Conceptual and perceptual factors in the picture superiority effect

OpenAIRE

Stenberg, Georg

2006-01-01

The picture superiority effect, i.e. better memory for pictures than for corresponding words, has been variously ascribed to a conceptual or a perceptual processing advantage. The present study aimed to disentangle perceptual and conceptual contributions. Pictures and words were tested for recognition in both their original formats and translated into participants´ second language. Multinomial Processing Tree (Batchelder & Riefer, 1999) and MINERVA (Hintzman, 1984) models were fitted to t...

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

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. 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. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield...

Local fit evaluation of structural equation models using graphical criteria.

Science.gov (United States)

Thoemmes, Felix; Rosseel, Yves; Textor, Johannes

2018-03-01

Evaluation of model fit is critically important for every structural equation model (SEM), and sophisticated methods have been developed for this task. Among them are the χ² goodness-of-fit test, decomposition of the χ², derived measures like the popular root mean square error of approximation (RMSEA) or comparative fit index (CFI), or inspection of residuals or modification indices. Many of these methods provide a global approach to model fit evaluation: A single index is computed that quantifies the fit of the entire SEM to the data. In contrast, graphical criteria like d-separation or trek-separation allow derivation of implications that can be used for local fit evaluation, an approach that is hardly ever applied. We provide an overview of local fit evaluation from the viewpoint of SEM practitioners. In the presence of model misfit, local fit evaluation can potentially help in pinpointing where the problem with the model lies. For models that do fit the data, local tests can identify the parts of the model that are corroborated by the data. Local tests can also be conducted before a model is fitted at all, and they can be used even for models that are globally underidentified. We discuss appropriate statistical local tests, and provide applied examples. We also present novel software in R that automates this type of local fit evaluation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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.

Physical activity enhances metabolic fitness independently of cardiorespiratory fitness in marathon runners

DEFF Research Database (Denmark)

Laye, M J; Nielsen, M B; Hansen, L S

2015-01-01

High levels of cardiovascular fitness (CRF) and physical activity (PA) are associated with decreased mortality and risk to develop metabolic diseases. The independent contributions of CRF and PA to metabolic disease risk factors are unknown. We tested the hypothesis that runners who run consisten......High levels of cardiovascular fitness (CRF) and physical activity (PA) are associated with decreased mortality and risk to develop metabolic diseases. The independent contributions of CRF and PA to metabolic disease risk factors are unknown. We tested the hypothesis that runners who run...... consistently >50 km/wk and/or >2 marathons/yr for the last 5 years have superior metabolic fitness compared to matched sedentary subjects (CRF, age, gender, and BMI). Case-control recruitment of 31 pairs of runner-sedentary subjects identified 10 matched pairs with similar VO2max (mL/min/kg) (similar-VO2max......). The similar-VO2max group was compared with a group of age, gender, and BMI matched pairs who had the largest difference in VO2max (different-VO2max). Primary outcomes that defined metabolic fitness including insulin response to an oral glucose tolerance test, fasting lipids, and fasting insulin were superior...

Reducing sample size by combining superiority and non-inferiority for two primary endpoints in the Social Fitness study.

Science.gov (United States)

Donkers, Hanneke; Graff, Maud; Vernooij-Dassen, Myrra; Nijhuis-van der Sanden, Maria; Teerenstra, Steven

2017-01-01

In randomized controlled trials, two endpoints may be necessary to capture the multidimensional concept of the intervention and the objectives of the study adequately. We show how to calculate sample size when defining success of a trial by combinations of superiority and/or non-inferiority aims for the endpoints. The randomized controlled trial design of the Social Fitness study uses two primary endpoints, which can be combined into five different scenarios for defining success of the trial. We show how to calculate power and sample size for each scenario and compare these for different settings of power of each endpoint and correlation between them. Compared to a single primary endpoint, using two primary endpoints often gives more power when success is defined as: improvement in one of the two endpoints and no deterioration in the other. This also gives better power than when success is defined as: improvement in one prespecified endpoint and no deterioration in the remaining endpoint. When two primary endpoints are equally important, but a positive effect in both simultaneously is not per se required, the objective of having one superior and the other (at least) non-inferior could make sense and reduce sample size. Copyright © 2016 Elsevier Inc. All rights reserved.

Hearing Aid Fitting: Monaural vs. Binaural

Directory of Open Access Journals (Sweden)

Ahmad Keshani

2002-07-01

Full Text Available One of the most important issue for selecting and fitting of hearing aids that should receive special attention is binaural amplification. According to several investigations, superiority of binaural amplification on monaural one is confirmed. Binaural Amplification may have considerable effects on fromation and developing of superior dimensions of hearing including: Localization, Binaural squelch (Better hearing in presence of noise. So, it is necessary to know the basic and scientific concepts and applicable principles of binaural hearing and binaural fitting. Present paper deals with this important subject.

