutions to the detection of model misfit in IRT. Douglas and Cohen introduced a general nonparametric approach, RISE (Root Integrated Squared Error), for detecting…

  10. Modelling metabolic evolution on phenotypic fitness landscapes: a case study on C4 photosynthesis.

    Science.gov (United States)

    Heckmann, David

    2015-12-01

    How did the complex metabolic systems we observe today evolve through adaptive evolution? The fitness landscape is the theoretical framework to answer this question. Since experimental data on natural fitness landscapes is scarce, computational models are a valuable tool to predict landscape topologies and evolutionary trajectories. Careful assumptions about the genetic and phenotypic features of the system under study can simplify the design of such models significantly. The analysis of C4 photosynthesis evolution provides an example for accurate predictions based on the phenotypic fitness landscape of a complex metabolic trait. The C4 pathway evolved multiple times from the ancestral C3 pathway and models predict a smooth 'Mount Fuji' landscape accordingly. The modelled phenotypic landscape implies evolutionary trajectories that agree with data on modern intermediate species, indicating that evolution can be predicted based on the phenotypic fitness landscape. Future directions will have to include structural changes of metabolic fitness landscape structure with changing environments. This will not only answer important evolutionary questions about reversibility of metabolic traits, but also suggest strategies to increase crop yields by engineering the C4 pathway into C3 plants.

  11. Fitting of adaptive neuron model to electrophysiological recordings using particle swarm optimization algorithm

    Science.gov (United States)

    Shan, Bonan; Wang, Jiang; Zhang, Lvxia; Deng, Bin; Wei, Xile

    2017-02-01

    In order to fit neural model’s spiking features to electrophysiological recordings, in this paper, a fitting framework based on particle swarm optimization (PSO) algorithm is proposed to estimate the model parameters in an augmented multi-timescale adaptive threshold (AugMAT) model. PSO algorithm is an advanced evolutionary calculation method based on iteration. Selecting a reasonable criterion function will ensure the effectiveness of PSO algorithm. In this work, firing rate information is used as the main spiking feature and the estimation error of firing rate is selected as the criterion for fitting. A series of simulations are presented to verify the performance of the framework. The first step is model validation; an artificial training data is introduced to test the fitting procedure. Then we talk about the suitable PSO parameters, which exhibit adequate compromise between speediness and accuracy. Lastly, this framework is used to fit the electrophysiological recordings, after three adjustment steps, the features of experimental data are translated into realistic spiking neuron model.

  12. Can a first-order exponential decay model fit heart rate recovery after resistance exercise?

    Science.gov (United States)

    Bartels-Ferreira, Rhenan; de Sousa, Élder D; Trevizani, Gabriela A; Silva, Lilian P; Nakamura, Fábio Y; Forjaz, Cláudia L M; Lima, Jorge Roberto P; Peçanha, Tiago

    2015-03-01

    The time-constant of postexercise heart rate recovery (HRRτ ) obtained by fitting heart rate decay curve by a first-order exponential fitting has being used to assess cardiac autonomic recovery after endurance exercise. The feasibility of this model was not tested after resistance exercise (RE). The aim of this study was to test the goodness of fit of the first-order exponential decay model to fit heart rate recovery (HRR) after RE. Ten healthy subjects participated in the study. The experimental sessions occurred in two separated days and consisted of performance of 1 set of 10 repetitions at 50% or 80% of the load achieved on the one-repetition maximum test [low-intensity (LI) and high-intensity (HI) sessions, respectively]. Heart rate (HR) was continuously registered before and during exercise and also for 10 min of recovery. A monoexponential equation was used to fit the HRR curve during the postexercise period using different time windows (i.e. 30, 60, 90, … 600 s). For each time window, (i) HRRτ was calculated and (ii) variation of HR explained by the model (R(2) goodness of fit index) was assessed. The HRRτ showed stabilization from 360 and 420 s on LI and HI, respectively. Acceptable R(2) values were observed from the 360 s on LI (R(2) > 0.65) and at all tested time windows on HI (R(2) > 0.75). In conclusion, this study showed that using a minimum length of monitoring (~420 s) HRR after RE can be adequately modelled by a first-order exponential fitting. © 2014 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

  13. The Predicting Model of E-commerce Site Based on the Ideas of Curve Fitting

    Science.gov (United States)

    Tao, Zhang; Li, Zhang; Dingjun, Chen

    On the basis of the idea of the second multiplication curve fitting, the number and scale of Chinese E-commerce site is analyzed. A preventing increase model is introduced in this paper, and the model parameters are solved by the software of Matlab. The validity of the preventing increase model is confirmed though the numerical experiment. The experimental results show that the precision of preventing increase model is ideal.

  14. Does the Foreign Income Shock in a Small Open Economy DSGE Model Fit Croatian Data?

    OpenAIRE

    Arčabić, Vladimir; Globan, Tomislav; Nadoveza, Ozana; Rogić Dumančić, Lucija; Tica, Josip

    2016-01-01

    The paper compares theoretical impulse response functions from a DSGE model for a small open economy with an empirical VAR model estimated for the Croatian economy. The theoretical model fits the data well as long as monetary policy is modelled as a fixed exchange rate regime. The paper considers only a foreign output gap shock. A positive foreign shock increases domestic GDP and prices and decreases terms of trade, which is in compliance with theoretical assumptions. Interest rates behave di...

  15. A goodness-of-fit test for occupancy models with correlated within-season revisits

    Science.gov (United States)

    Wright, Wilson; Irvine, Kathryn M.; Rodhouse, Thomas J.

    2016-01-01

    Occupancy modeling is important for exploring species distribution patterns and for conservation monitoring. Within this framework, explicit attention is given to species detection probabilities estimated from replicate surveys to sample units. A central assumption is that replicate surveys are independent Bernoulli trials, but this assumption becomes untenable when ecologists serially deploy remote cameras and acoustic recording devices over days and weeks to survey rare and elusive animals. Proposed solutions involve modifying the detection-level component of the model (e.g., first-order Markov covariate). Evaluating whether a model sufficiently accounts for correlation is imperative, but clear guidance for practitioners is lacking. Currently, an omnibus goodnessof- fit test using a chi-square discrepancy measure on unique detection histories is available for occupancy models (MacKenzie and Bailey, Journal of Agricultural, Biological, and Environmental Statistics, 9, 2004, 300; hereafter, MacKenzie– Bailey test). We propose a join count summary measure adapted from spatial statistics to directly assess correlation after fitting a model. We motivate our work with a dataset of multinight bat call recordings from a pilot study for the North American Bat Monitoring Program. We found in simulations that our join count test was more reliable than the MacKenzie–Bailey test for detecting inadequacy of a model that assumed independence, particularly when serial correlation was low to moderate. A model that included a Markov-structured detection-level covariate produced unbiased occupancy estimates except in the presence of strong serial correlation and a revisit design consisting only of temporal replicates. When applied to two common bat species, our approach illustrates that sophisticated models do not guarantee adequate fit to real data, underscoring the importance of model assessment. Our join count test provides a widely applicable goodness-of-fit test and

  16. Mathematical Modeling of Allelopathy. III. A Model for Curve-Fitting Allelochemical Dose Responses

    Science.gov (United States)

    Liu, De Li; An, Min; Johnson, Ian R.; Lovett, John V.

    2003-01-01

    Bioassay techniques are often used to study the effects of allelochemicals on plant processes, and it is generally observed that the processes are stimulated at low allelochemical concentrations and inhibited as the concentrations increase. A simple empirical model is presented to analyze this type of response. The stimulation-inhibition properties of allelochemical-dose responses can be described by the parameters in the model. The indices, p% reductions, are calculated to assess the allelochemical effects. The model is compared with experimental data for the response of lettuce seedling growth to Centaurepensin, the olfactory response of weevil larvae to α-terpineol, and the responses of annual ryegrass (Lolium multiflorum Lam.), creeping red fescue (Festuca rubra L., cv. Ensylva), Kentucky bluegrass (Poa pratensis L., cv. Kenblue), perennial ryegrass (L. perenne L., cv. Manhattan), and Rebel tall fescue (F. arundinacea Schreb) seedling growth to leachates of Rebel and Kentucky 31 tall fescue. The results show that the model gives a good description to observations and can be used to fit a wide range of dose responses. Assessments of the effects of leachates of Rebel and Kentucky 31 tall fescue clearly differentiate the properties of the allelopathic sources and the relative sensitivities of indicators such as the length of root and leaf. PMID:19330111

  17. Mathematical Modeling of Allelopathy. III. A Model for Curve-Fitting Allelochemical Dose Responses.

    Science.gov (United States)

    Liu, De Li; An, Min; Johnson, Ian R; Lovett, John V

    2003-01-01

    Bioassay techniques are often used to study the effects of allelochemicals on plant processes, and it is generally observed that the processes are stimulated at low allelochemical concentrations and inhibited as the concentrations increase. A simple empirical model is presented to analyze this type of response. The stimulation-inhibition properties of allelochemical-dose responses can be described by the parameters in the model. The indices, p% reductions, are calculated to assess the allelochemical effects. The model is compared with experimental data for the response of lettuce seedling growth to Centaurepensin, the olfactory response of weevil larvae to alpha-terpineol, and the responses of annual ryegrass (Lolium multiflorum Lam.), creeping red fescue (Festuca rubra L., cv. Ensylva), Kentucky bluegrass (Poa pratensis L., cv. Kenblue), perennial ryegrass (L. perenne L., cv. Manhattan), and Rebel tall fescue (F. arundinacea Schreb) seedling growth to leachates of Rebel and Kentucky 31 tall fescue. The results show that the model gives a good description to observations and can be used to fit a wide range of dose responses. Assessments of the effects of leachates of Rebel and Kentucky 31 tall fescue clearly differentiate the properties of the allelopathic sources and the relative sensitivities of indicators such as the length of root and leaf.

  18. Fitting simulated random events to experimental histograms by means of parametric models

    Energy Technology Data Exchange (ETDEWEB)

    Kortner, Oliver E-mail: oliver.kortner@cern.chkortner@mppmu.mpg.de; Zupancic, Crtomir

    2003-05-11

    Classical chi-square quantities are appropriate tools for fitting analytical parameter-dependent models to (multidimensional) measured histograms. In contrast, this article proposes a family of special chi-squares suitable for fits with models which simulate experimental data by Monte Carlo methods, thus introducing additional randomness. We investigate the dependence of such chi-squares on the number of experimental and simulated events in each bin, and on the theoretical parameter-dependent weight linking the two kinds of events. We identify the unknown probability distributions of the weights and their inter-bin correlations as the main obstacle to a general performance analysis of the proposed chi-square quantities.

  19. A new analytical edge spread function fitting model for modulation transfer function measurement

    Institute of Scientific and Technical Information of China (English)

    Tiecheng Li; Huajun Feng; Zhihai Xu

    2011-01-01

    @@ We propose a new analytical edge spread function (ESF) fitting model to measure the modulation transfer function (MTF).The ESF data obtained from a slanted-edge image are fitted to our model through the non-linear least squares (NLLSQ) method.The differentiation of the ESF yields the line spread function (LSF), the Fourier transform of which gives the profile of two-dimensional MTF.Compared with the previous methods, the MTF estimate determined by our method conforms more closely to the reference.A practical application of our MTF measurement in degraded image restoration also validates the accuracy of our model.%We propose a new analytical edge spread function (ESF) fitting model to measure the modulation transfer function (MTF). The ESF data obtained from a slanted-edge image are fitted to our model through the non-linear least squares (NLLSQ) method. The differentiation of the ESF yields the line spread function (LSF), the Fourier transform of which gives the profile of two-dimensional MTF. Compared with the previous methods, the MTF estimate determined by our method conforms more closely to the reference. A practical application of our MTF measurement in degraded image restoration also validates the accuracy of our model.

  20. Fitting and comparing competing models of the species abundance distribution: assessment and prospect

    Directory of Open Access Journals (Sweden)

    Thomas J Matthews

    2014-06-01

    Full Text Available A species abundance distribution (SAD characterises patterns in the commonness and rarity of all species within an ecological community. As such, the SAD provides the theoretical foundation for a number of other biogeographical and macroecological patterns, such as the species–area relationship, as well as being an interesting pattern in its own right. While there has been resurgence in the study of SADs in the last decade, less focus has been placed on methodology in SAD research, and few attempts have been made to synthesise the vast array of methods which have been employed in SAD model evaluation. As such, our review has two aims. First, we provide a general overview of SADs, including descriptions of the commonly used distributions, plotting methods and issues with evaluating SAD models. Second, we review a number of recent advances in SAD model fitting and comparison. We conclude by providing a list of recommendations for fitting and evaluating SAD models. We argue that it is time for SAD studies to move away from many of the traditional methods available for fitting and evaluating models, such as sole reliance on the visual examination of plots, and embrace statistically rigorous techniques. In particular, we recommend the use of both goodness-of-fit tests and model-comparison analyses because each provides unique information which one can use to draw inferences.

  1. Local and omnibus goodness-of-fit tests in classical measurement error models

    KAUST Repository

    Ma, Yanyuan

    2010-09-14

    We consider functional measurement error models, i.e. models where covariates are measured with error and yet no distributional assumptions are made about the mismeasured variable. We propose and study a score-type local test and an orthogonal series-based, omnibus goodness-of-fit test in this context, where no likelihood function is available or calculated-i.e. all the tests are proposed in the semiparametric model framework. We demonstrate that our tests have optimality properties and computational advantages that are similar to those of the classical score tests in the parametric model framework. The test procedures are applicable to several semiparametric extensions of measurement error models, including when the measurement error distribution is estimated non-parametrically as well as for generalized partially linear models. The performance of the local score-type and omnibus goodness-of-fit tests is demonstrated through simulation studies and analysis of a nutrition data set.

  2. Explaining the high voice superiority effect in polyphonic music: evidence from cortical evoked potentials and peripheral auditory models.

    Science.gov (United States)

    Trainor, Laurel J; Marie, Céline; Bruce, Ian C; Bidelman, Gavin M

    2014-02-01

    Natural auditory environments contain multiple simultaneously-sounding objects and the auditory system must parse the incoming complex sound wave they collectively create into parts that represent each of these individual objects. Music often similarly requires processing of more than one voice or stream at the same time, and behavioral studies demonstrate that human listeners show a systematic perceptual bias in processing the highest voice in multi-voiced music. Here, we review studies utilizing event-related brain potentials (ERPs), which support the notions that (1) separate memory traces are formed for two simultaneous voices (even without conscious awareness) in auditory cortex and (2) adults show more robust encoding (i.e., larger ERP responses) to deviant pitches in the higher than in the lower voice, indicating better encoding of the former. Furthermore, infants also show this high-voice superiority effect, suggesting that the perceptual dominance observed across studies might result from neurophysiological characteristics of the peripheral auditory system. Although musically untrained adults show smaller responses in general than musically trained adults, both groups similarly show a more robust cortical representation of the higher than of the lower voice. Finally, years of experience playing a bass-range instrument reduces but does not reverse the high voice superiority effect, indicating that although it can be modified, it is not highly neuroplastic. Results of new modeling experiments examined the possibility that characteristics of middle-ear filtering and cochlear dynamics (e.g., suppression) reflected in auditory nerve firing patterns might account for the higher-voice superiority effect. Simulations show that both place and temporal AN coding schemes well-predict a high-voice superiority across a wide range of interval spacings and registers. Collectively, we infer an innate, peripheral origin for the higher-voice superiority observed in human

  3. Hierarchical Shrinkage Priors and Model Fitting for High-dimensional Generalized Linear Models

    Science.gov (United States)

    Yi, Nengjun; Ma, Shuangge

    2013-01-01

    Genetic and other scientific studies routinely generate very many predictor variables, which can be naturally grouped, with predictors in the same groups being highly correlated. It is desirable to incorporate the hierarchical structure of the predictor variables into generalized linear models for simultaneous variable selection and coefficient estimation. We propose two prior distributions: hierarchical Cauchy and double-exponential distributions, on coefficients in generalized linear models. The hierarchical priors include both variable-specific and group-specific tuning parameters, thereby not only adopting different shrinkage for different coefficients and different groups but also providing a way to pool the information within groups. We fit generalized linear models with the proposed hierarchical priors by incorporating flexible expectation-maximization (EM) algorithms into the standard iteratively weighted least squares as implemented in the general statistical package R. The methods are illustrated with data from an experiment to identify genetic polymorphisms for survival of mice following infection with Listeria monocytogenes. The performance of the proposed procedures is further assessed via simulation studies. The methods are implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). PMID:23192052

  4. Comparing PyMorph and SDSS photometry. I. Background sky and model fitting effects

    Science.gov (United States)

    Fischer, J.-L.; Bernardi, M.; Meert, A.

    2017-01-01

    A number of recent estimates of the total luminosities of galaxies in the SDSS are significantly larger than those reported by the SDSS pipeline. This is because of a combination of three effects: one is simply a matter of defining the scale out to which one integrates the fit when defining the total luminosity, and amounts on average to ≤0.1 mags even for the most luminous galaxies. The other two are less trivial and tend to be larger; they are due to differences in how the background sky is estimated and what model is fit to the surface brightness profile. We show that PyMorph sky estimates are fainter than those of the SDSS DR7 or DR9 pipelines, but are in excellent agreement with the estimates of Blanton et al. (2011). Using the SDSS sky biases luminosities by more than a few tenths of a magnitude for objects with half-light radii ≥7 arcseconds. In the SDSS main galaxy sample these are typically luminous galaxies, so they are not necessarily nearby. This bias becomes worse when allowing the model more freedom to fit the surface brightness profile. When PyMorph sky values are used, then two component Sersic-Exponential fits to E+S0s return more light than single component deVaucouleurs fits (up to ˜0.2 mag), but less light than single Sersic fits (0.1 mag). Finally, we show that PyMorph fits of Meert et al. (2015) to DR7 data remain valid for DR9 images. Our findings show that, especially at large luminosities, these PyMorph estimates should be preferred to the SDSS pipeline values.

  5. Comparing pymorph and SDSS photometry - I. Background sky and model fitting effects

    Science.gov (United States)

    Fischer, J.-L.; Bernardi, M.; Meert, A.

    2017-05-01

    A number of recent estimates of the total luminosities of galaxies in the SDSS are significantly larger than those reported by the Sloan Digital Sky Survey (SDSS) pipeline. This is because of a combination of three effects: one is simply a matter of defining the scale out to which one integrates the fit when defining the total luminosity, and amounts on average to ≤0.1 mag even for the most luminous galaxies. The other two are less trivial and tend to be larger; they are due to differences in how the background sky is estimated and what model is fit to the surface brightness profile. We show that pymorph sky estimates are fainter than those of the Sloan Digital Sky Servey Data Release 7 or Data Release 9 pipelines, but are in excellent agreement with the estimates of Blanton et al. Using the SDSS sky biases luminosities by more than a few tenths of a magnitude for objects with half-light radii ≥7 arcsec. In the SDSS main galaxy sample, these are typically luminous galaxies, so they are not necessarily nearby. This bias becomes worse when allowing the model more freedom to fit the surface brightness profile. When pymorph sky values are used, then two-component Sérsic-exponential fits to E+S0s return more light than single component deVaucouleurs fits (up to ˜0.2 mag), but less light than single Sérsic fits (0.1 mag). Finally, we show that pymorph fits of Meert et al. to DR7 data remain valid for DR9 images. Our findings show that, especially at large luminosities, these pymorph estimates should be preferred to the SDSS pipeline values.

  6. Non-Uniqueness of the Geometry of Interplanetary Magnetic Flux Ropes Obtained from Model-Fitting

    Science.gov (United States)

    Marubashi, K.; Cho, K.-S.

    2015-12-01

    Since the early recognition of the important role of interplanetary magnetic flux ropes (IPFRs) to carry the southward magnetic fields to the Earth, many attempts have been made to determine the structure of the IPFRs by model-fitting analyses to the interplanetary magnetic field variations. This paper describes the results of fitting analyses for three selected solar wind structures in the latter half of 2014. In the fitting analysis a special attention was paid to identification of all the possible models or geometries that can reproduce the observed magnetic field variation. As a result, three or four geometries have been found for each of the three cases. The non-uniqueness of the fitted results include (1) the different geometries naturally stemming from the difference in the models used for fitting, and (2) an unexpected result that either of magnetic field chirality, left-handed and right-handed, can reproduce the observation in some cases. Thus we conclude that the model-fitting cannot always give us a unique geometry of the observed magnetic flux rope. In addition, we have found that the magnetic field chirality of a flux rope cannot be uniquely inferred from the sense of field vector rotation observed in the plane normal to the Earth-Sun line; the sense of rotation changes depending on the direction of the flux rope axis. These findings exert an important impact on the studies aimed at the geometrical relationships between the flux ropes and the magnetic field structures in the solar corona where the flux ropes were produced, such studies being an important step toward predicting geomagnetic storms based on observations of solar eruption phenomena.

  7. Testing the fitness consequences of the thermoregulatory and parental care models for the origin of endothermy.

    Directory of Open Access Journals (Sweden)

    Sabrina Clavijo-Baque

    Full Text Available The origin of endothermy is a puzzling phenomenon in the evolution of vertebrates. To address this issue several explicative models have been proposed. The main models proposed for the origin of endothermy are the aerobic capacity, the thermoregulatory and the parental care models. Our main proposal is that to compare the alternative models, a critical aspect is to determine how strongly natural selection was influenced by body temperature, and basal and maximum metabolic rates during the evolution of endothermy. We evaluate these relationships in the context of three main hypotheses aimed at explaining the evolution of endothermy, namely the parental care hypothesis and two hypotheses related to the thermoregulatory model (thermogenic capacity and higher body temperature models. We used data on basal and maximum metabolic rates and body temperature from 17 rodent populations, and used intrinsic population growth rate (R(max as a global proxy of fitness. We found greater support for the thermogenic capacity model of the thermoregulatory model. In other words, greater thermogenic capacity is associated with increased fitness in rodent populations. To our knowledge, this is the first test of the fitness consequences of the thermoregulatory and parental care models for the origin of endothermy.

  8. The FIT 2.0 Model - Fuel-cycle Integration and Tradeoffs

    Energy Technology Data Exchange (ETDEWEB)

    Steven J. Piet; Nick R. Soelberg; Layne F. Pincock; Eric L. Shaber; Gregory M Teske

    2011-06-01

    All mass streams from fuel separation and fabrication are products that must meet some set of product criteria – fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the “system losses study” team that developed it [Shropshire2009, Piet2010b] are steps by the Fuel Cycle Technology program toward an analysis that accounts for the requirements and capabilities of each fuel cycle component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R&D needs and set longer-term goals. This report describes FIT 2, an update of the original FIT model.[Piet2010c] FIT is a method to analyze different fuel cycles; in particular, to determine how changes in one part of a fuel cycle (say, fuel burnup, cooling, or separation efficiencies) chemically affect other parts of the fuel cycle. FIT provides the following: Rough estimate of physics and mass balance feasibility of combinations of technologies. If feasibility is an issue, it provides an estimate of how performance would have to change to achieve feasibility. Estimate of impurities in fuel and impurities in waste as function of separation performance, fuel fabrication, reactor, uranium source, etc.

  9. The FIT 2.0 Model - Fuel-cycle Integration and Tradeoffs

    Energy Technology Data Exchange (ETDEWEB)

    Steven J. Piet; Nick R. Soelberg; Layne F. Pincock; Eric L. Shaber; Gregory M Teske

    2011-06-01

    All mass streams from fuel separation and fabrication are products that must meet some set of product criteria – fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the “system losses study” team that developed it [Shropshire2009, Piet2010b] are steps by the Fuel Cycle Technology program toward an analysis that accounts for the requirements and capabilities of each fuel cycle component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R&D needs and set longer-term goals. This report describes FIT 2, an update of the original FIT model.[Piet2010c] FIT is a method to analyze different fuel cycles; in particular, to determine how changes in one part of a fuel cycle (say, fuel burnup, cooling, or separation efficiencies) chemically affect other parts of the fuel cycle. FIT provides the following: Rough estimate of physics and mass balance feasibility of combinations of technologies. If feasibility is an issue, it provides an estimate of how performance would have to change to achieve feasibility. Estimate of impurities in fuel and impurities in waste as function of separation performance, fuel fabrication, reactor, uranium source, etc.

  10. Source Localization with Acoustic Sensor Arrays Using Generative Model Based Fitting with Sparse Constraints

    Directory of Open Access Journals (Sweden)

    Javier Macias-Guarasa

    2012-10-01

    Full Text Available This paper presents a novel approach for indoor acoustic source localization using sensor arrays. The proposed solution starts by defining a generative model, designed to explain the acoustic power maps obtained by Steered Response Power (SRP strategies. An optimization approach is then proposed to fit the model to real input SRP data and estimate the position of the acoustic source. Adequately fitting the model to real SRP data, where noise and other unmodelled effects distort the ideal signal, is the core contribution of the paper. Two basic strategies in the optimization are proposed. First, sparse constraints in the parameters of the model are included, enforcing the number of simultaneous active sources to be limited. Second, subspace analysis is used to filter out portions of the input signal that cannot be explained by the model. Experimental results on a realistic speech database show statistically significant localization error reductions of up to 30% when compared with the SRP-PHAT strategies.

  11. A Nonparametric Approach for Assessing Goodness-of-Fit of IRT Models in a Mixed Format Test

    Science.gov (United States)

    Liang, Tie; Wells, Craig S.

    2015-01-01

    Investigating the fit of a parametric model plays a vital role in validating an item response theory (IRT) model. An area that has received little attention is the assessment of multiple IRT models used in a mixed-format test. The present study extends the nonparametric approach, proposed by Douglas and Cohen (2001), to assess model fit of three…

  12. On Fitting Nonlinear Latent Curve Models to Multiple Variables Measured Longitudinally

    Science.gov (United States)

    Blozis, Shelley A.

    2007-01-01

    This article shows how nonlinear latent curve models may be fitted for simultaneous analysis of multiple variables measured longitudinally using Mx statistical software. Longitudinal studies often involve observation of several variables across time with interest in the associations between change characteristics of different variables measured…

  13. Assessing item fit for unidimensional item response theory models using residuals from estimated item response functions.

    Science.gov (United States)

    Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee

    2013-07-01

    Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models.

  14. Longitudinal Changes in Physical Fitness Performance in Youth: A Multilevel Latent Growth Curve Modeling Approach

    Science.gov (United States)

    Wang, Chee Keng John; Pyun, Do Young; Liu, Woon Chia; Lim, Boon San Coral; Li, Fuzhong

    2013-01-01

    Using a multilevel latent growth curve modeling (LGCM) approach, this study examined longitudinal change in levels of physical fitness performance over time (i.e. four years) in young adolescents aged from 12-13 years. The sample consisted of 6622 students from 138 secondary schools in Singapore. Initial analyses found between-school variation on…

  15. Checking the Adequacy of Fit of Models from Split-Plot Designs

    DEFF Research Database (Denmark)

    Almini, A. A.; Kulahci, Murat; Montgomery, D. C.

    2009-01-01

    One of the main features that distinguish split-plot experiments from other experiments is that they involve two types of experimental errors: the whole-plot (WP) error and the subplot (SP) error. Taking this into consideration is very important when computing measures of adequacy of fit for split......-plot models. In this article, we propose the computation of two R-2, R-2-adjusted, prediction error sums of squares (PRESS), and R-2-prediction statistics to measure the adequacy of fit for the WP and the SP submodels in a split-plot design. This is complemented with the graphical analysis of the two types...... of errors to check for any violation of the underlying assumptions and the adequacy of fit of split-plot models. Using examples, we show how computing two measures of model adequacy of fit for each split-plot design model is appropriate and useful as they reveal whether the correct WP and SP effects have...

  16. Fit Gap Analysis – The Role of Business Process Reference Models

    Directory of Open Access Journals (Sweden)

    Dejan Pajk

    2013-12-01

    Full Text Available Enterprise resource planning (ERP systems support solutions for standard business processes such as financial, sales, procurement and warehouse. In order to improve the understandability and efficiency of their implementation, ERP vendors have introduced reference models that describe the processes and underlying structure of an ERP system. To select and successfully implement an ERP system, the capabilities of that system have to be compared with a company’s business needs. Based on a comparison, all of the fits and gaps must be identified and further analysed. This step usually forms part of ERP implementation methodologies and is called fit gap analysis. The paper theoretically overviews methods for applying reference models and describes fit gap analysis processes in detail. The paper’s first contribution is its presentation of a fit gap analysis using standard business process modelling notation. The second contribution is the demonstration of a process-based comparison approach between a supply chain process and an ERP system process reference model. In addition to its theoretical contributions, the results can also be practically applied to projects involving the selection and implementation of ERP systems.

  17. Impact of Missing Data on Person-Model Fit and Person Trait Estimation

    Science.gov (United States)

    Zhang, Bo; Walker, Cindy M.

    2008-01-01

    The purpose of this research was to examine the effects of missing data on person-model fit and person trait estimation in tests with dichotomous items. Under the missing-completely-at-random framework, four missing data treatment techniques were investigated including pairwise deletion, coding missing responses as incorrect, hotdeck imputation,…

  18. Longitudinal Changes in Physical Fitness Performance in Youth: A Multilevel Latent Growth Curve Modeling Approach

    Science.gov (United States)

    Wang, Chee Keng John; Pyun, Do Young; Liu, Woon Chia; Lim, Boon San Coral; Li, Fuzhong

    2013-01-01

    Using a multilevel latent growth curve modeling (LGCM) approach, this study examined longitudinal change in levels of physical fitness performance over time (i.e. four years) in young adolescents aged from 12-13 years. The sample consisted of 6622 students from 138 secondary schools in Singapore. Initial analyses found between-school variation on…

  19. Dynamic modeling and analysis of vortex filament motion using a novel curve-fitting method

    Directory of Open Access Journals (Sweden)

    Chang-Joo Kim

    2016-02-01

    Full Text Available Applications of a novel curve-fitting technique are presented to efficiently predict the motion of the vortex filament, which is trailed from a rigid body such as wings and rotors. The governing equations of the motion, when a Lagrangian approach with the present curve-fitting method is applied, can be transformed into an easily solvable form of the system of nonlinear ordinary differential equations. The applicability of Bézier curves, B-spline, and Lagrange interpolating polynomials is investigated. Local Lagrange interpolating polynomials with a shift operator are proposed as the best selection for applications, since it provides superior system characteristics with minimum computing time, compared to other methods. In addition, the Gauss quadrature formula with local refinement strategy has been developed for an accurate prediction of the induced velocity computed with the line integration of the Biot–Savart law. Rotary-wing problems including a vortex ring problem are analyzed to show the efficiency, accuracy, and flexibility in the applications of the proposed method.

  20. Modeling of pharmaceuticals mixtures toxicity with deviation ratio and best-fit functions models.

    Science.gov (United States)

    Wieczerzak, Monika; Kudłak, Błażej; Yotova, Galina; Nedyalkova, Miroslava; Tsakovski, Stefan; Simeonov, Vasil; Namieśnik, Jacek

    2016-11-15

    The present study deals with assessment of ecotoxicological parameters of 9 drugs (diclofenac (sodium salt), oxytetracycline hydrochloride, fluoxetine hydrochloride, chloramphenicol, ketoprofen, progesterone, estrone, androstenedione and gemfibrozil), present in the environmental compartments at specific concentration levels, and their mutual combinations by couples against Microtox® and XenoScreen YES/YAS® bioassays. As the quantitative assessment of ecotoxicity of drug mixtures is an complex and sophisticated topic in the present study we have used two major approaches to gain specific information on the mutual impact of two separate drugs present in a mixture. The first approach is well documented in many toxicological studies and follows the procedure for assessing three types of models, namely concentration addition (CA), independent action (IA) and simple interaction (SI) by calculation of a model deviation ratio (MDR) for each one of the experiments carried out. The second approach used was based on the assumption that the mutual impact in each mixture of two drugs could be described by a best-fit model function with calculation of weight (regression coefficient or other model parameter) for each of the participants in the mixture or by correlation analysis. It was shown that the sign and the absolute value of the weight or the correlation coefficient could be a reliable measure for the impact of either drug A on drug B or, vice versa, of B on A. Results of studies justify the statement, that both of the approaches show similar assessment of the mode of mutual interaction of the drugs studied. It was found that most of the drug mixtures exhibit independent action and quite few of the mixtures show synergic or dependent action. Copyright © 2016. Published by Elsevier B.V.

  1. UVMULTIFIT: Fitting astronomical radio interferometric data

    Science.gov (United States)

    Marti-Vidal, I.; Vlemmings, W. H. T.; Muller, S.; Casey, S.

    2014-02-01

    UVMULTIFIT, written in Python, is a versatile library for fitting models directly to visibility data. These models can depend on frequency and fitting parameters in an arbitrary algebraic way. The results from the fit to the visibilities of sources with sizes smaller than the diffraction limit of the interferometer are superior to the output obtained from a mere analysis of the deconvolved images. Though UVMULTIFIT is based on the CASA package, it can be easily adapted to other analysis packages that have a Python API.

  2. A CONTRASTIVE ANALYSIS OF THE FACTORIAL STRUCTURE OF THE PCL-R: WHICH MODEL FITS BEST THE DATA?

    Directory of Open Access Journals (Sweden)

    Beatriz Pérez

    2015-01-01

    Full Text Available The aim of this study was to determine which of the factorial solutions proposed for the Hare Psychopathy Checklist-Revised (PCL-R of two, three, four factors, and unidimensional fitted best the data. Two trained and experienced independent raters scored 197 prisoners from the Villabona Penitentiary (Asturias, Spain, age range 21 to 73 years (M = 36.0, SD = 9.7, of whom 60.12% were reoffenders and 73% had committed violent crimes. The results revealed that the two-factor correlational, three-factor hierarchical without testlets, four-factor correlational and hierarchical, and unidimensional models were a poor fit for the data (CFI ≤ .86, and the three-factor model with testlets was a reasonable fit for the data (CFI = .93. The scale resulting from the three-factor hierarchical model with testlets (13 items classified psychopathy significantly higher than the original 20-item scale. The results are discussed in terms of their implications for theoretical models of psychopathy, decision-making, prison classification and intervention, and prevention. Se diseñó un estudio con el objetivo de conocer cuál de las soluciones factoriales propuestas para la Hare Psychopathy Checklist-Revised (PCL-R de dos, tres y cuatro factores y unidimensional era la que presentaba mejor ajuste a los datos. Para ello, dos evaluadores entrenados y con experiencia evaluaron de forma independiente a 197 internos en la prisión Villabona (Asturias, España, con edades comprendidas entre los 21 y los 73 años (M = 36.0, DT = 9.7, de los cuales el 60.12% eran reincidentes y el 73% había cometido delitos violentos. Los resultados mostraron que los modelos unidimensional, correlacional de 2 factores, jerárquico de 3 factores sin testlest y correlacional y jerárquico de 4 factores, presentaban un pobre ajuste con los datos (CFI ≤ .86 y un ajuste razonable del modelo jerárquico de tres factores con testlets (CFI = .93. La escala resultante del modelo de tres factores

  3. Automatic segmentation of vertebral arteries in CT angiography using combined circular and cylindrical model fitting

    Science.gov (United States)

    Lee, Min Jin; Hong, Helen; Chung, Jin Wook

    2014-03-01

    We propose an automatic vessel segmentation method of vertebral arteries in CT angiography using combined circular and cylindrical model fitting. First, to generate multi-segmented volumes, whole volume is automatically divided into four segments by anatomical properties of bone structures along z-axis of head and neck. To define an optimal volume circumscribing vertebral arteries, anterior-posterior bounding and side boundaries are defined as initial extracted vessel region. Second, the initial vessel candidates are tracked using circular model fitting. Since boundaries of the vertebral arteries are ambiguous in case the arteries pass through the transverse foramen in the cervical vertebra, the circle model is extended along z-axis to cylinder model for considering additional vessel information of neighboring slices. Finally, the boundaries of the vertebral arteries are detected using graph-cut optimization. From the experiments, the proposed method provides accurate results without bone artifacts and eroded vessels in the cervical vertebra.

  4. Erroneous Arrhenius: modified arrhenius model best explains the temperature dependence of ectotherm fitness.

    Science.gov (United States)

    Knies, Jennifer L; Kingsolver, Joel G

    2010-08-01

    The initial rise of fitness that occurs with increasing temperature is attributed to Arrhenius kinetics, in which rates of reaction increase exponentially with increasing temperature. Models based on Arrhenius typically assume single rate-limiting reactions over some physiological temperature range for which all the rate-limiting enzymes are in 100% active conformation. We test this assumption using data sets for microbes that have measurements of fitness (intrinsic rate of population growth) at many temperatures and over a broad temperature range and for diverse ectotherms that have measurements at fewer temperatures. When measurements are available at many temperatures, strictly Arrhenius kinetics are rejected over the physiological temperature range. However, over a narrower temperature range, we cannot reject strictly Arrhenius kinetics. The temperature range also affects estimates of the temperature dependence of fitness. These results indicate that Arrhenius kinetics only apply over a narrow range of temperatures for ectotherms, complicating attempts to identify general patterns of temperature dependence.

  5. Modelling of the toe trajectory during normal gait using circle-fit approximation.

    Science.gov (United States)

    Fang, Juan; Hunt, Kenneth J; Xie, Le; Yang, Guo-Yuan

    2016-10-01

    This work aimed to validate the approach of using a circle to fit the toe trajectory relative to the hip and to investigate linear regression models for describing such toe trajectories from normal gait. Twenty-four subjects walked at seven speeds. Best-fit circle algorithms were developed to approximate the relative toe trajectory using a circle. It was detected that the mean approximation error between the toe trajectory and its best-fit circle was less than 4 %. Regarding the best-fit circles for the toe trajectories from all subjects, the normalised radius was constant, while the normalised centre offset reduced when the walking cadence increased; the curve range generally had a positive linear relationship with the walking cadence. The regression functions of the circle radius, the centre offset and the curve range with leg length and walking cadence were definitively defined. This study demonstrated that circle-fit approximation of the relative toe trajectories is generally applicable in normal gait. The functions provided a quantitative description of the relative toe trajectories. These results have potential application for design of gait rehabilitation technologies.

  6. Econometric modelling of risk adverse behaviours of entrepreneurs in the provision of house fittings in China

    Directory of Open Access Journals (Sweden)

    Rita Yi Man Li

    2012-03-01

    Full Text Available Entrepreneurs have always born the risk of running their business. They reap a profit in return for their risk taking and work. Housing developers are no different. In many countries, such as Australia, the United Kingdom and the United States, they interpret the tastes of the buyers and provide the dwellings they develop with basic fittings such as floor and wall coverings, bathroom fittings and kitchen cupboards. In mainland China, however, in most of the developments, units or houses are sold without floor or wall coverings, kitchen  or bathroom fittings. What is the motive behind this choice? This paper analyses the factors affecting housing developers’ decisions to provide fittings based on 1701 housing developments in Hangzhou, Chongqing and Hangzhou using a Probit model. The results show that developers build a higher proportion of bare units in mainland China when: 1 there is shortage of housing; 2 land costs are high so that the comparative costs of providing fittings become relatively low.

  7. The fitness landscape of HIV-1 gag: advanced modeling approaches and validation of model predictions by in vitro testing.

    Directory of Open Access Journals (Sweden)

    Jaclyn K Mann

    2014-08-01

    Full Text Available Viral immune evasion by sequence variation is a major hindrance to HIV-1 vaccine design. To address this challenge, our group has developed a computational model, rooted in physics, that aims to predict the fitness landscape of HIV-1 proteins in order to design vaccine immunogens that lead to impaired viral fitness, thus blocking viable escape routes. Here, we advance the computational models to address previous limitations, and directly test model predictions against in vitro fitness measurements of HIV-1 strains containing multiple Gag mutations. We incorporated regularization into the model fitting procedure to address finite sampling. Further, we developed a model that accounts for the specific identity of mutant amino acids (Potts model, generalizing our previous approach (Ising model that is unable to distinguish between different mutant amino acids. Gag mutation combinations (17 pairs, 1 triple and 25 single mutations within these predicted to be either harmful to HIV-1 viability or fitness-neutral were introduced into HIV-1 NL4-3 by site-directed mutagenesis and replication capacities of these mutants were assayed in vitro. The predicted and measured fitness of the corresponding mutants for the original Ising model (r = -0.74, p = 3.6×10-6 are strongly correlated, and this was further strengthened in the regularized Ising model (r = -0.83, p = 3.7×10-12. Performance of the Potts model (r = -0.73, p = 9.7×10-9 was similar to that of the Ising model, indicating that the binary approximation is sufficient for capturing fitness effects of common mutants at sites of low amino acid diversity. However, we show that the Potts model is expected to improve predictive power for more variable proteins. Overall, our results support the ability of the computational models to robustly predict the relative fitness of mutant viral strains, and indicate the potential value of this approach for understanding viral immune evasion

  8. Fitting parametric models of diffusion MRI in regions of partial volume

    Science.gov (United States)

    Eaton-Rosen, Zach; Cardoso, M. J.; Melbourne, Andrew; Orasanu, Eliza; Bainbridge, Alan; Kendall, Giles S.; Robertson, Nicola J.; Marlow, Neil; Ourselin, Sebastien

    2016-03-01

    Regional analysis is normally done by fitting models per voxel and then averaging over a region, accounting for partial volume (PV) only to some degree. In thin, folded regions such as the cerebral cortex, such methods do not work well, as the partial volume confounds parameter estimation. Instead, we propose to fit the models per region directly with explicit PV modeling. In this work we robustly estimate region-wise parameters whilst explicitly accounting for partial volume effects. We use a high-resolution segmentation from a T1 scan to assign each voxel in the diffusion image a probabilistic membership to each of k tissue classes. We rotate the DW signal at each voxel so that it aligns with the z-axis, then model the signal at each voxel as a linear superposition of a representative signal from each of the k tissue types. Fitting involves optimising these representative signals to best match the data, given the known probabilities of belonging to each tissue type that we obtained from the segmentation. We demonstrate this method improves parameter estimation in digital phantoms for the diffusion tensor (DT) and `Neurite Orientation Dispersion and Density Imaging' (NODDI) models. The method provides accurate parameter estimates even in regions where the normal approach fails completely, for example where partial volume is present in every voxel. Finally, we apply this model to brain data from preterm infants, where the thin, convoluted, maturing cortex necessitates such an approach.