Physical Activity Enhances Metabolic Fitness Independently of Cardiorespiratory Fitness in Marathon Runners

Directory of Open Access Journals (Sweden)

M. J. Laye

2015-01-01

Full Text Available High levels of cardiovascular fitness (CRF and physical activity (PA are associated with decreased mortality and risk to develop metabolic diseases. The independent contributions of CRF and PA to metabolic disease risk factors are unknown. We tested the hypothesis that runners who run consistently >50 km/wk and/or >2 marathons/yr for the last 5 years have superior metabolic fitness compared to matched sedentary subjects (CRF, age, gender, and BMI. Case-control recruitment of 31 pairs of runner-sedentary subjects identified 10 matched pairs with similar VO2max (mL/min/kg (similar-VO2max. The similar-VO2max group was compared with a group of age, gender, and BMI matched pairs who had the largest difference in VO2max (different-VO2max. Primary outcomes that defined metabolic fitness including insulin response to an oral glucose tolerance test, fasting lipids, and fasting insulin were superior in runners versus sedentary controls despite similar VO2max. Furthermore, performance (velocity at VO2max, running economy, improved exercise metabolism (lactate threshold, and skeletal muscle levels of mitochondrial proteins were superior in runners versus sedentary controls with similar VO2max. In conclusion subjects with a high amount of PA have more positive metabolic health parameters independent of CRF. PA is thus a good marker against metabolic diseases.

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.

Goodness-of-Fit Assessment of Item Response Theory Models

Science.gov (United States)

Maydeu-Olivares, Alberto

2013-01-01

The article provides an overview of goodness-of-fit assessment methods for item response theory (IRT) models. It is now possible to obtain accurate "p"-values of the overall fit of the model if bivariate information statistics are used. Several alternative approaches are described. As the validity of inferences drawn on the fitted model…

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....

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.

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.

Reliability and Model Fit

Science.gov (United States)

Stanley, Leanne M.; Edwards, Michael C.

2016-01-01

The purpose of this article is to highlight the distinction between the reliability of test scores and the fit of psychometric measurement models, reminding readers why it is important to consider both when evaluating whether test scores are valid for a proposed interpretation and/or use. It is often the case that an investigator judges both the…

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.

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…

ITEM LEVEL DIAGNOSTICS AND MODEL - DATA FIT IN ITEM ...

African Journals Online (AJOL)

Global Journal

Item response theory (IRT) is a framework for modeling and analyzing item response ... data. Though, there is an argument that the evaluation of fit in IRT modeling has been ... National Council on Measurement in Education ... model data fit should be based on three types of ... prediction should be assessed through the.

Assessing fit in Bayesian models for spatial processes

KAUST Repository

Jun, M.; Katzfuss, M.; Hu, J.; Johnson, V. E.

2014-01-01

© 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.

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.

Set-fit effects in choice.

Science.gov (United States)

Evers, Ellen R K; Inbar, Yoel; Zeelenberg, Marcel

2014-04-01

In 4 experiments, we investigate how the "fit" of an item with a set of similar items affects choice. We find that people have a notion of a set that "fits" together--one where all items are the same, or all items differ, on salient attributes. One consequence of this notion is that in addition to preferences over the set's individual items, choice reflects set-fit. This leads to predictable shifts in preferences, sometimes even resulting in people choosing normatively inferior options over superior ones.

Papaya Development Model As A Competitive Local Superior Commodity

Directory of Open Access Journals (Sweden)

Reny Sukmawani

2014-12-01

Full Text Available The aim of this research is to study the comparative advantage and papaya competitive and to design its development model by using the approach of local base agriculture development. This research uses survey method. The resulting research shows that papaya is a base commodity that has comparative advantage and competitive. The development papaya in the district of Sukabumi is quite good bases on eight superior creations. But in order to be the main sector in economic development and has a competition, the development of papaya must concern to its influence factors. In supporting papaya development as a competitive local superior commodity, it needs to be done some efforts are as follows: (1 increase a skillful worker; (2 improve business management; (3 increase papaya productivity by using technology and study papaya planted technology in specific local superior commodity; (4 develop the involvement of the business relation; (5 provide market information and information technology network; and (6 improve infrastructures.

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

Automated model fit method for diesel engine control development

NARCIS (Netherlands)

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

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

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.

Active appearance pyramids for object parametrisation and fitting.

Science.gov (United States)

Zhang, Qiang; Bhalerao, Abhir; Dickenson, Edward; Hutchinson, Charles

2016-08-01

Object class representation is one of the key problems in various medical image analysis tasks. We propose a part-based parametric appearance model we refer to as an Active Appearance Pyramid (AAP). The parts are delineated by multi-scale Local Feature Pyramids (LFPs) for superior spatial specificity and distinctiveness. An AAP models the variability within a population with local translations of multi-scale parts and linear appearance variations of the assembly of the parts. It can fit and represent new instances by adjusting the shape and appearance parameters. The fitting process uses a two-step iterative strategy: local landmark searching followed by shape regularisation. We present a simultaneous local feature searching and appearance fitting algorithm based on the weighted Lucas and Kanade method. A shape regulariser is derived to calculate the maximum likelihood shape with respect to the prior and multiple landmark candidates from multi-scale LFPs, with a compact closed-form solution. We apply the 2D AAP on the modelling of variability in patients with lumbar spinal stenosis (LSS) and validate its performance on 200 studies consisting of routine axial and sagittal MRI scans. Intervertebral sagittal and parasagittal cross-sections are typically used for the diagnosis of LSS, we therefore build three AAPs on L3/4, L4/5 and L5/S1 axial cross-sections and three on parasagittal slices. Experiments show significant improvement in convergence range, robustness to local minima and segmentation precision compared with Constrained Local Models (CLMs), Active Shape Models (ASMs) and Active Appearance Models (AAMs), as well as superior performance in appearance reconstruction compared with AAMs. We also validate the performance on 3D CT volumes of hip joints from 38 studies. Compared to AAMs, AAPs achieve a higher segmentation and reconstruction precision. Moreover, AAPs have a significant improvement in efficiency, consuming about half the memory and less than 10% of

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.

Does model fit decrease the uncertainty of the data in comparison with a general non-model least squares fit?

International Nuclear Information System (INIS)

Pronyaev, V.G.

2003-01-01

The information entropy is taken as a measure of knowledge about the object and the reduced univariante variance as a common measure of uncertainty. Covariances in the model versus non-model least square fits are discussed

Efficient occupancy model-fitting for extensive citizen-science data

Science.gov (United States)

Morgan, Byron J. T.; Freeman, Stephen N.; Ridout, Martin S.; Brereton, Tom M.; Fox, Richard; Powney, Gary D.; Roy, David B.

2017-01-01

Appropriate large-scale citizen-science data present important new opportunities for biodiversity modelling, due in part to the wide spatial coverage of information. Recently proposed occupancy modelling approaches naturally incorporate random effects in order to account for annual variation in the composition of sites surveyed. In turn this leads to Bayesian analysis and model fitting, which are typically extremely time consuming. Motivated by presence-only records of occurrence from the UK Butterflies for the New Millennium data base, we present an alternative approach, in which site variation is described in a standard way through logistic regression on relevant environmental covariates. This allows efficient occupancy model-fitting using classical inference, which is easily achieved using standard computers. This is especially important when models need to be fitted each year, typically for many different species, as with British butterflies for example. Using both real and simulated data we demonstrate that the two approaches, with and without random effects, can result in similar conclusions regarding trends. There are many advantages to classical model-fitting, including the ability to compare a range of alternative models, identify appropriate covariates and assess model fit, using standard tools of maximum likelihood. In addition, modelling in terms of covariates provides opportunities for understanding the ecological processes that are in operation. We show that there is even greater potential; the classical approach allows us to construct regional indices simply, which indicate how changes in occupancy typically vary over a species’ range. In addition we are also able to construct dynamic occupancy maps, which provide a novel, modern tool for examining temporal changes in species distribution. These new developments may be applied to a wide range of taxa, and are valuable at a time of climate change. They also have the potential to motivate citizen

A Model Fit Statistic for Generalized Partial Credit Model

Science.gov (United States)

Liang, Tie; Wells, Craig S.

2009-01-01

Investigating the fit of a parametric model is an important part of the measurement process when implementing item response theory (IRT), but research examining it is limited. A general nonparametric approach for detecting model misfit, introduced by J. Douglas and A. S. Cohen (2001), has exhibited promising results for the two-parameter logistic…

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

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…

Sensitivity of Fit Indices to Misspecification in Growth Curve Models

Science.gov (United States)

Wu, Wei; West, Stephen G.

2010-01-01

This study investigated the sensitivity of fit indices to model misspecification in within-individual covariance structure, between-individual covariance structure, and marginal mean structure in growth curve models. Five commonly used fit indices were examined, including the likelihood ratio test statistic, root mean square error of…

Standard error propagation in R-matrix model fitting for light elements

International Nuclear Information System (INIS)

Chen Zhenpeng; Zhang Rui; Sun Yeying; Liu Tingjin

2003-01-01

The error propagation features with R-matrix model fitting 7 Li, 11 B and 17 O systems were researched systematically. Some laws of error propagation were revealed, an empirical formula P j = U j c / U j d = K j · S-bar · √m / √N for describing standard error propagation was established, the most likely error ranges for standard cross sections of 6 Li(n,t), 10 B(n,α0) and 10 B(n,α1) were estimated. The problem that the standard error of light nuclei standard cross sections may be too small results mainly from the R-matrix model fitting, which is not perfect. Yet R-matrix model fitting is the most reliable evaluation method for such data. The error propagation features of R-matrix model fitting for compound nucleus system of 7 Li, 11 B and 17 O has been studied systematically, some laws of error propagation are revealed, and these findings are important in solving the problem mentioned above. Furthermore, these conclusions are suitable for similar model fitting in other scientific fields. (author)

Model-fitting approach to kinetic analysis of non-isothermal oxidation of molybdenite

International Nuclear Information System (INIS)

Ebrahimi Kahrizsangi, R.; Abbasi, M. H.; Saidi, A.