  9. Improved cosmological model fitting of Planck data with a dark energy spike

    Science.gov (United States)

    Park, Chan-Gyung

    2015-06-01

    The Λ cold dark matter (Λ CDM ) model is currently known as the simplest cosmology model that best describes observations with a minimal number of parameters. Here we introduce a cosmology model that is preferred over the conventional Λ CDM one by constructing dark energy as the sum of the cosmological constant Λ and an additional fluid that is designed to have an extremely short transient spike in energy density during the radiation-matter equality era and an early scaling behavior with radiation and matter densities. The density parameter of the additional fluid is defined as a Gaussian function plus a constant in logarithmic scale-factor space. Searching for the best-fit cosmological parameters in the presence of such a dark energy spike gives a far smaller chi-square value by about 5 times the number of additional parameters introduced and narrower constraints on the matter density and Hubble constant compared with the best-fit Λ CDM model. The significant improvement in reducing the chi square mainly comes from the better fitting of the Planck temperature power spectrum around the third (ℓ≈800 ) and sixth (ℓ≈1800 ) acoustic peaks. The likelihood ratio test and the Akaike information criterion suggest that the model of a dark energy spike is strongly favored by the current cosmological observations over the conventional Λ CDM model. However, based on the Bayesian information criterion which penalizes models with more parameters, the strong evidence supporting the presence of a dark energy spike disappears. Our result emphasizes that the alternative cosmological parameter estimation with even better fitting of the same observational data is allowed in Einstein's gravity.

  10. A flexible, interactive software tool for fitting the parameters of neuronal models

    Directory of Open Access Journals (Sweden)

    Péter eFriedrich

    2014-07-01

    Full Text Available The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problem of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting

  11. Kompaneets Model Fitting of the Orion-Eridanus Superbubble II: Thinking Outside of Barnard's Loop

    CERN Document Server

    Pon, Andy; Alves, Joao; Bally, John; Basu, Shantanu; Tielens, Alexander G G M

    2016-01-01

    The Orion star-forming region is the nearest active high-mass star-forming region and has created a large superbubble, the Orion-Eridanus superbubble. Recent work by Ochsendorf et al. (2015) has extended the accepted boundary of the superbubble. We fit Kompaneets models of superbubbles expanding in exponential atmospheres to the new, larger shape of the Orion-Eridanus superbubble. We find that this larger morphology of the superbubble is consistent with the evolution of the superbubble being primarily controlled by expansion into the exponential Galactic disk ISM if the superbubble is oriented with the Eridanus side farther from the Sun than the Orion side. Unlike previous Kompaneets model fits that required abnormally small scale heights for the Galactic disk (<40 pc), we find morphologically consistent models with scale heights of 80 pc, similar to that expected for the Galactic disk.

  12. Fitting a mixture model by expectation maximization to discover motifs in biopolymers

    Energy Technology Data Exchange (ETDEWEB)

    Bailey, T.L.; Elkan, C. [Univ. of California, La Jolla, CA (United States)

    1994-12-31

    The algorithm described in this paper discovers one or more motifs in a collection of DNA or protein sequences by using the technique of expectation maximization to fit a two-component finite mixture model to the set of sequences. Multiple motifs are found by fitting a mixture model to the data, probabilistically erasing the occurrences of the motif thus found, and repeating the process to find successive motifs. The algorithm requires only a set of unaligned sequences and a number specifying the width of the motifs as input. It returns a model of each motif and a threshold which together can be used as a Bayes-optimal classifier for searching for occurrences of the motif in other databases. The algorithm estimates how many times each motif occurs in each sequence in the dataset and outputs an alignment of the occurrences of the motif. The algorithm is capable of discovering several different motifs with differing numbers of occurrences in a single dataset.

  13. Spin models inferred from patient-derived viral sequence data faithfully describe HIV fitness landscapes

    Science.gov (United States)

    Shekhar, Karthik; Ruberman, Claire F.; Ferguson, Andrew L.; Barton, John P.; Kardar, Mehran; Chakraborty, Arup K.

    2017-01-01

    Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus’ fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses. PMID:24483484

  14. Assessing the Fit of Structural Equation Models With Multiply Imputed Data.

    Science.gov (United States)

    Enders, Craig K; Mansolf, Maxwell

    2016-11-28

    Multiple imputation has enjoyed widespread use in social science applications, yet the application of imputation-based inference to structural equation modeling has received virtually no attention in the literature. Thus, this study has 2 overarching goals: evaluate the application of Meng and Rubin's (1992) pooling procedure for likelihood ratio statistic to the SEM test of model fit, and explore the possibility of using this test statistic to define imputation-based versions of common fit indices such as the TLI, CFI, and RMSEA. Computer simulation results suggested that, when applied to a correctly specified model, the pooled likelihood ratio statistic performed well as a global test of model fit and was closely calibrated to the corresponding full information maximum likelihood (FIML) test statistic. However, when applied to misspecified models with high rates of missingness (30%-40%), the imputation-based test statistic generally exhibited lower power than that of FIML. Using the pooled test statistic to construct imputation-based versions of the TLI, CFI, and RMSEA worked well and produced indices that were well-calibrated with those of full information maximum likelihood estimation. This article gives Mplus and R code to implement the pooled test statistic, and it offers a number of recommendations for future research. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  15. Hydrodynamic modelling and characterisation of a shallow fluvial lake: a study on the Superior Lake of Mantua

    Directory of Open Access Journals (Sweden)

    Andrea Fenocchi

    2016-04-01

    Full Text Available This paper presents a numerical modelling framework developed to simulate circulations and to generally characterise the hydrodynamics of the Superior Lake of Mantua, a shallow fluvial lake in Northern Italy. Such eutrophied basin is characterised by low winds, reduced discharges during the summer and by the presence of large lotus flower (Nelumbo nucifera meadows, all contributing to water stagnation. A hydrodynamic numerical model was built to understand how physical drivers shape basic circulation dynamics, selecting appropriate methodologies for the lake. These include a 3D code to reproduce the interaction between wind and through-flowing current, a fetch-dependent wind stress model, a porous media approach for canopy flow resistance and the consideration of wave-current interaction. The model allowed to estimate the circulation modes and water residence time distributions under identified typical ordinary, storm and drought conditions, the hydrodynamic influence of the newly-opened secondary outlet of the lake, the surface wave parameters, their influence on circulations and the bottom stress they originate, and the adaptation time scales of circulations to storm events. Some probable effects of the obtained hydrodynamic characteristics of the Superior Lake of Mantua on its biochemical processes are also introduced.

  16. Foraging and predation risk for larval cisco (Coregonus artedi) in Lake Superior: a modelling synthesis of empirical survey data

    Science.gov (United States)

    Myers, Jared T.; Yule, Daniel L.; Jones, Michael L.; Quinlan, Henry R.; Berglund, Eric K.

    2014-01-01

    The relative importance of predation and food availability as contributors to larval cisco (Coregonus artedi) mortality in Lake Superior were investigated using a visual foraging model to evaluate potential predation pressure by rainbow smelt (Osmerus mordax) and a bioenergetic model to evaluate potential starvation risk. The models were informed by observations of rainbow smelt, larval cisco, and zooplankton abundance at three Lake Superior locations during the period of spring larval cisco emergence and surface-oriented foraging. Predation risk was highest at Black Bay, ON, where average rainbow smelt densities in the uppermost 10 m of the water column were >1000 ha−1. Turbid conditions at the Twin Ports, WI-MN, affected larval cisco predation risk because rainbow smelt remained suspended in the upper water column during daylight, placing them alongside larval cisco during both day and night hours. Predation risk was low at Cornucopia, WI, owing to low smelt densities (cisco survival at Black Bay and to a lesser extent at Twin Ports, and that starvation may be a major source of mortality at all three locations. The framework we describe has the potential to further our understanding of the relative importance of starvation and predation on larval fish survivorship, provided information on prey resources available to larvae are measured at sufficiently fine spatial scales and the models provide a realistic depiction of the dynamic processes that the larvae experience.

  17. Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components

    KAUST Repository

    Zhang, Saijuan

    2011-01-06

    There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components.We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole

  18. Kinetic modelling of RDF pyrolysis: Model-fitting and model-free approaches.

    Science.gov (United States)

    Çepelioğullar, Özge; Haykırı-Açma, Hanzade; Yaman, Serdar

    2016-02-01

    In this study, refuse derived fuel (RDF) was selected as solid fuel and it was pyrolyzed in a thermal analyzer from room temperature to 900°C at heating rates of 5, 10, 20, and 50°C/min in N2 atmosphere. The obtained thermal data was used to calculate the kinetic parameters using Coats-Redfern, Friedman, Flylnn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS) methods. As a result of Coats-Redfern model, decomposition process was assumed to be four independent reactions with different reaction orders. On the other hand, model free methods demonstrated that activation energy trend had similarities for the reaction progresses of 0.1, 0.2-0.7 and 0.8-0.9. The average activation energies were found between 73-161kJ/mol and it is possible to say that FWO and KAS models produced closer results to the average activation energies compared to Friedman model. Experimental studies showed that RDF may be a sustainable and promising feedstock for alternative processes in terms of waste management strategies.

  19. Multiple phase transitions in an agent-based evolutionary model with neutral fitness.

    Science.gov (United States)

    King, Dawn M; Scott, Adam D; Bahar, Sonya

    2017-04-01

    Null models are crucial for understanding evolutionary processes such as speciation and adaptive radiation. We analyse an agent-based null model, considering a case without selection-neutral evolution-in which organisms are defined only by phenotype. Universal dynamics has previously been demonstrated in a related model on a neutral fitness landscape, showing that this system belongs to the directed percolation (DP) universality class. The traditional null condition of neutral fitness (where fitness is defined as the number of offspring each organism produces) is extended here to include equal probability of death among organisms. We identify two types of phase transition: (i) a non-equilibrium DP transition through generational time (i.e. survival), and (ii) an equilibrium ordinary percolation transition through the phenotype space (based on links between mating organisms). Owing to the dynamical rules of the DP reaction-diffusion process, organisms can only sparsely fill the phenotype space, resulting in significant phenotypic diversity within a cluster of mating organisms. This highlights the necessity of understanding hierarchical evolutionary relationships, rather than merely developing taxonomies based on phenotypic similarity, in order to develop models that can explain phylogenetic patterns found in the fossil record or to make hypotheses for the incomplete fossil record of deep time.

  20. llc: a collection of R functions for fitting a class of Lee-Carter mortality models using iterative fitting algorithms

    OpenAIRE

    Butt, Z.; Haberman, S

    2009-01-01

    We implement a specialised iterative regression methodology in R for the analysis of age-period mortality data based on a class of generalised Lee-Carter (LC) type modelling structures. The LC-based modelling frameworks is viewed in the current literature as among the most efficient and transparent methods of modelling and projecting mortality improvements. Thus, we make use of the modelling approach discussed in Renshaw and Haberman (2006), which extends the basic LC model and proposes to ma...

  1. Impact of Economic Development Model on the Fitting Effect of the Mathematical Model of Changes in Cultivated Land Resources

    Institute of Scientific and Technical Information of China (English)

    Xin; YAO; Min; ZHANG

    2014-01-01

    The mathematical model is often used for fitting the trend of changes in cultivated land resources in the land use planning,but the fitting effect is different in different study areas. In this paper,we take two geographically adjacent cities with great differences in the economic development model,Xinghua City and Jingjiang City,as the research object. Using logarithmic model( M1),Kuznets model( M2),logistic model( M3) and multivariate linear model( M4),we fit the process of changes in cultivated land resources during the period 1980- 2009,and compare the differences in the fitting effect between different models. In terms of the model fitting effect in Xinghua City,it is in the order of M3 > M4 > M1 > M2,which is related to the fact that the local areas lay great emphasis on agricultural development,and pay close attention to ensuring the cultivated land area; in terms of the model fitting effect in Jingjiang City,it is in the order of M1 > M3 > M4 > M2,and the deep-seated cause is that its development model is dominated by extended trade expansion,and the level of intensive land use is constantly improved. In addition,we discuss the multi-stage characteristics of changes in cultivated land resources,and propose a solution of using the same model to simulate in various phases. The research results in Jingjiang City show that the coefficient of determination in the first phase( R2=0. 958) and the standard error( SE = 0. 261) are both better than those of the original model( R2= 0. 945,SE = 0. 312); the coefficient of determination in the second phase is slightly low( R2= 0. 851),but the standard error is greatly improved( SE = 0. 137). Compared with the research conclusions of other scholars,it can be believed that this method can better solve the problems that the scatter plot of logistic model presents wave-shape and the scatter plot of Kuznets model presents " M"-shape,in order to improve the applicability of mathematical models.

  2. Tectonic plate under a localized boundary stress: fitting of a zero-range solvable model

    CERN Document Server

    Petrova, L

    2008-01-01

    We suggest a method of fitting of a zero-range model of a tectonic plate under a boundary stress on the basis of comparison of the theoretical formulae for the corresponding eigenfunctions/eigenvalues with the results extraction under monitoring, in the remote zone, of non-random (regular) oscillations of the Earth with periods 0.2-6 hours, on the background seismic process, in case of low seismic activity. Observations of changes of the characteristics of the oscillations (frequency, amplitude and polarization) in course of time, together with the theoretical analysis of the fitted model, would enable us to localize the stressed zone on the boundary of the plate and estimate the risk of a powerful earthquake at the zone.

  3. Validation of a Best-Fit Pharmacokinetic Model for Scopolamine Disposition after Intranasal Administration

    Science.gov (United States)

    Wu, L.; Chow, D. S-L.; Tam, V.; Putcha, L.

    2015-01-01

    An intranasal gel formulation of scopolamine (INSCOP) was developed for the treatment of Motion Sickness. Bioavailability and pharmacokinetics (PK) were determined per Investigative New Drug (IND) evaluation guidance by the Food and Drug Administration. Earlier, we reported the development of a PK model that can predict the relationship between plasma, saliva and urinary scopolamine (SCOP) concentrations using data collected from an IND clinical trial with INSCOP. This data analysis project is designed to validate the reported best fit PK model for SCOP by comparing observed and model predicted SCOP concentration-time profiles after administration of INSCOP.

  4. Nonlocal nonlinear refractive index of gold nanoparticles synthesized by ascorbic acid reduction: comparison of fitting models.

    Science.gov (United States)

    Balbuena Ortega, A; Arroyo Carrasco, M L; Méndez Otero, M M; Gayou, V L; Delgado Macuil, R; Martínez Gutiérrez, H; Iturbe Castillo, M D

    2014-12-12

    In this paper, the nonlinear refractive index of colloidal gold nanoparticles under continuous wave illumination is investigated with the z-scan technique. Gold nanoparticles were synthesized using ascorbic acid as reductant, phosphates as stabilizer and cetyltrimethylammonium chloride (CTAC) as surfactant agent. The nanoparticle size was controlled with the CTAC concentration. Experiments changing incident power and sample concentration were done. The experimental z-scan results were fitted with three models: thermal lens, aberrant thermal lens and the nonlocal model. It is shown that the nonlocal model reproduces with exceptionally good agreement; the obtained experimental behaviour.

  5. Effects of new mutations on fitness: insights from models and data.

    Science.gov (United States)

    Bataillon, Thomas; Bailey, Susan F

    2014-07-01

    The rates and properties of new mutations affecting fitness have implications for a number of outstanding questions in evolutionary biology. Obtaining estimates of mutation rates and effects has historically been challenging, and little theory has been available for predicting the distribution of fitness effects (DFE); however, there have been recent advances on both fronts. Extreme-value theory predicts the DFE of beneficial mutations in well-adapted populations, while phenotypic fitness landscape models make predictions for the DFE of all mutations as a function of the initial level of adaptation and the strength of stabilizing selection on traits underlying fitness. Direct experimental evidence confirms predictions on the DFE of beneficial mutations and favors distributions that are roughly exponential but bounded on the right. A growing number of studies infer the DFE using genomic patterns of polymorphism and divergence, recovering a wide range of DFE. Future work should be aimed at identifying factors driving the observed variation in the DFE. We emphasize the need for further theory explicitly incorporating the effects of partial pleiotropy and heterogeneity in the environment on the expected DFE.

  6. Hair length, facial attractiveness, personality attribution: A multiple fitness model of hairdressing

    OpenAIRE

    Bereczkei, Tamas; Mesko, Norbert

    2007-01-01

    Multiple Fitness Model states that attractiveness varies across multiple dimensions, with each feature representing a different aspect of mate value. In the present study, male raters judged the attractiveness of young females with neotenous and mature facial features, with various hair lengths. Results revealed that the physical appearance of long-haired women was rated high, regardless of their facial attractiveness being valued high or low. Women rated as most attractive were those whose f...

  7. SCAN-based hybrid and double-hybrid density functionals from models without fitted parameters

    OpenAIRE

    Hui, Kerwin; Chai, Jeng-Da

    2015-01-01

    By incorporating the nonempirical SCAN semilocal density functional [Sun, Ruzsinszky, and Perdew, Phys. Rev. Lett. 115, 036402 (2015)] in the underlying expression of four existing hybrid and double-hybrid models, we propose one hybrid (SCAN0) and three double-hybrid (SCAN0-DH, SCAN-QIDH, and SCAN0-2) density functionals, which are free from any fitted parameters. The SCAN-based double-hybrid functionals consistently outperform their parent SCAN semilocal functional for self-interaction probl...

  8. Model fitting of kink waves in the solar atmosphere: Gaussian damping and time-dependence

    CERN Document Server

    Morton, R J

    2016-01-01

    {Observations of the solar atmosphere have shown that magnetohydrodynamic waves are ubiquitous throughout. Improvements in instrumentation and the techniques used for measurement of the waves now enables subtleties of competing theoretical models to be compared with the observed waves behaviour. Some studies have already begun to undertake this process. However, the techniques employed for model comparison have generally been unsuitable and can lead to erroneous conclusions about the best model. The aim here is to introduce some robust statistical techniques for model comparison to the solar waves community, drawing on the experiences from other areas of astrophysics. In the process, we also aim to investigate the physics of coronal loop oscillations. } {The methodology exploits least-squares fitting to compare models to observational data. We demonstrate that the residuals between the model and observations contain significant information about the ability for the model to describe the observations, and show...

  9. Goodness of fit to a mathematical model for Drosophila sleep behavior is reduced in hyposomnolent mutants

    Directory of Open Access Journals (Sweden)

    Joshua M. Diamond

    2016-01-01

    Full Text Available The conserved nature of sleep in Drosophila has allowed the fruit fly to emerge in the last decade as a powerful model organism in which to study sleep. Recent sleep studies in Drosophila have focused on the discovery and characterization of hyposomnolent mutants. One common feature of these animals is a change in sleep architecture: sleep bout count tends to be greater, and sleep bout length lower, in hyposomnolent mutants. I propose a mathematical model, produced by least-squares nonlinear regression to fit the form Y = aX∧b, which can explain sleep behavior in the healthy animal as well as previously-reported changes in total sleep and sleep architecture in hyposomnolent mutants. This model, fit to sleep data, yields coefficient of determination R squared, which describes goodness of fit. R squared is lower, as compared to control, in hyposomnolent mutants insomniac and fumin. My findings raise the possibility that low R squared is a feature of all hyposomnolent mutants, not just insomniac and fumin. If this were the case, R squared could emerge as a novel means by which sleep researchers might assess sleep dysfunction.

  10. Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU

    Directory of Open Access Journals (Sweden)

    Jinwei Wang

    2014-01-01

    Full Text Available The active appearance model (AAM is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA on the Nvidia’s GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.

  11. Design and verifications of an eye model fitted with contact lenses for wavefront measurement systems

    Science.gov (United States)

    Cheng, Yuan-Chieh; Chen, Jia-Hong; Chang, Rong-Jie; Wang, Chung-Yen; Hsu, Wei-Yao; Wang, Pei-Jen

    2015-09-01

    Contact lenses are typically measured by the wet-box method because of the high optical power resulting from the anterior central curvature of cornea, even though the back vertex power of the lenses are small. In this study, an optical measurement system based on the Shack-Hartmann wavefront principle was established to investigate the aberrations of soft contact lenses. Fitting conditions were micmicked to study the optical design of an eye model with various topographical shapes in the anterior cornea. Initially, the contact lenses were measured by the wet-box method, and then by fitting the various topographical shapes of cornea to the eye model. In addition, an optics simulation program was employed to determine the sources of errors and assess the accuracy of the system. Finally, samples of soft contact lenses with various Diopters were measured; and, both simulations and experimental results were compared for resolving the controversies of fitting contact lenses to an eye model for optical measurements. More importantly, the results show that the proposed system can be employed for study of primary aberrations in contact lenses.

  12. Efficient parallel implementation of active appearance model fitting algorithm on GPU.

    Science.gov (United States)

    Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou

    2014-01-01

    The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.

  13. Role Modeling Attitudes, Physical Activity and Fitness Promoting Behaviors of Prospective Physical Education Specialists and Non-Specialists.

    Science.gov (United States)

    Cardinal, Bradley J.; Cardinal, Marita K.

    2002-01-01

    Compared the role modeling attitudes and physical activity and fitness promoting behaviors of undergraduate students majoring in physical education and in elementary education. Student teacher surveys indicated that physical education majors had more positive attitudes toward role modeling physical activity and fitness promoting behaviors and…

  14. Fitting the HIV epidemic in Zambia: a two-sex micro-simulation model.

    Directory of Open Access Journals (Sweden)

    Pauline M Leclerc

    Full Text Available BACKGROUND: In describing and understanding how the HIV epidemic spreads in African countries, previous studies have not taken into account the detailed periods at risk. This study is based on a micro-simulation model (individual-based of the spread of the HIV epidemic in the population of Zambia, where women tend to marry early and where divorces are not frequent. The main target of the model was to fit the HIV seroprevalence profiles by age and sex observed at the Demographic and Health Survey conducted in 2001. METHODS AND FINDINGS: A two-sex micro-simulation model of HIV transmission was developed. Particular attention was paid to precise age-specific estimates of exposure to risk through the modelling of the formation and dissolution of relationships: marriage (stable union, casual partnership, and commercial sex. HIV transmission was exclusively heterosexual for adults or vertical (mother-to-child for children. Three stages of HIV infection were taken into account. All parameters were derived from empirical population-based data. Results show that basic parameters could not explain the dynamics of the HIV epidemic in Zambia. In order to fit the age and sex patterns, several assumptions were made: differential susceptibility of young women to HIV infection, differential susceptibility or larger number of encounters for male clients of commercial sex workers, and higher transmission rate. The model allowed to quantify the role of each type of relationship in HIV transmission, the proportion of infections occurring at each stage of disease progression, and the net reproduction rate of the epidemic (R(0 = 1.95. CONCLUSIONS: The simulation model reproduced the dynamics of the HIV epidemic in Zambia, and fitted the age and sex pattern of HIV seroprevalence in 2001. The same model could be used to measure the effect of changing behaviour in the future.

  15. Measuring fit of sequence data to phylogenetic model: gain of power using marginal tests.

    Science.gov (United States)

    Waddell, Peter J; Ota, Rissa; Penny, David

    2009-10-01

    Testing fit of data to model is fundamentally important to any science, but publications in the field of phylogenetics rarely do this. Such analyses discard fundamental aspects of science as prescribed by Karl Popper. Indeed, not without cause, Popper (Unended quest: an intellectual autobiography. Fontana, London, 1976) once argued that evolutionary biology was unscientific as its hypotheses were untestable. Here we trace developments in assessing fit from Penny et al. (Nature 297:197-200, 1982) to the present. We compare the general log-likelihood ratio (the G or G (2) statistic) statistic between the evolutionary tree model and the multinomial model with that of marginalized tests applied to an alignment (using placental mammal coding sequence data). It is seen that the most general test does not reject the fit of data to model (P approximately 0.5), but the marginalized tests do. Tests on pairwise frequency (F) matrices, strongly (P < 0.001) reject the most general phylogenetic (GTR) models commonly in use. It is also clear (P < 0.01) that the sequences are not stationary in their nucleotide composition. Deviations from stationarity and homogeneity seem to be unevenly distributed amongst taxa; not necessarily those expected from examining other regions of the genome. By marginalizing the 4( t ) patterns of the i.i.d. model to observed and expected parsimony counts, that is, from constant sites, to singletons, to parsimony informative characters of a minimum possible length, then the likelihood ratio test regains power, and it too rejects the evolutionary model with P < 0.001. Given such behavior over relatively recent evolutionary time, readers in general should maintain a healthy skepticism of results, as the scale of the systematic errors in published trees may really be far larger than the analytical methods (e.g., bootstrap) report.

  16. Total liquid ventilation provides superior respiratory support to conventional mechanical ventilation in a large animal model of severe respiratory failure.

    Science.gov (United States)

    Pohlmann, Joshua R; Brant, David O; Daul, Morgan A; Reoma, Junewai L; Kim, Anne C; Osterholzer, Kathryn R; Johnson, Kent J; Bartlett, Robert H; Cook, Keith E; Hirschl, Ronald B

    2011-01-01

    Total liquid ventilation (TLV) has the potential to provide respiratory support superior to conventional mechanical ventilation (CMV) in the acute respiratory distress syndrome (ARDS). However, laboratory studies are limited to trials in small animals for no longer than 4 hours. The objective of this study was to compare TLV and CMV in a large animal model of ARDS for 24 hours. Ten sheep weighing 53 ± 4 (SD) kg were anesthetized and ventilated with 100% oxygen. Oleic acid was injected into the pulmonary circulation until PaO2:FiO2 ≤ 60 mm Hg, followed by transition to a protective CMV protocol (n = 5) or TLV (n = 5) for 24 hours. Pathophysiology was recorded, and the lungs were harvested for histological analysis. Animals treated with CMV became progressively hypoxic and hypercarbic despite maximum ventilatory support. Sheep treated with TLV maintained normal blood gases with statistically greater PO2 (p < 10(-9)) and lower PCO2 (p < 10(-3)) than the CMV group. Survival at 24 hours in the TLV and CMV groups were 100% and 40%, respectively (p < 0.05). Thus, TLV provided gas exchange superior to CMV in this laboratory model of severe ARDS.

  17. Computational Software for Fitting Seismic Data to Epidemic-Type Aftershock Sequence Models

    Science.gov (United States)

    Chu, A.

    2014-12-01

    Modern earthquake catalogs are often analyzed using spatial-temporal point process models such as the epidemic-type aftershock sequence (ETAS) models of Ogata (1998). My work introduces software to implement two of ETAS models described in Ogata (1998). To find the Maximum-Likelihood Estimates (MLEs), my software provides estimates of the homogeneous background rate parameter and the temporal and spatial parameters that govern triggering effects by applying the Expectation-Maximization (EM) algorithm introduced in Veen and Schoenberg (2008). Despite other computer programs exist for similar data modeling purpose, using EM-algorithm has the benefits of stability and robustness (Veen and Schoenberg, 2008). Spatial shapes that are very long and narrow cause difficulties in optimization convergence and problems with flat or multi-modal log-likelihood functions encounter similar issues. My program uses a robust method to preset a parameter to overcome the non-convergence computational issue. In addition to model fitting, the software is equipped with useful tools for examining modeling fitting results, for example, visualization of estimated conditional intensity, and estimation of expected number of triggered aftershocks. A simulation generator is also given with flexible spatial shapes that may be defined by the user. This open-source software has a very simple user interface. The user may execute it on a local computer, and the program also has potential to be hosted online. Java language is used for the software's core computing part and an optional interface to the statistical package R is provided.

  18. Kinetic modeling and fitting software for interconnected reaction schemes: VisKin.

    Science.gov (United States)

    Zhang, Xuan; Andrews, Jared N; Pedersen, Steen E

    2007-02-15

    Reaction kinetics for complex, highly interconnected kinetic schemes are modeled using analytical solutions to a system of ordinary differential equations. The algorithm employs standard linear algebra methods that are implemented using MatLab functions in a Visual Basic interface. A graphical user interface for simple entry of reaction schemes facilitates comparison of a variety of reaction schemes. To ensure microscopic balance, graph theory algorithms are used to determine violations of thermodynamic cycle constraints. Analytical solutions based on linear differential equations result in fast comparisons of first order kinetic rates and amplitudes as a function of changing ligand concentrations. For analysis of higher order kinetics, we also implemented a solution using numerical integration. To determine rate constants from experimental data, fitting algorithms that adjust rate constants to fit the model to imported data were implemented using the Levenberg-Marquardt algorithm or using Broyden-Fletcher-Goldfarb-Shanno methods. We have included the ability to carry out global fitting of data sets obtained at varying ligand concentrations. These tools are combined in a single package, which we have dubbed VisKin, to guide and analyze kinetic experiments. The software is available online for use on PCs.

  19. Fitting the CDO correlation skew: a tractable structural jump-diffusion model

    DEFF Research Database (Denmark)

    Willemann, Søren

    2007-01-01

    We extend a well-known structural jump-diffusion model for credit risk to handle both correlations through diffusion of asset values and common jumps in asset value. Through a simplifying assumption on the default timing and efficient numerical techniques, we develop a semi-analytic framework...... allowing for instantaneous calibration to heterogeneous CDS curves and fast computation of CDO tranche spreads. We calibrate the model to CDX and iTraxx data from February 2007 and achieve a satisfactory fit. To price the senior tranches for both indices, we require a risk-neutral probability of a market...

  20. Fitting of different models for water vapour sorption on potato starch granules

    Science.gov (United States)

    Czepirski, L.; Komorowska-Czepirska, E.; Szymońska, J.

    2002-08-01

    Water vapour adsorption isotherms for native and modified potato starch were investigated. To obtain the best fit for the experimental data several models based on the BET approach were evaluated. The hypothesis that water is adsorbed on the starch granules at the primary and secondary adsorption sites as well as a concept considering the adsorbent fractality were also tested. It was found, that the equilibrium adsorption points in the examined range of relative humidity (0.03-0.90) were most accurately predicted by using a three-parameter model proposed by Kats and Kutarov.

  1. Parameter Estimation of a Plucked String Synthesis Model Using a Genetic Algorithm with Perceptual Fitness Calculation

    Directory of Open Access Journals (Sweden)

    Riionheimo Janne

    2003-01-01

    Full Text Available We describe a technique for estimating control parameters for a plucked string synthesis model using a genetic algorithm. The model has been intensively used for sound synthesis of various string instruments but the fine tuning of the parameters has been carried out with a semiautomatic method that requires some hand adjustment with human listening. An automated method for extracting the parameters from recorded tones is described in this paper. The calculation of the fitness function utilizes knowledge of the properties of human hearing.

  2. A NON-UNIFORM SEDIMENT TRANSPORT MODEL WITH THE BOUNDARY-FITTING ORTHOGONAL COORDINATE SYSTEM

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    A 2-D non-uniform sediment mathmatical model in the boundary-fitting orthogonal coordinate system was developed in this paper. The governing equations, the numerical scheme, the boundary conditions, the movable boundary technique and the numerical solutions were presented. The model was verified by the data of the reach 25km upstream the Jialingjiang estuary and the 44km long main stream of the Chongqing reach of the Yangtze river. The calculated results show that, the water elevation, the velocity distribution and the river bed deformation are in agreement with the measured data.

  3. Testing Lack-of-fit for a Polynomial Errors-in-variables Model

    Institute of Scientific and Technical Information of China (English)

    Li-xing Zhu; Wei-xing Song; Heng-jian Gui

    2003-01-01

    When a regression model is applied as an approximation of underlying model of data, the model checking is important and relevant. In this paper, we investigate the lack-of-fit test for a polynomial errorin-variables model. As the ordinary residuals are biased when there exist measurement errors in covariables,we correct them and then construct a residual-based test of score type. The constructed test is asymptotically chi-squared under null hypotheses. Simulation study shows that the test can maintain the significance level well.The choice of weight functions involved in the test statistic and the related power study are also investigated.The application to two examples is illustrated. The approach can be readily extended to handle more general models.

  4. Model fitting of kink waves in the solar atmosphere: Gaussian damping and time-dependence

    Science.gov (United States)

    Morton, R. J.; Mooroogen, K.

    2016-09-01

    Aims: Observations of the solar atmosphere have shown that magnetohydrodynamic waves are ubiquitous throughout. Improvements in instrumentation and the techniques used for measurement of the waves now enables subtleties of competing theoretical models to be compared with the observed waves behaviour. Some studies have already begun to undertake this process. However, the techniques employed for model comparison have generally been unsuitable and can lead to erroneous conclusions about the best model. The aim here is to introduce some robust statistical techniques for model comparison to the solar waves community, drawing on the experiences from other areas of astrophysics. In the process, we also aim to investigate the physics of coronal loop oscillations. Methods: The methodology exploits least-squares fitting to compare models to observational data. We demonstrate that the residuals between the model and observations contain significant information about the ability for the model to describe the observations, and show how they can be assessed using various statistical tests. In particular we discuss the Kolmogorov-Smirnoff one and two sample tests, as well as the runs test. We also highlight the importance of including any observational trend line in the model-fitting process. Results: To demonstrate the methodology, an observation of an oscillating coronal loop undergoing standing kink motion is used. The model comparison techniques provide evidence that a Gaussian damping profile provides a better description of the observed wave attenuation than the often used exponential profile. This supports previous analysis from Pascoe et al. (2016, A&A, 585, L6). Further, we use the model comparison to provide evidence of time-dependent wave properties of a kink oscillation, attributing the behaviour to the thermodynamic evolution of the local plasma.

  5. Summary goodness-of-fit statistics for binary generalized linear models with noncanonical link functions.

    Science.gov (United States)

    Canary, Jana D; Blizzard, Leigh; Barry, Ronald P; Hosmer, David W; Quinn, Stephen J

    2016-05-01

    Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) .

  6. Blowout Jets: Hinode X-Ray Jets that Don't Fit the Standard Model

    Science.gov (United States)

    Moore, Ronald L.; Cirtain, Jonathan W.; Sterling, Alphonse C.; Falconer, David A.

    2010-01-01

    Nearly half of all H-alpha macrospicules in polar coronal holes appear to be miniature filament eruptions. This suggests that there is a large class of X-ray jets in which the jet-base magnetic arcade undergoes a blowout eruption as in a CME, instead of remaining static as in most solar X-ray jets, the standard jets that fit the model advocated by Shibata. Along with a cartoon depicting the standard model, we present a cartoon depicting the signatures expected of blowout jets in coronal X-ray images. From Hinode/XRT movies and STEREO/EUVI snapshots in polar coronal holes, we present examples of (1) X-ray jets that fit the standard model, and (2) X-ray jets that do not fit the standard model but do have features appropriate for blowout jets. These features are (1) a flare arcade inside the jet-base arcade in addition to the small flare arcade (bright point) outside that standard jets have, (2) a filament of cool (T is approximately 80,000K) plasma that erupts from the core of the jetbase arcade, and (3) an extra jet strand that should not be made by the reconnection for standard jets but could be made by reconnection between the ambient unipolar open field and the opposite-polarity leg of the filament-carrying flux-rope core field of the erupting jet-base arcade. We therefore infer that these non-standard jets are blowout jets, jets made by miniature versions of the sheared-core-arcade eruptions that make CMEs

  7. A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit

    Science.gov (United States)

    Kim, K. Han; Young, Karen S.; Bernal, Yaritza; Boppana, Abhishektha; Vu, Linh Q.; Benson, Elizabeth A.; Jarvis, Sarah; Rajulu, Sudhakar L.

    2016-01-01

    Shoulder injury is one of the most severe risks that have the potential to impair crewmembers' performance and health in long duration space flight. Overall, 64% of crewmembers experience shoulder pain after extra-vehicular training in a space suit, and 14% of symptomatic crewmembers require surgical repair (Williams & Johnson, 2003). Suboptimal suit fit, in particular at the shoulder region, has been identified as one of the predominant risk factors. However, traditional suit fit assessments and laser scans represent only a single person's data, and thus may not be generalized across wide variations of body shapes and poses. The aim of this work is to develop a software tool based on a statistical analysis of a large dataset of crewmember body shapes. This tool can accurately predict the skin deformation and shape variations for any body size and shoulder pose for a target population, from which the geometry can be exported and evaluated against suit models in commercial CAD software. A preliminary software tool was developed by statistically analyzing 150 body shapes matched with body dimension ranges specified in the Human-Systems Integration Requirements of NASA ("baseline model"). Further, the baseline model was incorporated with shoulder joint articulation ("articulation model"), using additional subjects scanned in a variety of shoulder poses across a pre-specified range of motion. Scan data was cleaned and aligned using body landmarks. The skin deformation patterns were dimensionally reduced and the co-variation with shoulder angles was analyzed. A software tool is currently in development and will be presented in the final proceeding. This tool would allow suit engineers to parametrically generate body shapes in strategically targeted anthropometry dimensions and shoulder poses. This would also enable virtual fit assessments, with which the contact volume and clearance between the suit and body surface can be predictively quantified at reduced time and

  8. Correlated parameter fit of arrhenius model for thermal denaturation of proteins and cells.

    Science.gov (United States)

    Qin, Zhenpeng; Balasubramanian, Saravana Kumar; Wolkers, Willem F; Pearce, John A; Bischof, John C

    2014-12-01

    Thermal denaturation of proteins is critical to cell injury, food science and other biomaterial processing. For example protein denaturation correlates strongly with cell death by heating, and is increasingly of interest in focal thermal therapies of cancer and other diseases at temperatures which often exceed 50 °C. The Arrhenius model is a simple yet widely used model for both protein denaturation and cell injury. To establish the utility of the Arrhenius model for protein denaturation at 50 °C and above its sensitivities to the kinetic parameters (activation energy E a and frequency factor A) were carefully examined. We propose a simplified correlated parameter fit to the Arrhenius model by treating E a, as an independent fitting parameter and allowing A to follow dependently. The utility of the correlated parameter fit is demonstrated on thermal denaturation of proteins and cells from the literature as a validation, and new experimental measurements in our lab using FTIR spectroscopy to demonstrate broad applicability of this method. Finally, we demonstrate that the end-temperature within which the denaturation is measured is important and changes the kinetics. Specifically, higher E a and A parameters were found at low end-temperature (50 °C) and reduce as end-temperatures increase to 70 °C. This trend is consistent with Arrhenius parameters for cell injury in the literature that are significantly higher for clonogenics (45-50 °C) vs. membrane dye assays (60-70 °C). Future opportunities to monitor cell injury by spectroscopic measurement of protein denaturation are discussed.

  9. Finding the right fit: A comparison of process assumptions underlying popular drift-diffusion models.

    Science.gov (United States)

    Ashby, Nathaniel J S; Jekel, Marc; Dickert, Stephan; Glöckner, Andreas

    2016-12-01

    Recent research makes increasing use of eye-tracking methodologies to generate and test process models. Overall, such research suggests that attention, generally indexed by fixations (gaze duration), plays a critical role in the construction of preference, although the methods used to support this supposition differ substantially. In 2 studies we empirically test prototypical versions of prominent processing assumptions against 1 another and several base models. We find that general evidence accumulation processes provide a good fit to the data. An accumulation process that assumes leakage and temporal variability in evidence weighting (i.e., a primacy effect) fits the aggregate data, both in terms of choices and decision times, and does so across varying types of choices (e.g., charitable giving and hedonic consumption) and numbers of options well. However, when comparing models on the level of the individual, for a majority of participants simpler models capture choice data better. The theoretical and practical implications of these findings are discussed. (PsycINFO Database Record

  10. The Herschel Orion Protostar Survey: Spectral Energy Distributions and Fits Using a Grid of Protostellar Models

    CERN Document Server

    Furlan, E; Ali, B; Stutz, A M; Stanke, T; Tobin, J J; Megeath, S T; Osorio, M; Hartmann, L; Calvet, N; Poteet, C A; Booker, J; Manoj, P; Watson, D M; Allen, L

    2016-01-01

    We present key results from the Herschel Orion Protostar Survey (HOPS): spectral energy distributions (SEDs) and model fits of 330 young stellar objects, predominantly protostars, in the Orion molecular clouds. This is the largest sample of protostars studied in a single, nearby star-formation complex. With near-infrared photometry from 2MASS, mid- and far-infrared data from Spitzer and Herschel, and sub-millimeter photometry from APEX, our SEDs cover 1.2-870 $\\mu$m and sample the peak of the protostellar envelope emission at ~100 $\\mu$m. Using mid-IR spectral indices and bolometric temperatures, we classify our sample into 92 Class 0 protostars, 125 Class I protostars, 102 flat-spectrum sources, and 11 Class II pre-main-sequence stars. We implement a simple protostellar model (including a disk in an infalling envelope with outflow cavities) to generate a grid of 30400 model SEDs and use it to determine the best-fit model parameters for each protostar. We argue that far-IR data are essential for accurate cons...

  11. Implicit Active Contour Model with Local and Global Intensity Fitting Energies

    Directory of Open Access Journals (Sweden)

    Xiaozeng Xu

    2013-01-01

    Full Text Available We propose a new active contour model which integrates a local intensity fitting (LIF energy with an auxiliary global intensity fitting (GIF energy. The LIF energy is responsible for attracting the contour toward object boundaries and is dominant near object boundaries, while the GIF energy incorporates global image information to improve the robustness to initialization of the contours. The proposed model not only can provide desirable segmentation results in the presence of intensity inhomogeneity but also allows for more flexible initialization of the contour compared to the RSF and LIF models, and we give a theoretical proof to compute a unique steady state regardless of the initialization; that is, the convergence of the zero-level line is irrespective of the initial function. This means that we can obtain the same zero-level line in the steady state, if we choose the initial function as a bounded function. In particular, our proposed model has the capability of detecting multiple objects or objects with interior holes or blurred edges.

  12. Empirical evaluation reveals best fit of a logistic mutation model for human Y-chromosomal microsatellites.

    Science.gov (United States)

    Jochens, Arne; Caliebe, Amke; Rösler, Uwe; Krawczak, Michael

    2011-12-01

    The rate of microsatellite mutation is dependent upon both the allele length and the repeat motif, but the exact nature of this relationship is still unknown. We analyzed data on the inheritance of human Y-chromosomal microsatellites in father-son duos, taken from 24 published reports and comprising 15,285 directly observable meioses. At the six microsatellites analyzed (DYS19, DYS389I, DYS390, DYS391, DYS392, and DYS393), a total of 162 mutations were observed. For each locus, we employed a maximum-likelihood approach to evaluate one of several single-step mutation models on the basis of the data. For five of the six loci considered, a novel logistic mutation model was found to provide the best fit according to Akaike's information criterion. This implies that the mutation probability at the loci increases (nonlinearly) with allele length at a rate that differs between upward and downward mutations. For DYS392, the best fit was provided by a linear model in which upward and downward mutation probabilities increase equally with allele length. This is the first study to empirically compare different microsatellite mutation models in a locus-specific fashion.

  13. An improved cosmological model fitting of Planck data with a dark energy spike

    CERN Document Server

    Park, Chan-Gyung

    2015-01-01

    The $\\Lambda$ cold dark matter ($\\Lambda\\textrm{CDM}$) model is currently known as the simplest cosmology model that best describes observations with minimal number of parameters. Here we introduce a cosmology model that is preferred over the conventional $\\Lambda\\textrm{CDM}$ one by constructing dark energy as the sum of the cosmological constant $\\Lambda$ and the additional fluid that is designed to have an extremely short transient spike in energy density during the radiation-matter equality era and the early scaling behavior with radiation and matter densities. The density parameter of the additional fluid is defined as a Gaussian function plus a constant in logarithmic scale-factor space. Searching for the best-fit cosmological parameters in the presence of such a dark energy spike gives a far smaller chi-square value by about five times the number of additional parameters introduced and narrower constraints on matter density and Hubble constant compared with the best-fit $\\Lambda\\textrm{CDM}$ model. The...

  14. A Multiple Criteria Decision Modelling approach to selection of estimation techniques for fitting extreme floods

    Science.gov (United States)

    Duckstein, L.; Bobée, B.; Ashkar, F.

    1991-09-01

    The problem of fitting a probability distribution, here log-Pearson Type III distribution, to extreme floods is considered from the point of view of two numerical and three non-numerical criteria. The six techniques of fitting considered include classical techniques (maximum likelihood, moments of logarithms of flows) and new methods such as mixed moments and the generalized method of moments developed by two of the co-authors. The latter method consists of fitting the distribution using moments of different order, in particular the SAM method (Sundry Averages Method) uses the moments of order 0 (geometric mean), 1 (arithmetic mean), -1 (harmonic mean) and leads to a smaller variance of the parameters. The criteria used to select the method of parameter estimation are: - the two statistical criteria of mean square error and bias; - the two computational criteria of program availability and ease of use; - the user-related criterion of acceptability. These criteria are transformed into value functions or fuzzy set membership functions and then three Multiple Criteria Decision Modelling (MCDM) techniques, namely, composite programming, ELECTRE, and MCQA, are applied to rank the estimation techniques.

  15. Systematic effects on the size-luminosity relation: dependence on model fitting and morphology

    CERN Document Server

    Bernardi, M; Vikram, V; Huertas-Company, M; Mei, S; Shankar, F; Sheth, R K

    2012-01-01

    We quantify the systematics in the size-luminosity relation of galaxies in the SDSS main sample which arise from fitting different 1- and 2-component model profiles to the images. In objects brighter than L*, fitting a single Sersic profile to what is really a two-component SerExp system leads to biases: the half-light radius is increasingly overestimated as n of the fitted single component increases; it is also overestimated at B/T ~ 0.6. However, the net effect on the R-L relation is small, except for the most luminous tail, where it curves upwards towards larger sizes. We also study how this relation depends on morphological type. Our analysis is one of the first to use Bayesian-classifier derived weights, rather than hard cuts, to define morphology. Crudely, there appear to be only two relations: one for early-types (Es, S0s and Sa's) and another for late-types (Sbs and Scds). However, closer inspection shows that within the early-type sample S0s tend to be 15% smaller than Es of the same luminosity, and,...

  16. Adapted strategic plannig model applied to small business: a case study in the fitness area

    Directory of Open Access Journals (Sweden)

    Eduarda Tirelli Hennig

    2012-06-01

    Full Text Available The strategic planning is an important management tool in the corporate scenario and shall not be restricted to big Companies. However, this kind of planning process in small business may need special adaptations due to their own characteristics. This paper aims to identify and adapt the existent models of strategic planning to the scenario of a small business in the fitness area. Initially, it is accomplished a comparative study among models of different authors to identify theirs phases and activities. Then, it is defined which of these phases and activities should be present in a model that will be utilized in a small business. That model was applied to a Pilates studio; it involves the establishment of an organizational identity, an environmental analysis as well as the definition of strategic goals, strategies and actions to reach them. Finally, benefits to the organization could be identified, as well as hurdles in the implementation of the tool.

  17. The Shape of Dark Matter Haloes II. The Galactus HI Modelling & Fitting Tool

    CERN Document Server

    Peters, S P C; Allen, R J; Freeman, K C

    2016-01-01

    We present a new HI modelling tool called \\textsc{Galactus}. The program has been designed to perform automated fits of disc-galaxy models to observations. It includes a treatment for the self-absorption of the gas. The software has been released into the public domain. We describe the design philosophy and inner workings of the program. After this, we model the face-on galaxy NGC2403, using both self-absorption and optically thin models, showing that self-absorption occurs even in face-on galaxies. It is shown that the maximum surface brightness plateaus seen in Paper I of this series are indeed signs of self-absorption. The apparent HI mass of an edge-on galaxy can be drastically lower compared to that same galaxy seen face-on. The Tully-Fisher relation is found to be relatively free from self-absorption issues.

  18. Cobinamide is superior to other treatments in a mouse model of cyanide poisoning

    Science.gov (United States)

    Chan, Adriano; Balasubramanian, Maheswari; Blackledge, William; Mohammad, Othman M.; Alvarez, Luis; Boss, Gerry R.; Bigby, Timothy D.

    2011-01-01

    Context Cyanide is a rapidly acting cellular poison, primarily targeting cytochrome c oxidase, and is a common occupational and residential toxin, mostly via smoke inhalation. Cyanide is also a potential weapon of mass destruction, with recent credible threats of attacks focusing the need for better treatments, since current cyanide antidotes are limited and impractical for rapid deployment in mass casualty settings. Objective We have used mouse models of cyanide poisoning to compare the efficacy of cobinamide, the precursor to cobalamin (vitamin B12), to currently approved cyanide antidotes. Cobinamide has extremely high affinity for cyanide and substantial solubility in water. Materials and Methods We studied cobinamide in both an inhaled and intraperitoneal model of cyanide poisoning in mice. Results We found cobinamide more effective than hydroxocobalamin, sodium thiosulfate, sodium nitrite, and the combination of sodium thiosulfate-sodium nitrite in treating cyanide poisoning. Compared to hydroxocobalamin, cobinamide was 3 and 11 times more potent in the intraperitoneal and inhalation models, respectively. Cobinamide sulfite was rapidly absorbed after intramuscular injection, and mice recovered from a lethal dose of cyanide even when given at a time when they had been apneic for over two minutes. In range finding studies, cobinamide sulfite at doses up to 2000 mg/kg exhibited no clinical toxicity. Discussion and Conclusion These studies demonstrate that cobinamide is a highly effective cyanide antidote in mouse models, and suggest it could be used in a mass casualty setting, because it can be given rapidly as an intramuscular injection when administered as cobinamide sulfite. Based on these animal data cobinamide sulfite appears to be an antidote worthy of further testing as a therapy for mass casualties. PMID:20704457

  19. A gamma variate model that includes stretched exponential is a better fit for gastric emptying data from mice.

    Science.gov (United States)

    Bajzer, Željko; Gibbons, Simon J; Coleman, Heidi D; Linden, David R; Farrugia, Gianrico

    2015-08-01

    Noninvasive breath tests for gastric emptying are important techniques for understanding the changes in gastric motility that occur in disease or in response to drugs. Mice are often used as an animal model; however, the gamma variate model currently used for data analysis does not always fit the data appropriately. The aim of this study was to determine appropriate mathematical models to better fit mouse gastric emptying data including when two peaks are present in the gastric emptying curve. We fitted 175 gastric emptying data sets with two standard models (gamma variate and power exponential), with a gamma variate model that includes stretched exponential and with a proposed two-component model. The appropriateness of the fit was assessed by the Akaike Information Criterion. We found that extension of the gamma variate model to include a stretched exponential improves the fit, which allows for a better estimation of T1/2 and Tlag. When two distinct peaks in gastric emptying are present, a two-component model is required for the most appropriate fit. We conclude that use of a stretched exponential gamma variate model and when appropriate a two-component model will result in a better estimate of physiologically relevant parameters when analyzing mouse gastric emptying data.

  20. Fitting parametric random effects models in very large data sets with application to VHA national data.

    Science.gov (United States)

    Gebregziabher, Mulugeta; Egede, Leonard; Gilbert, Gregory E; Hunt, Kelly; Nietert, Paul J; Mauldin, Patrick

    2012-10-24

    With the current focus on personalized medicine, patient/subject level inference is often of key interest in translational research. As a result, random effects models (REM) are becoming popular for patient level inference. However, for very large data sets that are characterized by large sample size, it can be difficult to fit REM using commonly available statistical software such as SAS since they require inordinate amounts of computer time and memory allocations beyond what are available preventing model convergence. For example, in a retrospective cohort study of over 800,000 Veterans with type 2 diabetes with longitudinal data over 5 years, fitting REM via generalized linear mixed modeling using currently available standard procedures in SAS (e.g. PROC GLIMMIX) was very difficult and same problems exist in Stata's gllamm or R's lme packages. Thus, this study proposes and assesses the performance of a meta regression approach and makes comparison with methods based on sampling of the full data. We use both simulated and real data from a national cohort of Veterans with type 2 diabetes (n=890,394) which was created by linking multiple patient and administrative files resulting in a cohort with longitudinal data collected over 5 years. The outcome of interest was mean annual HbA1c measured over a 5 years period. Using this outcome, we compared parameter estimates from the proposed random effects meta regression (REMR) with estimates based on simple random sampling and VISN (Veterans Integrated Service Networks) based stratified sampling of the full data. Our results indicate that REMR provides parameter estimates that are less likely to be biased with tighter confidence intervals when the VISN level estimates are homogenous. When the interest is to fit REM in repeated measures data with very large sample size, REMR can be used as a good alternative. It leads to reasonable inference for both Gaussian and non-Gaussian responses if parameter estimates are

  1. Inclusion complex between β-cyclodextrin and hecogenin acetate produces superior analgesic effect in animal models for orofacial pain.

    Science.gov (United States)

    Carvalho, Yasmim M B G; Menezes, Paula P; Sousa, Bruna M H; Lima, Bruno S; Trindade, Igor A S; Serafini, Mairim R; Pereira, Erik W M; Rezende, Marilia M; Quintans, Jullyana S S; Quintans-Júnior, Lucindo J; Nakamura, Celso V; Silva-Júnior, Edeildo F; Crispim, Alessandre C; Aquino, Thiago M; Araújo, Adriano A S

    2017-09-01

    Hecogenin acetate (HA) is a steroidal sapogenin-acetylated with pharmacological properties which have already been described in the literature such as, anti-inflammatory, anti-hyperalgesic and antinociceptive, but it has low solubility in aqueous media. Therefore, in an attempt to overcome this, we set out to create inclusion complexes between HA and b-cyclodextrin (b-CD) and evaluate the antinociceptive effects in the orofacial nociception in mice. The complexes were prepared using different methods in the molar ratios 1:1 and 1:2 and characterized physicochemically. The results of the physicochemical characterization elucidated inclusion complexes formation between b-CD and HA by freeze drying method in the molar ratio 1:2, which obtained a complexation efficiency of 92% and produced superior analgesic effect in animal models for orofacial pain at a lower dose when compared to HA alone. Copyright © 2017. Published by Elsevier Masson SAS.

  2. An amino acid substitution-selection model adjusts residue fitness to improve phylogenetic estimation.

    Science.gov (United States)

    Wang, Huai-Chun; Susko, Edward; Roger, Andrew J

    2014-04-01

    Standard protein phylogenetic models use fixed rate matrices of amino acid interchange derived from analyses of large databases. Differences between the stationary amino acid frequencies of these rate matrices from those of a data set of interest are typically adjusted for by matrix multiplication that converts the empirical rate matrix to an exchangeability matrix which is then postmultiplied by the amino acid frequencies in the alignment. The result is a time-reversible rate matrix with stationary amino acid frequencies equal to the data set frequencies. On the basis of population genetics principles, we develop an amino acid substitution-selection model that parameterizes the fitness of an amino acid as the logarithm of the ratio of the frequency of the amino acid to the frequency of the same amino acid under no selection. The model gives rise to a different sequence of matrix multiplications to convert an empirical rate matrix to one that has stationary amino acid frequencies equal to the data set frequencies. We incorporated the substitution-selection model with an improved amino acid class frequency mixture (cF) model to partially take into account site-specific amino acid frequencies in the phylogenetic models. We show that 1) the selection models fit data significantly better than corresponding models without selection for most of the 21 test data sets; 2) both cF and cF selection models favored the phylogenetic trees that were inferred under current sophisticated models and methods for three difficult phylogenetic problems (the positions of microsporidia and breviates in eukaryote phylogeny and the position of the root of the angiosperm tree); and 3) for data simulated under site-specific residue frequencies, the cF selection models estimated trees closer to the generating trees than a standard Г model or cF without selection. We also explored several ways of estimating amino acid frequencies under neutral evolution that are required for these selection

  3. Design and construction of models of solar thermal facilities in the ''Centro integrado de FP superior de energias renovables de Imarcoain''(Navarra); Maquetas de instalaciones solares termicas para la formacion profesional de grado superior en el centro integrado de formacion profesional superior de energias renovables

    Energy Technology Data Exchange (ETDEWEB)

    Hernandez, M. A.; Orus, L. M.; Yerro, C.; Aguado, H.; Cambra, T.; Oroz, J.

    2004-07-01

    This article shows how we have approached the solar energy installations in the ''Centro integrado de FP superior de energias renovables de Imarcoain''(Navarra) with the design and construction of models which allow us to teach in this type of installations at different levels. (Author)

  4. Antisaccade Performance in Schizophrenia: A Neural Model of Decision Making in the Superior Colliculus

    Directory of Open Access Journals (Sweden)

    Vassilis eCutsuridis

    2014-02-01

    Full Text Available Antisaccade performance deficits in schizophrenia are generally interpreted as an impaired top-down inhibitory signal failing to suppress the erroneous response. We recorded the antisaccade performance (error rates and latencies of healthy and schizophrenia subjects performing the mirror antisaccade task. A neural rise-to-threshold model of antisaccade performance was developed to uncover the biophysical mechanisms giving rise to the observed deficits in schizophrenia. Schizophrenia patients displayed greater variability in the antisaccade and corrected antisaccade latency distributions, increased error rates and decreased corrected errors, relative to healthy participants. Our model showed that i increased variability is due to a more noisy accumulation of information by schizophrenia patients, but their confidence level required before making a decision is unaffected, and ii competition between the correct and erroneous decision processes, and not a third top-down inhibitory signal of the erroneous response, accounts for the antisaccade performance of healthy and schizophrenia subjects. Local competition further ensured that a correct antisaccade is never followed by an error prosaccade.

  5. Current status of the Standard Model CKM fit and constraints on $\\Delta F=2$ New Physics

    CERN Document Server

    Charles, J; Descotes-Genon, S; Lacker, H; Menzel, A; Monteil, S; Niess, V; Ocariz, J; Orloff, J; Perez, A; Qian, W; Tisserand, V; Trabelsi, K; Urquijo, P; Silva, L Vale

    2015-01-01

    This letter summarises the status of the global fit of the CKM parameters within the Standard Model performed by the CKMfitter group. Special attention is paid to the inputs for the CKM angles $\\alpha$ and $\\gamma$ and the status of $B_s\\to\\mu\\mu$ and $B_d\\to \\mu\\mu$ decays. We illustrate the current situation for other unitarity triangles. We also discuss the constraints on generic $\\Delta F=2$ New Physics. All results have been obtained with the CKMfitter analysis package, featuring the frequentist statistical approach and using Rfit to handle theoretical uncertainties.

  6. Inverse problem theory methods for data fitting and model parameter estimation

    CERN Document Server

    Tarantola, A

    2002-01-01

    Inverse Problem Theory is written for physicists, geophysicists and all scientists facing the problem of quantitative interpretation of experimental data. Although it contains a lot of mathematics, it is not intended as a mathematical book, but rather tries to explain how a method of acquisition of information can be applied to the actual world.The book provides a comprehensive, up-to-date description of the methods to be used for fitting experimental data, or to estimate model parameters, and to unify these methods into the Inverse Problem Theory. The first part of the book deals wi

  7. Understanding Systematics in ZZ Ceti Model Fitting to Enable Differential Seismology

    Science.gov (United States)

    Fuchs, J. T.; Dunlap, B. H.; Clemens, J. C.; Meza, J. A.; Dennihy, E.; Koester, D.

    2017-03-01

    We are conducting a large spectroscopic survey of over 130 Southern ZZ Cetis with the Goodman Spectrograph on the SOAR Telescope. Because it employs a single instrument with high UV throughput, this survey will both improve the signal-to-noise of the sample of SDSS ZZ Cetis and provide a uniform dataset for model comparison. We are paying special attention to systematics in the spectral fitting and quantify three of those systematics here. We show that relative positions in the log g -Teff plane are consistent for these three systematics.

  8. Understanding Systematics in ZZ Ceti Model Fitting to Enable Differential Seismology

    CERN Document Server

    Fuchs, J T; Clemens, J C; Meza, J A; Dennihy, E; Koester, D

    2016-01-01

    We are conducting a large spectroscopic survey of over 130 Southern ZZ Cetis with the Goodman Spectrograph on the SOAR Telescope. Because it employs a single instrument with high UV throughput, this survey will both improve the signal-to-noise of the sample of SDSS ZZ Cetis and provide a uniform dataset for model comparison. We are paying special attention to systematics in the spectral fitting and quantify three of those systematics here. We show that relative positions in the $\\log{g}$-$T_{\\rm eff}$ plane are consistent for these three systematics.

  9. Evaluating Fit Indices for Multivariate t-Based Structural Equation Modeling with Data Contamination

    Directory of Open Access Journals (Sweden)

    Mark H. C. Lai

    2017-07-01

    Full Text Available In conventional structural equation modeling (SEM, with the presence of even a tiny amount of data contamination due to outliers or influential observations, normal-theory maximum likelihood (ML-Normal is not efficient and can be severely biased. The multivariate-t-based SEM, which recently got implemented in Mplus as an approach for mixture modeling, represents a robust estimation alternative to downweigh the impact of outliers and influential observations. To our knowledge, the use of maximum likelihood estimation with a multivariate-t model (ML-t to handle outliers has not been shown in SEM literature. In this paper we demonstrate the use of ML-t using the classic Holzinger and Swineford (1939 data set with a few observations modified as outliers or influential observations. A simulation study is then conducted to examine the performance of fit indices and information criteria under ML-Normal and ML-t in the presence of outliers. Results showed that whereas all fit indices got worse for ML-Normal with increasing amount of outliers and influential observations, their values were relatively stable with ML-t, and the use of information criteria was effective in selecting ML-normal without data contamination and selecting ML-t with data contamination, especially when the sample size was at least 200.

  10. Analytical Light Curve Models of Super-Luminous Supernvae: chi^2-Minimizations of Parameter Fits

    CERN Document Server

    Chatzopoulos, E; Vinko, J; Horvath, Z L; Nagy, A

    2013-01-01

    We present fits of generalized semi-analytic supernova (SN) light curve (LC) models for a variety of power inputs including Ni-56 and Co-56 radioactive decay, magnetar spin-down, and forward and reverse shock heating due to supernova ejecta-circumstellar matter (CSM) interaction. We apply our models to the observed LCs of the H-rich Super Luminous Supernovae (SLSN-II) SN 2006gy, SN 2006tf, SN 2008am, SN 2008es, CSS100217, the H-poor SLSN-I SN 2005ap, SCP06F6, SN 2007bi, SN 2010gx and SN 2010kd as well as to the interacting SN 2008iy and PTF09uj. Our goal is to determine the dominant mechanism that powers the LCs of these extraordinary events and the physical conditions involved in each case. We also present a comparison of our semi-analytical results with recent results from numerical radiation hydrodynamics calculations in the particular case of SN 2006gy in order to explore the strengths and weaknesses of our models. We find that CS shock heating produced by ejecta-CSM interaction provides a better fit to t...

  11. A global fit study on the new agegraphic dark energy model

    CERN Document Server

    Zhang, Jing-Fei; Zhang, Xin

    2012-01-01

    We perform a global fit study on the new agegraphic dark energy (NADE) model in a non-flat universe by using the MCMC method with the full CMB power spectra data from the WMAP 7-yr observations, the SNIa data from Union2.1 sample, BAO data from SDSS DR7 and WiggleZ Dark Energy Survey, and the latest measurements of $H_0$ from HST. We find that the value of $\\Omega_{k0}$ is greater than 0 at least at the 3$\\sigma$ confidence levels (CLs), which implies that the NADE model distinctly favors an open universe. Besides, our results show that the value of the key parameter of NADE model, $n=2.673^{+0.053+0.127+0.199}_{-0.077-0.151-0.222}$, at the 1--3$\\sigma$ CLs, where its best-fit value is significantly smaller than those obtained in previous works. We find that the reason leading to such a change comes from the different SNIa samples used. Our further test indicates that there is a distinct tension between the Union2 sample of SNIa and other observations, and the tension will be relieved once the Union2 sample i...

  12. Fitting mathematical models to describe the rheological behaviour of chocolate pastes

    Science.gov (United States)

    Barbosa, Carla; Diogo, Filipa; Alves, M. Rui

    2016-06-01

    The flow behavior is of utmost importance for the chocolate industry. The objective of this work was to study two mathematical models, Casson and Windhab models that can be used to fit chocolate rheological data and evaluate which better infers or previews the rheological behaviour of different chocolate pastes. Rheological properties (viscosity, shear stress and shear rates) were obtained with a rotational viscometer equipped with a concentric cylinder. The chocolate samples were white chocolate and chocolate with varying percentages in cacao (55%, 70% and 83%). The results showed that the Windhab model was the best to describe the flow behaviour of all the studied samples with higher determination coefficients (r2 > 0.9).

  13. GRace: a MATLAB-based application for fitting the discrimination-association model.

    Science.gov (United States)

    Stefanutti, Luca; Vianello, Michelangelo; Anselmi, Pasquale; Robusto, Egidio

    2014-10-28

    The Implicit Association Test (IAT) is a computerized two-choice discrimination task in which stimuli have to be categorized as belonging to target categories or attribute categories by pressing, as quickly and accurately as possible, one of two response keys. The discrimination association model has been recently proposed for the analysis of reaction time and accuracy of an individual respondent to the IAT. The model disentangles the influences of three qualitatively different components on the responses to the IAT: stimuli discrimination, automatic association, and termination criterion. The article presents General Race (GRace), a MATLAB-based application for fitting the discrimination association model to IAT data. GRace has been developed for Windows as a standalone application. It is user-friendly and does not require any programming experience. The use of GRace is illustrated on the data of a Coca Cola-Pepsi Cola IAT, and the results of the analysis are interpreted and discussed.

  14. Towards greater realism in inclusive fitness models: the case of worker reproduction in insect societies.

    Science.gov (United States)

    Wenseleers, Tom; Helanterä, Heikki; Alves, Denise A; Dueñez-Guzmán, Edgar; Pamilo, Pekka

    2013-01-01

    The conflicts over sex allocation and male production in insect societies have long served as an important test bed for Hamilton's theory of inclusive fitness, but have for the most part been considered separately. Here, we develop new coevolutionary models to examine the interaction between these two conflicts and demonstrate that sex ratio and colony productivity costs of worker reproduction can lead to vastly different outcomes even in species that show no variation in their relatedness structure. Empirical data on worker-produced males in eight species of Melipona bees support the predictions from a model that takes into account the demographic details of colony growth and reproduction. Overall, these models contribute significantly to explaining behavioural variation that previous theories could not account for.

  15. Goodness-of-fit tests and model diagnostics for negative binomial regression of RNA sequencing data.

    Directory of Open Access Journals (Sweden)

    Gu Mi

    Full Text Available This work is about assessing model adequacy for negative binomial (NB regression, particularly (1 assessing the adequacy of the NB assumption, and (2 assessing the appropriateness of models for NB dispersion parameters. Tools for the first are appropriate for NB regression generally; those for the second are primarily intended for RNA sequencing (RNA-Seq data analysis. The typically small number of biological samples and large number of genes in RNA-Seq analysis motivate us to address the trade-offs between robustness and statistical power using NB regression models. One widely-used power-saving strategy, for example, is to assume some commonalities of NB dispersion parameters across genes via simple models relating them to mean expression rates, and many such models have been proposed. As RNA-Seq analysis is becoming ever more popular, it is appropriate to make more thorough investigations into power and robustness of the resulting methods, and into practical tools for model assessment. In this article, we propose simulation-based statistical tests and diagnostic graphics to address model adequacy. We provide simulated and real data examples to illustrate that our proposed methods are effective for detecting the misspecification of the NB mean-variance relationship as well as judging the adequacy of fit of several NB dispersion models.

  16. Goodness-of-fit tests and model diagnostics for negative binomial regression of RNA sequencing data.

    Science.gov (United States)

    Mi, Gu; Di, Yanming; Schafer, Daniel W

    2015-01-01

    This work is about assessing model adequacy for negative binomial (NB) regression, particularly (1) assessing the adequacy of the NB assumption, and (2) assessing the appropriateness of models for NB dispersion parameters. Tools for the first are appropriate for NB regression generally; those for the second are primarily intended for RNA sequencing (RNA-Seq) data analysis. The typically small number of biological samples and large number of genes in RNA-Seq analysis motivate us to address the trade-offs between robustness and statistical power using NB regression models. One widely-used power-saving strategy, for example, is to assume some commonalities of NB dispersion parameters across genes via simple models relating them to mean expression rates, and many such models have been proposed. As RNA-Seq analysis is becoming ever more popular, it is appropriate to make more thorough investigations into power and robustness of the resulting methods, and into practical tools for model assessment. In this article, we propose simulation-based statistical tests and diagnostic graphics to address model adequacy. We provide simulated and real data examples to illustrate that our proposed methods are effective for detecting the misspecification of the NB mean-variance relationship as well as judging the adequacy of fit of several NB dispersion models.

  17. A diffusion process to model generalized von Bertalanffy growth patterns: fitting to real data.

    Science.gov (United States)

    Román-Román, Patricia; Romero, Desirée; Torres-Ruiz, Francisco

    2010-03-07

    The von Bertalanffy growth curve has been commonly used for modeling animal growth (particularly fish). Both deterministic and stochastic models exist in association with this curve, the latter allowing for the inclusion of fluctuations or disturbances that might exist in the system under consideration which are not always quantifiable or may even be unknown. This curve is mainly used for modeling the length variable whereas a generalized version, including a new parameter b > or = 1, allows for modeling both length and weight for some animal species in both isometric (b = 3) and allometric (b not = 3) situations. In this paper a stochastic model related to the generalized von Bertalanffy growth curve is proposed. This model allows to investigate the time evolution of growth variables associated both with individual behaviors and mean population behavior. Also, with the purpose of fitting the above-mentioned model to real data and so be able to forecast and analyze particular characteristics, we study the maximum likelihood estimation of the parameters of the model. In addition, and regarding the numerical problems posed by solving the likelihood equations, a strategy is developed for obtaining initial solutions for the usual numerical procedures. Such strategy is validated by means of simulated examples. Finally, an application to real data of mean weight of swordfish is presented. 2009 Elsevier Ltd. All rights reserved.

  18. Antitrypanosomal Treatment with Benznidazole Is Superior to Posaconazole Regimens in Mouse Models of Chagas Disease.

    Science.gov (United States)

    Khare, Shilpi; Liu, Xianzhong; Stinson, Monique; Rivera, Ianne; Groessl, Todd; Tuntland, Tove; Yeh, Vince; Wen, Ben; Molteni, Valentina; Glynne, Richard; Supek, Frantisek

    2015-10-01

    Two CYP51 inhibitors, posaconazole and the ravuconazole prodrug E1224, were recently tested in clinical trials for efficacy in indeterminate Chagas disease. The results from these studies show that both drugs cleared parasites from the blood of infected patients at the end of the treatment but that parasitemia rebounded over the following months. In the current study, we sought to identify a dosing regimen of posaconazole that could permanently clear Trypanosoma cruzi from mice with experimental Chagas disease. Infected mice were treated with posaconazole or benznidazole, an established Chagas disease drug, and parasitological cure was defined as an absence of parasitemia recrudescence after immunosuppression. Twenty-day therapy with benznidazole (10 to 100 mg/kg of body weight/day) resulted in a dose-dependent increase in antiparasitic activity, and the 100-mg/kg regimen effected parasitological cure in all treated mice. In contrast, all mice remained infected after a 25-day treatment with posaconazole at all tested doses (10 to 100 mg/kg/day). Further extension of posaconazole therapy to 40 days resulted in only a marginal improvement of treatment outcome. We also observed similar differences in antiparasitic activity between benznidazole and posaconazole in acute T. cruzi heart infections. While benznidazole induced rapid, dose-dependent reductions in heart parasite burdens, the antiparasitic activity of posaconazole plateaued at low doses (3 to 10 mg/kg/day) despite increasing drug exposure in plasma. These observations are in good agreement with the outcomes of recent phase 2 trials with posaconazole and suggest that the efficacy models combined with the pharmacokinetic analysis employed here will be useful in predicting clinical outcomes of new drug candidates.

  19. Superior protection elicited by live-attenuated vaccines in the murine model of paratuberculosis.

    Science.gov (United States)

    Ghosh, Pallab; Shippy, Daniel C; Talaat, Adel M

    2015-12-16

    Mycobacterium avium subspecies paratuberculosis (M. paratuberculosis) causes Johne's disease, a chronic enteric infection in ruminants with severe economic impact on the dairy industry in the USA and worldwide. Currently, available vaccines have limited protective efficacy against disease progression and does not prevent spread of the infection among animals. Because of their ability to elicit wide-spectrum immune responses, we adopted a live-attenuated vaccine approach based on a sigH knock-out strain of M. paratuberculosis (ΔsigH). Earlier analysis of the ΔsigH mutant in mice indicated their inadequate ability to colonize host tissues, unlike the isogenic wild-type strain, validating the role of this sigma factor in M. paratuberculosis virulence. In the present study, we evaluated the performance of the ΔsigH mutant compared to inactivated vaccine constructs in a vaccine/challenge model of murine paratuberculosis. The presented analysis indicated that ΔsigH mutant with or without QuilA adjuvant is capable of eliciting strong immune responses (such as interferon gamma-γ, IFN-γ) suggesting their immunogenicity and ability to potentially initiate effective vaccine-induced immunity. Following a challenge with virulent strains of M. paratuberculosis, ΔsigH conferred protective immunity as indicated by the reduced bacterial burden accompanied with reduced lesions in main body organs (liver, spleen and intestine) usually infected with M. paratuberculosis. More importantly, our data indicated better ability of the ΔsigH vaccine to confer protection compared to the inactivated vaccine constructs even with the presence of oil-adjuvant. Overall, our approach provides a rational basis for using live-attenuated mutant strains to develop improved vaccines that elicit robust immunity against this chronic infection.

  20. Bootstrapping Topological Properties and Systemic Risk of Complex Networks Using the Fitness Model

    Science.gov (United States)

    Musmeci, Nicolò; Battiston, Stefano; Caldarelli, Guido; Puliga, Michelangelo; Gabrielli, Andrea

    2013-05-01

    In this paper we present a novel method to reconstruct global topological properties of a complex network starting from limited information. We assume to know for all the nodes a non-topological quantity that we interpret as fitness. In contrast, we assume to know the degree, i.e. the number of connections, only for a subset of the nodes in the network. We then use a fitness model, calibrated on the subset of nodes for which degrees are known, in order to generate ensembles of networks. Here, we focus on topological properties that are relevant for processes of contagion and distress propagation in networks, i.e. network density and k-core structure, and we study how well these properties can be estimated as a function of the size of the subset of nodes utilized for the calibration. Finally, we also study how well the resilience to distress propagation in the network can be estimated using our method. We perform a first test on ensembles of synthetic networks generated with the Exponential Random Graph model, which allows to apply common tools from statistical mechanics. We then perform a second test on empirical networks taken from economic and financial contexts. In both cases, we find that a subset as small as 10 % of nodes can be enough to estimate the properties of the network along with its resilience with an error of 5 %.

  1. Reconstructing topological properties of complex networks from partial information using the Fitness Model

    Science.gov (United States)

    Gabrielli, Andrea; Battiston, Stefano; Caldarelli, Guido; Musmeci, Nicoló; Puliga, Michelangelo

    2014-03-01

    We present a new method to reconstruct global topological properties of complex networks starting from limited information. We assume to know for all nodes a non-topological quantity that we interpret as fitness, while the degree is known only for a subset of the nodes. We then use a fitness model, calibrated on the subset of nodes for which degrees are known, to generate ensembles of networks. We focus on topological properties relevant for processes of contagion and distress propagation in networks, i.e. network density and k-core structure. We study how well these properties can be estimated as a function of the size of the subset of nodes utilized for the calibration. We perform a first test on ensembles of synthetic networks generated with the Exponential Random Graph model. We then perform a second test on empirical networks taken from economic and financial contexts (World Trade Web and e-mid interbank network). In both cases, we find that a subset as small as 10% of nodes can be enough to estimate the properties of the network with an error of 5%.

  2. A simulation study of person-fit in the Rasch model

    Directory of Open Access Journals (Sweden)

    Richard Artner

    2016-09-01

    Full Text Available The validation of individual test scores in the Rasch model (1-PL model is of primary importance, but the decision which person-fit index to choose is still not sufficiently answered. In this work, a simulation study was conducted in order to compare five well known person-fit indices in terms of specificity and sensitivity, under different testing conditions. Furthermore, this study analyzed the decrease in specificity of Andersen´s Likelihood-Ratio test in case of person-misfit, using the median of the raw score as an internal criterion, as well as the positive effect of removing suspicious respondents with the index C*. The three non-parametric indices Ht, C* and U3 performed slightly better than the parametric indices OUTFIT and INFIT. All indices performed better with a higher number of respondents and a higher number of items. Ht, OUTFIT, and INFIT showed huge deviations between nominal and actual specificity levels. The simulation revealed that person-misfit has a huge negative impact on the specificity of Andersen´s Likelihood-Ratio test. However, the removal of suspicious respondents with C* worked quite well and the nominal specificity can be almost respected if the specificity level of C* is set to 0.95.

  3. A PID Positioning Controller with a Curve Fitting Model Based on RFID Technology

    Directory of Open Access Journals (Sweden)

    Young-Long Chen

    2013-04-01

    Full Text Available The global positioning system (GPS is an important research topic to solve outdoor positioning problems, but GPS is unable to locate objects accurately and precisely indoors. Some available systems apply ultrasound or optical tracking. This paper presents an efficient proportional-integral-derivative (PID controller with curve fitting model for mobile robot localization and position estimation which adopts passive radio frequency identification (RFID tags in a space. This scheme is based on a mobile robot carries an RFID reader module which reads the installed low-cost passive tags under the floor in a grid-like pattern. The PID controllers increase the efficiency of captured RFID tags and the curve fitting model is used to systematically identify the revolutions per minute (RPM of the motor. We control and monitor the position of the robot from a remote location through a mobile phone via Wi-Fi and Bluetooth network. Experiment results present that the number of captured RFID tags of our proposed scheme outperforms that of the previous scheme.

  4. Lévy Flights and Self-Similar Exploratory Behaviour of Termite Workers: Beyond Model Fitting

    Science.gov (United States)

    Miramontes, Octavio; DeSouza, Og; Paiva, Leticia Ribeiro; Marins, Alessandra; Orozco, Sirio

    2014-01-01

    Animal movements have been related to optimal foraging strategies where self-similar trajectories are central. Most of the experimental studies done so far have focused mainly on fitting statistical models to data in order to test for movement patterns described by power-laws. Here we show by analyzing over half a million movement displacements that isolated termite workers actually exhibit a range of very interesting dynamical properties –including Lévy flights– in their exploratory behaviour. Going beyond the current trend of statistical model fitting alone, our study analyses anomalous diffusion and structure functions to estimate values of the scaling exponents describing displacement statistics. We evince the fractal nature of the movement patterns and show how the scaling exponents describing termite space exploration intriguingly comply with mathematical relations found in the physics of transport phenomena. By doing this, we rescue a rich variety of physical and biological phenomenology that can be potentially important and meaningful for the study of complex animal behavior and, in particular, for the study of how patterns of exploratory behaviour of individual social insects may impact not only their feeding demands but also nestmate encounter patterns and, hence, their dynamics at the social scale. PMID:25353958

  5. Levy flights and self-similar exploratory behaviour of termite workers: beyond model fitting.

    Directory of Open Access Journals (Sweden)

    Octavio Miramontes

    Full Text Available Animal movements have been related to optimal foraging strategies where self-similar trajectories are central. Most of the experimental studies done so far have focused mainly on fitting statistical models to data in order to test for movement patterns described by power-laws. Here we show by analyzing over half a million movement displacements that isolated termite workers actually exhibit a range of very interesting dynamical properties--including Lévy flights--in their exploratory behaviour. Going beyond the current trend of statistical model fitting alone, our study analyses anomalous diffusion and structure functions to estimate values of the scaling exponents describing displacement statistics. We evince the fractal nature of the movement patterns and show how the scaling exponents describing termite space exploration intriguingly comply with mathematical relations found in the physics of transport phenomena. By doing this, we rescue a rich variety of physical and biological phenomenology that can be potentially important and meaningful for the study of complex animal behavior and, in particular, for the study of how patterns of exploratory behaviour of individual social insects may impact not only their feeding demands but also nestmate encounter patterns and, hence, their dynamics at the social scale.

  6. Fitting multilevel models in complex survey data with design weights: Recommendations

    Directory of Open Access Journals (Sweden)

    Carle Adam C

    2009-07-01

    Full Text Available Abstract Background Multilevel models (MLM offer complex survey data analysts a unique approach to understanding individual and contextual determinants of public health. However, little summarized guidance exists with regard to fitting MLM in complex survey data with design weights. Simulation work suggests that analysts should scale design weights using two methods and fit the MLM using unweighted and scaled-weighted data. This article examines the performance of scaled-weighted and unweighted analyses across a variety of MLM and software programs. Methods Using data from the 2005–2006 National Survey of Children with Special Health Care Needs (NS-CSHCN: n = 40,723 that collected data from children clustered within states, I examine the performance of scaling methods across outcome type (categorical vs. continuous, model type (level-1, level-2, or combined, and software (Mplus, MLwiN, and GLLAMM. Results Scaled weighted estimates and standard errors differed slightly from unweighted analyses, agreeing more with each other than with unweighted analyses. However, observed differences were minimal and did not lead to different inferential conclusions. Likewise, results demonstrated minimal differences across software programs, increasing confidence in results and inferential conclusions independent of software choice. Conclusion If including design weights in MLM, analysts should scale the weights and use software that properly includes the scaled weights in the estimation.