2007-01-01

The kinetics of molybdenite oxidation was studied by non-isothermal TGA-DTA with heating rate 5 d eg C .min -1 . The model-fitting kinetic approach applied to TGA data. The Coats-Redfern method used of model fitting. The popular model-fitting gives excellent fit non-isothermal data in chemically controlled regime. The apparent activation energy was determined to be about 34.2 kcalmol -1 With pre-exponential factor about 10 8 sec -1 for extent of reaction less than 0.5

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.

Parametric fitting of corneal height data to a biconic surface.

Science.gov (United States)

Janunts, Edgar; Kannengießer, Marc; Langenbucher, Achim

2015-03-01

As the average corneal shape can effectively be approximated by a conic section, a determination of the corneal shape by biconic parameters is desired. The purpose of the paper is to introduce a straightforward mathematical approach for extracting clinically relevant parameters of corneal surface, such as radii of curvature and conic constants for principle meridians and astigmatism. A general description for modeling the ocular surfaces in a biconic form is given, based on which an implicit parametric surface fitting algorithm is introduced. The solution of the biconic fitting is obtained by a two sequential least squares optimization approach with constrains. The data input can be raw information from any corneal topographer with not necessarily a uniform data distribution. Various simulated and clinical data are studied including surfaces with rotationally symmetric and non-symmetric geometries. The clinical data was obtained from the Pentacam (Oculus) for the patient having undergone a refractive surgery. A sub-micrometer fitting accuracy was obtained for all simulated surfaces: 0,08 μm RMS fitting error at max for rotationally symmetric and 0,125 μm for non-symmetric surfaces. The astigmatism was recovered in a sub-minutes resolution. The equality in rotational symmetric and the superiority in non-symmetric surfaces of the presented model over the widely used quadric fitting model is shown. The introduced biconic surface fitting algorithm is able to recover the apical radii of curvature and conic constants in principle meridians. This methodology could be a platform for advanced IOL calculations and enhanced contact lens fitting. Copyright © 2014. Published by Elsevier GmbH.

Flexible competing risks regression modeling and goodness-of-fit

DEFF Research Database (Denmark)

Scheike, Thomas; Zhang, Mei-Jie

2008-01-01

In this paper we consider different approaches for estimation and assessment of covariate effects for the cumulative incidence curve in the competing risks model. The classic approach is to model all cause-specific hazards and then estimate the cumulative incidence curve based on these cause...... models that is easy to fit and contains the Fine-Gray model as a special case. One advantage of this approach is that our regression modeling allows for non-proportional hazards. This leads to a new simple goodness-of-fit procedure for the proportional subdistribution hazards assumption that is very easy...... of the flexible regression models to analyze competing risks data when non-proportionality is present in the data....

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…

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.

Item level diagnostics and model - data fit in item response theory ...

African Journals Online (AJOL)

Item response theory (IRT) is a framework for modeling and analyzing item response data. Item-level modeling gives IRT advantages over classical test theory. The fit of an item score pattern to an item response theory (IRT) models is a necessary condition that must be assessed for further use of item and models that best fit ...

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)

The picture superiority effect: support for the distinctiveness model.

Science.gov (United States)

Mintzer, M Z; Snodgrass, J G

1999-01-01

The form change paradigm was used to explore the basis for the picture superiority effect. Recognition memory for studied pictures and words was tested in their study form or the alternate form. Form change cost was defined as the difference between recognition performance for same and different form items. Based on the results of Experiment 1 and previous studies, it was difficult to determine the relative cost for studied pictures and words due to a reversal of the mirror effect. We hypothesized that the reversed mirror effect results from subjects' basing their recognition decisions on their assumptions about the study form. Experiments 2 and 3 confirmed this hypothesis and generated a method for evaluating the relative cost for pictures and words despite the reversed mirror effect. More cost was observed for pictures than words, supporting the distinctiveness model of the picture superiority effect.

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.

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

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.

LEP asymmetries and fits of the standard model

International Nuclear Information System (INIS)

Pietrzyk, B.

1994-01-01

The lepton and quark asymmetries measured at LEP are presented. The results of the Standard Model fits to the electroweak data presented at this conference are given. The top mass obtained from the fit to the LEP data is 172 -14-20 +13+18 GeV; it is 177 -11-19 +11+18 when also the collider, ν and A LR data are included. (author). 10 refs., 3 figs., 2 tabs

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

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......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...... 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...