  7. Spectral observations of Ellerman bombs and fitting with a two-cloud model

    CERN Document Server

    Hong, Jie; Li, Ying; Fang, Cheng; Cao, Wenda

    2014-01-01

    We study the H$\\alpha$ and Ca II 8542 \\r{A} line spectra of four typical Ellerman bombs (EBs) in active region NOAA 11765 on 2013 June 6, observed with the Fast Imaging Solar Spectrograph installed at the 1.6 meter New Solar Telescope at Big Bear Solar Observatory. Considering that EBs may occur in a restricted region in the lower atmosphere, and that their spectral lines show particular features, we propose a two-cloud model to fit the observed line profiles. The lower cloud can account for the wing emission, and the upper cloud is mainly responsible for the absorption at line center. After choosing carefully the free parameters, we get satisfactory fitting results. As expected, the lower cloud shows an increase of the source function, corresponding to a temperature increase of 400--1000 K in EBs relative to the quiet Sun. This is consistent with previous results deduced from semi-empirical models and confirms that a local heating occurs in the lower atmosphere during the appearance of EBs. We also find that...

  8. A PID Positioning Controller with a Curve Fitting Model Based on RFID Technology

    Directory of Open Access Journals (Sweden)

    Young-Long Chen

    2013-03-01

    Full Text Available The global positioning system (GPS is an important research topic to solve outdoor positioning problems, but GPSis unable to locate objects accurately and precisely indoors. Some available systems apply ultrasound or opticaltracking. This paper presents an efficient proportional-integral-derivative (PID controller with curve fitting model formobile robot localization and position estimation which adopts passive radio frequency identification (RFID tags ina space. This scheme is based on a mobile robot carries an RFID reader module which reads the installed low-costpassive tags under the floor in a grid-like pattern. The PID controllers increase the efficiency of captured RFID tagsand the curve fitting model is used to systematically identify the revolutions per minute (RPM of the motor. Wecontrol and monitor the position of the robot from a remote location through a mobile phone via Wi-Fi and Bluetoothnetwork. Experiment results present that the number of captured RFID tags of our proposed scheme outperformsthat of the previous scheme.

  9. Energy-dependent fitness: a quantitative model for the evolution of yeast transcription factor binding sites.

    Science.gov (United States)

    Mustonen, Ville; Kinney, Justin; Callan, Curtis G; Lässig, Michael

    2008-08-26

    We present a genomewide cross-species analysis of regulation for broad-acting transcription factors in yeast. Our model for binding site evolution is founded on biophysics: the binding energy between transcription factor and site is a quantitative phenotype of regulatory function, and selection is given by a fitness landscape that depends on this phenotype. The model quantifies conservation, as well as loss and gain, of functional binding sites in a coherent way. Its predictions are supported by direct cross-species comparison between four yeast species. We find ubiquitous compensatory mutations within functional sites, such that the energy phenotype and the function of a site evolve in a significantly more constrained way than does its sequence. We also find evidence for substantial evolution of regulatory function involving point mutations as well as sequence insertions and deletions within binding sites. Genes lose their regulatory link to a given transcription factor at a rate similar to the neutral point mutation rate, from which we infer a moderate average fitness advantage of functional over nonfunctional sites. In a wider context, this study provides an example of inference of selection acting on a quantitative molecular trait.

  10. A healthy fear of the unknown: perspectives on the interpretation of parameter fits from computational models in neuroscience.

    Directory of Open Access Journals (Sweden)

    Matthew R Nassar

    2013-04-01

    Full Text Available Fitting models to behavior is commonly used to infer the latent computational factors responsible for generating behavior. However, the complexity of many behaviors can handicap the interpretation of such models. Here we provide perspectives on problems that can arise when interpreting parameter fits from models that provide incomplete descriptions of behavior. We illustrate these problems by fitting commonly used and neurophysiologically motivated reinforcement-learning models to simulated behavioral data sets from learning tasks. These model fits can pass a host of standard goodness-of-fit tests and other model-selection diagnostics even when the models do not provide a complete description of the behavioral data. We show that such incomplete models can be misleading by yielding biased estimates of the parameters explicitly included in the models. This problem is particularly pernicious when the neglected factors are unknown and therefore not easily identified by model comparisons and similar methods. An obvious conclusion is that a parsimonious description of behavioral data does not necessarily imply an accurate description of the underlying computations. Moreover, general goodness-of-fit measures are not a strong basis to support claims that a particular model can provide a generalized understanding of the computations that govern behavior. To help overcome these challenges, we advocate the design of tasks that provide direct reports of the computational variables of interest. Such direct reports complement model-fitting approaches by providing a more complete, albeit possibly more task-specific, representation of the factors that drive behavior. Computational models then provide a means to connect such task-specific results to a more general algorithmic understanding of the brain.

  11. Observations from using models to fit the gas production of varying volume test cells and landfills.

    Science.gov (United States)

    Lamborn, Julia

    2012-12-01

    Landfill operators are looking for more accurate models to predict waste degradation and landfill gas production. The simple microbial growth and decay models, whilst being easy to use, have been shown to be inaccurate. Many of the newer and more complex (component) models are highly parameter hungry and many of the required parameters have not been collected or measured at full-scale landfills. This paper compares the results of using different models (LANDGEM, HBM, and two Monod models developed by the author) to fit the gas production of laboratory scale, field test cell and full-scale landfills and discusses some observations that can be made regarding the scalability of gas generation rates. The comparison of these results show that the fast degradation rate that occurs at laboratory scale is not replicated at field-test cell and full-scale landfills. At small scale, all the models predict a slower rate of gas generation than actually occurs. At field test cell and full-scale a number of models predict a faster gas generation than actually occurs. Areas for future work have been identified, which include investigations into the capture efficiency of gas extraction systems and into the parameter sensitivity and identification of the critical parameters for field-test cell and full-scale landfill predication.

  12. The challenges of fitting an item response theory model to the Social Anhedonia Scale.

    Science.gov (United States)

    Reise, Steven P; Horan, William P; Blanchard, Jack J

    2011-05-01

    This study explored the application of latent variable measurement models to the Social Anhedonia Scale (SAS; Eckblad, Chapman, Chapman, & Mishlove, 1982), a widely used and influential measure in schizophrenia-related research. Specifically, we applied unidimensional and bifactor item response theory (IRT) models to data from a community sample of young adults (n = 2,227). Ordinal factor analyses revealed that identifying a coherent latent structure in the 40-item SAS data was challenging due to (a) the presence of multiple small content clusters (e.g., doublets); (b) modest relations between those clusters, which, in turn, implies a general factor of only modest strength; (c) items that shared little variance with the majority of items; and (d) cross-loadings in bifactor solutions. Consequently, we conclude that SAS responses cannot be modeled accurately by either unidimensional or bifactor IRT models. Although the application of a bifactor model to a reduced 17-item set met with better success, significant psychometric and substantive problems remained. Results highlight the challenges of applying latent variable models to scales that were not originally designed to fit these models.

  13. Comprehensive two-dimensional river ice model based on boundary-fitted coordinate transformation method

    Directory of Open Access Journals (Sweden)

    Ze-yu MAO

    2014-01-01

    Full Text Available River ice is a natural phenomenon in cold regions, influenced by meteorology, geomorphology, and hydraulic conditions. River ice processes involve complex interactions between hydrodynamic, mechanical, and thermal processes, and they are also influenced by weather and hydrologic conditions. Because natural rivers are serpentine, with bends, narrows, and straight reaches, the commonly-used one-dimensional river ice models and two-dimensional models based on the rectangular Cartesian coordinates are incapable of simulating the physical phenomena accurately. In order to accurately simulate the complicated river geometry and overcome the difficulties of numerical simulation resulting from both complex boundaries and differences between length and width scales, a two-dimensional river ice numerical model based on a boundary-fitted coordinate transformation method was developed. The presented model considers the influence of the frazil ice accumulation under ice cover and the shape of the leading edge of ice cover during the freezing process. The model is capable of determining the velocity field, the distribution of water temperature, the concentration distribution of frazil ice, the transport of floating ice, the progression, stability, and thawing of ice cover, and the transport, accumulation, and erosion of ice under ice cover. A MacCormack scheme was used to solve the equations numerically. The model was validated with field observations from the Hequ Reach of the Yellow River. Comparison of simulation results with field data indicates that the model is capable of simulating the river ice process with high accuracy.

  14. Tanning Shade Gradations of Models in Mainstream Fitness and Muscle Enthusiast Magazines: Implications for Skin Cancer Prevention in Men

    National Research Council Canada - National Science Library

    Basch, Corey H; Hillyer, Grace Clarke; Ethan, Danna; Berdnik, Alyssa; Basch, Charles E

    2015-01-01

    .... This study evaluated and compared tanning shade gradations of adult Caucasian male and female model images in mainstream fitness and muscle enthusiast magazines. Sixty-nine U.S. magazine issues...

  15. The use of the Levenberg-Marquardt curve-fitting algorithm in pharmacokinetic modelling of DCE-MRI data.

    Science.gov (United States)

    Ahearn, T S; Staff, R T; Redpath, T W; Semple, S I K

    2005-05-07

    The use of curve-fitting and compartmental modelling for calculating physiological parameters from measured data has increased in popularity in recent years. Finding the 'best fit' of a model to data involves the minimization of a merit function. An example of a merit function is the sum of the squares of the differences between the data points and the model estimated points. This is facilitated by curve-fitting algorithms. Two curve-fitting methods, Levenberg-Marquardt and MINPACK-1, are investigated with respect to the search start points that they require and the accuracy of the returned fits. We have simulated one million dynamic contrast enhanced MRI curves using a range of parameters and investigated the use of single and multiple search starting points. We found that both algorithms, when used with a single starting point, return unreliable fits. When multiple start points are used, we found that both algorithms returned reliable parameters. However the MINPACK-1 method generally outperformed the Levenberg-Marquardt method. We conclude that the use of a single starting point when fitting compartmental modelling data such as this produces unsafe results and we recommend the use of multiple start points in order to find the global minima.

  16. Fit model between participation statement of exhibitors and visitors to improve the exhibition performance

    Directory of Open Access Journals (Sweden)

    Cristina García Magro

    2015-06-01

    Full Text Available Purpose: The aims of the paper is offers a model of analysis which allows to measure the impact on the performance of fairs, as well as the knowledge or not of the motives of participation of the visitors on the part of the exhibitors. Design/methodology: A review of the literature is established concerning two of the principal interested agents, exhibitors and visitors, focusing. The study is focused on the line of investigation referred to the motives of participation or not in a trade show. According to the information thrown by each perspectives of study, a comparative analysis is carried out in order to determine the degree of existing understanding between both. Findings: The trade shows allow to be studied from an integrated strategic marketing approach. The fit model between the reasons for participation of exhibitors and visitors offer information on the lack of an understanding between exhibitors and visitors, leading to dissatisfaction with the participation, a fact that is reflected in the fair success. The model identified shows that a strategic plan must be designed in which the reason for participation of visitor was incorporated as moderating variable of the reason for participation of exhibitors. The article concludes with the contribution of a series of proposals for the improvement of fairground results. Social implications: The fit model that improve the performance of trade shows, implicitly leads to successful achievement of targets for multiple stakeholders beyond the consideration of visitors and exhibitors. Originality/value: The integrated perspective of stakeholders allows the study of the existing relationships between the principal groups of interest, in such a way that, having knowledge on the condition of the question of the trade shows facilitates the task of the investigator in future academic works and allows that the interested groups obtain a better performance to the participation in fairs, as visitor or as

  17. Improving the Fit of a Land-Surface Model to Data Using its Adjoint

    Science.gov (United States)

    Raoult, Nina; Jupp, Tim; Cox, Peter; Luke, Catherine

    2016-04-01

    Land-surface models (LSMs) are crucial components of the Earth System Models (ESMs) which are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. In this study, JULES is automatically differentiated using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed, to search for locally optimum parameter sets by calibrating against observations. We present an introduction to the adJULES system and demonstrate its ability to improve the model-data fit using eddy covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the 5 Plant Functional Types (PFTS) in JULES. The optimised PFT-specific parameters improve the performance of JULES over 90% of the FLUXNET sites used in the study. These reductions in error are shown and compared to reductions found due to site-specific optimisations. Finally, we show that calculation of the 2nd derivative of JULES allows us to produce posterior probability density functions of the parameters and how knowledge of parameter values is constrained by observations.

  18. Variance analysis for model updating with a finite element based subspace fitting approach

    Science.gov (United States)

    Gautier, Guillaume; Mevel, Laurent; Mencik, Jean-Mathieu; Serra, Roger; Döhler, Michael

    2017-07-01

    Recently, a subspace fitting approach has been proposed for vibration-based finite element model updating. The approach makes use of subspace-based system identification, where the extended observability matrix is estimated from vibration measurements. Finite element model updating is performed by correlating the model-based observability matrix with the estimated one, by using a single set of experimental data. Hence, the updated finite element model only reflects this single test case. However, estimates from vibration measurements are inherently exposed to uncertainty due to unknown excitation, measurement noise and finite data length. In this paper, a covariance estimation procedure for the updated model parameters is proposed, which propagates the data-related covariance to the updated model parameters by considering a first-order sensitivity analysis. In particular, this propagation is performed through each iteration step of the updating minimization problem, by taking into account the covariance between the updated parameters and the data-related quantities. Simulated vibration signals are used to demonstrate the accuracy and practicability of the derived expressions. Furthermore, an application is shown on experimental data of a beam.

  19. Explicit finite element modelling of the impaction of metal press-fit acetabular components.

    Science.gov (United States)

    Hothi, H S; Busfield, J J C; Shelton, J C

    2011-03-01

    Metal press-fit cups and shells are widely used in hip resurfacing and total hip replacement procedures. These acetabular components are inserted into a reamed acetabula cavity by either impacting their inner polar surface (shells) or outer rim (cups). Two-dimensional explicit dynamics axisymmetric finite element models were developed to simulate these impaction methods. Greater impact velocities were needed to insert the components when the interference fit was increased; a minimum velocity of 2 m/s was required to fully seat a component with a 2 mm interference between the bone and outer diameter. Changing the component material from cobalt-chromium to titanium alloy resulted in a reduction in the number of impacts on the pole to seat it from 14 to nine. Of greatest significance, it was found that locking a rigid cap to the cup or shell rim resulted in up to nine fewer impactions being necessary to seat it than impacting directly on the polar surface or using a cap free from the rim of the component, as is the case with many commercial resurfacing cup impaction devices currently used. This is important to impactor design and could make insertion easier and also reduce acetabula bone damage.

  20. Fitting Data to Model: Structural Equation Modeling Diagnosis Using Two Scatter Plots

    Science.gov (United States)

    Yuan, Ke-Hai; Hayashi, Kentaro

    2010-01-01

    This article introduces two simple scatter plots for model diagnosis in structural equation modeling. One plot contrasts a residual-based M-distance of the structural model with the M-distance for the factor score. It contains information on outliers, good leverage observations, bad leverage observations, and normal cases. The other plot contrasts…

  1. ANALYTICAL LIGHT CURVE MODELS OF SUPERLUMINOUS SUPERNOVAE: {chi}{sup 2}-MINIMIZATION OF PARAMETER FITS

    Energy Technology Data Exchange (ETDEWEB)

    Chatzopoulos, E.; Wheeler, J. Craig; Vinko, J. [Department of Astronomy, University of Texas at Austin, Austin, TX (United States); Horvath, Z. L.; Nagy, A., E-mail: manolis@astro.as.utexas.edu [Department of Optics and Quantum Electronics, University of Szeged (Hungary)

    2013-08-10

    We present fits of generalized semi-analytic supernova (SN) light curve (LC) models for a variety of power inputs including {sup 56}Ni and {sup 56}Co radioactive decay, magnetar spin-down, and forward and reverse shock heating due to supernova ejecta-circumstellar matter (CSM) interaction. We apply our models to the observed LCs of the H-rich superluminous supernovae (SLSN-II) SN 2006gy, SN 2006tf, SN 2008am, SN 2008es, CSS100217, the H-poor SLSN-I SN 2005ap, SCP06F6, SN 2007bi, SN 2010gx, and SN 2010kd, as well as to the interacting SN 2008iy and PTF 09uj. Our goal is to determine the dominant mechanism that powers the LCs of these extraordinary events and the physical conditions involved in each case. We also present a comparison of our semi-analytical results with recent results from numerical radiation hydrodynamics calculations in the particular case of SN 2006gy in order to explore the strengths and weaknesses of our models. We find that CS shock heating produced by ejecta-CSM interaction provides a better fit to the LCs of most of the events we examine. We discuss the possibility that collision of supernova ejecta with hydrogen-deficient CSM accounts for some of the hydrogen-deficient SLSNe (SLSN-I) and may be a plausible explanation for the explosion mechanism of SN 2007bi, the pair-instability supernova candidate. We characterize and discuss issues of parameter degeneracy.

  2. FIT ANALYSIS OF INDOSAT DOMPETKU BUSINESS MODEL USING A STRATEGIC DIAGNOSIS APPROACH

    Directory of Open Access Journals (Sweden)

    Fauzi Ridwansyah

    2015-09-01

    Full Text Available Mobile payment is an industry's response to global and regional technological-driven, as well as national social-economical driven in less cash society development. The purposes of this study were 1 identifying positioning of PT. Indosat in providing a response to Indonesian mobile payment market, 2 analyzing Indosat’s internal capabilities and business model fit with environment turbulence, and 3 formulating the optimum mobile payment business model development design for Indosat. The method used in this study was a combination of qualitative and quantitative analysis through in-depth interviews with purposive judgment sampling. The analysis tools used in this study were Business Model Canvas (MBC and Ansoff’s Strategic Diagnosis. The interviewees were the representatives of PT. Indosat internal management and mobile payment business value chain stakeholders. Based on BMC mapping which is then analyzed by strategic diagnosis model, a considerable gap (>1 between the current market environment and Indosat strategy of aggressiveness with the expected future of environment turbulence level was obtained. Therefore, changes in the competitive strategy that need to be conducted include 1 developing a new customer segment, 2 shifting the value proposition that leads to the extensification of mobile payment, 3 monetizing effective value proposition, and 4 integrating effective collaboration for harmonizing company’s objective with the government's vision. Keywords: business model canvas, Indosat, mobile payment, less cash society, strategic diagnosis

  3. The shape of dark matter haloes - II. The GALACTUS H I modelling & fitting tool

    Science.gov (United States)

    Peters, S. P. C.; van der Kruit, P. C.; Allen, R. J.; Freeman, K. C.

    2017-01-01

    We present a new H I modelling tool called GALACTUS. The program has been designed to perform automated fits of disc-galaxy models to observations. It includes a treatment for the self-absorption of gas. The software has been released into the public domain. We describe the design philosophy and inner workings of the program. After this, we model the face-on galaxy NGC 2403 using both self-absorption and optically thin models, showing that self-absorption occurs even in face-on galaxies. These results are then used to model an edge-on galaxy. It is shown that the maximum surface brightness plateaus seen in Paper I of this series are indeed signs of self-absorption. The apparent H I mass of an edge-on galaxy can be drastically lower compared with that same galaxy seen face-on. The Tully-Fisher relation is found to be relatively free from self-absorption issues.

  4. Optimized aerodynamic design process for subsonic transport wing fitted with winglets. [wind tunnel model

    Science.gov (United States)

    Kuhlman, J. M.

    1979-01-01

    The aerodynamic design of a wind-tunnel model of a wing representative of that of a subsonic jet transport aircraft, fitted with winglets, was performed using two recently developed optimal wing-design computer programs. Both potential flow codes use a vortex lattice representation of the near-field of the aerodynamic surfaces for determination of the required mean camber surfaces for minimum induced drag, and both codes use far-field induced drag minimization procedures to obtain the required spanloads. One code uses a discrete vortex wake model for this far-field drag computation, while the second uses a 2-D advanced panel wake model. Wing camber shapes for the two codes are very similar, but the resulting winglet camber shapes differ widely. Design techniques and considerations for these two wind-tunnel models are detailed, including a description of the necessary modifications of the design geometry to format it for use by a numerically controlled machine for the actual model construction.

  5. Body-Fitted Detonation Shock Dynamics and the Pseudo-Reaction-Zone Energy Release Model

    Science.gov (United States)

    Meyer, Chad; Quirk, James; Short, Mark; Chqiuete, Carlos

    2016-11-01

    Programmed-burn methods are a class of models used to propagate a detonation wave, without the high resolution cost associated with a direct numerical simulation. They separate the detonation evolution calculation into two components: timing and energy release. The timing component is usually calculated with a Detonation Shock Dynamics model, a surface evolution representation that relates the normal velocity of the surface (Dn) to its local curvature. The energy release component must appropriately capture the degree of energy change associated with chemical reaction while simultaneously remaining synchronized with the timing component. The Pseudo-Reaction-Zone (PRZ) model is a reactive burn like energy release model, converting reactants into products, but with a conversion rate that is a function of the DSD surface Dn field. As such, it requires the DSD calculation produce smooth Dn fields, a challenge in complex geometries. We describe a new body-fitted approach to the Detonation Shock Dynamics calculation which produces the required smooth Dn fields, and a method for calibrating the PRZ model such that the rate of energy release remains as synced as possible with the timing component. We show results for slab, rate-stick and arc geometries.

  6. Fitting parametric random effects models in very large data sets with application to VHA national data

    Directory of Open Access Journals (Sweden)

    Gebregziabher Mulugeta

    2012-10-01

    Full Text Available Abstract Background With the current focus on personalized medicine, patient/subject level inference is often of key interest in translational research. As a result, random effects models (REM are becoming popular for patient level inference. However, for very large data sets that are characterized by large sample size, it can be difficult to fit REM using commonly available statistical software such as SAS since they require inordinate amounts of computer time and memory allocations beyond what are available preventing model convergence. For example, in a retrospective cohort study of over 800,000 Veterans with type 2 diabetes with longitudinal data over 5 years, fitting REM via generalized linear mixed modeling using currently available standard procedures in SAS (e.g. PROC GLIMMIX was very difficult and same problems exist in Stata’s gllamm or R’s lme packages. Thus, this study proposes and assesses the performance of a meta regression approach and makes comparison with methods based on sampling of the full data. Data We use both simulated and real data from a national cohort of Veterans with type 2 diabetes (n=890,394 which was created by linking multiple patient and administrative files resulting in a cohort with longitudinal data collected over 5 years. Methods and results The outcome of interest was mean annual HbA1c measured over a 5 years period. Using this outcome, we compared parameter estimates from the proposed random effects meta regression (REMR with estimates based on simple random sampling and VISN (Veterans Integrated Service Networks based stratified sampling of the full data. Our results indicate that REMR provides parameter estimates that are less likely to be biased with tighter confidence intervals when the VISN level estimates are homogenous. Conclusion When the interest is to fit REM in repeated measures data with very large sample size, REMR can be used as a good alternative. It leads to reasonable inference for

  7. A new fit-for-purpose model testing framework: Decision Crash Tests

    Science.gov (United States)

    Tolson, Bryan; Craig, James

    2016-04-01

    Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building

  8. Fast hybrid fitting energy-based active contour model for target detection

    Institute of Scientific and Technical Information of China (English)

    Dengwei Wang; Tianxu Zhang; Luxin Yan

    2011-01-01

    A novel hybrid fitting energy-based active contour model in the level set framework is proposed.The method fuses the region and boundary information of the target to achieve accurate and robust detection performance.A special extra term that penalizes the deviation of the level set function from a signed distance function is also included in our method. This term allows the time-consuming redistancing operation to be removed completely.Moreover,a fast unconditionally stable numerical scheme is introduced to solve the problem.Experimental results on real infrared images show that our method can improve target detection performance efficiently in terms of the number of iterations and the wasted central processing unit(CPU) time.

  9. Strain estimation in 3D by fitting linear and planar data to the March model

    Science.gov (United States)

    Mulchrone, Kieran F.; Talbot, Christopher J.

    2016-08-01

    The probability density function associated with the March model is derived and used in a maximum likelihood method to estimate the best fit distribution and 3D strain parameters for a given set of linear or planar data. Typically it is assumed that in the initial state (pre-strain) linear or planar data are uniformly distributed on the sphere which means the number of strain parameters estimated needs to be reduced so that the numerical technique succeeds. Essentially this requires that the data are rotated into a suitable reference frame prior to analysis. The method has been applied to a suitable example from the Dalradian of SW Scotland and results obtained are consistent with those from an independent method of strain analysis. Despite March theory having been incorporated deep into the fabric of geological strain analysis, its full potential as a simple direct 3D strain analytical tool has not been achieved. The method developed here may help remedy this situation.

  10. Corneal modeling using conic section fits of PAR corneal topography system measurements

    Science.gov (United States)

    Zipper, Stanley; Manns, Fabrice; Fernandez, Viviana; Sandadi, Samith; Ho, Arthur; Parel, Jean-Marie A.

    2001-06-01

    The purpose of this study was to measure the average shape and variability of human corneas and to develop a tool for analyzing, height, curvature, and aberrations based on a conic section model. Fresh Eye Bank Eyes were placed in Dextran until the corneal thickness reached a physiological value. The eyes were placed in a custom made holder and measured using an intraoperative PAR Corneal Topography System (CTS) mounted on an operation microscope. Topography was measured before and after removal of the epithelium. A series of MATLAB functions were written to analyze the raw-z (height) data in polar coordinates. The functions fit conic sections to the PAR CTS data along hemi-meridians at 5 degree(s) intervals. The conic shape factor and apical radius were used to calculate and display the curvature. The dependence of these parameters with meridional position was examined.

  11. Goodness-of-fit tests for vector autoregressive models in time series

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The paper proposes and studies some diagnostic tools for checking the goodness-of-fit of general parametric vector autoregressive models in time series. The resulted tests are asymptotically chi-squared under the null hypothesis and can detect the alternatives converging to the null at a parametric rate. The tests involve weight functions,which provides us with the flexibility to choose scores for enhancing power performance,especially under directional alternatives. When the alternatives are not directional,we construct asymptotically distribution-free maximin tests for a large class of alternatives. A possibility to construct score-based omnibus tests is discussed when the alternative is saturated. The power performance is also investigated. In addition,when the sample size is small,a nonparametric Monte Carlo test approach for dependent data is proposed to improve the performance of the tests. The algorithm is easy to implement. Simulation studies and real applications are carried out for illustration.

  12. On the Model-Based Bootstrap with Missing Data: Obtaining a "P"-Value for a Test of Exact Fit

    Science.gov (United States)

    Savalei, Victoria; Yuan, Ke-Hai

    2009-01-01

    Evaluating the fit of a structural equation model via bootstrap requires a transformation of the data so that the null hypothesis holds exactly in the sample. For complete data, such a transformation was proposed by Beran and Srivastava (1985) for general covariance structure models and applied to structural equation modeling by Bollen and Stine…

  13. Applying the Bollen-Stine Bootstrap for Goodness-of-Fit Measures to Structural Equation Models with Missing Data.

    Science.gov (United States)

    Enders, Craig K.

    2002-01-01

    Proposed a method for extending the Bollen-Stine bootstrap model (K. Bollen and R. Stine, 1992) fit to structural equation models with missing data. Developed a Statistical Analysis System macro program to implement this procedure, and assessed its usefulness in a simulation. The new method yielded model rejection rates close to the nominal 5%…

  14. A simple algorithm for optimization and model fitting: AGA (asexual genetic algorithm)

    Science.gov (United States)

    Cantó, J.; Curiel, S.; Martínez-Gómez, E.

    2009-07-01

    Context: Mathematical optimization can be used as a computational tool to obtain the optimal solution to a given problem in a systematic and efficient way. For example, in twice-differentiable functions and problems with no constraints, the optimization consists of finding the points where the gradient of the objective function is zero and using the Hessian matrix to classify the type of each point. Sometimes, however it is impossible to compute these derivatives and other type of techniques must be employed such as the steepest descent/ascent method and more sophisticated methods such as those based on the evolutionary algorithms. Aims: We present a simple algorithm based on the idea of genetic algorithms (GA) for optimization. We refer to this algorithm as AGA (asexual genetic algorithm) and apply it to two kinds of problems: the maximization of a function where classical methods fail and model fitting in astronomy. For the latter case, we minimize the chi-square function to estimate the parameters in two examples: the orbits of exoplanets by taking a set of radial velocity data, and the spectral energy distribution (SED) observed towards a YSO (Young Stellar Object). Methods: The algorithm AGA may also be called genetic, although it differs from standard genetic algorithms in two main aspects: a) the initial population is not encoded; and b) the new generations are constructed by asexual reproduction. Results: Applying our algorithm in optimizing some complicated functions, we find the global maxima within a few iterations. For model fitting to the orbits of exoplanets and the SED of a YSO, we estimate the parameters and their associated errors.

  15. Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS

    DEFF Research Database (Denmark)

    Bolker, B.M.; Gardner, B.; Maunder, M.

    2013-01-01

    ) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical...

  16. Ignoring imperfect detection in biological surveys is dangerous: a response to 'fitting and interpreting occupancy models'.

    Directory of Open Access Journals (Sweden)

    Gurutzeta Guillera-Arroita

    Full Text Available In a recent paper, Welsh, Lindenmayer and Donnelly (WLD question the usefulness of models that estimate species occupancy while accounting for detectability. WLD claim that these models are difficult to fit and argue that disregarding detectability can be better than trying to adjust for it. We think that this conclusion and subsequent recommendations are not well founded and may negatively impact the quality of statistical inference in ecology and related management decisions. Here we respond to WLD's claims, evaluating in detail their arguments, using simulations and/or theory to support our points. In particular, WLD argue that both disregarding and accounting for imperfect detection lead to the same estimator performance regardless of sample size when detectability is a function of abundance. We show that this, the key result of their paper, only holds for cases of extreme heterogeneity like the single scenario they considered. Our results illustrate the dangers of disregarding imperfect detection. When ignored, occupancy and detection are confounded: the same naïve occupancy estimates can be obtained for very different true levels of occupancy so the size of the bias is unknowable. Hierarchical occupancy models separate occupancy and detection, and imprecise estimates simply indicate that more data are required for robust inference about the system in question. As for any statistical method, when underlying assumptions of simple hierarchical models are violated, their reliability is reduced. Resorting in those instances where hierarchical occupancy models do no perform well to the naïve occupancy estimator does not provide a satisfactory solution. The aim should instead be to achieve better estimation, by minimizing the effect of these issues during design, data collection and analysis, ensuring that the right amount of data is collected and model assumptions are met, considering model extensions where appropriate.

  17. The extended Lennard-Jones potential energy function: A simpler model for direct-potential-fit analysis

    Science.gov (United States)

    Hajigeorgiou, Photos G.

    2016-12-01

    An analytical model for the diatomic potential energy function that was recently tested as a universal function (Hajigeorgiou, 2010) has been further modified and tested as a suitable model for direct-potential-fit analysis. Applications are presented for the ground electronic states of three diatomic molecules: oxygen, carbon monoxide, and hydrogen fluoride. The adjustable parameters of the extended Lennard-Jones potential model are determined through nonlinear regression by fits to calculated rovibrational energy term values or experimental spectroscopic line positions. The model is shown to lead to reliable, compact and simple representations for the potential energy functions of these systems and could therefore be classified as a suitable and attractive model for direct-potential-fit analysis.

  18. Assessing performance of Bayesian state-space models fit to Argos satellite telemetry locations processed with Kalman filtering.

    Science.gov (United States)

    Silva, Mónica A; Jonsen, Ian; Russell, Deborah J F; Prieto, Rui; Thompson, Dave; Baumgartner, Mark F

    2014-01-01

    Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF). The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS) algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs) fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina) tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to "true" GPS locations. Data on 6 fin whales (Balaenoptera physalus) were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM) fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were model estimates (5.6 ± 5.6 km) was nearly half that of LS estimates (11.6 ± 8.4 km). Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Precision of KF locations for whales was generally higher. Whales' behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates.

  19. Mathematical Modeling of Allelopathy. III. A Model for Curve-Fitting Allelochemical Dose Responses

    OpenAIRE

    Liu, Li; An, Min; Johnson, Ian R.; Lovett, John V.

    2003-01-01

    Bioassay techniques are often used to study the effects of allelochemicals on plant processes, and it is generally observed that the processes are stimulated at low allelochemical concentrations and inhibited as the concentrations increase. A simple empirical model is presented to analyze this type of response. The stimulation-inhibition properties of allelochemical-dose responses can be described by the parameters in the model. The indices, p% reductions, are calculated to assess the alleloc...

  20. An approximation to the adaptive exponential integrate-and-fire neuron model allows fast and predictive fitting to physiological data

    Directory of Open Access Journals (Sweden)

    Loreen eHertäg

    2012-09-01

    Full Text Available For large-scale network simulations, it is often desirable to have computationally tractable, yet in a defined sense still physiologically valid neuron models. In particular, these models should be able to reproduce physiological measurements, ideally in a predictive sense, and under different input regimes in which neurons may operate in vivo. Here we present an approach to parameter estimation for a simple spiking neuron model mainly based on standard f-I curves obtained from in vitro recordings. Such recordings are routinely obtained in standard protocols and assess a neuron's response under a wide range of mean input currents. Our fitting procedure makes use of closed-form expressions for the firing rate derived from an approximation to the adaptive exponential integrate-and-fire (AdEx model. The resulting fitting process is simple and about two orders of magnitude faster compared to methods based on numerical integration of the differential equations. We probe this method on different cell types recorded from rodent prefrontal cortex. After fitting to the f-I current-clamp data, the model cells are tested on completely different sets of recordings obtained by fluctuating ('in-vivo-like' input currents. For a wide range of different input regimes, cell types, and cortical layers, the model could predict spike times on these test traces quite accurately within the bounds of physiological reliability, although no information from these distinct test sets was used for model fitting. Further analyses delineated some of the empirical factors constraining model fitting and the model's generalization performance. An even simpler adaptive LIF neuron was also examined in this context. Hence, we have developed a 'high-throughput' model fitting procedure which is simple and fast, with good prediction performance, and which relies only on firing rate information and standard physiological data widely and easily available.

  1. Experimental Evidence of the Superiority of the Prevalence Model of Conceptual Change over the Classical Models and Repetition

    Science.gov (United States)

    Potvin, Patrice; Sauriol, Érik; Riopel, Martin

    2015-01-01

    This quasi-experimental study investigated the effects on 558 grades five and six students of three different teaching conditions: the "classical" model of conceptual change (for which cognitive conflict is considered as a precondition to the transformation of knowledge), the "prevalence" model of conceptual change (in which…

  2. Fitting density models to observational data - The local Schmidt law in molecular clouds

    CERN Document Server

    Lombardi, Marco; Alves, João

    2013-01-01

    We consider the general problem of fitting a parametric density model to discrete observations, taken to follow a non-homogeneous Poisson point process. This class of models is very common, and can be used to describe many astrophysical processes, including the distribution of protostars in molecular clouds. We give the expression for the likelihood of a given spatial density distribution of protostars and apply it to infer the most probable dependence of the protostellar surface density on the gas surface density. Finally, we apply this general technique to model the distribution of protostars in the Orion molecular cloud and robustly derive the local star formation scaling (Schmidt) law for a molecular cloud. We find that in this cloud the protostellar surface density, \\Sigma_YSO, is directly proportional to the square gas column density, here expressed as infrared extinction in the K-band, A_K: more precisely, \\Sigma_YSO = (1.65 +/- 0.19) A_K^(2.03 +/- 0.15) stars pc^-2.

  3. Minimal see-saw model predicting best fit lepton mixing angles

    Energy Technology Data Exchange (ETDEWEB)

    King, Stephen F., E-mail: king@soton.ac.uk

    2013-07-09

    We discuss a minimal predictive see-saw model in which the right-handed neutrino mainly responsible for the atmospheric neutrino mass has couplings to (ν{sub e},ν{sub μ},ν{sub τ}) proportional to (0,1,1) and the right-handed neutrino mainly responsible for the solar neutrino mass has couplings to (ν{sub e},ν{sub μ},ν{sub τ}) proportional to (1,4,2), with a relative phase η=−2π/5. We show how these patterns of couplings could arise from an A{sub 4} family symmetry model of leptons, together with Z{sub 3} and Z{sub 5} symmetries which fix η=−2π/5 up to a discrete phase choice. The PMNS matrix is then completely determined by one remaining parameter which is used to fix the neutrino mass ratio m{sub 2}/m{sub 3}. The model predicts the lepton mixing angles θ{sub 12}≈34{sup ∘},θ{sub 23}≈41{sup ∘},θ{sub 13}≈9.5{sup ∘}, which exactly coincide with the current best fit values for a normal neutrino mass hierarchy, together with the distinctive prediction for the CP violating oscillation phase δ≈106{sup ∘}.

  4. Fitting models of continuous trait evolution to incompletely sampled comparative data using approximate Bayesian computation.

    Science.gov (United States)

    Slater, Graham J; Harmon, Luke J; Wegmann, Daniel; Joyce, Paul; Revell, Liam J; Alfaro, Michael E

    2012-03-01

    In recent years, a suite of methods has been developed to fit multiple rate models to phylogenetic comparative data. However, most methods have limited utility at broad phylogenetic scales because they typically require complete sampling of both the tree and the associated phenotypic data. Here, we develop and implement a new, tree-based method called MECCA (Modeling Evolution of Continuous Characters using ABC) that uses a hybrid likelihood/approximate Bayesian computation (ABC)-Markov-Chain Monte Carlo approach to simultaneously infer rates of diversification and trait evolution from incompletely sampled phylogenies and trait data. We demonstrate via simulation that MECCA has considerable power to choose among single versus multiple evolutionary rate models, and thus can be used to test hypotheses about changes in the rate of trait evolution across an incomplete tree of life. We finally apply MECCA to an empirical example of body size evolution in carnivores, and show that there is no evidence for an elevated rate of body size evolution in the pinnipeds relative to terrestrial carnivores. ABC approaches can provide a useful alternative set of tools for future macroevolutionary studies where likelihood-dependent approaches are lacking.

  5. Supersymmetric Fits after the Higgs Discovery and Implications for Model Building

    CERN Document Server

    Ellis, John

    2014-01-01

    The data from the first run of the LHC at 7 and 8 TeV, together with the information provided by other experiments such as precision electroweak measurements, flavour measurements, the cosmological density of cold dark matter and the direct search for the scattering of dark matter particles in the LUX experiment, provide important constraints on supersymmetric models. Important information is provided by the ATLAS and CMS measurements of the mass of the Higgs boson, as well as the negative results of searches at the LHC for events with missing transverse energy accompanied by jets, and the LHCb and CMS measurements off BR($B_s \\to \\mu^+ \\mu^-$). Results are presented from frequentist analyses of the parameter spaces of the CMSSM and NUHM1. The global $\\chi^2$ functions for the supersymmetric models vary slowly over most of the parameter spaces allowed by the Higgs mass and the missing transverse energy search, with best-fit values that are comparable to the $\\chi^2$ for the Standard Model. The $95\\%$ CL lower...

  6. Fitting a Thurstonian IRT model to forced-choice data using Mplus.

    Science.gov (United States)

    Brown, Anna; Maydeu-Olivares, Alberto

    2012-12-01

    To counter response distortions associated with the use of rating scales (a.k.a. Likert scales), items can be presented in a comparative fashion, so that respondents are asked to rank the items within blocks (forced-choice format). However, classical scoring procedures for these forced-choice designs lead to ipsative data, which presents psychometric challenges that are well described in the literature. Recently, Brown and Maydeu-Olivares (Educational and Psychological Measurement 71: 460-502, 2011a) introduced a model based on Thurstone's law of comparative judgment, which overcomes the problems of ipsative data. Here, we provide a step-by-step tutorial for coding forced-choice responses, specifying a Thurstonian item response theory model that is appropriate for the design used, assessing the model's fit, and scoring individuals on psychological attributes. Estimation and scoring is performed using Mplus, and a very straightforward Excel macro is provided that writes full Mplus input files for any forced-choice design. Armed with these tools, using a forced-choice design is now as easy as using ratings.

  7. Global fits of GUT-scale SUSY models with GAMBIT arXiv

    CERN Document Server

    Athron, Peter; Bringmann, Torsten; Buckley, Andy; Chrząszcz, Marcin; Conrad, Jan; Cornell, Jonathan M.; Dal, Lars A.; Edsjö, Joakim; Farmer, Ben; Jackson, Paul; Krislock, Abram; Kvellestad, Anders; Mahmoudi, Farvah; \\ Martinez, Gregory D.; Putze, Antje; Raklev, Are; Rogan, Christopher; Ruiz de Austri, Roberto; Saavedra, Aldo; Savage, Christopher; Scott, Pat; Serra, Nicola; Weniger, Christoph; White, Martin

    We present the most comprehensive global fits to date of three supersymmetric models motivated by grand unification: the Constrained Minimal Supersymmetric Standard Model (CMSSM), and its Non-Universal Higgs Mass generalisations NUHM1 and NUHM2. We include likelihoods from a number of direct and indirect dark matter searches, a large collection of electroweak precision and flavour observables, direct searches for supersymmetry at LEP and Runs I and II of the LHC, and constraints from Higgs observables. Our analysis improves on existing results not only in terms of the number of included observables, but also in the level of detail with which we treat them, our sampling techniques for scanning the parameter space, and our treatment of nuisance parameters. We show that stau co-annihilation is now ruled out in the CMSSM at more than 95\\% confidence. Stop co-annihilation turns out to be one of the most promising mechanisms for achieving an appropriate relic density of dark matter in all three models, whilst avoid...

  8. Modeling of physical fitness of young karatyst on the pre basic training

    Directory of Open Access Journals (Sweden)

    Galimskyi V.A.