Repair models of cell survival and corresponding computer program for survival curve fitting

International Nuclear Information System (INIS)

Shen Xun; Hu Yiwei

1992-01-01

Some basic concepts and formulations of two repair models of survival, the incomplete repair (IR) model and the lethal-potentially lethal (LPL) model, are introduced. An IBM-PC computer program for survival curve fitting with these models was developed and applied to fit the survivals of human melanoma cells HX118 irradiated at different dose rates. Comparison was made between the repair models and two non-repair models, the multitar get-single hit model and the linear-quadratic model, in the fitting and analysis of the survival-dose curves. It was shown that either IR model or LPL model can fit a set of survival curves of different dose rates with same parameters and provide information on the repair capacity of cells. These two mathematical models could be very useful in quantitative study on the radiosensitivity and repair capacity of cells

HDFITS: Porting the FITS data model to HDF5

Science.gov (United States)

Price, D. C.; Barsdell, B. R.; Greenhill, L. J.

2015-09-01

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 a FITS-like manner. We show that HDFITS allows faster reading of data (up to 100x of FITS in some use cases), and improved compression (higher compression ratios and higher throughput). Finally, we show that by only changing the import lines in Python-based FITS utilities, HDFITS formatted data can be presented transparently as an in-memory FITS equivalent.

Model Fit and Item Factor Analysis: Overfactoring, Underfactoring, and a Program to Guide Interpretation.

Science.gov (United States)

Clark, D Angus; Bowles, Ryan P

2018-04-23

In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker-Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.

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.  

Revisiting the Global Electroweak Fit of the Standard Model and Beyond with Gfitter

CERN Document Server

Flächer, Henning; Haller, J; Höcker, A; Mönig, K; Stelzer, J

2009-01-01

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 projec...

Evaluating the behavior of polychlorinated biphenyl compounds in Lake Superior using a dynamic multimedia model

Science.gov (United States)

Khan, T.; Perlinger, J. A.; Urban, N. R.

2017-12-01

Certain toxic, persistent, bioaccumulative, and semivolatile compounds known as atmosphere-surface exchangeable pollutants or ASEPs are emitted into the environment by primary sources, are transported, deposited to water surfaces, and can be later re-emitted causing the water to act as a secondary source. Polychlorinated biphenyl (PCB) compounds, a class of ASEPs, are of major concern in the Laurentian Great Lakes because of their historical use primarily as additives to oils and industrial fluids, and discharge from industrial sources. Following the ban on production in the U.S. in 1979, atmospheric concentrations of PCBs in the Lake Superior region decreased rapidly. Subsequently, PCB concentrations in the lake surface water also reached near equilibrium as the atmospheric levels of PCBs declined. However, previous studies on long-term PCB levels and trends in lake trout and walleye suggested that the initial rate of decline of PCB concentrations in fish has leveled off in Lake Superior. In this study, a dynamic multimedia flux model was developed with the objective to investigate the observed levelling off of PCB concentrations in Lake Superior fish. The model structure consists of two water layers (the epilimnion and the hypolimnion), and the surface mixed sediment layer, while atmospheric deposition is the primary external pathway of PCB inputs to the lake. The model was applied for different PCB congeners having a range of hydrophobicity and volatility. Using this model, we compare the long-term trends in predicted PCB concentrations in different environmental media with relevant available measurements for Lake Superior. We examine the seasonal depositional and exchange patterns, the relative importance of different process terms, and provide the most probable source of the current observed PCB levels in Lake Superior fish. In addition, we evaluate the role of current atmospheric PCB levels in sustaining the observed fish concentrations and appraise the need

Tests of fit of historically-informed models of African American Admixture.

Science.gov (United States)

Gross, Jessica M

2018-02-01

African American populations in the U.S. formed primarily by mating between Africans and Europeans over the last 500 years. To date, studies of admixture have focused on either a one-time admixture event or continuous input into the African American population from Europeans only. Our goal is to gain a better understanding of the admixture process by examining models that take into account (a) assortative mating by ancestry in the African American population, (b) continuous input from both Europeans and Africans, and (c) historically informed variation in the rate of African migration over time. We used a model-based clustering method to generate distributions of African ancestry in three samples comprised of 147 African Americans from two published sources. We used a log-likelihood method to examine the fit of four models to these distributions and used a log-likelihood ratio test to compare the relative fit of each model. The mean ancestry estimates for our datasets of 77% African/23% European to 83% African/17% European ancestry are consistent with previous studies. We find admixture models that incorporate continuous gene flow from Europeans fit significantly better than one-time event models, and that a model involving continuous gene flow from Africans and Europeans fits better than one with continuous gene flow from Europeans only for two samples. Importantly, models that involve continuous input from Africans necessitate a higher level of gene flow from Europeans than previously reported. We demonstrate that models that take into account information about the rate of African migration over the past 500 years fit observed patterns of African ancestry better than alternative models. Our approach will enrich our understanding of the admixture process in extant and past populations. © 2017 Wiley Periodicals, Inc.

[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.

A versatile curve-fit model for linear to deeply concave rank abundance curves

NARCIS (Netherlands)

Neuteboom, J.H.; Struik, P.C.

2005-01-01

A new, flexible curve-fit model for linear to concave rank abundance curves was conceptualized and validated using observational data. The model links the geometric-series model and log-series model and can also fit deeply concave rank abundance curves. The model is based ¿ in an unconventional way

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....

Fast Algorithms for Fitting Active Appearance Models to Unconstrained Images

NARCIS (Netherlands)

Tzimiropoulos, Georgios; Pantic, Maja

2016-01-01

Fitting algorithms for Active Appearance Models (AAMs) are usually considered to be robust but slow or fast but less able to generalize well to unseen variations. In this paper, we look into AAM fitting algorithms and make the following orthogonal contributions: We present a simple “project-out‿

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…

The l z ( p ) * Person-Fit Statistic in an Unfolding Model Context.

Science.gov (United States)

Tendeiro, Jorge N

2017-01-01

Although person-fit analysis has a long-standing tradition within item response theory, it has been applied in combination with dominance response models almost exclusively. In this article, a popular log likelihood-based parametric person-fit statistic under the framework of the generalized graded unfolding model is used. Results from a simulation study indicate that the person-fit statistic performed relatively well in detecting midpoint response style patterns and not so well in detecting extreme response style patterns.

Assessing Posttraumatic Stress Disorder's Latent Structure in Elderly Bereaved European Trauma Victims: Evidence for a Five Factor Dysphoric and Anxious Arousal Model

DEFF Research Database (Denmark)

Armour, Cherie; O'Connor, Maja; Elklit, Ask

2013-01-01

to provide superior fit over the existing four-factor models. The present study investigated the fit of the five-factor model against the existing four-factor models and assessed the resultant factors association with depression in a bereaved European trauma sample (N=325). Participants were assessed...... for PTSD via the Harvard Trauma Questionnaire and depression via the Beck Depression Inventory. The five-factor model provided superior fit to the data compared to the existing four-factor models. In the Dysphoric Arousal model depression was equally related to both Dysphoric Arousal and Emotional Numbing...

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.

Soil physical properties influencing the fitting parameters in Philip and Kostiakov infiltration models

International Nuclear Information System (INIS)

Mbagwu, J.S.C.

1994-05-01

Among the many models developed for monitoring the infiltration process those of Philip and Kostiakov have been studied in detail because of their simplicity and the ease of estimating their fitting parameters. The important soil physical factors influencing the fitting parameters in these infiltration models are reported in this study. The results of the study show that the single most important soil property affecting the fitting parameters in these models is the effective porosity. 36 refs, 2 figs, 5 tabs

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

Correcting Model Fit Criteria for Small Sample Latent Growth Models with Incomplete Data

Science.gov (United States)

McNeish, Daniel; Harring, Jeffrey R.

2017-01-01

To date, small sample problems with latent growth models (LGMs) have not received the amount of attention in the literature as related mixed-effect models (MEMs). Although many models can be interchangeably framed as a LGM or a MEM, LGMs uniquely provide criteria to assess global data-model fit. However, previous studies have demonstrated poor…

Physiological models of the lateral superior olive.

Directory of Open Access Journals (Sweden)

Go Ashida

2017-12-01

Full Text Available In computational biology, modeling is a fundamental tool for formulating, analyzing and predicting complex phenomena. Most neuron models, however, are designed to reproduce certain small sets of empirical data. Hence their outcome is usually not compatible or comparable with other models or datasets, making it unclear how widely applicable such models are. In this study, we investigate these aspects of modeling, namely credibility and generalizability, with a specific focus on auditory neurons involved in the localization of sound sources. The primary cues for binaural sound localization are comprised of interaural time and level differences (ITD/ILD, which are the timing and intensity differences of the sound waves arriving at the two ears. The lateral superior olive (LSO in the auditory brainstem is one of the locations where such acoustic information is first computed. An LSO neuron receives temporally structured excitatory and inhibitory synaptic inputs that are driven by ipsi- and contralateral sound stimuli, respectively, and changes its spike rate according to binaural acoustic differences. Here we examine seven contemporary models of LSO neurons with different levels of biophysical complexity, from predominantly functional ones ('shot-noise' models to those with more detailed physiological components (variations of integrate-and-fire and Hodgkin-Huxley-type. These models, calibrated to reproduce known monaural and binaural characteristics of LSO, generate largely similar results to each other in simulating ITD and ILD coding. Our comparisons of physiological detail, computational efficiency, predictive performances, and further expandability of the models demonstrate (1 that the simplistic, functional LSO models are suitable for applications where low computational costs and mathematical transparency are needed, (2 that more complex models with detailed membrane potential dynamics are necessary for simulation studies where sub

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.

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

2017-01-04

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 (T opt ) for maximum photosynthetic rate (P max ). 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.