    2014-05-01

    Full Text Available Purpose : to develop a program of physical fitness for the correction of the pre basic training on the basis of model performance. Material: 57 young karate sportsmen of 9-11 years old took part in the research. Results : the level of general and special physical preparedness of young karate 9-11 years old was determined. Classes in the control group occurred in the existing program for yous sports school Muay Thai (Thailand boxing. For the experimental group has developed a program of selective development of general and special physical qualities of model-based training sessions. Special program contains 6 direction: 1. Development of static and dynamic balance; 2. Development of vestibular stability (precision movements after rotation; 3. Development rate movements; 4. The development of the capacity for rapid restructuring movements; 5. Development capabilities to differentiate power and spatial parameters of movement; 6. Development of the ability to perform jumping movements of rotation. Development of special physical qualities continued to work to improve engineering complex shock motions on the place and with movement. Conclusions : the use of selective development of special physical qualities based models of training sessions has a significant performance advantage over the control group.

  9. Why Simple Stellar Population models do not fit the colours of Galactic open clusters

    CERN Document Server

    Piskunov, A E; Schilbach, E; Röser, S; Scholz, R -D; Zinnecker, H

    2009-01-01

    (...) We have found a disagreement between the observed integrated colours of 650 local Galactic clusters and theoretical colours of present-day SSP models and seek an explanation for this discrepancy. We check the hypothesis that the systematic offset between observed and theoretical colours, which is $(B$$-$$V)\\approx 0.3$ \\textbf{and $(J$$-$$K_s)\\approx 0.8$}, is due to neglecting the discrete nature of the underlying mass function. Using Monte Carlo simulations we construct artificial clusters of coeval stars drawn from a mass distribution according to the Salpeter IMF and compare them with corresponding "continuous-IMF" SSP models. If the discreteness of the IMF is taken into account, the model fits the observations perfectly and is able to explain naturally a number of red "outliers" observed in the empirical colour-age relation. We find that the \\textit{systematic} offset between the continuous- and discrete-IMF colours reaches its maximum of about 0.5 in $(B$$-$$V)$ for a cluster mass $M_c=10^2 m_\\odo...

  10. Unilateral Superior Laryngeal Nerve Lesion in an Animal Model of Dysphagia and Its Effect on Sucking and Swallowing

    Science.gov (United States)

    Campbell-Malone, Regina; Holman, Shaina D.; Lukasik, Stacey L.; Fukuhara, Takako; Gierbolini-Norat, Estela M.; Thexton, Allan J.; German, Rebecca Z.

    2013-01-01

    We tested two hypotheses relating to the sensory deficit that follows a unilateral superior laryngeal nerve (SLN) lesion in an infant animal model. We hypothesized that it would result in (1) a higher incidence of aspiration and (2) temporal changes in sucking and swallowing. We ligated the right-side SLN in six 2–3-week-old female pigs. Using videofluoroscopy, we recorded swallows in the same pre- and post-lesion infant pigs. We analyzed the incidence of aspiration and the duration and latency of suck and swallow cycles. After unilateral SLN lesioning, the incidence of silent aspiration during swallowing increased from 0.7 to 41.5 %. The durations of the suck containing the swallow, the suck immediately following the swallow, and the swallow itself were significantly longer in the post-lesion swallows, although the suck prior to the swallow was not different. The interval between the start of the suck containing a swallow and the subsequent epiglottal movement was longer in the post-lesion swallows. The number of sucks between swallows was significantly greater in post-lesion swallows compared to pre-lesion swallows. Unilateral SLN lesion increased the incidence of aspiration and changed the temporal relationships between sucking and swallowing. The longer transit time and the temporal coordinative dysfunction between suck and swallow cycles may contribute to aspiration. These results suggest that swallow dysfunction and silent aspiration are common and potentially overlooked sequelae of unilateral SLN injury. This validated animal model of aspiration has the potential for further dysphagia studies. PMID:23417250

  11. Experimental model for non-Newtonian fluid viscosity estimation: Fit to mathematical expressions

    Directory of Open Access Journals (Sweden)

    Guillem Masoliver i Marcos

    2017-01-01

    Full Text Available The  construction  process  of  a  viscometer,  developed  in  collaboration  with  a  final  project  student,  is  here  presented.  It  is  intended  to  be  used  by   first  year's  students  to  know  the  viscosity  as  a  fluid  property, for  both  Newtonian  and  non-Newtonian  flows.  Viscosity  determination  is  crucial  for  the  fluids  behaviour knowledge  related  to  their  reologic  and  physical  properties.  These  have  great  implications  in  engineering aspects  such  as  friction  or  lubrication.  With  the  present  experimental  model  device  three  different fluids are  analyzed  (water,  kétchup  and  a  mixture  with  cornstarch  and  water.  Tangential stress is measured versus velocity in order to characterize all the fluids in different thermal conditions. A mathematical fit process is proposed to be done in order to adjust the results to expected analytical expressions, obtaining good results for these fittings, with R2 greater than 0.88 in any case.

  12. Poisson distribution and process as a well-fitting pattern for counting variables in biologic models

    Directory of Open Access Journals (Sweden)

    Lucietta Betti

    2012-09-01

    Full Text Available One of the major criticisms directed to basic research on high dilution effects is the lack of a steady statistical approach; therefore, it seems crucial to fix some milestones in statistical analysis of this kind of experimentation. Since plant research in homeopathy has been recently developed and one of the mostly used models is based on in vitro seed germination, here we propose a statistical approach focused on the Poisson distribution, that satisfactorily fits the number of non-germinated seeds. Poisson distribution is a discrete-valued model often used in statistics when representing the number X of specific events (telephone calls, industrial machine failures, genetic mutations etc. that occur in a fixed period of time, supposing that instant probability of occurrence of such events is constant. If we denote with λ the average number of events that occur within the fixed period, the probability of observing exactly k events is: P(k = e-λ λk /k! , k = 0, 1,2,… This distribution is commonly used when dealing with rare effects, in the sense that it has to be almost impossible to have two events at the same time. Poisson distribution is the basic model of the socalled Poisson process, which is a counting process N(t, where t is a time parameter, having these properties: -The process starts with zero: N(0 = 0; -The increments are independent; -The number of events that occur in a period of time d(t follows a Poisson distribution with parameter proportional to d(t; -The waiting time, i.e. the time between an event and another one, follows and exponential distribution. In a series of experiments performed by our research group ([1], [2]., [3], [4] we tried to apply this distribution to the number X of non-germinated seeds out of a fixed number N* of seeds in a Petri dish (usually N* = 33 or N* = 36. The goodness-of-fit was checked by different tests (Kolmogorov distance and chi-squared, as well as

  13. On Eigen's Quasispecies Model, Two-Valued Fitness Landscapes, and Isometry Groups Acting on Finite Metric Spaces.

    Science.gov (United States)

    Semenov, Yuri S; Novozhilov, Artem S

    2016-05-01

    A two-valued fitness landscape is introduced for the classical Eigen's quasispecies model. This fitness landscape can be considered as a direct generalization of the so-called single- or sharply peaked landscape. A general, non-permutation invariant quasispecies model is studied, and therefore the dimension of the problem is [Formula: see text], where N is the sequence length. It is shown that if the fitness function is equal to [Formula: see text] on a G-orbit A and is equal to w elsewhere, then the mean population fitness can be found as the largest root of an algebraic equation of degree at most [Formula: see text]. Here G is an arbitrary isometry group acting on the metric space of sequences of zeroes and ones of the length N with the Hamming distance. An explicit form of this exact algebraic equation is given in terms of the spherical growth function of the G-orbit A. Motivated by the analysis of the two-valued fitness landscapes, an abstract generalization of Eigen's model is introduced such that the sequences are identified with the points of a finite metric space X together with a group of isometries acting transitively on X. In particular, a simplicial analog of the original quasispecies model is discussed, which can be considered as a mathematical model of the switching of the antigenic variants for some bacteria.

  14. Evapotranspiration measurement and modeling without fitting parameters in high-altitude grasslands

    Science.gov (United States)

    Ferraris, Stefano; Previati, Maurizio; Canone, Davide; Dematteis, Niccolò; Boetti, Marco; Balocco, Jacopo; Bechis, Stefano

    2016-04-01

    Mountain grasslands are important, also because one sixth of the world population lives inside watershed dominated by snowmelt. Also, grasslands provide food to both domestic and selvatic animals. The global warming will probably accelerate the hydrological cycle and increase the drought risk. The combination of measurements, modeling and remote sensing can furnish knowledge in such faraway areas (e.g.: Brocca et al., 2013). A better knowledge of water balance can also allow to optimize the irrigation (e.g.: Canone et al., 2015). This work is meant to build a model of water balance in mountain grasslands, ranging between 1500 and 2300 meters asl. The main input is the Digital Terrain Model, which is more reliable in grasslands than both in the woods and in the built environment. It drives the spatial variability of shortwave solar radiation. The other atmospheric forcings are more problematic to estimate, namely air temperature, wind and longwave radiation. Ad hoc routines have been written, in order to interpolate in space the meteorological hourly time variability. The soil hydraulic properties are less variable than in the plains, but the soil depth estimation is still an open issue. The soil vertical variability has been modeled taking into account the main processes: soil evaporation, root uptake, and fractured bedrock percolation. The time variability latent heat flux and soil moisture results have been compared with the data measured in an eddy covariance station. The results are very good, given the fact that the model has no fitting parameters. The space variability results have been compared with the results of a model based on Landsat 7 and 8 data, applied over an area of about 200 square kilometers. The spatial correlation is quite in agreement between the two models. Brocca et al. (2013). "Soil moisture estimation in alpine catchments through modelling and satellite observations". Vadose Zone Journal, 12(3), 10 pp. Canone et al. (2015). "Field

  15. Equilibrium Reconstructions with V3FIT and Current Evolution Modeling for 3-D Stellarator Plasmas

    Science.gov (United States)

    Schmitt, J. C.; Cianciosa, M.; Geiger, J.; Lazerson, S.

    2016-10-01

    V3FIT is a powerful equilibrium reconstruction tool for magnetic confinement fusion experiments which are inherently 3-D in nature (i.e. stellarators) or have 3-D components (tokamaks with 3-D shaping, reversed field pinches with helical states, etc). Here, we present details of the diagnostic modeling, constraints and the user interface for reconstructions of W7-X plasmas. For typical discharges during the OP1.1 run campaign of W7-X, the net toroidal current and current density profile do not reach steady-state. When modeling the current evolution in 3-D plasmas, both poloidal and toroidal currents are linked with both poloidal and toroidal fluxes. In contrast, in toroidally axisymmetric plasmas, the poloidal flux is linked only with the toroidal current and the toroidal current is linked only with the poloidal flux. Compared to an equivalently-sized axisymmetric configuration, the current diffusion in 3-D plasmas is enhanced, leading to a faster relaxation of the current profile to its steady-state. Implications for the time-evolution of the current and rotational transform profiles in stellarator plasmas are discussed. This work is supported by DoE Grant DE-SC00014529.

  16. Model Order Selection for Short Data: An Exponential Fitting Test (EFT

    Directory of Open Access Journals (Sweden)

    Martin Haardt

    2007-01-01

    Full Text Available High-resolution methods for estimating signal processing parameters such as bearing angles in array processing or frequencies in spectral analysis may be hampered by the model order if poorly selected. As classical model order selection methods fail when the number of snapshots available is small, this paper proposes a method for noncoherent sources, which continues to work under such conditions, while maintaining low computational complexity. For white Gaussian noise and short data we show that the profile of the ordered noise eigenvalues is seen to approximately fit an exponential law. This fact is used to provide a recursive algorithm which detects a mismatch between the observed eigenvalue profile and the theoretical noise-only eigenvalue profile, as such a mismatch indicates the presence of a source. Moreover this proposed method allows the probability of false alarm to be controlled and predefined, which is a crucial point for systems such as RADARs. Results of simulations are provided in order to show the capabilities of the algorithm.

  17. A Mathematical Images Group Model to Estimate the Sound Level in a Close-Fitting Enclosure

    Directory of Open Access Journals (Sweden)

    Michael J. Panza

    2014-01-01

    Full Text Available This paper describes a special mathematical images model to determine the sound level inside a close-fitting sound enclosure. Such an enclosure is defined as the internal air volume defined by a machine vibration noise source at one wall and a parallel reflecting wall located very close to it and acts as the outside radiating wall of the enclosure. Four smaller surfaces define a parallelepiped for the volume. The main reverberation group is between the two large parallel planes. Viewed as a discrete line-type source, the main group is extended as additional discrete line-type source image groups due to reflections from the four smaller surfaces. The images group approach provides a convergent solution for the case where hard reflective surfaces are modeled with absorption coefficients equal to zero. Numerical examples are used to calculate the sound pressure level incident on the outside wall and the effect of adding high absorption to the front wall. This is compared to the result from the general large room diffuse reverberant field enclosure formula for several hard wall absorption coefficients and distances between machine and front wall. The images group method is shown to have low sensitivity to hard wall absorption coefficient value and presents a method where zero sound absorption for hard surfaces can be used rather than an initial hard surface sound absorption estimate or measurement to predict the internal sound levels the effect of adding absorption.

  18. A simulation-based goodness-of-fit test for random effects in generalized linear mixed models

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus

    2006-01-01

    The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...

  19. A simulation-based goodness-of-fit test for random effects in generalized linear mixed models

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus Plenge

    The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...

  20. A differential equation for the asymptotic fitness distribution in the Bak-Sneppen model with five species.

    Science.gov (United States)

    Schlemm, Eckhard

    2015-09-01

    The Bak-Sneppen model is an abstract representation of a biological system that evolves according to the Darwinian principles of random mutation and selection. The species in the system are characterized by a numerical fitness value between zero and one. We show that in the case of five species the steady-state fitness distribution can be obtained as a solution to a linear differential equation of order five with hypergeometric coefficients. Similar representations for the asymptotic fitness distribution in larger systems may help pave the way towards a resolution of the question of whether or not, in the limit of infinitely many species, the fitness is asymptotically uniformly distributed on the interval [fc, 1] with fc ≳ 2/3. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. Selection in spatial stochastic models of cancer: Migration as a key modulator of fitness

    Directory of Open Access Journals (Sweden)

    Stupack Dwayne

    2010-04-01

    Full Text Available Abstract Background We study the selection dynamics in a heterogeneous spatial colony of cells. We use two spatial generalizations of the Moran process, which include cell divisions, death and migration. In the first model, migration is included explicitly as movement to a proximal location. In the second, migration is implicit, through the varied ability of cell types to place their offspring a distance away, in response to another cell's death. Results In both models, we find that migration has a direct positive impact on the ability of a single mutant cell to invade a pre-existing colony. Thus, a decrease in the growth potential can be compensated by an increase in cell migration. We further find that the neutral ridges (the set of all types with the invasion probability equal to that of the host cells remain invariant under the increase of system size (for large system sizes, thus making the invasion probability a universal characteristic of the cells selection status. We find that repeated instances of large scale cell-death, such as might arise during therapeutic intervention or host response, strongly select for the migratory phenotype. Conclusions These models can help explain the many examples in the biological literature, where genes involved in cell's migratory and invasive machinery are also associated with increased cellular fitness, even though there is no known direct effect of these genes on the cellular reproduction. The models can also help to explain how chemotherapy may provide a selection mechanism for highly invasive phenotypes. Reviewers This article was reviewed by Marek Kimmel and Glenn Webb.

  2. Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting

    Energy Technology Data Exchange (ETDEWEB)

    Ross, James C., E-mail: jross@bwh.harvard.edu [Channing Laboratory, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Surgical Planning Lab, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Laboratory of Mathematics in Imaging, Brigham and Women' s Hospital, Boston, Massachusetts 02126 (United States); Kindlmann, Gordon L. [Computer Science Department and Computation Institute, University of Chicago, Chicago, Illinois 60637 (United States); Okajima, Yuka; Hatabu, Hiroto [Department of Radiology, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Díaz, Alejandro A. [Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 and Department of Pulmonary Diseases, Pontificia Universidad Católica de Chile, Santiago (Chile); Silverman, Edwin K. [Channing Laboratory, Brigham and Women' s Hospital, Boston, Massachusetts 02215 and Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 (United States); Washko, George R. [Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 (United States); Dy, Jennifer [ECE Department, Northeastern University, Boston, Massachusetts 02115 (United States); Estépar, Raúl San José [Department of Radiology, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Surgical Planning Lab, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Laboratory of Mathematics in Imaging, Brigham and Women' s Hospital, Boston, Massachusetts 02126 (United States)

    2013-12-15

    Purpose: Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. Methods: The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. Results: The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. Conclusions: The

  3. Are all models created equal? A content analysis of women in advertisements of fitness versus fashion magazines.

    Science.gov (United States)

    Wasylkiw, L; Emms, A A; Meuse, R; Poirier, K F

    2009-03-01

    The current study is a content analysis of women appearing in advertisements in two types of magazines: fitness/health versus fashion/beauty chosen because of their large and predominantly female readerships. Women appearing in advertisements of the June 2007 issue of five fitness/health magazines were compared to women appearing in advertisements of the June 2007 issue of five beauty/fashion magazines. Female models appearing in advertisements of both types of magazines were primarily young, thin Caucasians; however, images of models were more likely to emphasize appearance over performance when they appeared in fashion magazines. This difference in emphasis has implications for future research.

  4. An empirical study on the relationship between teacher's judgments and fit statistics of the partial credit model.

    Science.gov (United States)

    Baek, Sun-Geun; Kim, Hye-Sook

    2009-01-01

    The main purpose of the study was to investigate empirically the relationship between classroom teacher's judgment and the item and person fit-statistics of the partial credit model. In this study, classroom teacher's judgments were made intuitively checking each item's consistency with the general response pattern and each student's need for additional treatment or advice. The item and person fit statistics of the partial credit model were estimated using the WINSTEPS program (Linacre, 2003). The subjects of this study were 321 sixth grade students in 9 classrooms within 3 elementary schools in Seoul, Korea. For this research, a performance assessment test for 6th grade mathematics was developed. It consisted of 20 polytomous response items and its total scores ranged between 0 and 50. In addition, the 9 classroom teachers made their judgments for each item of the test and for each student in their own classroom. They judged intuitively using 4 categories; (1) well fit, (2) fit, (3) misfit, and (4) badly misfit for each item as well as each student. Their judgments were scored from 1 to 4 for each item as well as each student. There are two significant findings in this study. First, there is a statistically significant relationship between the classroom teacher's judgment and item fit statistic for each item (The median correlation coefficient between the teacher's judgment and the item outfit ZSTD is 0.61). Second, there is a statistically significant relationship between the teacher's judgment and the person fit statistic for each student (The median correlation coefficient between the teacher's judgment and the person outfit ZSTD is 0.52). In conclusion, the item and person fit statistics of the partial credit model correspond with the teacher's judgments for each test item and each student.

  5. High-resolution modeling of protein structures based on flexible fitting of low-resolution structural data.

    Science.gov (United States)

    Zheng, Wenjun; Tekpinar, Mustafa

    2014-01-01

    To circumvent the difficulty of directly solving high-resolution biomolecular structures, low-resolution structural data from Cryo-electron microscopy (EM) and small angle solution X-ray scattering (SAXS) are increasingly used to explore multiple conformational states of biomolecular assemblies. One promising venue to obtain high-resolution structural models from low-resolution data is via data-constrained flexible fitting. To this end, we have developed a new method based on a coarse-grained Cα-only protein representation, and a modified form of the elastic network model (ENM) that allows large-scale conformational changes while maintaining the integrity of local structures including pseudo-bonds and secondary structures. Our method minimizes a pseudo-energy which linearly combines various terms of the modified ENM energy with an EM/SAXS-fitting score and a collision energy that penalizes steric collisions. Unlike some previous flexible fitting efforts using the lowest few normal modes, our method effectively utilizes all normal modes so that both global and local structural changes can be fully modeled with accuracy. This method is also highly efficient in computing time. We have demonstrated our method using adenylate kinase as a test case which undergoes a large open-to-close conformational change. The EM-fitting method is available at a web server (http://enm.lobos.nih.gov), and the SAXS-fitting method is available as a pre-compiled executable upon request.

  6. Competitive Fitness of Influenza B Viruses with Neuraminidase Inhibitor-Resistant Substitutions in a Coinfection Model of the Human Airway Epithelium

    Science.gov (United States)

    Burnham, Andrew J.; Armstrong, Jianling; Lowen, Anice C.; Webster, Robert G.

    2015-01-01

    ABSTRACT Influenza A and B viruses are human pathogens that are regarded to cause almost equally significant disease burdens. Neuraminidase (NA) inhibitors (NAIs) are the only class of drugs available to treat influenza A and B virus infections, so the development of NAI-resistant viruses with superior fitness is a public health concern. The fitness of NAI-resistant influenza B viruses has not been widely studied. Here we examined the replicative capacity and relative fitness in normal human bronchial epithelial (NHBE) cells of recombinant influenza B/Yamanashi/166/1998 viruses containing a single amino acid substitution in NA generated by reverse genetics (rg) that is associated with NAI resistance. The replication in NHBE cells of viruses with reduced inhibition by oseltamivir (recombinant virus with the E119A mutation generated by reverse genetics [rg-E119A], rg-D198E, rg-I222T, rg-H274Y, rg-N294S, and rg-R371K, N2 numbering) or zanamivir (rg-E119A and rg-R371K) failed to be inhibited by the presence of the respective NAI. In a fluorescence-based assay, detection of rg-E119A was easily masked by the presence of NAI-susceptible virus. We coinfected NHBE cells with NAI-susceptible and -resistant viruses and used next-generation deep sequencing to reveal the order of relative fitness compared to that of recombinant wild-type (WT) virus generated by reverse genetics (rg-WT): rg-H274Y > rg-WT > rg-I222T > rg-N294S > rg-D198E > rg-E119A ≫ rg-R371K. Based on the lack of attenuated replication of rg-E119A in NHBE cells in the presence of oseltamivir or zanamivir and the fitness advantage of rg-H274Y over rg-WT, we emphasize the importance of these substitutions in the NA glycoprotein. Human infections with influenza B viruses carrying the E119A or H274Y substitution could limit the therapeutic options for those infected; the emergence of such viruses should be closely monitored. IMPORTANCE Influenza B viruses are important human respiratory pathogens contributing to a

  7. Sample Size and Statistical Conclusions from Tests of Fit to the Rasch Model According to the Rasch Unidimensional Measurement Model (Rumm) Program in Health Outcome Measurement.

    Science.gov (United States)

    Hagell, Peter; Westergren, Albert

    Sample size is a major factor in statistical null hypothesis testing, which is the basis for many approaches to testing Rasch model fit. Few sample size recommendations for testing fit to the Rasch model concern the Rasch Unidimensional Measurement Models (RUMM) software, which features chi-square and ANOVA/F-ratio based fit statistics, including Bonferroni and algebraic sample size adjustments. This paper explores the occurrence of Type I errors with RUMM fit statistics, and the effects of algebraic sample size adjustments. Data with simulated Rasch model fitting 25-item dichotomous scales and sample sizes ranging from N = 50 to N = 2500 were analysed with and without algebraically adjusted sample sizes. Results suggest the occurrence of Type I errors with N less then or equal to 500, and that Bonferroni correction as well as downward algebraic sample size adjustment are useful to avoid such errors, whereas upward adjustment of smaller samples falsely signal misfit. Our observations suggest that sample sizes around N = 250 to N = 500 may provide a good balance for the statistical interpretation of the RUMM fit statistics studied here with respect to Type I errors and under the assumption of Rasch model fit within the examined frame of reference (i.e., about 25 item parameters well targeted to the sample).

  8. Facultative control of matrix production optimizes competitive fitness in Pseudomonas aeruginosa PA14 biofilm models.

    Science.gov (United States)

    Madsen, Jonas S; Lin, Yu-Cheng; Squyres, Georgia R; Price-Whelan, Alexa; de Santiago Torio, Ana; Song, Angela; Cornell, William C; Sørensen, Søren J; Xavier, Joao B; Dietrich, Lars E P

    2015-12-01

    As biofilms grow, resident cells inevitably face the challenge of resource limitation. In the opportunistic pathogen Pseudomonas aeruginosa PA14, electron acceptor availability affects matrix production and, as a result, biofilm morphogenesis. The secreted matrix polysaccharide Pel is required for pellicle formation and for colony wrinkling, two activities that promote access to O2. We examined the exploitability and evolvability of Pel production at the air-liquid interface (during pellicle formation) and on solid surfaces (during colony formation). Although Pel contributes to the developmental response to electron acceptor limitation in both biofilm formation regimes, we found variation in the exploitability of its production and necessity for competitive fitness between the two systems. The wild type showed a competitive advantage against a non-Pel-producing mutant in pellicles but no advantage in colonies. Adaptation to the pellicle environment selected for mutants with a competitive advantage against the wild type in pellicles but also caused a severe disadvantage in colonies, even in wrinkled colony centers. Evolution in the colony center produced divergent phenotypes, while adaptation to the colony edge produced mutants with clear competitive advantages against the wild type in this O2-replete niche. In general, the structurally heterogeneous colony environment promoted more diversification than the more homogeneous pellicle. These results suggest that the role of Pel in community structure formation in response to electron acceptor limitation is unique to specific biofilm models and that the facultative control of Pel production is required for PA14 to maintain optimum benefit in different types of communities.

  9. A simple algorithm for optimization and model fitting: AGA (asexual genetic algorithm)

    CERN Document Server

    Canto, J; Martinez-Gomez, E; 10.1051/0004-6361/200911740

    2009-01-01

    Context. Mathematical optimization can be used as a computational tool to obtain the optimal solution to a given problem in a systematic and efficient way. For example, in twice-differentiable functions and problems with no constraints, the optimization consists of finding the points where the gradient of the objective function is zero and using the Hessian matrix to classify the type of each point. Sometimes, however it is impossible to compute these derivatives and other type of techniques must be employed such as the steepest descent/ascent method and more sophisticated methods such as those based on the evolutionary algorithms. Aims. We present a simple algorithm based on the idea of genetic algorithms (GA) for optimization. We refer to this algorithm as AGA (Asexual Genetic Algorithm) and apply it to two kinds of problems: the maximization of a function where classical methods fail and model fitting in astronomy. For the latter case, we minimize the chi-square function to estimate the parameters in two e...

  10. Regulation of Neutrophil Degranulation and Cytokine Secretion: A Novel Model Approach Based on Linear Fitting

    Directory of Open Access Journals (Sweden)

    Isabelle Naegelen

    2015-01-01

    Full Text Available Neutrophils participate in the maintenance of host integrity by releasing various cytotoxic proteins during degranulation. Due to recent advances, a major role has been attributed to neutrophil-derived cytokine secretion in the initiation, exacerbation, and resolution of inflammatory responses. Because the release of neutrophil-derived products orchestrates the action of other immune cells at the infection site and, thus, can contribute to the development of chronic inflammatory diseases, we aimed to investigate in more detail the spatiotemporal regulation of neutrophil-mediated release mechanisms of proinflammatory mediators. Purified human neutrophils were stimulated for different time points with lipopolysaccharide. Cells and supernatants were analyzed by flow cytometry techniques and used to establish secretion profiles of granules and cytokines. To analyze the link between cytokine release and degranulation time series, we propose an original strategy based on linear fitting, which may be used as a guideline, to (i define the relationship of granule proteins and cytokines secreted to the inflammatory site and (ii investigate the spatial regulation of neutrophil cytokine release. The model approach presented here aims to predict the correlation between neutrophil-derived cytokine secretion and degranulation and may easily be extrapolated to investigate the relationship between other types of time series of functional processes.

  11. Regulation of Neutrophil Degranulation and Cytokine Secretion: A Novel Model Approach Based on Linear Fitting

    Science.gov (United States)

    Naegelen, Isabelle; Beaume, Nicolas; Plançon, Sébastien; Schenten, Véronique; Tschirhart, Eric J.; Bréchard, Sabrina

    2015-01-01

    Neutrophils participate in the maintenance of host integrity by releasing various cytotoxic proteins during degranulation. Due to recent advances, a major role has been attributed to neutrophil-derived cytokine secretion in the initiation, exacerbation, and resolution of inflammatory responses. Because the release of neutrophil-derived products orchestrates the action of other immune cells at the infection site and, thus, can contribute to the development of chronic inflammatory diseases, we aimed to investigate in more detail the spatiotemporal regulation of neutrophil-mediated release mechanisms of proinflammatory mediators. Purified human neutrophils were stimulated for different time points with lipopolysaccharide. Cells and supernatants were analyzed by flow cytometry techniques and used to establish secretion profiles of granules and cytokines. To analyze the link between cytokine release and degranulation time series, we propose an original strategy based on linear fitting, which may be used as a guideline, to (i) define the relationship of granule proteins and cytokines secreted to the inflammatory site and (ii) investigate the spatial regulation of neutrophil cytokine release. The model approach presented here aims to predict the correlation between neutrophil-derived cytokine secretion and degranulation and may easily be extrapolated to investigate the relationship between other types of time series of functional processes. PMID:26579547

  12. A Multivariate Fit Luminosity Function and World Model for Long GRBs

    CERN Document Server

    Shahmoradi, Amir

    2012-01-01

    It is proposed that the luminosity function, the comoving-frame spectral correlations and distributions of cosmological Long-duration Gamma-Ray Bursts (LGRBs) may be very well described as multivariate log-normal distribution. This result is based on careful selection, analysis and modeling of the spectral parameters of LGRBs in the largest catalog of Gamma-Ray Bursts available to date: 2130 BATSE GRBs, while taking into account the detection threshold and possible selection effects on observational data. Constraints on the joint quadru-variate distribution of the isotropic peak luminosity, the total isotropic emission, the comoving-frame time-integrated spectral peak energy and the comoving-frame duration of LGRBs are derived. Extensive goodness-of-fit tests are performed. The presented analysis provides evidence for a relatively large fraction of LGRBs that have been missed by BATSE detector with total isotropic emissions extending down to 10^49 [erg] and observed spectral peak energies as low as 5 [KeV]. T...

  13. Fitting hidden Markov models of protein domains to a target species: application to Plasmodium falciparum

    Directory of Open Access Journals (Sweden)

    Terrapon Nicolas

    2012-05-01

    Full Text Available Abstract Background Hidden Markov Models (HMMs are a powerful tool for protein domain identification. The Pfam database notably provides a large collection of HMMs which are widely used for the annotation of proteins in new sequenced organisms. In Pfam, each domain family is represented by a curated multiple sequence alignment from which a profile HMM is built. In spite of their high specificity, HMMs may lack sensitivity when searching for domains in divergent organisms. This is particularly the case for species with a biased amino-acid composition, such as P. falciparum, the main causal agent of human malaria. In this context, fitting HMMs to the specificities of the target proteome can help identify additional domains. Results Using P. falciparum as an example, we compare approaches that have been proposed for this problem, and present two alternative methods. Because previous attempts strongly rely on known domain occurrences in the target species or its close relatives, they mainly improve the detection of domains which belong to already identified families. Our methods learn global correction rules that adjust amino-acid distributions associated with the match states of HMMs. These rules are applied to all match states of the whole HMM library, thus enabling the detection of domains from previously absent families. Additionally, we propose a procedure to estimate the proportion of false positives among the newly discovered domains. Starting with the Pfam standard library, we build several new libraries with the different HMM-fitting approaches. These libraries are first used to detect new domain occurrences with low E-values. Second, by applying the Co-Occurrence Domain Discovery (CODD procedure we have recently proposed, the libraries are further used to identify likely occurrences among potential domains with higher E-values. Conclusion We show that the new approaches allow identification of several domain families previously absent in

  14. A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit

    Science.gov (United States)

    Kim, K. Han; Young, Karen S.; Bernal, Yaritza; Boppana, Abhishektha; Vu, Linh Q.; Benson, Elizabeth A.; Jarvis, Sarah; Rajulu, Sudhakar L.

    2016-01-01

    Suboptimal suit fit is a known risk factor for crewmember shoulder injury. Suit fit assessment is however prohibitively time consuming and cannot be generalized across wide variations of body shapes and poses. In this work, we have developed a new design tool based on the statistical analysis of body shape scans. This tool is aimed at predicting the skin deformation and shape variations for any body size and shoulder pose for a target population. This new process, when incorporated with CAD software, will enable virtual suit fit assessments, predictively quantifying the contact volume, and clearance between the suit and body surface at reduced time and cost.

  15. ProFit: Bayesian galaxy fitting tool

    Science.gov (United States)

    Robotham, A. S. G.; Taranu, D.; Tobar, R.

    2016-12-01

    ProFit is a Bayesian galaxy fitting tool that uses the fast C++ image generation library libprofit (ascl:1612.003) and a flexible R interface to a large number of likelihood samplers. It offers a fully featured Bayesian interface to galaxy model fitting (also called profiling), using mostly the same standard inputs as other popular codes (e.g. GALFIT ascl:1104.010), but it is also able to use complex priors and a number of likelihoods.

  16. The fitting of general force-of-infection models to wildlife disease prevalence data

    Science.gov (United States)

    Heisey, D.M.; Joly, D.O.; Messier, F.

    2006-01-01

    Researchers and wildlife managers increasingly find themselves in situations where they must deal with infectious wildlife diseases such as chronic wasting disease, brucellosis, tuberculosis, and West Nile virus. Managers are often charged with designing and implementing control strategies, and researchers often seek to determine factors that influence and control the disease process. All of these activities require the ability to measure some indication of a disease's foothold in a population and evaluate factors affecting that foothold. The most common type of data available to managers and researchers is apparent prevalence data. Apparent disease prevalence, the proportion of animals in a sample that are positive for the disease, might seem like a natural measure of disease's foothold, but several properties, in particular, its dependency on age structure and the biasing effects of disease-associated mortality, make it less than ideal. In quantitative epidemiology, the a??force of infection,a?? or infection hazard, is generally the preferred parameter for measuring a disease's foothold, and it can be viewed as the most appropriate way to a??adjusta?? apparent prevalence for age structure. The typical ecology curriculum includes little exposure to quantitative epidemiological concepts such as cumulative incidence, apparent prevalence, and the force of infection. The goal of this paper is to present these basic epidemiological concepts and resulting models in an ecological context and to illustrate how they can be applied to understand and address basic epidemiological questions. We demonstrate a practical approach to solving the heretofore intractable problem of fitting general force-of-infection models to wildlife prevalence data using a generalized regression approach. We apply the procedures to Mycobacterium bovis (bovine tuberculosis) prevalence in bison (Bison bison) in Wood Buffalo National Park, Canada, and demonstrate strong age dependency in the force of

  17. 3D MODELLING OF A SHRINK FITTED CONCAVE ENDED CYLINDRICAL TANK FOR AUTOMOTIVE INDUSTRY

    National Research Council Canada - National Science Library

    Mirela C Ghita; Constantin A Micu; Mihai D L Talu; Stefan D L Talu

    2013-01-01

      The aim of this work is to present a method that allows the optimal design of a shrink fitted concave ended cylindrical tank for the storage of methane gas, based on the application of the Finite Element Method (FEM...

  18. Predicting the Best Fit: A Comparison of Response Surface Models for Midazolam and Alfentanil Sedation in Procedures With Varying Stimulation.

    Science.gov (United States)

    Liou, Jing-Yang; Ting, Chien-Kun; Mandell, M Susan; Chang, Kuang-Yi; Teng, Wei-Nung; Huang, Yu-Yin; Tsou, Mei-Yung

    2016-08-01

    Selecting an effective dose of sedative drugs in combined upper and lower gastrointestinal endoscopy is complicated by varying degrees of pain stimulation. We tested the ability of 5 response surface models to predict depth of sedation after administration of midazolam and alfentanil in this complex model. The procedure was divided into 3 phases: esophagogastroduodenoscopy (EGD), colonoscopy, and the time interval between the 2 (intersession). The depth of sedation in 33 adult patients was monitored by Observer Assessment of Alertness/Scores. A total of 218 combinations of midazolam and alfentanil effect-site concentrations derived from pharmacokinetic models were used to test 5 response surface models in each of the 3 phases of endoscopy. Model fit was evaluated with objective function value, corrected Akaike Information Criterion (AICc), and Spearman ranked correlation. A model was arbitrarily defined as accurate if the predicted probability is fit. The reduced Greco model had the lowest objective function value and AICc and thus the best fit. This model was reliable with acceptable predictive ability based on adequate clinical correlation. We suggest that this model has practical clinical value for patients undergoing procedures with varying degrees of stimulation.

  19. Estimating Important Electrode Parameters of High Temperature PEM Fuel Cells By Fitting a Model to Polarisation Curves and Impedance Spectra

    DEFF Research Database (Denmark)

    Vang, Jakob Rabjerg; Zhou, Fan; Andreasen, Søren Juhl;

    2015-01-01

    A high temperature PEM (HTPEM) fuel cell model capable of simulating both steady state and dynamic operation is presented. The purpose is to enable extraction of unknown parameters from sets of impedance spectra and polarisation curves. The model is fitted to two polarisation curves and four...... impedance spectra measured on a Dapozol 77 MEA. The model is capable of achieving good agreement with the recorded curves. Except at OCV, where the voltage is overpredicted, the simulated polarisation curves deviate maximum 3.0% from the measurements. The impedance spectra deviate maximum 3.7%. The fitted...... parameter values are within the range reported in literature. The only exception is the catalyst layer acid content, which is an order of magnitude lower. This may derive from acid migration. The model is used to illustrate the effect of reactant dynamics on the impedance spectrum. The model can aid...

  20. The Use of the L[subscript z] and L[subscript z]* Person-Fit Statistics and Problems Derived from Model Misspecification

    Science.gov (United States)

    Meijer, Rob R.; Tendeiro, Jorge N.

    2012-01-01

    We extend a recent didactic by Magis, Raiche, and Beland on the use of the l[subscript z] and l[subscript z]* person-fit statistics. We discuss a number of possibly confusing details and show that it is important to first investigate item response theory model fit before assessing person fit. Furthermore, it is argued that appropriate…

  1. Limited-Information Goodness-of-Fit Testing of Diagnostic Classification Item Response Theory Models. CRESST Report 840

    Science.gov (United States)

    Hansen, Mark; Cai, Li; Monroe, Scott; Li, Zhen

    2014-01-01

    It is a well-known problem in testing the fit of models to multinomial data that the full underlying contingency table will inevitably be sparse for tests of reasonable length and for realistic sample sizes. Under such conditions, full-information test statistics such as Pearson's X[superscript 2]?? and the likelihood ratio statistic…

  2. A study of M Mira variables based on IRAS LRS observations. II. Model fits and derived parameters for 109 Miras

    Energy Technology Data Exchange (ETDEWEB)

    Onaka, T.; Jong, T. de; Willems, F.J. (Amsterdam Univ. (NL))

    1989-12-01

    We have fitted dust shell models to the IRAS LRS spectra of 109 M Mira variables. The main assumptions in the model calculations are: (i) the dust shell is spherical and optically thin, (ii) the dust grains consist of aluminum oxide and amorphous magnesium silicate, (iii) the mass loss rate is constant, (iv) the stellar photosphere is characterized by R = 3 x 10{sup 13} cm and T = 2500 K. Best fit models are calculated for each star. A model is completely determined by five parameters: the dust temperatures at the inner boundaries of the aluminum oxide and silicate dust shells, the column densities of each dust grain component, and the distance to the star. It turns out that the 1 - 200 {mu}m infrared energy distributions calculated for the best fit parameters also provide quite satisfactory fits to the observed near- and far-infrared broad-band data for most sources. The material presented here forms the basis for a study of dust condensation in the circumstellar shells around Mira variables.

  3. Promoting Fitness and Safety in Elementary Students: A Randomized Control Study of the Michigan Model for Health

    Science.gov (United States)

    O'Neill, James M.; Clark, Jeffrey K.; Jones, James A.

    2016-01-01

    Background: In elementary grades, comprehensive health education curricula have demonstrated effectiveness in addressing singular health issues. The Michigan Model for Health (MMH) was implemented and evaluated to determine its impact on nutrition, physical fitness, and safety knowledge and skills. Methods: Schools (N = 52) were randomly assigned…

  4. Fit-for-purpose: species distribution model performance depends on evaluation criteria - Dutch Hoverflies as a case study.

    Science.gov (United States)

    Aguirre-Gutiérrez, Jesús; Carvalheiro, Luísa G; Polce, Chiara; van Loon, E Emiel; Raes, Niels; Reemer, Menno; Biesmeijer, Jacobus C

    2013-01-01

    Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM algorithm is not straightforward as these are plentiful and can be applied in many different ways. SDM are used mainly to gain insight in 1) overall species distributions, 2) their past-present-future probability of occurrence and/or 3) to understand their ecological niche limits (also referred to as ecological niche modelling). The fact that these three aims may require different models and outputs is, however, rarely considered and has not been evaluated consistently. Here we use data from a systematically sampled set of species occurrences to specifically test the performance of Species Distribution Models across several commonly used algorithms. Species range in distribution patterns from rare to common and from local to widespread. We compare overall model fit (representing species distribution), the accuracy of the predictions at multiple spatial scales, and the consistency in selection of environmental correlations all across multiple modelling runs. As expected, the choice of modelling algorithm determines model outcome. However, model quality depends not only on the algorithm, but also on the measure of model fit used and the scale at which it is used. Although model fit was higher for the consensus approach and Maxent, Maxent and GAM models were more consistent in estimating local occurrence, while RF and GBM showed higher consistency in environmental variables selection. Model outcomes diverged more for narrowly distributed species than for widespread species. We suggest that matching study aims with modelling approach is essential in Species Distribution Models, and provide suggestions how to do this for different modelling aims and species' data

  5. Fast fitting of non-Gaussian state-space models to animal movement data via Template Model Builder.

    Science.gov (United States)

    Albertsen, Christoffer Moesgaard; Whoriskey, Kim; Yurkowski, David; Nielsen, Anders; Mills, Joanna

    2015-10-01

    State-space models (SSM) are often used for analyzing complex ecological processes that are not observed directly, such as marine animal movement. When outliers are present in the measurements, special care is needed in the analysis to obtain reliable location and process estimates. Here we recommend using the Laplace approximation combined with automatic differentiation (as implemented in the novel R package Template Model Builder; TMB) for the fast fitting of continuous-time multivariate non-Gaussian SSMs. Through Argos satellite tracking data, we demonstrate that the use of continuous-time t-distributed measurement errors for error-prone data is more robust to outliers and improves the location estimation compared to using discretized-time t-distributed errors (implemented with a Gibbs sampler) or using continuous-time Gaussian errors (as with the Kalman filter). Using TMB, we are able to estimate additional parameters compared to previous methods, all without requiring a substantial increase in computational time. The model implementation is made available through the R package argosTrack.