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.

A person fit test for IRT models for polytomous items

NARCIS (Netherlands)

Glas, Cornelis A.W.; Dagohoy, A.V.

2007-01-01

A person fit test based on the Lagrange multiplier test is presented for three item response theory models for polytomous items: the generalized partial credit model, the sequential model, and the graded response model. The test can also be used in the framework of multidimensional ability

The lz(p)* Person-Fit Statistic in an Unfolding Model Context

NARCIS (Netherlands)

Tendeiro, Jorge N.

2017-01-01

Although person-fit analysis has a long-standing tradition within item response theory, it has been applied in combination with dominance response models almost exclusively. In this article, a popular log likelihood-based parametric person-fit statistic under the framework of the generalized graded

Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components

KAUST Repository

Zhang, Saijuan; Krebs-Smith, Susan M.; Midthune, Douglas; Perez, Adriana; Buckman, Dennis W.; Kipnis, Victor; Freedman, Laurence S.; Dodd, Kevin W.; Carroll, Raymond J

2011-01-01

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

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

Nonlinear models for fitting growth curves of Nellore cows reared in the Amazon Biome

Directory of Open Access Journals (Sweden)

Kedma Nayra da Silva Marinho

2013-09-01

Full Text Available Growth curves of Nellore cows were estimated by comparing six nonlinear models: Brody, Logistic, two alternatives by Gompertz, Richards and Von Bertalanffy. The models were fitted to weight-age data, from birth to 750 days of age of 29,221 cows, born between 1976 and 2006 in the Brazilian states of Acre, Amapá, Amazonas, Pará, Rondônia, Roraima and Tocantins. The models were fitted by the Gauss-Newton method. The goodness of fit of the models was evaluated by using mean square error, adjusted coefficient of determination, prediction error and mean absolute error. Biological interpretation of parameters was accomplished by plotting estimated weights versus the observed weight means, instantaneous growth rate, absolute maturity rate, relative instantaneous growth rate, inflection point and magnitude of the parameters A (asymptotic weight and K (maturing rate. The Brody and Von Bertalanffy models fitted the weight-age data but the other models did not. The average weight (A and growth rate (K were: 384.6±1.63 kg and 0.0022±0.00002 (Brody and 313.40±0.70 kg and 0.0045±0.00002 (Von Bertalanffy. The Brody model provides better goodness of fit than the Von Bertalanffy model.

Three dimensional fuzzy influence analysis of fitting algorithms on integrated chip topographic modeling

International Nuclear Information System (INIS)

Liang, Zhong Wei; Wang, Yi Jun; Ye, Bang Yan; Brauwer, Richard Kars

2012-01-01

In inspecting the detailed performance results of surface precision modeling in different external parameter conditions, the integrated chip surfaces should be evaluated and assessed during topographic spatial modeling processes. The application of surface fitting algorithms exerts a considerable influence on topographic mathematical features. The influence mechanisms caused by different surface fitting algorithms on the integrated chip surface facilitate the quantitative analysis of different external parameter conditions. By extracting the coordinate information from the selected physical control points and using a set of precise spatial coordinate measuring apparatus, several typical surface fitting algorithms are used for constructing micro topographic models with the obtained point cloud. In computing for the newly proposed mathematical features on surface models, we construct the fuzzy evaluating data sequence and present a new three dimensional fuzzy quantitative evaluating method. Through this method, the value variation tendencies of topographic features can be clearly quantified. The fuzzy influence discipline among different surface fitting algorithms, topography spatial features, and the external science parameter conditions can be analyzed quantitatively and in detail. In addition, quantitative analysis can provide final conclusions on the inherent influence mechanism and internal mathematical relation in the performance results of different surface fitting algorithms, topographic spatial features, and their scientific parameter conditions in the case of surface micro modeling. The performance inspection of surface precision modeling will be facilitated and optimized as a new research idea for micro-surface reconstruction that will be monitored in a modeling process

Three dimensional fuzzy influence analysis of fitting algorithms on integrated chip topographic modeling

Energy Technology Data Exchange (ETDEWEB)

Liang, Zhong Wei; Wang, Yi Jun [Guangzhou Univ., Guangzhou (China); Ye, Bang Yan [South China Univ. of Technology, Guangzhou (China); Brauwer, Richard Kars [Indian Institute of Technology, Kanpur (India)