  6. Genome-wide fitness analyses of the foodborne pathogen Campylobacter jejuni in in vitro and in vivo models

    DEFF Research Database (Denmark)

    de Vries, Stefan P. W.; Gupta, Srishti; Baig, Abiyad

    2017-01-01

    Campylobacter is the most common cause of foodborne bacterial illness worldwide. Faecal contamination of meat, especially chicken, during processing represents a key route of transmission to humans. There is a lack of insight into the mechanisms driving C. jejuni growth and survival within hosts...... and the environment. Here, we report a detailed analysis of C. jejuni fitness across models reflecting stages in its life cycle. Transposon (Tn) gene-inactivation libraries were generated in three C. jejuni strains and the impact on fitness during chicken colonisation, survival in houseflies and under nutrient......-rich and -poor conditions at 4 degrees C and infection of human gut epithelial cells was assessed by Tn-insertion site sequencing (Tn-seq). A total of 331 homologous gene clusters were essential for fitness during in vitro growth in three C. jejuni strains, revealing that a large part of its genome is dedicated...

  7. The universal Higgs fit

    DEFF Research Database (Denmark)

    Giardino, P. P.; Kannike, K.; Masina, I.

    2014-01-01

    Higgs models, models with extra Higgs doublets, supersymmetry, extra particles in the loops, anomalous top couplings, and invisible Higgs decays into Dark Matter. Best fit regions lie around the Standard Model predictions and are well approximated by our 'universal' fit. Latest data exclude the dilaton...

  8. On fitting the k-C* first order model to batch loaded sub-surface treatment wetlands.

    Science.gov (United States)

    Stein, O R; Towler, B W; Hook, P B; Biederman, J A

    2007-01-01

    The k-C* first order model was fit to time-series COD data collected from batch-loaded model wetlands. Four replicates of four plant species treatments; Carex utriculata (sedge), Schoenoplectus acutus (bulrush), Typha latifolia (cattail) and unplanted controls were compared. Temperature was varied by 4 degrees C from 24 degrees C to 4 degrees C to 24 degrees C over a year-long period. One mathematical fit was made for each wetland replicate at each temperature setting (192 fits). Temperature effects on both parameters were subsequently estimated by fitting the Arrhenius relationship to the estimated coefficients. Inherent interactions between k and C* make values dependent on sample timing and statistical technique for either time series (batch load) or distance profile (plug flow) data. Coefficients calibrated using the Levenberg-Marquardt method are compared to values previously reported using a nonlinear mixed effect regression technique. Overall conclusions are similar across approaches: (a) the magnitude of the coefficients varies strongly by species; (b) the rate constant k decreases with increasing temperature; and (c) temperature and species variation in the residual concentration C* is greater than the variation in k, such that variation in k alone is a poor predictor of performance. However, the magnitudes of the coefficients, especially the rate parameter k, vary between the statistical techniques, highlighting the need to better document the statistical routines used to calibrate the k-C* model.

  9. Linking the Fits, Fitting the Links: Connecting Different Types of PO Fit to Attitudinal Outcomes

    Science.gov (United States)

    Leung, Aegean; Chaturvedi, Sankalp

    2011-01-01

    In this paper we explore the linkages among various types of person-organization (PO) fit and their effects on employee attitudinal outcomes. We propose and test a conceptual model which links various types of fits--objective fit, perceived fit and subjective fit--in a hierarchical order of cognitive information processing and relate them to…

  10. Surface layer independent model fitting by phase matching: theory and application to HD 49933 and HD 177153 (aka Perky)

    Science.gov (United States)

    Roxburgh, Ian W.

    2015-01-01

    Aims: Our aim is to describe the theory of surface layer independent model fitting by phase matching and to apply this to the stars HD 49933 observed by CoRoT, and HD 177153 (aka Perky) observed by Kepler. Methods: We use theoretical analysis, phase shifts, and model fitting. Results: We define the inner and outer phase shifts of a frequency set of a model star and show that the outer phase shifts are (almost) independent of degree ℓ, and that a function of the inner phase shifts (the phase function) collapses to an ℓ independent function of frequency in the outer layers. We then show how to use this result in a model fitting technique to find a best fit model to an observed frequency set by calculating the inner phase shifts of a model using the observed frequencies and determining the extent to which the phase function collapses to a single function of frequency in the outer layers. This technique does not depend on the radial order n assigned to the observed frequencies. We give two examples applying this technique to the frequency sets of HD 49933 observed by CoRoT and HD 177153 (aka Perky) observed by Kepler, for which measurements of angular diameters and bolometric fluxes are available. For HD 49933 we find a very wide range of models to be consistent with the data (all with convective core overshooting) - and conclude that the data is not precise enough to make any useful restrictions on the structure of this star. For HD 177153 our best fit models have no convective cores, masses in the range 1.15-1.17 M⊙, ages of 4.45-4.70 × 109 yr, Z in the range 0.021-0.024, XH = 0.71-0.72, Y = 0.256 - 0.266 and mixing length parameter α = 1.8. We compare our results to those of previous studies. We contrast the phase matching technique to that using the ratios of small to large separations, showing that it avoids the problem of correlated errors in separation ratio fitting and of assigning radial order n to the modes.

  11. Model-based analysis of multi-shell diffusion MR data for tractography: How to get over fitting problems

    Science.gov (United States)

    Jbabdi, Saad; Sotiropoulos, Stamatios N; Savio, Alexander M; Graña, Manuel; Behrens, Timothy EJ

    2012-01-01

    In this article, we highlight an issue that arises when using multiple b-values in a model-based analysis of diffusion MR data for tractography. The non-mono-exponential decay, commonly observed in experimental data, is shown to induce over-fitting in the distribution of fibre orientations when not considered in the model. Extra fibre orientations perpendicular to the main orientation arise to compensate for the slower apparent signal decay at higher b-values. We propose a simple extension to the ball and stick model based on a continuous Gamma distribution of diffusivities, which significantly improves the fitting and reduces the over-fitting. Using in-vivo experimental data, we show that this model outperforms a simpler, noise floor model, especially at the interfaces between brain tissues, suggesting that partial volume effects are a major cause of the observed non-mono-exponential decay. This model may be helpful for future data acquisition strategies that may attempt to combine multiple shells to improve estimates of fibre orientations in white matter and near the cortex. PMID:22334356

  12. Invited commentary: Lost in estimation--searching for alternatives to markov chains to fit complex Bayesian models.

    Science.gov (United States)

    Molitor, John

    2012-03-01

    Bayesian methods have seen an increase in popularity in a wide variety of scientific fields, including epidemiology. One of the main reasons for their widespread application is the power of the Markov chain Monte Carlo (MCMC) techniques generally used to fit these models. As a result, researchers often implicitly associate Bayesian models with MCMC estimation procedures. However, Bayesian models do not always require Markov-chain-based methods for parameter estimation. This is important, as MCMC estimation methods, while generally quite powerful, are complex and computationally expensive and suffer from convergence problems related to the manner in which they generate correlated samples used to estimate probability distributions for parameters of interest. In this issue of the Journal, Cole et al. (Am J Epidemiol. 2012;175(5):368-375) present an interesting paper that discusses non-Markov-chain-based approaches to fitting Bayesian models. These methods, though limited, can overcome some of the problems associated with MCMC techniques and promise to provide simpler approaches to fitting Bayesian models. Applied researchers will find these estimation approaches intuitively appealing and will gain a deeper understanding of Bayesian models through their use. However, readers should be aware that other non-Markov-chain-based methods are currently in active development and have been widely published in other fields.

  13. Right atrium and superior vena cava pressure measurements in a novel animal model to study one and a half ventricle repair as compared to Fontan type procedure

    Directory of Open Access Journals (Sweden)

    Anil Bhattarai

    2017-01-01

    Full Text Available Background & Objectives: To evaluate the advantages of the one and a half ventricle repair on maintaining a low pressure in the inferior vena cava district. Also evaluate the competition of flows at the superior vena cava – right pulmonary artery anastomosis site, in order to understand the hemodynamic interaction of a pulsatile flow in combination to a laminar one. Materials & Methods: Adult rabbits (n=30 in terminal anaesthesia with a follow up of 8 h were used, randomly distributed in three experimental groups: Group 1: animals with an anastomosis between superior vena cava and right pulmonary artery, as a model of one and one half ventricle repair; Group 2: animals with the cavopulmonary anastomosis followed by clamping of the right pulmonary artery proximal to the anastomosis; and Group 3: sham animals. Pressures of superior vena cava and pulmonary arteries were afterwards measured, in a resting condition as well as after induced pharmacological stress test.Results: In Group 1, superior vena cava pressure was significantly higher, while venous pressure in the inferior vena cava – right atrium district was constant or lower in comparison with the other groups. After stress test, the pressure in the superior vena cava and the heart rate both increased further, but the right ventricular, right atrial and pulmonary artery pressures remained similar to the values in a resting condition. This proved that the inferior vena cava return was well-preserved, and no venous hypertension was present in the inferior vena cava district even after stress test (good exercise tolerance.Conclusion: One and one half ventricle repair can be considered a good surgical strategy for maintaining a low pressure in the inferior vena cava district with potential for right ventricle growth, restoring the more physiological circulation in borderline or failing right ventricle conditions. The experiment presented a positive finding in favour of one and one half

  14. Fitness club

    CERN Multimedia

    Fitness club

    2011-01-01

    General fitness Classes Enrolments are open for general fitness classes at CERN taking place on Monday, Wednesday, and Friday lunchtimes in the Pump Hall (building 216). There are shower facilities for both men and women. It is possible to pay for 1, 2 or 3 classes per week for a minimum of 1 month and up to 6 months. Check out our rates and enrol at: http://cern.ch/club-fitness Hope to see you among us! CERN Fitness Club fitness.club@cern.ch  

  15. Group Targets Tracking Using Multiple Models GGIW-CPHD Based on Best-Fitting Gaussian Approximation and Strong Tracking Filter

    Directory of Open Access Journals (Sweden)

    Yun Wang

    2016-01-01

    Full Text Available Gamma Gaussian inverse Wishart cardinalized probability hypothesis density (GGIW-CPHD algorithm was always used to track group targets in the presence of cluttered measurements and missing detections. A multiple models GGIW-CPHD algorithm based on best-fitting Gaussian approximation method (BFG and strong tracking filter (STF is proposed aiming at the defect that the tracking error of GGIW-CPHD algorithm will increase when the group targets are maneuvering. The best-fitting Gaussian approximation method is proposed to implement the fusion of multiple models using the strong tracking filter to correct the predicted covariance matrix of the GGIW component. The corresponding likelihood functions are deduced to update the probability of multiple tracking models. From the simulation results we can see that the proposed tracking algorithm MM-GGIW-CPHD can effectively deal with the combination/spawning of groups and the tracking error of group targets in the maneuvering stage is decreased.

  16. Testing the Youth Physical Activity Promotion Model: Fatness and Fitness as Enabling Factors

    Science.gov (United States)

    Chen, Senlin; Welk, Gregory J.; Joens-Matre, Roxane R.

    2014-01-01

    As the prevalence of childhood obesity increases, it is important to examine possible differences in psychosocial correlates of physical activity between normal weight and overweight children. The study examined fatness (weight status) and (aerobic) fitness as Enabling factors related to youth physical activity within the Youth Physical Activity…

  17. Testing the Youth Physical Activity Promotion Model: Fatness and Fitness as Enabling Factors

    Science.gov (United States)

    Chen, Senlin; Welk, Gregory J.; Joens-Matre, Roxane R.

    2014-01-01

    As the prevalence of childhood obesity increases, it is important to examine possible differences in psychosocial correlates of physical activity between normal weight and overweight children. The study examined fatness (weight status) and (aerobic) fitness as Enabling factors related to youth physical activity within the Youth Physical Activity…

  18. Modeling relationships between physical fitness, executive functioning, and academic achievement in primary school children

    NARCIS (Netherlands)

    van der Niet, Anneke G.; Hartman, Esther; Smith, Joanne; Visscher, Chris

    2014-01-01

    Objectives: The relationship between physical fitness and academic achievement in children has received much attention, however, whether executive functioning plays a mediating role in this relationship is unclear. The aim of this study therefore was to investigate the relationships between physical

  19. Modeling relationships between physical fitness, executive functioning, and academic achievement in primary school children

    NARCIS (Netherlands)

    van der Niet, Anneke G.; Hartman, Esther; Smith, Joanne; Visscher, Chris

    Objectives: The relationship between physical fitness and academic achievement in children has received much attention, however, whether executive functioning plays a mediating role in this relationship is unclear. The aim of this study therefore was to investigate the relationships between physical

  20. Quasispecies on Fitness Landscapes.

    Science.gov (United States)

    Schuster, Peter

    2016-01-01

    Selection-mutation dynamics is studied as adaptation and neutral drift on abstract fitness landscapes. Various models of fitness landscapes are introduced and analyzed with respect to the stationary mutant distributions adopted by populations upon them. The concept of quasispecies is introduced, and the error threshold phenomenon is analyzed. Complex fitness landscapes with large scatter of fitness values are shown to sustain error thresholds. The phenomenological theory of the quasispecies introduced in 1971 by Eigen is compared to approximation-free numerical computations. The concept of strong quasispecies understood as mutant distributions, which are especially stable against changes in mutations rates, is presented. The role of fitness neutral genotypes in quasispecies is discussed.

  1. Fitting model-based psychometric functions to simultaneity and temporal-order judgment data: MATLAB and R routines.

    Science.gov (United States)

    Alcalá-Quintana, Rocío; García-Pérez, Miguel A

    2013-12-01

    Research on temporal-order perception uses temporal-order judgment (TOJ) tasks or synchrony judgment (SJ) tasks in their binary SJ2 or ternary SJ3 variants. In all cases, two stimuli are presented with some temporal delay, and observers judge the order of presentation. Arbitrary psychometric functions are typically fitted to obtain performance measures such as sensitivity or the point of subjective simultaneity, but the parameters of these functions are uninterpretable. We describe routines in MATLAB and R that fit model-based functions whose parameters are interpretable in terms of the processes underlying temporal-order and simultaneity judgments and responses. These functions arise from an independent-channels model assuming arrival latencies with exponential distributions and a trichotomous decision space. Different routines fit data separately for SJ2, SJ3, and TOJ tasks, jointly for any two tasks, or also jointly for the three tasks (for common cases in which two or even the three tasks were used with the same stimuli and participants). Additional routines provide bootstrap p-values and confidence intervals for estimated parameters. A further routine is included that obtains performance measures from the fitted functions. An R package for Windows and source code of the MATLAB and R routines are available as Supplementary Files.

  2. Intensity-specific leisure-time physical activity and the built environment among Brazilian adults: a best-fit model.

    Science.gov (United States)

    Salvo, Deborah; Reis, Rodrigo S; Hino, Adriano A F; Hallal, Pedro C; Pratt, Michael

    2015-03-01

    There is little understanding about which sets of environmental features could simultaneously predict intensity-specific leisure-time physical activity (LTPA) among Brazilians. The objectives were to identify the environmental correlates for intensity-specific LTPA, and to build the best-fit linear models to predict intensity-specific LTPA among adults of Curitiba, Brazil. Cross sectional study in Curitiba, Brazil (2009, n = 1461). The International Physical Activity Questionnaire and Abbreviated Neighborhood Environment Assessment Scale were used. Ninety-two perceived environment variables were categorized in 10 domains. LTPA was classified as walking for leisure (LWLK), moderate-intensity leisure-time PA (MLPA), vigorous-intensity leisure-time PA (VLPA), and moderate-to-vigorous intensity leisure-time PA (MVLPA). Best fitting linear predictive models were built. Forty environmental variables were correlated to at least 1 LTPA outcome. The variability explained by the 4 best-fit models ranged from 17% (MLPA) to 46% (MVLPA). All models contained recreation areas and aesthetics variables; none included residential density predictors. At least 1 neighborhood satisfaction variable was present in each of the intensity-specific models, but not for overall MVLPA. This study demonstrates the simultaneous effect of sets of perceived environmental features on intensity-specific LTPA among Brazilian adults. The differences found compared with high-income countries suggest caution in generalizing results across settings.

  3. Fitting mathematical models to lactation curves from Holstein cows in the southwestern region of the state of Parana, Brazil.

    Science.gov (United States)

    Ferreira, Abílio G T; Henrique, Douglas S; Vieira, Ricardo A M; Maeda, Emilyn M; Valotto, Altair A

    2015-03-01

    The objective of this study was to evaluate four mathematical models with regards to their fit to lactation curves of Holstein cows from herds raised in the southwestern region of the state of Parana, Brazil. Initially, 42,281 milk production records from 2005 to 2011 were obtained from "Associação Paranaense de Criadores de Bovinos da Raça Holandesa (APCBRH)". Data lacking dates of drying and total milk production at 305 days of lactation were excluded, resulting in a remaining 15,142 records corresponding to 2,441 Holstein cows. Data were sorted according to the parity order (ranging from one to six), and within each parity order the animals were divided into quartiles (Q25%, Q50%, Q75% and Q100%) corresponding to 305-day lactation yield. Within each parity order, for each quartile, four mathematical models were adjusted, two of which were predominantly empirical (Brody and Wood) whereas the other two presented more mechanistic characteristics (models Dijkstra and Pollott). The quality of fit was evaluated by the corrected Akaike information criterion. The Wood model showed the best fit in almost all evaluated situations and, therefore, may be considered as the most suitable model to describe, at least empirically, the lactation curves of Holstein cows raised in Southwestern Parana.

  4. Fitting mathematical models to lactation curves from holstein cows in the southwestern region of the state of Parana, Brazil

    Directory of Open Access Journals (Sweden)

    Abílio G.T. Ferreira

    2015-03-01

    Full Text Available The objective of this study was to evaluate four mathematical models with regards to their fit to lactation curves of Holstein cows from herds raised in the southwestern region of the state of Parana, Brazil. Initially, 42,281 milk production records from 2005 to 2011 were obtained from "Associação Paranaense de Criadores de Bovinos da Raça Holandesa (APCBRH". Data lacking dates of drying and total milk production at 305 days of lactation were excluded, resulting in a remaining 15,142 records corresponding to 2,441 Holstein cows. Data were sorted according to the parity order (ranging from one to six, and within each parity order the animals were divided into quartiles (Q25%, Q50%, Q75% and Q100% corresponding to 305-day lactation yield. Within each parity order, for each quartile, four mathematical models were adjusted, two of which were predominantly empirical (Brody and Wood whereas the other two presented more mechanistic characteristics (models Dijkstra and Pollott. The quality of fit was evaluated by the corrected Akaike information criterion. The Wood model showed the best fit in almost all evaluated situations and, therefore, may be considered as the most suitable model to describe, at least empirically, the lactation curves of Holstein cows raised in Southwestern Parana.

  5. Seasonality of Influenza A(H7N9) Virus in China—Fitting Simple Epidemic Models to Human Cases

    Science.gov (United States)

    Lin, Qianying; Lin, Zhigui; Chiu, Alice P. Y.; He, Daihai

    2016-01-01

    Background Three epidemic waves of influenza A(H7N9) (hereafter ‘H7N9’) human cases have occurred between March 2013 and July 2015 in China. However, the underlying transmission mechanism remains unclear. Our main objective is to use mathematical models to study how seasonality, secular changes and environmental transmission play a role in the spread of H7N9 in China. Methods Data on human cases and chicken cases of H7N9 infection were downloaded from the EMPRES-i Global Animal Disease Information System. We modelled on chicken-to-chicken transmission, assuming a constant ratio of 10−6 human case per chicken case, and compared the model fit with the observed human cases. We developed three different modified Susceptible-Exposed-Infectious-Recovered-Susceptible models: (i) a non-periodic transmission rate model with an environmental class, (ii) a non-periodic transmission rate model without an environmental class, and (iii) a periodic transmission rate model with an environmental class. We then estimated the key epidemiological parameters and compared the model fit using Akaike Information Criterion and Bayesian Information Criterion. Results Our results showed that a non-periodic transmission rate model with an environmental class provided the best model fit to the observed human cases in China during the study period. The estimated parameter values were within biologically plausible ranges. Conclusions This study highlighted the importance of considering secular changes and environmental transmission in the modelling of human H7N9 cases. Secular changes were most likely due to control measures such as Live Poultry Markets closures that were implemented during the initial phase of the outbreaks in China. Our results suggested that environmental transmission via viral shedding of infected chickens had contributed to the spread of H7N9 human cases in China. PMID:26963937

  6. Seasonality of Influenza A(H7N9 Virus in China-Fitting Simple Epidemic Models to Human Cases.

    Directory of Open Access Journals (Sweden)

    Qianying Lin

    Full Text Available Three epidemic waves of influenza A(H7N9 (hereafter 'H7N9' human cases have occurred between March 2013 and July 2015 in China. However, the underlying transmission mechanism remains unclear. Our main objective is to use mathematical models to study how seasonality, secular changes and environmental transmission play a role in the spread of H7N9 in China.Data on human cases and chicken cases of H7N9 infection were downloaded from the EMPRES-i Global Animal Disease Information System. We modelled on chicken-to-chicken transmission, assuming a constant ratio of 10-6 human case per chicken case, and compared the model fit with the observed human cases. We developed three different modified Susceptible-Exposed-Infectious-Recovered-Susceptible models: (i a non-periodic transmission rate model with an environmental class, (ii a non-periodic transmission rate model without an environmental class, and (iii a periodic transmission rate model with an environmental class. We then estimated the key epidemiological parameters and compared the model fit using Akaike Information Criterion and Bayesian Information Criterion.Our results showed that a non-periodic transmission rate model with an environmental class provided the best model fit to the observed human cases in China during the study period. The estimated parameter values were within biologically plausible ranges.This study highlighted the importance of considering secular changes and environmental transmission in the modelling of human H7N9 cases. Secular changes were most likely due to control measures such as Live Poultry Markets closures that were implemented during the initial phase of the outbreaks in China. Our results suggested that environmental transmission via viral shedding of infected chickens had contributed to the spread of H7N9 human cases in China.

  7. Eficacia educativa: avances de un modelo para la educación superior (Educational Efficacy: Advances of a Higher Education Model

    Directory of Open Access Journals (Sweden)

    Rafael Hernández-González

    2008-12-01

    Full Text Available ResumenSe analizó un modelo de eficacia educativa que permite al controlar el factor socioeconómico, determinar el valor agregado que las instituciones del Subsistema de Universidades Tecnológicas proporcionan a sus estudiantes. Es un estudio multinivel, longitudinal con resultados de 8,522 estudiantes de 38 universidades en 19 estados que sustentaron el examen nacional de ingreso a la educación superior (EXANI-II y el examen para el egreso de técnico superior universitario-Sistemas Informáticos (EGETSU-SI del Centro Nacional de Evaluación para la Educación Superior [CENEVAL] durante 2000-2006. El modelo identifica la eficacia de las instituciones y facilita la construcción de indicadores de calidad educativa.AbstractThis study analyzed a model for educational effectiveness, which after controlling for socioeconomic factors, determined the benefit that institutions of the subsystem of Technological Universities provide their students. This is a longitudinal multilevel study with a sample of 8,522 students from 38 universities in 19 states who took the national admissions exam for higher education (EXANI-II and the exam for technical higher education (CENEVAL during 2000-2006. The model identifies the efficacy of the institutions and facilitates the construction of educational quality indicators.ResumoAnalisa-se um modelo de eficácia educativa que controlando o fator socioeconômico, determina o valor agregado que as instituições do Subsistema de Universidades Tecnológicas proporcionam a seus estudantes. É um estudo multi-nível, longitudinal com resultados de 8,522 estudantes de 38 universidades em 19 estados que sustentaram o exame nacional de ingresso à educação superior (EXANI-II e o exame geral para Técnico Superior Universitário em Sistemas Informáticos (EGETSU-SI do Centro Nacional de Avaliação para a Educação Superior (CENEVAL período 2000-2006. O Modelo identifica a eficácia das instituições e facilita a

  8. Chempy: A flexible chemical evolution model for abundance fitting. Do the Sun's abundances alone constrain chemical evolution models?

    Science.gov (United States)

    Rybizki, Jan; Just, Andreas; Rix, Hans-Walter

    2017-09-01

    Elemental abundances of stars are the result of the complex enrichment history of their galaxy. Interpretation of observed abundances requires flexible modeling tools to explore and quantify the information about Galactic chemical evolution (GCE) stored in such data. Here we present Chempy, a newly developed code for GCE modeling, representing a parametrized open one-zone model within a Bayesian framework. A Chempy model is specified by a set of five to ten parameters that describe the effective galaxy evolution along with the stellar and star-formation physics: for example, the star-formation history (SFH), the feedback efficiency, the stellar initial mass function (IMF), and the incidence of supernova of type Ia (SN Ia). Unlike established approaches, Chempy can sample the posterior probability distribution in the full model parameter space and test data-model matches for different nucleosynthetic yield sets. It is essentially a chemical evolution fitting tool. We straightforwardly extend Chempy to a multi-zone scheme. As an illustrative application, we show that interesting parameter constraints result from only the ages and elemental abundances of the Sun, Arcturus, and the present-day interstellar medium (ISM). For the first time, we use such information to infer the IMF parameter via GCE modeling, where we properly marginalize over nuisance parameters and account for different yield sets. We find that 11.6+ 2.1-1.6% of the IMF explodes as core-collapse supernova (CC-SN), compatible with Salpeter (1955, ApJ, 121, 161). We also constrain the incidence of SN Ia per 103M⊙ to 0.5-1.4. At the same time, this Chempy application shows persistent discrepancies between predicted and observed abundances for some elements, irrespective of the chosen yield set. These cannot be remedied by any variations of Chempy's parameters and could be an indication of missing nucleosynthetic channels. Chempy could be a powerful tool to confront predictions from stellar

  9. Automated Kinematic Modelling of Warped Galaxy Discs in Large Hi Surveys: 3D Tilted Ring Fitting of HI Emission Cubes

    CERN Document Server

    Kamphuis, P; Oh, S- H; Spekkens, K; Urbancic, N; Serra, P; Koribalski, B S; Dettmar, R -J

    2015-01-01

    Kinematical parameterisations of disc galaxies, employing emission line observations, are indispensable tools for studying the formation and evolution of galaxies. Future large-scale HI surveys will resolve the discs of many thousands of galaxies, allowing a statistical analysis of their disc and halo kinematics, mass distribution and dark matter content. Here we present an automated procedure which fits tilted-ring models to Hi data cubes of individual, well-resolved galaxies. The method builds on the 3D Tilted Ring Fitting Code (TiRiFiC) and is called FAT (Fully Automated TiRiFiC). To assess the accuracy of the code we apply it to a set of 52 artificial galaxies and 25 real galaxies from the Local Volume HI Survey (LVHIS). Using LVHIS data, we compare our 3D modelling to the 2D modelling methods DiskFit and rotcur. A conservative result is that FAT accurately models the kinematics and the morphologies of galaxies with an extent of eight beams across the major axis in the inclination range 20$^{\\circ}$-90$^{...

  10. Update of the electroweak precision fit, interplay with Higgs-boson signal strengths and model-independent constraints on new physics

    CERN Document Server

    Ciuchini, Marco; Mishima, Satoshi; Pierini, Maurizio; Reina, Laura; Silvestrini, Luca

    2014-01-01

    We present updated global fits of the Standard Model and beyond to electroweak precision data, taking into account recent progress in theoretical calculations and experimental measurements. From the fits, we derive model-independent constraints on new physics by introducing oblique and epsilon parameters, and modified $Zb\\bar{b}$ and $HVV$ couplings. Furthermore, we also perform fits of the scale factors of the Higgs-boson couplings to observed signal strengths of the Higgs boson.

  11. Quantum spin model fitting the Yule distribution of oligonucleotides in DNA

    CERN Document Server

    Minichini, C

    2004-01-01

    A quantum spin chain is identified by the labels of a vector state of a Kashiwara crystal basis. The intensity of the one-spin flip is assumed to depend from the variation of the labels. The rank ordered plot of the numerically computed, averaged in time, transition probabilities is nicely fitted by a Yule distribution, which is the observed distribution of the ranked short oligonucleotides frequency in DNA.

  12. A KIM-compliant potfit for fitting sloppy interatomic potentials: Application to the EDIP model for silicon

    CERN Document Server

    Wen, Mingjian; Brommer, Peter; Elliott, Ryan S; Sethna, James P; Tadmor, Ellad B

    2016-01-01

    Fitted interatomic potentials are widely used in atomistic simulations thanks to their ability to compute the energy and forces on atoms quickly. However, the simulation results crucially depend on the quality of the potential being used. Force matching is a method aimed at constructing reliable and transferable interatomic potentials by matching the forces computed by the potential as closely as possible, with those obtained from first principles calculations. The potfit program is an implementation of the force-matching method that optimizes the potential parameters using a global minimization algorithm followed by a local minimization polish. We extended potfit in two ways. First, we adapted the code to be compliant with the KIM Application Programming Interface (API) standard (part of the Knowledgebase of Interatomic Models Project). This makes it possible to use potfit to fit many KIM potential models, not just those prebuilt into the potfit code. Second, we incorporated the geodesic Levenberg--Marquardt...

  13. Fitness Club

    CERN Multimedia

    Fitness Club

    2011-01-01

    The CERN Fitness Club is organising Zumba Classes on the first Wednesday of each month, starting 7 September (19.00 – 20.00). What is Zumba®? It’s an exhilarating, effective, easy-to-follow, Latin-inspired, calorie-burning dance fitness-party™ that’s moving millions of people toward joy and health. Above all it’s great fun and an excellent work out. Price: 22 CHF/person Sign-up via the following form: https://espace.cern.ch/club-fitness/Lists/Zumba%20Subscription/NewForm.aspx For more info: fitness.club@cern.ch

  14. Reproductive fitness and dietary choice behavior of the genetic model organism Caenorhabditis elegans under semi-natural conditions.

    Science.gov (United States)

    Freyth, Katharina; Janowitz, Tim; Nunes, Frank; Voss, Melanie; Heinick, Alexander; Bertaux, Joanne; Scheu, Stefan; Paul, Rüdiger J

    2010-10-01

    Laboratory breeding conditions of the model organism C. elegans do not correspond with the conditions in its natural soil habitat. To assess the consequences of the differences in environmental conditions, the effects of air composition, medium and bacterial food on reproductive fitness and/or dietary-choice behavior of C. elegans were investigated. The reproductive fitness of C. elegans was maximal under oxygen deficiency and not influenced by a high fractional share of carbon dioxide. In media approximating natural soil structure, reproductive fitness was much lower than in standard laboratory media. In seminatural media, the reproductive fitness of C. elegans was low with the standard laboratory food bacterium E. coli (γ-Proteobacteria), but significantly higher with C. arvensicola (Bacteroidetes) and B. tropica (β-Proteobacteria) as food. Dietary-choice experiments in semi-natural media revealed a low preference of C. elegans for E. coli but significantly higher preferences for C. arvensicola and B. tropica (among other bacteria). Dietary-choice experiments under quasi-natural conditions, which were feasible by fluorescence in situ hybridization (FISH) of bacteria, showed a high preference of C. elegans for Cytophaga-Flexibacter-Bacteroides, Firmicutes, and β-Proteobacteria, but a low preference for γ-Proteobacteria. The results show that data on C. elegans under standard laboratory conditions have to be carefully interpreted with respect to their biological significance.

  15. Fitting state-space integral projection models to size-structured time series data to estimate unknown parameters.

    Science.gov (United States)

    White, J Wilson; Nickols, Kerry J; Malone, Daniel; Carr, Mark H; Starr, Richard M; Cordoleani, Flora; Baskett, Marissa L; Hastings, Alan; Botsford, Louis W

    2016-12-01

    Integral projection models (IPMs) have a number of advantages over matrix-model approaches for analyzing size-structured population dynamics, because the latter require parameter estimates for each age or stage transition. However, IPMs still require appropriate data. Typically they are parameterized using individual-scale relationships between body size and demographic rates, but these are not always available. We present an alternative approach for estimating demographic parameters from time series of size-structured survey data using a Bayesian state-space IPM (SSIPM). By fitting an IPM in a state-space framework, we estimate unknown parameters and explicitly account for process and measurement error in a dataset to estimate the underlying process model dynamics. We tested our method by fitting SSIPMs to simulated data; the model fit the simulated size distributions well and estimated unknown demographic parameters accurately. We then illustrated our method using nine years of annual surveys of the density and size distribution of two fish species (blue rockfish, Sebastes mystinus, and gopher rockfish, S. carnatus) at seven kelp forest sites in California. The SSIPM produced reasonable fits to the data, and estimated fishing rates for both species that were higher than our Bayesian prior estimates based on coast-wide stock assessment estimates of harvest. That improvement reinforces the value of being able to estimate demographic parameters from local-scale monitoring data. We highlight a number of key decision points in SSIPM development (e.g., open vs. closed demography, number of particles in the state-space filter) so that users can apply the method to their own datasets. © 2016 by the Ecological Society of America.

  16. Using Geometry-Based Metrics as Part of Fitness-for-Purpose Evaluations of 3D City Models

    Science.gov (United States)

    Wong, K.; Ellul, C.

    2016-10-01

    Three-dimensional geospatial information is being increasingly used in a range of tasks beyond visualisation. 3D datasets, however, are often being produced without exact specifications and at mixed levels of geometric complexity. This leads to variations within the models' geometric and semantic complexity as well as the degree of deviation from the corresponding real world objects. Existing descriptors and measures of 3D data such as CityGML's level of detail are perhaps only partially sufficient in communicating data quality and fitness-for-purpose. This study investigates whether alternative, automated, geometry-based metrics describing the variation of complexity within 3D datasets could provide additional relevant information as part of a process of fitness-for-purpose evaluation. The metrics include: mean vertex/edge/face counts per building; vertex/face ratio; minimum 2D footprint area and; minimum feature length. Each metric was tested on six 3D city models from international locations. The results show that geometry-based metrics can provide additional information on 3D city models as part of fitness-for-purpose evaluations. The metrics, while they cannot be used in isolation, may provide a complement to enhance existing data descriptors if backed up with local knowledge, where possible.

  17. Comparison of model fitting and gated integration for pulse shape discrimination and spectral estimation of digitized lanthanum halide scintillator pulses

    Energy Technology Data Exchange (ETDEWEB)

    McFee, J.E., E-mail: jemcfee@telus.net; Mosquera, C.M.; Faust, A.A.

    2016-08-21

    An analysis of digitized pulse waveforms from experiments with LaBr{sub 3}(Ce) and LaCl{sub 3}(Ce) detectors is presented. Pulse waveforms from both scintillator types were captured in the presence of {sup 22}Na and {sup 60}Co sources and also background alone. Two methods to extract pulse shape discrimination (PSD) parameters and estimate energy spectra were compared. The first involved least squares fitting of the pulse waveforms to a physics-based model of one or two exponentially modified Gaussian functions. The second was the conventional gated integration method. The model fitting method produced better PSD than gated integration for LaCl{sub 3}(Ce) and higher resolution energy spectra for both scintillator types. A disadvantage to the model fitting approach is that it is more computationally complex and about 5 times slower. LaBr{sub 3}(Ce) waveforms had a single decay component and showed no ability for alpha/electron PSD. LaCl{sub 3}(Ce) was observed to have short and long decay components and alpha/electron discrimination was observed.

  18. Fitting and Calibrating a Multilevel Mixed-Effects Stem Taper Model for Maritime Pine in NW Spain

    Science.gov (United States)

    Arias-Rodil, Manuel; Castedo-Dorado, Fernando; Cámara-Obregón, Asunción; Diéguez-Aranda, Ulises

    2015-01-01

    Stem taper data are usually hierarchical (several measurements per tree, and several trees per plot), making application of a multilevel mixed-effects modelling approach essential. However, correlation between trees in the same plot/stand has often been ignored in previous studies. Fitting and calibration of a variable-exponent stem taper function were conducted using data from 420 trees felled in even-aged maritime pine (Pinus pinaster Ait.) stands in NW Spain. In the fitting step, the tree level explained much more variability than the plot level, and therefore calibration at plot level was omitted. Several stem heights were evaluated for measurement of the additional diameter needed for calibration at tree level. Calibration with an additional diameter measured at between 40 and 60% of total tree height showed the greatest improvement in volume and diameter predictions. If additional diameter measurement is not available, the fixed-effects model fitted by the ordinary least squares technique should be used. Finally, we also evaluated how the expansion of parameters with random effects affects the stem taper prediction, as we consider this a key question when applying the mixed-effects modelling approach to taper equations. The results showed that correlation between random effects should be taken into account when assessing the influence of random effects in stem taper prediction. PMID:26630156

  19. Selecting best-fit models for estimating the body mass from 3D data of the human calcaneus.

    Science.gov (United States)

    Jung, Go-Un; Lee, U-Young; Kim, Dong-Ho; Kwak, Dai-Soon; Ahn, Yong-Woo; Han, Seung-Ho; Kim, Yi-Suk

    2016-05-01

    Body mass (BM) estimation could facilitate the interpretation of skeletal materials in terms of the individual's body size and physique in forensic anthropology. However, few metric studies have tried to estimate BM by focusing on prominent biomechanical properties of the calcaneus. The purpose of this study was to prepare best-fit models for estimating BM from the 3D human calcaneus by two major linear regression analysis (the heuristic statistical and all-possible-regressions techniques) and validate the models through predicted residual sum of squares (PRESS) statistics. A metric analysis was conducted based on 70 human calcaneus samples (29 males and 41 females) taken from 3D models in the Digital Korean Database and 10 variables were measured for each sample. Three best-fit models were postulated by F-statistics, Mallows' Cp, and Akaike information criterion (AIC) and Bayes information criterion (BIC) for each available candidate models. Finally, the most accurate regression model yields lowest %SEE and 0.843 of R(2). Through the application of leave-one-out cross validation, the predictive power was indicated a high level of validation accuracy. This study also confirms that the equations for estimating BM using 3D models of human calcaneus will be helpful to establish identification in forensic cases with consistent reliability. Copyright © 2016. Published by Elsevier Ireland Ltd.

  20. A KIM-compliant potfit for fitting sloppy interatomic potentials: application to the EDIP model for silicon

    Science.gov (United States)

    Wen, Mingjian; Li, Junhao; Brommer, Peter; Elliott, Ryan S.; Sethna, James P.; Tadmor, Ellad B.

    2017-01-01

    Fitted interatomic potentials are widely used in atomistic simulations thanks to their ability to compute the energy and forces on atoms quickly. However, the simulation results crucially depend on the quality of the potential being used. Force matching is a method aimed at constructing reliable and transferable interatomic potentials by matching the forces computed by the potential as closely as possible, with those obtained from first principles calculations. The potfit program is an implementation of the force-matching method that optimizes the potential parameters using a global minimization algorithm followed by a local minimization polish. We extended potfit in two ways. First, we adapted the code to be compliant with the KIM Application Programming Interface (API) standard (part of the Knowledgebase of Interatomic Models project). This makes it possible to use potfit to fit many KIM potential models, not just those prebuilt into the potfit code. Second, we incorporated the geodesic Levenberg-Marquardt (LM) minimization algorithm into potfit as a new local minimization algorithm. The extended potfit was tested by generating a training set using the KIM environment-dependent interatomic potential (EDIP) model for silicon and using potfit to recover the potential parameters from different initial guesses. The results show that EDIP is a ‘sloppy model’ in the sense that its predictions are insensitive to some of its parameters, which makes fitting more difficult. We find that the geodesic LM algorithm is particularly efficient for this case. The extended potfit code is the first step in developing a KIM-based fitting framework for interatomic potentials for bulk and two-dimensional materials. The code is available for download via https://www.potfit.net.

  1. An improved cognitive model of the Iowa and Soochow Gambling Tasks with regard to model fitting performance and tests of parameter consistency

    Science.gov (United States)

    Dai, Junyi; Kerestes, Rebecca; Upton, Daniel J.; Busemeyer, Jerome R.; Stout, Julie C.

    2015-01-01

    The Iowa Gambling Task (IGT) and the Soochow Gambling Task (SGT) are two experience-based risky decision-making tasks for examining decision-making deficits in clinical populations. Several cognitive models, including the expectancy-valence learning (EVL) model and the prospect valence learning (PVL) model, have been developed to disentangle the motivational, cognitive, and response processes underlying the explicit choices in these tasks. The purpose of the current study was to develop an improved model that can fit empirical data better than the EVL and PVL models and, in addition, produce more consistent parameter estimates across the IGT and SGT. Twenty-six opiate users (mean age 34.23; SD 8.79) and 27 control participants (mean age 35; SD 10.44) completed both tasks. Eighteen cognitive models varying in evaluation, updating, and choice rules were fit to individual data and their performances were compared to that of a statistical baseline model to find a best fitting model. The results showed that the model combining the prospect utility function treating gains and losses separately, the decay-reinforcement updating rule, and the trial-independent choice rule performed the best in both tasks. Furthermore, the winning model produced more consistent individual parameter estimates across the two tasks than any of the other models. PMID:25814963

  2. An Improved Cognitive Model of the Iowa and Soochow Gambling Tasks With Regard to Model Fitting Performance and Tests of Parameter Consistency

    Directory of Open Access Journals (Sweden)

    Junyi eDai

    2015-03-01

    Full Text Available The Iowa Gambling Task (IGT and the Soochow Gambling Task (SGT are two experience-based risky decision-making tasks for examining decision-making deficits in clinical populations. Several cognitive models, including the expectancy-valence learning model (EVL and the prospect valence learning model (PVL, have been developed to disentangle the motivational, cognitive, and response processes underlying the explicit choices in these tasks. The purpose of the current study was to develop an improved model that can fit empirical data better than the EVL and PVL models and, in addition, produce more consistent parameter estimates across the IGT and SGT. Twenty-six opiate users (mean age 34.23; SD 8.79 and 27 control participants (mean age 35; SD 10.44 completed both tasks. Eighteen cognitive models varying in evaluation, updating, and choice rules were fit to individual data and their performances were compared to that of a statistical baseline model to find a best fitting model. The results showed that the model combining the prospect utility function treating gains and losses separately, the decay-reinforcement updating rule, and the trial-independent choice rule performed the best in both tasks. Furthermore, the winning model produced more consistent individual parameter estimates across the two tasks than any of the other models.

  3. Evaluation of RGP Contact Lens Fitting in Keratoconus Patients Using Hierarchical Fuzzy Model and Genetic Algorithms.

    Science.gov (United States)

    Falahati Marvast, Fatemeh; Arabalibeik, Hossein; Alipour, Fatemeh; Sheikhtaheri, Abbas; Nouri, Leila; Soozande, Mehdi; Yarmahmoodi, Masood

    2016-01-01

    Keratoconus is a progressive non-inflammatory disease of the cornea. Rigid gas permeable contact lenses (RGPs) are prescribed when the disease progresses. Contact lens fitting and assessment is very difficult in these patients and is a concern of ophthalmologists and optometrists. In this study, a hierarchical fuzzy system is used to capture the expertise of experienced ophthalmologists during the lens evaluation phase of prescription. The system is fine-tuned using genetic algorithms. Sensitivity, specificity and accuracy of the final system are 88.9%, 94.4% and 92.6% respectively.

  4. Next-to-leading order unitarity fits in Two-Higgs-Doublet models with soft $\\mathbb{Z}_2$ breaking

    CERN Document Server

    Cacchio, Vincenzo; Eberhardt, Otto; Murphy, Christopher W

    2016-01-01

    We fit the next-to-leading order unitarity conditions to the Two-Higgs-Doublet model with a softly broken $\\mathbb{Z}_2$ symmetry. In doing so, we alleviate the existing uncertainty on how to treat higher order corrections to quartic couplings of its Higgs potential. A simplified approach to implementing the next-to-leading order unitarity conditions is presented. These new bounds are then combined with all other relevant constraints, including the complete set of LHC Run I data. The upper $95\\%$ bounds we find are $4.2$ on the absolute values of the quartic couplings, and $235$ GeV ($100$ GeV) for the mass degeneracies between the heavy Higgs particles in the type I (type II) scenario. In type II, we exclude an unbroken $\\mathbb{Z}_2$ symmetry with a probability of $95\\%$. All fits are performed using the open-source code HEPfit.

  5. Genome-Enabled Modeling of Biogeochemical Processes Predicts Metabolic Dependencies that Connect the Relative Fitness of Microbial Functional Guilds

    Science.gov (United States)

    Brodie, E.; King, E.; Molins, S.; Karaoz, U.; Steefel, C. I.; Banfield, J. F.; Beller, H. R.; Anantharaman, K.; Ligocki, T. J.; Trebotich, D.

    2015-12-01

    Pore-scale processes mediated by microorganisms underlie a range of critical ecosystem services, regulating carbon stability, nutrient flux, and the purification of water. Advances in cultivation-independent approaches now provide us with the ability to reconstruct thousands of genomes from microbial populations from which functional roles may be assigned. With this capability to reveal microbial metabolic potential, the next step is to put these microbes back where they belong to interact with their natural environment, i.e. the pore scale. At this scale, microorganisms communicate, cooperate and compete across their fitness landscapes with communities emerging that feedback on the physical and chemical properties of their environment, ultimately altering the fitness landscape and selecting for new microbial communities with new properties and so on. We have developed a trait-based model of microbial activity that simulates coupled functional guilds that are parameterized with unique combinations of traits that govern fitness under dynamic conditions. Using a reactive transport framework, we simulate the thermodynamics of coupled electron donor-acceptor reactions to predict energy available for cellular maintenance, respiration, biomass development, and enzyme production. From metagenomics, we directly estimate some trait values related to growth and identify the linkage of key traits associated with respiration and fermentation, macromolecule depolymerizing enzymes, and other key functions such as nitrogen fixation. Our simulations were carried out to explore abiotic controls on community emergence such as seasonally fluctuating water table regimes across floodplain organic matter hotspots. Simulations and metagenomic/metatranscriptomic observations highlighted the many dependencies connecting the relative fitness of functional guilds and the importance of chemolithoautotrophic lifestyles. Using an X-Ray microCT-derived soil microaggregate physical model combined

  6. Parametric bootstrap for testing model fitting in the proportional hazards framework: an application to the survival analysis of Bruna dels Pirineus beef calves.

    Science.gov (United States)

    Casellas, J; Tarrés, J; Piedrafita, J; Varona, L

    2006-10-01

    Given that correct assumptions on the baseline survival function are determinant for the validity of further inferences, specific tools to test the fit of a model to real data become essential in proportional hazards models. In this sense, we have proposed a parametric bootstrap to test the fit of survival models. Monte Carlo simulations are used to generate new data sets from the estimates obtained through the assumed models, and then bootstrap intervals can be established for the survival function along the time space studied. Significant fitting deficiencies are revealed when the real survival function is not included within the bootstrap interval. We tested this procedure in a survival data set of Bruna dels Pirineus beef calves, assuming 4 parametric models (exponential, Weibull, exponential time-dependent, Weibull time-dependent) and the Cox's semiparametric model. Fitting deficiencies were not observed for the Cox's model and the exponential time-dependent model, whereas the Weibull time-dependent model suffered from moderate overestimation at different ages. Thus, the exponential time-dependent model appears to be preferable because of its correct fit for survival data of beef calves and its smaller computational and time requirements. Exponential and Weibull models were completely rejected due to the continuous over- and underestimation of the survival probability reported. Results here highlighted the flexibility of parametric models with time-dependent effects, achieving a fit comparable to nonparametric models.

  7. Use of Approximate Bayesian Computation to Assess and Fit Models of Mycobacterium leprae to Predict Outcomes of the Brazilian Control Program.

    Directory of Open Access Journals (Sweden)

    Rebecca Lee Smith

    Full Text Available Hansen's disease (leprosy elimination has proven difficult in several countries, including Brazil, and there is a need for a mathematical model that can predict control program efficacy. This study applied the Approximate Bayesian Computation algorithm to fit 6 different proposed models to each of the 5 regions of Brazil, then fitted hierarchical models based on the best-fit regional models to the entire country. The best model proposed for most regions was a simple model. Posterior checks found that the model results were more similar to the observed incidence after fitting than before, and that parameters varied slightly by region. Current control programs were predicted to require additional measures to eliminate Hansen's Disease as a public health problem in Brazil.

  8. Extensive fitness and human cooperation.

    Science.gov (United States)

    van Hateren, J H

    2015-12-01

    Evolution depends on the fitness of organisms, the expected rate of reproducing. Directly getting offspring is the most basic form of fitness, but fitness can also be increased indirectly by helping genetically related individuals (such as kin) to increase their fitness. The combined effect is known as inclusive fitness. Here it is argued that a further elaboration of fitness has evolved, particularly in humans. It is called extensive fitness and it incorporates producing organisms that are merely similar in phenotype. The evolvability of this mechanism is illustrated by computations on a simple model combining heredity and behaviour. Phenotypes are driven into the direction of high fitness through a mechanism that involves an internal estimate of fitness, implicitly made within the organism itself. This mechanism has recently been conjectured to be responsible for producing agency and goals. In the model, inclusive and extensive fitness are both implemented by letting fitness increase nonlinearly with the size of subpopulations of similar heredity (for the indirect part of inclusive fitness) and of similar phenotype (for the phenotypic part of extensive fitness). Populations implementing extensive fitness outcompete populations implementing mere inclusive fitness. This occurs because groups with similar phenotype tend to be larger than groups with similar heredity, and fitness increases more when groups are larger. Extensive fitness has two components, a direct component where individuals compete in inducing others to become like them and an indirect component where individuals cooperate and help others who are already similar to them.

  9. Modelling the Factors that Affect Individuals' Utilisation of Online Learning Systems: An Empirical Study Combining the Task Technology Fit Model with the Theory of Planned Behaviour

    Science.gov (United States)

    Yu, Tai-Kuei; Yu, Tai-Yi

    2010-01-01

    Understanding learners' behaviour, perceptions and influence in terms of learner performance is crucial to predict the use of electronic learning systems. By integrating the task-technology fit (TTF) model and the theory of planned behaviour (TPB), this paper investigates the online learning utilisation of Taiwanese students. This paper provides a…

  10. Modelling the Factors that Affect Individuals' Utilisation of Online Learning Systems: An Empirical Study Combining the Task Technology Fit Model with the Theory of Planned Behaviour

    Science.gov (United States)

    Yu, Tai-Kuei; Yu, Tai-Yi

    2010-01-01

    Understanding learners' behaviour, perceptions and influence in terms of learner performance is crucial to predict the use of electronic learning systems. By integrating the task-technology fit (TTF) model and the theory of planned behaviour (TPB), this paper investigates the online learning utilisation of Taiwanese students. This paper provides a…

  11. Fitness Club

    CERN Multimedia

    Fitness Club

    2012-01-01

    Open to All: http://cern.ch/club-fitness  fitness.club@cern.ch Boxing Your supervisor makes your life too tough ! You really need to release the pressure you've been building up ! Come and join the fit-boxers. We train three times a week in Bd 216, classes for beginners and advanced available. Visit our website cern.ch/Boxing General Fitness Escape from your desk with our general fitness classes, to strengthen your heart, muscles and bones, improve you stamina, balance and flexibility, achieve new goals, be more productive and experience a sense of well-being, every Monday, Wednesday and Friday lunchtime, Tuesday mornings before work and Thursday evenings after work – join us for one of our monthly fitness workshops. Nordic Walking Enjoy the great outdoors; Nordic Walking is a great way to get your whole body moving and to significantly improve the condition of your muscles, heart and lungs. It will boost your energy levels no end. Pilates A body-conditioning technique de...

  12. Exchange interactions in [2 × 2] Cu(II) grids: on the reliability of the fitting spin models.

    Science.gov (United States)

    Calzado, Carmen J; Evangelisti, Stefano

    2014-02-21

    This paper reports a theoretical analysis of the electronic structure and magnetic properties of a ferromagnetic Cu(II) [2 × 2] grid. The calculations confirm a quintet (S = 2) ground state and an energy-level distribution of the magnetic states in accordance with Heisenberg behaviour. The whole set of first- and second-neighbour magnetic coupling constants has been evaluated, all in agreement with the structure and arrangement of the Cu 3dx(2) - y(2) magnetic orbitals. The results indicate that the dominant interaction in the system is the ferromagnetic coupling between the nearest Cu sites. The calculated J values suggest a C(2v) spin-spin interaction pattern, instead of the D(4h) model employed in the magnetic data fit. However, both spin models provide similar plots of the thermal dependence of the susceptibility and magnetic moment data. This study highlights the fact that the spin models resulting from the fittings can be just effective models, capable of correctly reproducing the macroscopic properties, although not always in accordance with the microscopic interactions governing these properties.

  13. The electroweak fit of the standard model after the discovery of a new boson at the LHC

    Energy Technology Data Exchange (ETDEWEB)

    Baak, M.; Hoecker, A.; Schott, M. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Goebel, M.; Kennedy, D.; Moenig, K. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany); Haller, J.; Kogler, R. [Hamburg Univ. (Germany). Inst. fuer Experimentalphysik; Stelzer, J. [Michigan State Univ., East Lansing, MI (United States). Dept. of Physics and Astronomy; Collaboration: The Gfitter Group

    2012-09-15

    In view of the discovery of a new boson by the ATLAS and CMS Collaborations at the LHC, we present an update of the global Standard Model (SM) fit to electroweak precision data. Assuming the new particle to be the SM Higgs boson, all fundamental parameters of the SM are known allowing, for the first time, to overconstrain the SM at the electroweak scale and assert its validity. Including the effects of radiative corrections and the experimental and theoretical uncertainties, the global fit exhibits a p-value of 0.07. The mass measurements by ATLAS and CMS agree within 1.3{sigma} with the indirect determination M{sub H}=94{sup +25}{sub -22} GeV. Within the SM the W boson mass and the effective weak mixing angle can be accurately predicted to be M{sub W}=80.359{+-}0.011 GeV and sin{sup 2}{theta}{sup l}{sub eff}=0.23150{+-}0.00010 from the global fit. These results are compatible with, and exceed in precision, the direct measurements. For the indirect determination of the top quark mass we find m{sub t}=175.8{sup +2.7}{sub -2.4} GeV, in agreement with the kinematic and cross-section based measurements.

  14. Percentile Analysis for Goodness-of-Fit Comparisons of Models to Data

    Science.gov (United States)

    2014-07-01

    obtaining a high R2. One solution to the problem is to consider a metric that is both sensitive to the number of data points under investigation as well...other facets of the model (e.g., its parsimony, breath, and ability; see Cassimatis, Bello , & Langley, 2008). 4. Model A and Model B have...278. Busemeyer, J. R. & Diederich, A. (2010). Cognitive Modeling. Sage. Cassimatis, N., Bello , P. & Langley, P. (2008). Ability, breadth and

  15. Fitting Proportional Odds Models to Educational Data in Ordinal Logistic Regression Using Stata, SAS and SPSS

    Science.gov (United States)

    Liu, Xing

    2008-01-01

    The proportional odds (PO) model, which is also called cumulative odds model (Agresti, 1996, 2002 ; Armstrong & Sloan, 1989; Long, 1997, Long & Freese, 2006; McCullagh, 1980; McCullagh & Nelder, 1989; Powers & Xie, 2000; O'Connell, 2006), is one of the most commonly used models for the analysis of ordinal categorical data and comes from the class…

  16. Examining the factor structure and convergent and discriminant validity of the Levenson self-report psychopathy scale: is the two-factor model the best fitting model?

    Science.gov (United States)

    Salekin, Randall T; Chen, Debra R; Sellbom, Martin; Lester, Whitney S; MacDougall, Emily

    2014-07-01

    The Levenson, Kiehl, and Fitzpatrick (1995) Self-Report Psychopathy Scale (LSRP) was introduced in the mid-1990s as a brief measure of psychopathy and has since gained considerable popularity. Despite its attractiveness as a brief psychopathy tool, the LSRP has received limited research regarding its factor structure and convergent and discriminant validity. The present study examined the construct validity of the LSRP, testing both its factor structure and the convergent and discriminant validity. Using a community sample of 1,257 undergraduates (869 females; 378 males), we tested whether a 1-, 2-, or 3-factor model best fit the data and examined the links between the resultant factor structures and external correlates. Confirmatory factor analysis (CFA) findings revealed a 3-factor model best matched the data, followed by an adequate-fitting original 2-factor model. Next, comparisons were made regarding the convergent and discriminant validity of the competing 2- and 3-factor models. Findings showed the LSRP traditional primary and secondary factors had meaningful relations with extratest variables such as neuroticism, stress tolerance, and lack of empathy. The 3-factor model showed particular problems with the Callousness scale. These findings underscore the importance of examining not only CFA fit statistics but also convergent and discriminant validity when testing factor structure models. The current findings suggest that the 2-factor model might still be the best way to interpret the LSRP. (c) 2014 APA, all rights reserved.

  17. Ajuste de modelos de platô de resposta via regressão isotônica Response plateau models fitting via isotonic regression

    Directory of Open Access Journals (Sweden)

    Renata Pires Gonçalves

    2012-02-01

    . The experiments of type dosage x response are very common in the determination of levels of nutrients in optimal food balance and include the use of regression models to achieve this objective. Nevertheless, the regression analysis routine, generally, uses a priori information about a possible relationship between the response variable. The isotonic regression is a method of estimation by least squares that generates estimates which preserves data ordering. In the theory of isotonic regression this information is essential and it is expected to increase fitting efficiency. The objective of this work was to use an isotonic regression methodology, as an alternative way of analyzing data of Zn deposition in tibia of male birds of Hubbard lineage. We considered the models of plateau response of polynomial quadratic and linear exponential forms. In addition to these models, we also proposed the fitting of a logarithmic model to the data and the efficiency of the methodology was evaluated by Monte Carlo simulations, considering different scenarios for the parametric values. The isotonization of the data yielded an improvement in all the fitting quality parameters evaluated. Among the models used, the logarithmic presented estimates of the parameters more consistent with the values reported in literature.

  18. How sensitive are the thermal fits to heavy-ion hadron yield data to the modeling of the eigenvolume interactions?

    CERN Document Server

    Vovchenko, Volodymyr

    2016-01-01

    The hadron-resonance gas (HRG) model with eigenvolume corrections is employed to fit the hadron yield data of the NA49 collaboration for central Pb+Pb collisions at $\\sqrt{s_{NN}}$ = 6.3, 7.6, 8.8, 12.3, and 17.3 GeV, the hadron midrapidity yield data of the STAR collaboration for Au+Au collisions at $\\sqrt{s_{NN}}$ = 200 GeV, and the hadron midrapidity yield data of the ALICE collaboration for Pb+Pb collisions at $\\sqrt{s_{NN}}$ = 2760 GeV. The influence of the EV corrections is studied within two different formulations of the EV HRG model. For the case of the point-particle HRG the extracted values of temperature and chemical potential are consistent with previous findings. The situation is very different when we apply the eigenvolume corrections with mass-proportional eigenvolumes $v_i \\sim m_i$, fixed to different values of the proton hard-core radius of $r_p$. At given bombarding energy the EV HRG model fits do not just yield a single $T-\\mu_B$ pair, but a whole range of $T-\\mu_B$ pairs. These pairs form...

  19. Multi-reaction-channel fitting calculations in a coupled-channel model: Photoinduced strangeness production

    Indian Academy of Sciences (India)

    O Scholten; A Usov

    2010-08-01

    To describe photo- and meson-induced reactions on the nucleon, one is faced with a rather extensive coupled-channel problem. Ignoring the effects of channel coupling, as one would do in describing a certain reaction at the tree level, invariably creates a large inconsistency between the different reactions that are described. In addition, the imaginary parts of the amplitude, which are related through the optical theorem, to total cross-sections, are directly reflected in certain polarization observables. Performing a full coupled-channel calculation thus offers the possibility to implement the maximum number of constraints. The drawback one is faced with is to arrive at a simultaneous fit of a large number of reaction channels. While some of the parameters are common to many reactions, one is still faced with the challenge to optimize a large number of parameters in a highly non-linear calculation. Here we show that such an approach is possible and present some results for photoinduced strangeness production.

  20. Recent Progress on Labfit: a Multispectrum Analysis Program for Fitting Lineshapes Including the Htp Model and Temperature Dependence

    Science.gov (United States)

    Cich, Matthew J.; Guillaume, Alexandre; Drouin, Brian; Benner, D. Chris

    2017-06-01

    Multispectrum analysis can be a challenge for a variety of reasons. It can be computationally intensive to fit a proper line shape model especially for high resolution experimental data. Band-wide analyses including many transitions along with interactions, across many pressures and temperatures are essential to accurately model, for example, atmospherically relevant systems. Labfit is a fast multispectrum analysis program originally developed by D. Chris Benner with a text-based interface. More recently at JPL a graphical user interface was developed with the goal of increasing the ease of use but also the number of potential users. The HTP lineshape model has been added to Labfit keeping it up-to-date with community standards. Recent analyses using labfit will be shown to demonstrate its ability to competently handle large experimental datasets, including high order lineshape effects, that are otherwise unmanageable.

  1. The PX-EM algorithm for fast stable fitting of Henderson's mixed model

    Directory of Open Access Journals (Sweden)

    Van Dyk David A

    2000-03-01

    Full Text Available Abstract This paper presents procedures for implementing the PX-EM algorithm of Liu, Rubin and Wu to compute REML estimates of variance covariance components in Henderson's linear mixed models. The class of models considered encompasses several correlated random factors having the same vector length e.g., as in random regression models for longitudinal data analysis and in sire-maternal grandsire models for genetic evaluation. Numerical examples are presented to illustrate the procedures. Much better results in terms of convergence characteristics (number of iterations and time required for convergence are obtained for PX-EM relative to the basic EM algorithm in the random regression.

  2. Micrometeorological measurement of hexachlorobenzene and polychlorinated biphenyl compound air-water gas exchange in Lake Superior and comparison to model predictions

    Directory of Open Access Journals (Sweden)

    M. D. Rowe

    2012-05-01

    Full Text Available Air-water exchange fluxes of persistent, bioaccumulative and toxic (PBT substances are frequently estimated using the Whitman two-film (W2F method, but micrometeorological flux measurements of these compounds over water are rarely attempted. We measured air-water exchange fluxes of hexachlorobenzene (HCB and polychlorinated biphenyls (PCBs on 14 July 2006 in Lake Superior using the modified Bowen ratio (MBR method. Measured fluxes were compared to estimates using the W2F method, and to estimates from an Internal Boundary Layer Transport and Exchange (IBLTE model that implements the NOAA COARE bulk flux algorithm and gas transfer model. We reveal an inaccuracy in the estimate of water vapor transfer velocity that is commonly used with the W2F method for PBT flux estimation, and demonstrate the effect of use of an improved estimation method. Flux measurements were conducted at three stations with increasing fetch in offshore flow (15, 30, and 60 km in southeastern Lake Superior. This sampling strategy enabled comparison of measured and predicted flux, as well as modification in near-surface atmospheric concentration with fetch, using the IBLTE model. Fluxes estimated using the W2F model were compared to fluxes measured by MBR. In five of seven cases in which the MBR flux was significantly greater than zero, concentration increased with fetch at 1-m height, which is qualitatively consistent with the measured volatilization flux. As far as we are aware, these are the first reported ship-based micrometeorological air-water exchange flux measurements of PCBs.

  3. Micrometeorological measurement of hexachlorobenzene and polychlorinated biphenyl compound air-water gas exchange in Lake Superior and comparison to model predictions

    Directory of Open Access Journals (Sweden)

    M. D. Rowe

    2012-01-01

    Full Text Available Air-water exchange fluxes of persistent, bioaccumulative and toxic (PBT substances are frequently estimated using the Whitman two-film (W2F method, but micrometeorological flux measurements of these compounds over water are rarely attempted. We measured air-water exchange fluxes of hexachlorobenzene (HCB and polychlorinated biphenyls (PCBs on 14 July 2006 in Lake Superior using the modified Bowen ratio (MBR method. Measured fluxes were compared to estimates using the W2F method, and to estimates from an Internal Boundary Layer Transport and Exchange (IBLTE model that implements the NOAA COARE bulk flux algorithm and gas transfer model. We reveal an inaccuracy in the estimate of water vapor transfer velocity that is commonly used with the W2F method for PBT flux estimation, and demonstrate the effect of use of an improved estimation method. Flux measurements were conducted at three stations with increasing fetch in offshore flow (15, 30, and 60 km in southeastern Lake Superior. This sampling strategy enabled comparison of measured and predicted flux, as well as modification in near-surface atmospheric concentration with fetch, using the IBLTE model. Fluxes estimated using the W2F model were compared to fluxes measured by MBR. In five of seven cases in which the MBR flux was significantly greater than zero, concentration increased with fetch at 1-m height, which is qualitatively consistent with the measured volatilization flux. As far as we are aware, these are the first reported micrometeorological air-water exchange flux measurements of PCBs.

  4. Fitness cost

    DEFF Research Database (Denmark)

    Nielsen, Karen L.; Pedersen, Thomas M.; Udekwu, Klas I.

    2012-01-01

    of each isolate was determined in a growth competition assay with a reference isolate. Significant fitness costs of 215 were determined for the MRSA isolates studied. There was a significant negative correlation between number of antibiotic resistances and relative fitness. Multiple regression analysis...... to that seen in Denmark. We propose a significant fitness cost of resistance as the main bacteriological explanation for the disappearance of the multiresistant complex 83A MRSA in Denmark following a reduction in antibiotic usage.......Denmark and several other countries experienced the first epidemic of methicillin-resistant Staphylococcus aureus (MRSA) during the period 196575, which was caused by multiresistant isolates of phage complex 83A. In Denmark these MRSA isolates disappeared almost completely, being replaced by other...

  5. Three-dimensional modeling of the cochlea by use of an arc fitting approach.

    Science.gov (United States)

    Schurzig, Daniel; Lexow, G Jakob; Majdani, Omid; Lenarz, Thomas; Rau, Thomas S

    2016-12-01

    A cochlea modeling approach is presented allowing for a user defined degree of geometry simplification which automatically adjusts to the patient specific anatomy. Model generation can be performed in a straightforward manner due to error estimation prior to the actual generation, thus minimizing modeling time. Therefore, the presented technique is well suited for a wide range of applications including finite element analyses where geometrical simplifications are often inevitable. The method is presented for n=5 cochleae which were segmented using a custom software for increased accuracy. The linear basilar membrane cross sections are expanded to areas while the scalae contours are reconstructed by a predefined number of arc segments. Prior to model generation, geometrical errors are evaluated locally for each cross section as well as globally for the resulting models and their basal turn profiles. The final combination of all reconditioned features to a 3D volume is performed in Autodesk Inventor using the loft feature. Due to the volume generation based on cubic splines, low errors could be achieved even for low numbers of arc segments and provided cross sections, both of which correspond to a strong degree of model simplification. Model generation could be performed in a time efficient manner. The proposed simplification method was proven to be well suited for the helical cochlea geometry. The generated output data can be imported into commercial software tools for various analyses representing a time efficient way to create cochlea models optimally suited for the desired task.

  6. Fitting multistate transition models with autoregressive logistic regression : Supervised exercise in intermittent claudication

    NARCIS (Netherlands)

    de Vries, S O; Fidler, Vaclav; Kuipers, Wietze D; Hunink, Maria G M

    1998-01-01

    The purpose of this study was to develop a model that predicts the outcome of supervised exercise for intermittent claudication. The authors present an example of the use of autoregressive logistic regression for modeling observed longitudinal data. Data were collected from 329 participants in a six

  7. Linear indices in nonlinear structural equation models : best fitting proper indices and other composites

    NARCIS (Netherlands)

    Dijkstra, T.K.; Henseler, J.

    2011-01-01

    The recent advent of nonlinear structural equation models with indices poses a new challenge to the measurement of scientific constructs. We discuss, exemplify and add to a family of statistical methods aimed at creating linear indices, and compare their suitability in a complex path model with line

  8. Fitting macroevolutionary models to phylogenies: an example using vertebrate body sizes

    NARCIS (Netherlands)

    Mooers, Arne Ø.; Schluter, Dolph

    1998-01-01

    How do traits change through time and with speciation? We present a simple and generally applicable method for comparing various models of the macroevolution of traits within a maximum likelihood framework. We illustrate four such models: 1) variance among species accumulates in direct proportion to

  9. Structural model for gamma-aminobutyric acid receptor noncompetitive antagonist binding: widely diverse structures fit the same site.

    Science.gov (United States)

    Chen, Ligong; Durkin, Kathleen A; Casida, John E

    2006-03-28

    Several major insecticides, including alpha-endosulfan, lindane, and fipronil, and the botanical picrotoxinin are noncompetitive antagonists (NCAs) for the GABA receptor. We showed earlier that human beta(3) homopentameric GABA(A) receptor recognizes all of the important GABAergic insecticides and reproduces the high insecticide sensitivity and structure-activity relationships of the native insect receptor. Despite large structural diversity, the NCAs are proposed to fit a single binding site in the chloride channel lumen lined by five transmembrane 2 segments. This hypothesis is examined with the beta(3) homopentamer by mutagenesis, pore structure studies, NCA binding, and molecular modeling. The 15 amino acids in the cytoplasmic half of the pore were mutated to cysteine, serine, or other residue for 22 mutants overall. Localization of A-1'C, A2'C, T6'C, and L9'C (index numbers for the transmembrane 2 region) in the channel lumen was established by disulfide cross-linking. Binding of two NCA radioligands [(3)H]1-(4-ethynylphenyl)-4-n-propyl-2,6,7-trioxabicyclo[2.2.2]octane and [(3)H] 3,3-bis-trifluoromethyl-bicyclo[2,2,1]heptane-2,2-dicarbonitrile was dramatically reduced with 8 of the 15 mutated positions, focusing attention on A2', T6', and L9' as proposed binding sites, consistent with earlier mutagenesis studies. The cytoplasmic half of the beta3 homopentamer pore was modeled as an alpha-helix. The six NCAs listed above plus t-butylbicyclophosphorothionate fit the 2' to 9' pore region forming hydrogen bonds with the T6' hydroxyl and hydrophobic interactions with A2', T6', and L9' alkyl substituents, thereby blocking the channel. Thus, widely diverse NCA structures fit the same GABA receptor beta subunit site with important implications for insecticide cross-resistance and selective toxicity between insects and mammals.

  10. Effects of a Three-Tiered Intervention Model on Physical Activity and Fitness Levels of Elementary School Children.

    Science.gov (United States)

    Dauenhauer, Brian; Keating, Xiaofen; Lambdin, Dolly

    2016-08-01

    Response to intervention (RtI) models are frequently used in schools to tailor academic instruction to the needs of students. The purpose of this study was to examine the effects of using RtI to promote physical activity (PA) and fitness in one urban elementary school. Ninety-nine students in grades 2-5 participated in up to three tiers of intervention throughout the course of one school year. Tier one included 150 min/week of physical education (increased from 90 min/week the previous year) and coordinated efforts to improve school health. Tier two consisted of 30 min/week of small group instruction based on goal setting and social support. Tier three included an after-school program for parents and children focused on healthy living. PA, cardiovascular fitness, and body composition were assessed before and after the interventions using pedometers, a 20-m shuttle run, and height/weight measurements. From pre- to post-testing, PA remained relatively stable in tier one and increased by 2349 steps/day in tier two. Cardiovascular fitness increased in tiers one and two by 1.17 and 1.35 ml/kg/min, respectively. Although body mass index did not change, 17 of the 99 students improved their weight status over the course of the school year, resulting in an overall decline in the prevalence of overweight/obesity from 59.6 to 53.5 %. Preliminary results suggest that the RtI model can be an effective way to structure PA/health interventions in an elementary school setting.

  11. Fitting HIV Prevalence 1981 Onwards for Three Indian States Using the Goals Model and the Estimation and Projection Package

    Science.gov (United States)

    Bhatnagar, Tarun; Dutta, Tapati; Stover, John; Godbole, Sheela; Sahu, Damodar; Boopathi, Kangusamy; Bembalkar, Shilpa; Singh, Kh. Jitenkumar; Goyal, Rajat; Pandey, Arvind; Mehendale, Sanjay M.

    2016-01-01

    Models are designed to provide evidence for strategic program planning by examining the impact of different interventions on projected HIV incidence. We employed the Goals Model to fit the HIV epidemic curves in Andhra Pradesh, Maharashtra and Tamil Nadu states of India where HIV epidemic is considered to have matured and in a declining phase. Input data in the Goals Model consisted of demographic, epidemiological, transmission-related and risk group wise behavioral parameters. The HIV prevalence curves generated in the Goals Model for each risk group in the three states were compared with the epidemic curves generated by the Estimation and Projection Package (EPP) that the national program is routinely using. In all the three states, the HIV prevalence trends for high-risk populations simulated by the Goals Model matched well with those derived using state-level HIV surveillance data in the EPP. However, trends for the low- and medium-risk populations differed between the two models. This highlights the need to generate more representative and robust data in these sub-populations and consider some structural changes in the modeling equation and parameters in the Goals Model to effectively use it to assess the impact of future strategies of HIV control in various sub-populations in India at the sub-national level. PMID:27711212

  12. Superior Hiking Trail

    Data.gov (United States)

    Minnesota Department of Natural Resources — Superior Hiking Trail main trail, spurs, and camp spurs for completed trail throughout Cook, Lake, St. Louis and Carlton counties. These data were collected with...

  13. Bathymetry of Lake Superior

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetry of Lake Superior has been compiled as a component of a NOAA project to rescue Great Lakes lake floor geological and geophysical data and make it more...

  14. Superior Hiking Trail Facilities

    Data.gov (United States)

    Minnesota Department of Natural Resources — Superior Hiking Trail main trail, spurs, and camp spurs for completed trail throughout Cook, Lake, St. Louis and Carlton counties. These data were collected with...

  15. DOES YOUR EVENT LOG FIT THE HIGH-LEVEL PROCESS MODEL?

    Directory of Open Access Journals (Sweden)

    A. K. Begicheva

    2015-01-01

    Full Text Available Process mining is a relatively new field of computer science, which deals with process discovery and analysis based on event logs. In this paper we consider the problem of models and event logs conformance checking. Conformance checking is intensively studied in the frame of process mining research, but only models and event logs of the same granularity were considered in the literature. Here we present and justify the method of checking conformance between a high-level model (e.g. built by an expert and a low-level log (generated by a system.The article is published in the author’s wording.

  16. Some Properties of A Lack-of-Fit Test for a Linear Errors in Variables Model

    Institute of Scientific and Technical Information of China (English)

    Li-xing Zhu; Heng-jian Cui; K.W.Ng

    2004-01-01

    The relationship between the linear errors-in-variables model and the corresponding ordinary linear model in statistical inference is studied.It is shown that normality of the distribution of covariate is a necessary and su cient condition for the equivalence.Therefore,testing for lack-of-t in linear errors-in-variables model can be converted into testing for it in the corresponding ordinary linear model under normality assumption.A test of score type is constructed and the limiting chi-squared distribution is derived under the null hypothesis.Furthermore,we discuss the power of the test and the choice of the weight function involved in the test statistic.

  17. An improved nonlinear model of HEMTs with independent transconductance tail-off fitting

    Institute of Scientific and Technical Information of China (English)

    Liu Linsheng

    2011-01-01

    We present an improved large-signal device model of GaAs/GaN HEMTs, amenable for use in commercial nonlinear simulators. The proposed model includes a new exponential function to independently control the transconductance compression/tail-offbehaviors. The main advantage of this model is to provide a simple and coherent description of the bias-dependent drain current (I-V) that is valid in all regions of operation. All aspects of the model are validated for 0.25-μm gate-length GaAs and GaN HEMT processes. The simulation results of DC/pulsed I-V, RF large-signal power and intermodulation distortion products show excellent agreement with the measured data.

  18. SDSS-II: Determination of shape and color parameter coefficients for SALT-II fit model

    Energy Technology Data Exchange (ETDEWEB)

    Dojcsak, L.; Marriner, J.; /Fermilab

    2010-08-01

    In this study we look at the SALT-II model of Type IA supernova analysis, which determines the distance moduli based on the known absolute standard candle magnitude of the Type IA supernovae. We take a look at the determination of the shape and color parameter coefficients, {alpha} and {beta} respectively, in the SALT-II model with the intrinsic error that is determined from the data. Using the SNANA software package provided for the analysis of Type IA supernovae, we use a standard Monte Carlo simulation to generate data with known parameters to use as a tool for analyzing the trends in the model based on certain assumptions about the intrinsic error. In order to find the best standard candle model, we try to minimize the residuals on the Hubble diagram by calculating the correct shape and color parameter coefficients. We can estimate the magnitude of the intrinsic errors required to obtain results with {chi}{sup 2}/degree of freedom = 1. We can use the simulation to estimate the amount of color smearing as indicated by the data for our model. We find that the color smearing model works as a general estimate of the color smearing, and that we are able to use the RMS distribution in the variables as one method of estimating the correct intrinsic errors needed by the data to obtain the correct results for {alpha} and {beta}. We then apply the resultant intrinsic error matrix to the real data and show our results.

  19. Fitting a Turbulent Cloud Model to CO Observations of Starless Bok Globules

    Science.gov (United States)

    Hegmann, M.; Hengel, C.; Röllig, M.; Kegel, W. H.

    We present observations of five starless Bok globules in transitions of 12CO (J=2-1 and {J=3-2}), 13CO (J=2-1), and C18O (J=2-1) which have been obtained at the Heinrich-Hertz-Telescope. For an analysis of the data we use the model of Kegel et al. (see e.g. Piehler & Kegel 1995, A&A 297, 841; Hegmann & Kegel 2000, A&A 359, 405) which describes an isothermal sphere stabilized by turbulent and thermal pressure. This approach deals with the full NLTE radiative transfer problem and accounts for a turbulent velocity field with finite correlation length. By a comparison of observed and calculated line profiles we are able not only to determine the kinetic temperature, hydrogen density and CO coloumn density of the globules, but also to study the properties of the turbulent velocity field, i.e. the variance of its one-point-distribution and its correlation length. We consider our model to be an alternative tool for the evaluation of molecular lines emitted by molecular clouds. The model assumptions are certainly closer to reality than the assumptions behind the standard evaluation models, as for example the LVG model. Our current study shows that that the results obtained from our model can differ significantly from those obtained from a LVG analysis.

  20. Heterogeneity in genetic diversity among non-coding loci fails to fit neutral coalescent models of population history.

    Directory of Open Access Journals (Sweden)

    Jeffrey L Peters

    Full Text Available Inferring aspects of the population histories of species using coalescent analyses of non-coding nuclear DNA has grown in popularity. These inferences, such as divergence, gene flow, and changes in population size, assume that genetic data reflect simple population histories and neutral evolutionary processes. However, violating model assumptions can result in a poor fit between empirical data and the models. We sampled 22 nuclear intron sequences from at least 19 different chromosomes (a genomic transect to test for deviations from selective neutrality in the gadwall (Anas strepera, a Holarctic duck. Nucleotide diversity among these loci varied by nearly two orders of magnitude (from 0.0004 to 0.029, and this heterogeneity could not be explained by differences in substitution rates alone. Using two different coalescent methods to infer models of population history and then simulating neutral genetic diversity under these models, we found that the observed among-locus heterogeneity in nucleotide diversity was significantly higher than expected for these simple models. Defining more complex models of population history demonstrated that a pre-divergence bottleneck was also unlikely to explain this heterogeneity. However, both selection and interspecific hybridization could account for the heterogeneity observed among loci. Regardless of the cause of the deviation, our results illustrate that violating key assumptions of coalescent models can mislead inferences of population history.

  1. Coarse-grained lattice model simulations of sequence-structure fitness of a ribosome-inactivating protein.

    Science.gov (United States)

    Olson, Mark A; Yeh, In-Chul; Lee, Michael S

    2008-02-01

    Many realistic protein-engineering design problems extend beyond the computational limits of what is considered practical when applying all-atom molecular-dynamics simulation methods. Lattice models provide computationally robust alternatives, yet most are regarded as too simplistic to accurately capture the details of complex designs. We revisit a coarse-grained lattice simulation model and demonstrate that a multiresolution modeling approach of reconstructing all-atom structures from lattice chains is of sufficient accuracy to resolve the comparability of sequence-structure modifications of the ricin A-chain (RTA) protein fold. For a modeled structure, the unfolding-folding transition temperature was calculated from the heat capacity using either the potential energy from the lattice model or the all-atom CHARMM19 force-field plus a generalized Born solvent approximation. We found, that despite the low-resolution modeling of conformational states, the potential energy functions were capable of detecting the relative change in the thermodynamic transition temperature that distinguishes between a protein design and the native RTA fold in excellent accord with reported experimental studies of thermal denaturation. A discussion is provided of different sequences fitted to the RTA fold and a possible unfolding model. (c) 2007 Wiley Periodicals, Inc.

  2. Fitness Club

    CERN Multimedia

    Fitness Club

    2012-01-01

    Get in Shape for Summer with the CERN Fitness Club Saturday 23 June 2012 from 14:30 to 16.30 (doors open at 14.00) Germana’s Fitness Workshop. Build strength and stamina, sculpt and tone your body and get your heart pumping with Germana’s workout mixture of Cardio Attack, Power Pump, Power Step, Cardio Combat and Cross-Training. Where: 216 (Pump room – equipped with changing rooms and showers). What to wear: comfortable clothes and indoor sports shoes + bring a drink! How much: 15 chf Sign up here: https://espace.cern.ch/club-fitness/Lists/Test_Subscription/NewForm.aspx? Join the Party and dance yourself into shape at Marco + Marials Zumba Masterclass. Saturday 30 June 2012 from 15:00 to 16:30 Marco + Mariel’s Zumba Masterclass Where: 216 (Pump room – equipped with changing rooms and showers). What to wear: comfortable clothes and indoor sports shoes + bring a drink! How much: 25 chf Sign up here: https://espace.cern.ch/club-fitness/Lists/Zumba%20...

  3. Fitness Club

    CERN Multimedia

    Fitness Club

    2012-01-01

      The CERN Fitness Club is pleased to announce its new early morning class which will be taking place on: Tuesdays from 24th April 07:30 to 08:15 216 (Pump Hall, close to entrance C) – Facilities include changing rooms and showers. The Classes: The early morning classes will focus on workouts which will help you build not only strength and stamina, but will also improve your balance, and coordination. Our qualified instructor Germana will accompany you throughout the workout  to ensure you stay motivated so you achieve the best results. Sign up and discover the best way to start your working day full of energy! How to subscribe? We invite you along to a FREE trial session, if you enjoy the activity, please sign up via our website: https://espace.cern.ch/club-fitness/Activities/SUBSCRIBE.aspx. * * * * * * * * Saturday 28th April Get in shape for the summer at our fitness workshop and zumba dance party: Fitness workshop with Germana 13:00 to 14:30 - 216 (Pump Hall) Price...

  4. Fitness club

    CERN Multimedia

    Fitness club

    2013-01-01

      Nordic Walking Classes Come join the Nordic walking classes and outings offered by the CERN Fitness Club starting September 2013. Our licensed instructor Christine offers classes for people who’ve never tried Nordic Walking and who would like to learn the technique, and outings for people who have completed the classes and enjoy going out as a group. Course 1: Tuesdays 12:30 - 13:30 24 September, 1 October, 8 October, 15 October Course 2: Tuesdays 12:30 - 13:30 5 November, 12 November, 19 November, 26 November Outings will take place on Thursdays (12:30 to 13:30) from 12 September 2013. We meet at the CERN Club Barracks car park (close to Entrance A) 10 minutes before departure. Prices: 50 CHF for 4 classes, including the 10 CHF Club membership. Payments made directly to instructor. Renting Poles: Poles can be rented from Christine at 5 CHF / hour. Subscription: Please subscribe at: http://cern.ch/club-fitness Looking forward to seeing you among us! Fitness Club FitnessClub@c...

  5. Modeling and estimation of replication fitness of human immunodeficiency virus type 1 in vitro experiments by using a growth competition assay.

    Science.gov (United States)

    Wu, Hulin; Huang, Yangxin; Dykes, Carrie; Liu, Dacheng; Ma, Jingming; Perelson, Alan S; Demeter, Lisa M

    2006-03-01

    Growth competition assays have been developed to quantify the relative fitnesses of human immunodeficiency virus (HIV-1) mutants. In this article we develop mathematical models to describe viral/cellular dynamic interactions in the assay experiment, from which new competitive fitness indices or parameters are defined. These indices include the log fitness ratio (LFR), the log relative fitness (LRF), and the production rate ratio (PRR). From the population genetics perspective, we clarify the confusion and correct the inconsistency in the definition of relative fitness in the literature of HIV-1 viral fitness. The LFR and LRF are easier to estimate from the experimental data than the PRR, which was misleadingly defined as the relative fitness in recent HIV-1 research literature. Calculation and estimation methods based on two data points and multiple data points were proposed and were carefully studied. In particular, we suggest using both standard linear regression (method of least squares) and a measurement error model approach for more-accurate estimates of competitive fitness parameters from multiple data points. The developed methodologies are generally applicable to any growth competition assays. A user-friendly computational tool also has been developed and is publicly available on the World Wide Web at http://www.urmc.rochester.edu/bstools/vfitness/virusfitness.htm.

  6. Do telemonitoring projects of heart failure fit the Chronic Care Model?

    Science.gov (United States)

    Willemse, Evi; Adriaenssens, Jef; Dilles, Tinne; Remmen, Roy

    2014-07-01

    This study describes the characteristics of extramural and transmural telemonitoring projects on chronic heart failure in Belgium. It describes to what extent these telemonitoring projects coincide with the Chronic Care Model of Wagner. The Chronic Care Model describes essential components for high-quality health care. Telemonitoring can be used to optimise home care for chronic heart failure. It provides a potential prospective to change the current care organisation. This qualitative study describes seven non-invasive home-care telemonitoring projects in patients with heart failure in Belgium. A qualitative design, including interviews and literature review, was used to describe the correspondence of these home-care telemonitoring projects with the dimensions of the Chronic Care Model. The projects were situated in primary and secondary health care. Their primary goal was to reduce the number of readmissions for chronic heart failure. None of these projects succeeded in a final implementation of telemonitoring in home care after the pilot phase. Not all the projects were initiated to accomplish all of the dimensions of the Chronic Care Model. A central role for the patient was sparse. Limited financial resources hampered continuation after the pilot phase. Cooperation and coordination in telemonitoring appears to be major barriers but are, within primary care as well as between the lines of care, important links in follow-up. This discrepancy can be prohibitive for deployment of good chronic care. Chronic Care Model is recommended as basis for future.

  7. Statistics of Dark Matter Substructure: I. Model and Universal Fitting Functions

    CERN Document Server

    Jiang, Fangzhou

    2014-01-01

    We present a new, semi-analytical model describing the evolution of dark matter subhaloes. The model uses merger trees constructed using the method of Parkinson et al. (2008) to describe the masses and redshifts of subhaloes at accretion, which are subsequently evolved using a simple model for the orbit-averaged mass loss rates. The model is extremely fast, treats subhaloes of all orders, accounts for scatter in orbital properties and halo concentrations, and uses a simple recipe to convert subhalo mass to maximum circular velocity. The model accurately reproduces the average subhalo mass and velocity functions in numerical simulations. The inferred subhalo mass loss rates imply that an average dark matter subhalo loses in excess of 80 percent of its infall mass during its first radial orbit within the host halo. We demonstrate that the total mass fraction in subhaloes is tightly correlated with the `dynamical age' of the host halo, defined as the number of halo dynamical times that have elapsed since its for...

  8. Comparing the relative fit of various factor models of the self-consciousness scale in two independent samples.

    Science.gov (United States)

    Cramer, K M

    2000-10-01

    Research shows that using highly self-aware participants yields studies of higher reliability, validity, and statistical power; dispositional self-awareness is commonly measured using the Fenigstein Self-Consciousness Scale (Fenigstein, Scheier, & Buss, 1975). This study used confirmatory factor analysis to compare various factor models that may underlie that scale. Two independent student samples (296 from Bernstein, Teng, & Garbin, 1986, and 350 from a large Canadian university) completed the scale. Using 6 fit criteria, results from both samples supported the Burnkrant and Page (1984) 4-factor model, namely, that self-consciousness consists of 3 principle scales: Social Anxiety, Public Self-Consciousness, and Private Self-Consciousness (divided into Internal State Awareness and Self-Reflectiveness). We discuss the psychometric implications of enhancing scale reliability, validity, and self-awareness.

  9. Cognitive fitness.

    Science.gov (United States)

    Gilkey, Roderick; Kilts, Clint

    2007-11-01

    Recent neuroscientific research shows that the health of your brain isn't, as experts once thought, just the product of childhood experiences and genetics; it reflects your adult choices and experiences as well. Professors Gilkey and Kilts of Emory University's medical and business schools explain how you can strengthen your brain's anatomy, neural networks, and cognitive abilities, and prevent functions such as memory from deteriorating as you age. The brain's alertness is the result of what the authors call cognitive fitness -a state of optimized ability to reason, remember, learn, plan, and adapt. Certain attitudes, lifestyle choices, and exercises enhance cognitive fitness. Mental workouts are the key. Brain-imaging studies indicate that acquiring expertise in areas as diverse as playing a cello, juggling, speaking a foreign language, and driving a taxicab expands your neural systems and makes them more communicative. In other words, you can alter the physical makeup of your brain by learning new skills. The more cognitively fit you are, the better equipped you are to make decisions, solve problems, and deal with stress and change. Cognitive fitness will help you be more open to new ideas and alternative perspectives. It will give you the capacity to change your behavior and realize your goals. You can delay senescence for years and even enjoy a second career. Drawing from the rapidly expanding body of neuroscience research as well as from well-established research in psychology and other mental health fields, the authors have identified four steps you can take to become cognitively fit: understand how experience makes the brain grow, work hard at play, search for patterns, and seek novelty and innovation. Together these steps capture some of the key opportunities for maintaining an engaged, creative brain.

  10. FITTING A THREE DIMENSIONAL PEM FUEL CELL MODEL TO MEASUREMENTS BY TUNING THE POROSITY AND

    DEFF Research Database (Denmark)

    Bang, Mads; Odgaard, Madeleine; Condra, Thomas Joseph

    2004-01-01

    PEM fuel cell are dealt with in detail.The model solves the convective and diffusive transport of thegaseous phase in the fuel cell and allows prediction of theconcentration of the species present. A special feature of themodel is a method that allows detailed modelling and predictionof electrode kinetics...... dependency on the gas concentration andactivation overpotential can thereby be addressed. The proposedmodel makes it possible to predict the effect of geometrical andmaterial properties on the fuel cell?s performance. It is shownhow the ionic conductivity and porosity of the catalyst layeraffects...... the distribution of current density and further how thisaffects the polarization curve.The porosity and conductivity of the catalyst layer are some ofthe most difficult parameters to measure, estimate and especiallycontrol. Yet the proposed model shows how these two parameterscan have significant influence...

  11. Using Advanced Continuous Simulation Language (ACSL) to simulate, solve, and fit mathematical models in nutrition.

    Science.gov (United States)

    Johnson, Heidi A

    2003-01-01

    The ACSL programs (AEgis Technologies, 2000a, b) are fairly easy to use and provide a good combination of canned programming with the flexibility to do more, if one is willing to learn the language (for Fortran and m files). The manuals are fairly easy to understand but are not detailed enough. The manuals are geared toward operating the software. For the Optimize software, the best references are the Simusolv manuals (Steiner et al., 1990). ACSL also provides an interface (Open API or ACSL Server) which can be purchased separately. The interface allows compiled models to be distributed and run as independent programs with Visual Basic or C/C++. For models built with the Graphic Modeler, the interface is shareware.

  12. Some Fast Methods for Fitting Some One-parameter Spatial Models

    Directory of Open Access Journals (Sweden)

    R. J. Martin

    2005-01-01

    Full Text Available It is common in geographic modelling to use a one-parameter spatial model to specify the inverse covariance matrix in terms of I-bW, for some known matrix W. Exact Gaussian maximum likelihood estimation of b requires evaluation of the determinant of the covariance matrix. For large data sets, this evaluation of the determinant can be slow and good approximations can be useful. Seventy regional configurations are used to consider some approximations to the determinant of I-bW that are fast to evaluate, and their usefulness is compared.

  13. Group Practices and Partnerships: A traditional model that Fits Many Situations.

    Science.gov (United States)

    Pickering, Stephen R

    2015-01-01

    The traditional group practice model can take many forms, including general practitioners, specialists, and combinations, as well as solo practitioners sharing space and staff, partnerships, and other legal entities. These practices may share some or all staff functions, including contracting for some functions. The essential characteristic is that those treating patients also have full control over and often direct management of the business aspects of the practice. The most important requirements for success in this model may be a common philosophy of patient care and mutual trust regarding business matters.

  14. Non-covalent interactions at electrochemical interfaces: one model fits all?

    Science.gov (United States)

    Cabello, Gema; Leiva, Ezequiel P M; Gutiérrez, Claudio; Cuesta, Angel

    2014-07-21

    The shift with increasing concentration of alkali-metal cations of the potentials of both the spike and the hump observed in the cyclic voltammograms of Pt(111) electrodes in sulfuric acid solutions is shown to obey the simple model recently developed by us to explain the effect of non-covalent interactions at the electrical double layer. The results suggest that the model, originally developed to describe the effect of alkali-metal cations on the cyclic voltammogram of cyanide-modified Pt(111) electrodes, is of general applicability and can explain quantitatively the effect of cations on the properties of the electrical double layer.

  15. A mathematical framework for estimating pathogen transmission fitness and inoculum size using data from a competitive mixtures animal model.

    Directory of Open Access Journals (Sweden)

    James M McCaw

    2011-04-01

    Full Text Available We present a method to measure the relative transmissibility ("transmission fitness" of one strain of a pathogen compared to another. The model is applied to data from "competitive mixtures" experiments in which animals are co-infected with a mixture of two strains. We observe the mixture in each animal over time and over multiple generations of transmission. We use data from influenza experiments in ferrets to demonstrate the approach. Assessment of the relative transmissibility between two strains of influenza is important in at least three contexts: 1 Within the human population antigenically novel strains of influenza arise and compete for susceptible hosts. 2 During a pandemic event, a novel sub-type of influenza competes with the existing seasonal strain(s. The unfolding epidemiological dynamics are dependent upon both the population's susceptibility profile and the inherent transmissibility of the novel strain compared to the existing strain(s. 3 Neuraminidase inhibitors (NAIs, while providing significant potential to reduce transmission of influenza, exert selective pressure on the virus and so promote the emergence of drug-resistant strains. Any adverse outcome due to selection and subsequent spread of an NAI-resistant strain is exquisitely dependent upon the transmission fitness of that strain. Measurement of the transmission fitness of two competing strains of influenza is thus of critical importance in determining the likely time-course and epidemiology of an influenza outbreak, or the potential impact of an intervention measure such as NAI distribution. The mathematical framework introduced here also provides an estimate for the size of the transmitted inoculum. We demonstrate the framework's behaviour using data from ferret transmission studies, and through simulation suggest how to optimise experimental design for assessment of transmissibility. The method introduced here for assessment of mixed transmission events has

  16. Effect of tectonic setting on the fit and performance of a long-range earthquake forecasting model

    Directory of Open Access Journals (Sweden)

    David Alan Rhoades

    2012-02-01

    Full Text Available The Every Earthquake a Precursor According to Scale (EEPAS long-range earthquake forecasting model has been shown to be informative in several seismically active regions, including New Zealand, California and Japan. In previous applications of the model, the tectonic setting of earthquakes has been ignored. Here we distinguish crustal, plate interface, and slab earthquakes and apply the model to earthquakes with magnitude M≥4 in the Japan region from 1926 onwards. The target magnitude range is M≥ 6; the fitting period is 1966-1995; and the testing period is 1996-2005. In forecasting major slab earthquakes, it is optimal to use only slab and interface events as precursors. In forecasting major interface events, it is optimal to use only interface events as precursors. In forecasting major crustal events, it is optimal to use only crustal events as precursors. For the smoothed-seismicity component of the EEPAS model, it is optimal to use slab and interface events for earthquakes in the slab, interface events only for earthquakes on the interface, and crustal and interface events for crustal earthquakes. The optimal model parameters indicate that the precursor areas for slab earthquakes are relatively small compared to those for earthquakes in other tectonic categories, and that the precursor times and precursory earthquake magnitudes for crustal earthquakes are relatively large. The optimal models fit the learning data sets better than the raw EEPAS model, with an average information gain per earthquake of about 0.4. The average information gain is similar in the testing period, although it is higher for crustal earthquakes and lower for slab and interface earthquakes than in the learning period. These results show that earthquake interactions are stronger between earthquakes of similar tectonic types and that distinguishing tectonic types improves forecasts by enhancing the depth resolution where tectonic categories of earthquakes are

  17. Fitting Models of the Population Consequences of Acoustic Disturbance to Data from Marine Mammal Populations

    Science.gov (United States)

    2012-09-30

    including humans . By using sporadic observations together with an underlying process model, we can infer how individuals are interacting with their... cetaceans (e.g. gray whales – (Bradford et al. 2012)), the right whale analysis provides a framework for analyzing many different mammalian species

  18. Heliospheric Propagation of Coronal Mass Ejections: Drag-Based Model Fitting

    CERN Document Server

    Žic, T; Temmer, M

    2015-01-01

    The so-called drag-based model (DBM) simulates analytically the propagation of coronal mass ejections (CMEs) in interplanetary space and allows the prediction of their arrival times and impact speeds at any point in the heliosphere ("target"). The DBM is based on the assumption that beyond a distance of about 20 solar radii from the Sun, the dominant force acting on CMEs is the "aerodynamic" drag force. In the standard form of DBM, the user provisionally chooses values for the model input parameters, by which the kinematics of the CME over the entire Sun--"target" distance range is defined. The choice of model input parameters is usually based on several previously undertaken statistical studies. In other words, the model is used by ad hoc implementation of statistics-based values of the input parameters, which are not necessarily appropriate for the CME under study. Furthermore, such a procedure lacks quantitative information on how well the simulation reproduces the coronagraphically observed kinematics of ...

  19. Fitness effects of beneficial mutations: the mutational landscape model in experimental evolution

    DEFF Research Database (Denmark)

    Betancourt, Andrea J.; Bollback, Jonathan Paul

    2006-01-01

    of beneficial mutations should be roughly exponentially distributed. The prediction appears to be borne out by most of these studies, at least qualitatively. Another study showed that a modified version of the model was able to predict, with reasonable accuracy, which of a ranked set of beneficial alleles...

  20. Fitting the Mixed Rasch Model to a Reading Comprehension Test: Identifying Reader Types

    Science.gov (United States)

    Baghaei, Purya; Carstensen, Claus H.

    2013-01-01

    Standard unidimensional Rasch models assume that persons with the same ability parameters are comparable. That is, the same interpretation applies to persons with identical ability estimates as regards the underlying mental processes triggered by the test. However, research in cognitive psychology shows that persons at the same trait level may…

  1. Properties of and algorithms for fitting three-way component models with offset terms

    NARCIS (Netherlands)

    Kiers, Henk A. L.

    2006-01-01

    Prior to a three-way component analysis of a three-way data set, it is customary to preprocess the data by centering and/or rescaling them. Harshman and Lundy (1984) considered that three-way data actually consist of a three-way model part, which in fact pertains to ratio scale measurements, as welt

  2. Fitting Social Network Models Using Varying Truncation Stochastic Approximation MCMC Algorithm

    KAUST Repository

    Jin, Ick Hoon

    2013-10-01

    The exponential random graph model (ERGM) plays a major role in social network analysis. However, parameter estimation for the ERGM is a hard problem due to the intractability of its normalizing constant and the model degeneracy. The existing algorithms, such as Monte Carlo maximum likelihood estimation (MCMLE) and stochastic approximation, often fail for this problem in the presence of model degeneracy. In this article, we introduce the varying truncation stochastic approximation Markov chain Monte Carlo (SAMCMC) algorithm to tackle this problem. The varying truncation mechanism enables the algorithm to choose an appropriate starting point and an appropriate gain factor sequence, and thus to produce a reasonable parameter estimate for the ERGM even in the presence of model degeneracy. The numerical results indicate that the varying truncation SAMCMC algorithm can significantly outperform the MCMLE and stochastic approximation algorithms: for degenerate ERGMs, MCMLE and stochastic approximation often fail to produce any reasonable parameter estimates, while SAMCMC can do; for nondegenerate ERGMs, SAMCMC can work as well as or better than MCMLE and stochastic approximation. The data and source codes used for this article are available online as supplementary materials. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

  3. Are Earth System model software engineering practices fit for purpose? A case study.

    Science.gov (United States)

    Easterbrook, S. M.; Johns, T. C.

    2009-04-01

    We present some analysis and conclusions from a case study of the culture and practices of scientists at the Met Office and Hadley Centre working on the development of software for climate and Earth System models using the MetUM infrastructure. The study examined how scientists think about software correctness, prioritize their requirements in making changes, and develop a shared understanding of the resulting models. We conclude that highly customized techniques driven strongly by scientific research goals have evolved for verification and validation of such models. In a formal software engineering context these represents costly, but invaluable, software integration tests with considerable benefits. The software engineering practices seen also exhibit recognisable features of both agile and open source software development projects - self-organisation of teams consistent with a meritocracy rather than top-down organisation, extensive use of informal communication channels, and software developers who are generally also users and science domain experts. We draw some general conclusions on whether these practices work well, and what new software engineering challenges may lie ahead as Earth System models become ever more complex and petascale computing becomes the norm.

  4. Understanding the Listening Process: Rethinking the "One Size Fits All" Model

    Science.gov (United States)

    Wolvin, Andrew

    2013-01-01

    Robert Bostrom's seminal contributions to listening theory and research represent an impressive legacy and provide listening scholars with important perspectives on the complexities of listening cognition and behavior. Bostrom's work provides a solid foundation on which to build models that more realistically explain how listeners function…

  5. Superior anti-tumor activity of the MDM2 antagonist idasanutlin and the Bcl-2 inhibitor venetoclax in p53 wild-type acute myeloid leukemia models

    Directory of Open Access Journals (Sweden)

    Christian Lehmann

    2016-06-01

    Full Text Available Abstract Background Venetoclax, a small molecule BH3 mimetic which inhibits the anti-apoptotic protein Bcl-2, and idasanutlin, a selective MDM2 antagonist, have both shown activity as single-agent treatments in pre-clinical and clinical studies in acute myeloid leukemia (AML. In this study, we deliver the rationale and molecular basis for the combination of idasanutlin and venetoclax for treatment of p53 wild-type AML. Methods The effect of idasanutlin and venetoclax combination on cell viability, apoptosis, and cell cycle progression was investigated in vitro using established AML cell lines. In vivo efficacy was demonstrated in subcutaneous and orthotopic xenograft models generated in female nude or non-obese diabetic/severe combined immunodeficiency (NOD/SCID mice. Mode-of-action analyses were performed by means of cell cycle kinetic studies, RNA sequencing as well as western blotting experiments. Results Combination treatment with venetoclax and idasanutlin results in synergistic anti-tumor activity compared with the respective single-agent treatments in vitro, in p53 wild-type AML cell lines, and leads to strongly superior efficacy in vivo, in subcutaneous and orthotopic AML models. The inhibitory effects of idasanutlin were cell-cycle dependent, with cells arresting in G1 in consecutive cycles and the induction of apoptosis only evident after cells had gone through at least two cell cycles. Combination treatment with venetoclax removed this dependency, resulting in an acceleration of cell death kinetics. As expected, gene expression studies using RNA sequencing showed significant alterations to pathways associated with p53 signaling and cell cycle arrest (CCND1 pathway in response to idasanutlin treatment. Only few gene expression changes were observed for venetoclax treatment and combination treatment, indicating that their effects are mediated mainly at the post-transcriptional level. Protein expression studies demonstrated that

  6. Do telemonitoring projects of heart failure fit the Chronic Care Model?

    Directory of Open Access Journals (Sweden)

    Evi Willemse

    2014-07-01

    Full Text Available This study describes the characteristics of extramural and transmural telemonitoring projects on chronic heart failure in Belgium. It describes to what extent these telemonitoring projects coincide with the Chronic Care Model of Wagner. Background: The Chronic Care Model describes essential components for high-quality health care. Telemonitoring can be used to optimise home care for chronic heart failure. It provides a potential prospective to change the current care organisation. Methods: This qualitative study describes seven non-invasive home-care telemonitoring projects in patients with heart failure in Belgium. A qualitative design, including interviews and literature review, was used to describe the correspondence of these home-care telemonitoring projects with the dimensions of the Chronic Care Model. Results: The projects were situated in primary and secondary health care. Their primary goal was to reduce the number of readmissions for chronic heart failure. None of these projects succeeded in a final implementation of telemonitoring in home care after the pilot phase. Not all the projects were initiated to accomplish all of the dimensions of the Chronic Care Model. A central role for the patient was sparse. Conclusion: Limited financial resources hampered continuation after the pilot phase. Cooperation and coordination in telemonitoring appears to be major barriers but are, within primary care as well as between the lines of care, important links in follow-up. This discrepancy can be prohibitive for deployment of good chronic care. Chronic Care Model is recommended as basis for future.

  7. Do telemonitoring projects of heart failure fit the Chronic Care Model?

    Directory of Open Access Journals (Sweden)

    Evi Willemse

    2014-07-01

    Full Text Available This study describes the characteristics of extramural and transmural telemonitoring projects on chronic heart failure in Belgium. It describes to what extent these telemonitoring projects coincide with the Chronic Care Model of Wagner.Background: The Chronic Care Model describes essential components for high-quality health care. Telemonitoring can be used to optimise home care for chronic heart failure. It provides a potential prospective to change the current care organisation.Methods: This qualitative study describes seven non-invasive home-care telemonitoring projects in patients with heart failure in Belgium. A qualitative design, including interviews and literature review, was used to describe the correspondence of these home-care telemonitoring projects with the dimensions of the Chronic Care Model.Results: The projects were situated in primary and secondary health care. Their primary goal was to reduce the number of readmissions for chronic heart failure. None of these projects succeeded in a final implementation of telemonitoring in home care after the pilot phase. Not all the projects were initiated to accomplish all of the dimensions of the Chronic Care Model. A central role for the patient was sparse.Conclusion: Limited financial resources hampered continuation after the pilot phase. Cooperation and coordination in telemonitoring appears to be major barriers but are, within primary care as well as between the lines of care, important links in follow-up. This discrepancy can be prohibitive for deployment of good chronic care. Chronic Care Model is recommended as basis for future.

  8. Predicting VO2peak from Submaximal- and Peak Exercise Models: The HUNT 3 Fitness Study, Norway.

    Directory of Open Access Journals (Sweden)

    Henrik Loe

    Full Text Available Peak oxygen uptake (VO2peak is seldom assessed in health care settings although being inversely linked to cardiovascular risk and all-cause mortality. The aim of this study was to develop VO2peak prediction models for men and women based on directly measured VO2peak from a large healthy population.VO2peak prediction models based on submaximal- and peak performance treadmill work were derived from multiple regression analysis. 4637 healthy men and women aged 20-90 years were included. Data splitting was used to generate validation and cross-validation samples.The accuracy for the peak performance models were 10.5% (SEE = 4.63 mL⋅kg(-1⋅min(-1 and 11.5% (SEE = 4.11 mL⋅kg(-1⋅min(-1 for men and women, respectively, with 75% and 72% of the variance explained. For the submaximal performance models accuracy were 14.1% (SEE = 6.24 mL⋅kg(-1⋅min(-1 and 14.4% (SEE = 5.17 mL⋅kg(-1⋅min(-1 for men and women, respectively, with 55% and 56% of the variance explained. The validation and cross-validation samples displayed SEE and variance explained in agreement with the total sample. Cross-classification between measured and predicted VO2peak accurately classified 91% of the participants within the correct or nearest quintile of measured VO2peak.Judicious use of the exercise prediction models presented in this study offers valuable information in providing a fairly accurate assessment of VO2peak, which may be beneficial for risk stratification in health care settings.

  9. Modelo de avaliação de desempenho global para instituição de ensino superior Evaluation Model of Global Performance for Higher Education Institutions

    Directory of Open Access Journals (Sweden)

    Henrique Martins Galvão

    2011-12-01

    Full Text Available This study proposes a model to evaluate overall performance for Higher Education Institutions. It is unquestionable the importance of organizations from the education sector for knowledge development and dissemination of information, necessary for the progress of a city, region or country. However, it is necessary to develop tools for planning and management control to monitor organizational performance. In this case, one of the most important tasks is related to the types of information that managers need to monitor and tune the performance of the organization. The proposed evaluation model helps to improve the organizational performance of education institutions, creating higher value in the services offered.Este estudo propõe um modelo de avaliação de desempenho global para instituições de ensino superior. É indiscutível a importância das organizações do setor da educação, decisivas para o progresso de uma cidade, região ou país, por serem indutoras do desenvolvimento do conhecimento e da disseminação da informação. Por isso, torna-se necessário desenvolver, para essas instituições educacionais, instrumentos gerenciais de planejamento e de controle que monitorem o desempenho organizacional. Neste caso, uma das tarefas mais relevantes relaciona-se aos tipos de informações que os gerentes necessitam para monitorar e ajustar o desempenho da organização. O modelo de avaliação proposto contribui para melhorar o desempenho organizacional das instituições de ensino, criando valor superior nos serviços oferecidos.

  10. Visualization-Directed Interactive Model-Fitting to Spectral Data Cubes

    CERN Document Server

    Fluke, Christopher J; Barnes, David G

    2010-01-01

    Spectral datasets obtained at radio frequencies and optical/IR wavelengths are increasing in complexity as new facilities and instruments come online, resulting in an increased need to visualize and quantitatively analyze the velocity structures. As the visible structure in spectral data cubes is not purely spatial, additional insight is required to relate structures in 2D space plus line-of-sight velocity to their true three-dimensional (3D) structures. This can be achieved through the use of models that are converted to velocity-space representations. We have used the S2PLOT programming library to enable intuitive, interactive comparison between 3D models and spectral data, with potential for improved understanding of the spatial configurations. We also report on the use of 3D Cartesian shapelets to support quantitative analysis.

  11. Exact Solution of Mutator Model with Linear Fitness and Finite Genome Length

    Science.gov (United States)

    Saakian, David B.

    2017-08-01

    We considered the infinite population version of the mutator phenomenon in evolutionary dynamics, looking at the uni-directional mutations in the mutator-specific genes and linear selection. We solved exactly the model for the finite genome length case, looking at the quasispecies version of the phenomenon. We calculated the mutator probability both in the statics and dynamics. The exact solution is important for us because the mutator probability depends on the genome length in a highly non-trivial way.

  12. Impact of calibration fitting models on the clinical value of chromogranin A

    OpenAIRE

    Ferraro, Simona; Marano, Giuseppe; Ciardi, Laura; Vendramin, Chiara; Bongo, Angelo S.; Bellomo, Giorgio; Boracchi, Patrizia; Biganzoli, Elia M.

    2009-01-01

    Background: The clinical relevance of chromogranin A (CgA) concentrations depends on the analytical performance of the assay. The goal of the present study was to define the clinical involvements in CgA calibration models by evaluating the confidence intervals (CIs) for values from patients who were undergoing monitoring for disease. Methods: Thirty calibration curves for the CgA assay [immunoradiometric assay (IRMA), (CIS-BIO)] were built using linear regression (LR), and four-parameter log...

  13. Fitting Models of the Population Consequences of Acoustic Disturbance to Data from Marine Mammal Populations

    Science.gov (United States)

    2010-09-30

    also traveled in June to St. Andrews , Scotland to work the other members of the PCAD modeling sub-group: John Harwood, Len Thomas, and Leslie New...In addition to colleagues at St. Andrews , we are working closely with Mark Hindell, Clive McMahon, Dan Costa, Patrick Robinson (elephant seal... Conger , A. R. Knowlton, M. K. Marx, C. K. Slay, S. D. Kraus and B. N. White (2007). "Patterns of male reproductive success in a highly promiscuous

  14. Modelled Group Fitted XAFS Debye-Waller factors for Zn metalloproteins

    Science.gov (United States)

    Dimakis, Nicholas; Bunker, Grant

    2003-03-01

    X-ray Absorption Fine Structure spectroscopy is one of the few direct methods for determining the structure of metalloprotein active sites that are applicable to noncrystalline proteins in solutions and membranes. Considerable progress has been made in the calculation of photoelectron scattering aspects of XAFS,but calculation of the vibrational aspects has lagged because of the difficulty of the accurate calculations. Recently we have presented initial results that enabled practical numerical evaluation of XAFS multiple scattering Debye Waller Factors (MSDWFs) of Zn ions bound to histidines in metalloproteins. Recently we have refined our Zn-histidine model to provide more accurate first shell single scattering Debye-Waller parameters, and we have developed a model for Zn-cysteine model that described the MSDWFs enabling for the first time quantitative full single- and multiple-scattering XAFS data analysis of Zn/His/Cys sites at arbitrary temperatures, without the use of ad hoc assumptions. This opens up a wide class of important Zn proteins for study by these methods. Illustrative examples will be presented.

  15. Model and Effectiveness of Endurance Exercise to Increase Physical Fitness in Intellectual Disability Subjects with Obesity: A Randomized Controlled Trial

    Directory of Open Access Journals (Sweden)

    Tirza Z Tamin

    2015-04-01

    Full Text Available Aim: to design a model and assess the effectiveness of endurance exercise to increase physical fitness in intelectual disability (ID patients with obesity. Methods: a randomized-controlled clinical trial was performed in ID patients with obesity aged 10-30 years old from all Special School in DKI Jakarta, which were randomly allocated into 3 groups and then given 3 different type of exercises: lower extremity muscles endurance exercise for 20 RM followed by cardiorespiratory endurance exercise for 24-25 minutes (type I, lower extremity muscles endurance exercises for 10 RM followed by cardiorespiratory endurance exercises for 26-27 minutes (type II, and threw a tennis ball with 10 m distance for 10 minutes as control (type III. These program was performed 3 times a week for 4 months. Assesment of the exercise effectiveness was done by measuring maximum load that can be lifted and six-minutes walking test on rectangular track which was converted with the VO2 max prediction formula. Analysis was perfomed with Kruskal Wallis test. Results: two hundred and twelve (212 subjects were included in the study, randomly allocated into three types (I, II, and III of exercises groups. The type II of endurance exercise model was proved to be more effective in increasing lower extremity muscles endurance level compared to type I and III for ID patients with obesity (p<0.05. Meanwhile, type I of endurance exercise model was proved to be more effective in increasing cardiorespiratory endurance level compared to type II and III for ID patients with obesity (p<0.05. Conclusion: lower extremity muscles endurance exercise followed by a cardiorespiratory endurance exercise can be used to increase physical fitness in ID patients with obesity. Key words: intelectual disability patient, obesity, lower extremity muscles and cardiorespiratory endurance exercise, lower extremity muscles endurance level, cardiorespiratory endurance level.

  16. A Monte Carlo-adjusted goodness-of-fit test for parametric models describing spatial point patterns

    KAUST Repository

    Dao, Ngocanh

    2014-04-03

    Assessing the goodness-of-fit (GOF) for intricate parametric spatial point process models is important for many application fields. When the probability density of the statistic of the GOF test is intractable, a commonly used procedure is the Monte Carlo GOF test. Additionally, if the data comprise a single dataset, a popular version of the test plugs a parameter estimate in the hypothesized parametric model to generate data for theMonte Carlo GOF test. In this case, the test is invalid because the resulting empirical level does not reach the nominal level. In this article, we propose a method consisting of nested Monte Carlo simulations which has the following advantages: the bias of the resulting empirical level of the test is eliminated, hence the empirical levels can always reach the nominal level, and information about inhomogeneity of the data can be provided.We theoretically justify our testing procedure using Taylor expansions and demonstrate that it is correctly sized through various simulation studies. In our first data application, we discover, in agreement with Illian et al., that Phlebocarya filifolia plants near Perth, Australia, can follow a homogeneous Poisson clustered process that provides insight into the propagation mechanism of these plants. In our second data application, we find, in contrast to Diggle, that a pairwise interaction model provides a good fit to the micro-anatomy data of amacrine cells designed for analyzing the developmental growth of immature retina cells in rabbits. This article has supplementary material online. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

  17. The VMC survey - XXIII. Model fitting of light and radial velocity curves of Small Magellanic Cloud classical Cepheids

    Science.gov (United States)

    Marconi, M.; Molinaro, R.; Ripepi, V.; Cioni, M.-R. L.; Clementini, G.; Moretti, M. I.; Ragosta, F.; de Grijs, R.; Groenewegen, M. A. T.; Ivanov, V. D.

    2017-04-01

    We present the results of the χ2 minimization model fitting technique applied to optical and near-infrared photometric and radial velocity data for a sample of nine fundamental and three first overtone classical Cepheids in the Small Magellanic Cloud (SMC). The near-infrared photometry (JK filters) was obtained by the European Southern Observatory (ESO) public survey 'VISTA near-infrared Y, J, Ks survey of the Magellanic Clouds system' (VMC). For each pulsator, isoperiodic model sequences have been computed by adopting a non-linear convective hydrodynamical code in order to reproduce the multifilter light and (when available) radial velocity curve amplitudes and morphological details. The inferred individual distances provide an intrinsic mean value for the SMC distance modulus of 19.01 mag and a standard deviation of 0.08 mag, in agreement with the literature. Moreover, the intrinsic masses and luminosities of the best-fitting model show that all these pulsators are brighter than the canonical evolutionary mass-luminosity relation (MLR), suggesting a significant efficiency of core overshooting and/or mass-loss. Assuming that the inferred deviation from the canonical MLR is only due to mass-loss, we derive the expected distribution of percentage mass-loss as a function of both the pulsation period and the canonical stellar mass. Finally, a good agreement is found between the predicted mean radii and current period-radius (PR) relations in the SMC available in the literature. The results of this investigation support the predictive capabilities of the adopted theoretical scenario and pave the way for the application to other extensive data bases at various chemical compositions, including the VMC Large Magellanic Cloud pulsators and Galactic Cepheids with Gaia parallaxes.

  18. Comparative Study on the Selection Criteria for Fitting Flood Frequency Distribution Models with Emphasis on Upper-Tail Behavior

    Directory of Open Access Journals (Sweden)

    Xiaohong Chen

    2017-05-01

    Full Text Available The upper tail of a flood frequency distribution is always specifically concerned with flood control. However, different model selection criteria often give different optimal distributions when the focus is on the upper tail of distribution. With emphasis on the upper-tail behavior, five distribution selection criteria including two hypothesis tests and three information-based criteria are evaluated in selecting the best fitted distribution from eight widely used distributions by using datasets from Thames River, Wabash River, Beijiang River and Huai River. The performance of the five selection criteria is verified by using a composite criterion with focus on upper tail events. This paper demonstrated an approach for optimally selecting suitable flood frequency distributions. Results illustrate that (1 there are different selections of frequency distributions in the four rivers by using hypothesis tests and information-based criteria approaches. Hypothesis tests are more likely to choose complex, parametric models, and information-based criteria prefer to choose simple, effective models. Different selection criteria have no particular tendency toward the tail of the distribution; (2 The information-based criteria perform better than hypothesis tests in most cases when the focus is on the goodness of predictions of the extreme upper tail events. The distributions selected by information-based criteria are more likely to be close to true values than the distributions selected by hypothesis test methods in the upper tail of the frequency curve; (3 The proposed composite criterion not only can select the optimal distribution, but also can evaluate the error of estimated value, which often plays an important role in the risk assessment and engineering design. In order to decide on a particular distribution to fit the high flow, it would be better to use the composite criterion.

  19. Wind Magnetic Clouds for 2010-2012: Model Parameter Fittings, Associated Shock Waves, and Comparisons to Earlier Periods

    Science.gov (United States)

    Lepping, R. P.; Wu, C.-C.; Berdichevsky, D. B.; Szabo, A.

    2015-01-01

    We fitted the parameters of magnetic clouds (MCs) as identified in the Wind spacecraft data from early 2010 to the end of 2012 using the model of Lepping, Jones, and Burlaga (J. Geophys. Res. 95, 1195, 1990). The interval contains 48 MCs and 39 magnetic cloud-like (MCL) events. This work is a continuation of MC model fittings of the earlier Wind sets, including those in a recent publication, which covers 2007 to 2009. This period (2010 - 2012) mainly covers the maximum portion of Solar Cycle 24. Between the previous and current interval, we document 5.7 years of MCs observations. For this interval, the occurrence frequency of MCs markedly increased in the last third of the time. In addition, over approximately the last six years, the MC type (i.e. the profile of the magnetic-field direction within an MC, such as North-to-South, South-to-North, all South) dramatically evolved to mainly North-to-South types when compared to earlier years. Furthermore, this evolution of MC type is consistent with global solar magnetic-field changes predicted by Bothmer and Rust (Coronal Mass Ejections, 139, 1997). Model fit parameters for the MCs are listed for 2010 - 2012. For the 5.7 year interval, the observed MCs are found to be slower, weaker in estimated axial magnetic-field intensity, and shorter in duration than those of the earlier 12.3 years, yielding much lower axial magnetic-field fluxes. For about the first half of this 5.7 year period, i.e. up to the end of 2009, there were very few associated MC-driven shock waves (distinctly fewer than the long-term average of about 50 % of MCs). But since 2010, such driven shocks have increased markedly, reflecting similar statistics as the long-term averages. We estimate that 56 % of the total observed MCs have upstream shocks when the full interval of 1995 - 2012 is considered. However, only 28 % of the total number of MCLs have driven shocks over the same period. Some interplanetary shocks during the 2010 - 2012 interval are seen

  20. Fitting Galaxies on GPUs

    Science.gov (United States)

    Barsdell, B. R.; Barnes, D. G.; Fluke, C. J.

    2011-07-01

    Structural parameters are normally extracted from observed galaxies by fitting analytic light profiles to the observations. Obtaining accurate fits to high-resolution images is a computationally expensive task, requiring many model evaluations and convolutions with the imaging point spread function. While these algorithms contain high degrees of parallelism, current implementations do not exploit this property. With ever-growing volumes of observational data, an inability to make use of advances in computing power can act as a constraint on scientific outcomes. This is the motivation behind our work, which aims to implement the model-fitting procedure on a graphics processing unit (GPU). We begin by analysing the algorithms involved in model evaluation with respect to their suitability for modern many-core computing architectures like GPUs, finding them to be well-placed to take advantage of the high memory bandwidth offered by this hardware. Following our analysis, we briefly describe a preliminary implementation of the model fitting procedure using freely-available GPU libraries. Early results suggest a speed-up of around 10× over a CPU implementation. We discuss the opportunities such a speed-up could provide, including the ability to use more computationally expensive but better-performing fitting routines to increase the quality and robustness of fits.