2012-10-15

In inspecting the detailed performance results of surface precision modeling in different external parameter conditions, the integrated chip surfaces should be evaluated and assessed during topographic spatial modeling processes. The application of surface fitting algorithms exerts a considerable influence on topographic mathematical features. The influence mechanisms caused by different surface fitting algorithms on the integrated chip surface facilitate the quantitative analysis of different external parameter conditions. By extracting the coordinate information from the selected physical control points and using a set of precise spatial coordinate measuring apparatus, several typical surface fitting algorithms are used for constructing micro topographic models with the obtained point cloud. In computing for the newly proposed mathematical features on surface models, we construct the fuzzy evaluating data sequence and present a new three dimensional fuzzy quantitative evaluating method. Through this method, the value variation tendencies of topographic features can be clearly quantified. The fuzzy influence discipline among different surface fitting algorithms, topography spatial features, and the external science parameter conditions can be analyzed quantitatively and in detail. In addition, quantitative analysis can provide final conclusions on the inherent influence mechanism and internal mathematical relation in the performance results of different surface fitting algorithms, topographic spatial features, and their scientific parameter conditions in the case of surface micro modeling. The performance inspection of surface precision modeling will be facilitated and optimized as a new research idea for micro-surface reconstruction that will be monitored in a modeling process.

Multi-binding site model-based curve-fitting program for the computation of RIA data

International Nuclear Information System (INIS)

Malan, P.G.; Ekins, R.P.; Cox, M.G.; Long, E.M.R.

1977-01-01

In this paper, a comparison will be made of model-based and empirical curve-fitting procedures. The implementation of a multiple binding-site curve-fitting model which will successfully fit a wide range of assay data, and which can be run on a mini-computer is described. The latter sophisticated model also provides estimates of binding site concentrations and the values of the respective equilibrium constants present: the latter have been used for refining assay conditions using computer optimisation techniques. (orig./AJ) [de

Using the Flipchem Photochemistry Model When Fitting Incoherent Scatter Radar Data

Science.gov (United States)

Reimer, A. S.; Varney, R. H.

2017-12-01

The North face Resolute Bay Incoherent Scatter Radar (RISR-N) routinely images the dynamics of the polar ionosphere, providing measurements of the plasma density, electron temperature, ion temperature, and line of sight velocity with seconds to minutes time resolution. RISR-N does not directly measure ionospheric parameters, but backscattered signals, recording them as voltage samples. Using signal processing techniques, radar autocorrelation functions (ACF) are estimated from the voltage samples. A model of the signal ACF is then fitted to the ACF using non-linear least-squares techniques to obtain the best-fit ionospheric parameters. The signal model, and therefore the fitted parameters, depend on the ionospheric ion composition that is used [e.g. Zettergren et. al. (2010), Zou et. al. (2017)].The software used to process RISR-N ACF data includes the "flipchem" model, which is an ion photochemistry model developed by Richards [2011] that was adapted from the Field LineInterhemispheric Plasma (FLIP) model. Flipchem requires neutral densities, neutral temperatures, electron density, ion temperature, electron temperature, solar zenith angle, and F10.7 as inputs to compute ion densities, which are input to the signal model. A description of how the flipchem model is used in RISR-N fitting software will be presented. Additionally, a statistical comparison of the fitted electron density, ion temperature, electron temperature, and velocity obtained using a flipchem ionosphere, a pure O+ ionosphere, and a Chapman O+ ionosphere will be presented. The comparison covers nearly two years of RISR-N data (April 2015 - December 2016). Richards, P. G. (2011), Reexamination of ionospheric photochemistry, J. Geophys. Res., 116, A08307, doi:10.1029/2011JA016613.Zettergren, M., Semeter, J., Burnett, B., Oliver, W., Heinselman, C., Blelly, P.-L., and Diaz, M.: Dynamic variability in F-region ionospheric composition at auroral arc boundaries, Ann. Geophys., 28, 651-664, https

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.

Twitter classification model: the ABC of two million fitness tweets.

Science.gov (United States)

Vickey, Theodore A; Ginis, Kathleen Martin; Dabrowski, Maciej

2013-09-01

The purpose of this project was to design and test data collection and management tools that can be used to study the use of mobile fitness applications and social networking within the context of physical activity. This project was conducted over a 6-month period and involved collecting publically shared Twitter data from five mobile fitness apps (Nike+, RunKeeper, MyFitnessPal, Endomondo, and dailymile). During that time, over 2.8 million tweets were collected, processed, and categorized using an online tweet collection application and a customized JavaScript. Using the grounded theory, a classification model was developed to categorize and understand the types of information being shared by application users. Our data show that by tracking mobile fitness app hashtags, a wealth of information can be gathered to include but not limited to daily use patterns, exercise frequency, location-based workouts, and overall workout sentiment.

Assessing posttraumatic stress disorder's latent structure in elderly bereaved European trauma survivors: evidence for a five-factor dysphoric and anxious arousal model.

Science.gov (United States)

Armour, Cherie; O'Connor, Maja; Elklit, Ask; Elhai, Jon D

2013-10-01

The three-factor structure of posttraumatic stress disorder (PTSD) specified by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, is not supported in the empirical literature. Two alternative four-factor models have received a wealth of empirical support. However, a consensus regarding which is superior has not been reached. A recent five-factor model has been shown to provide superior fit over the existing four-factor models. The present study investigated the fit of the five-factor model against the existing four-factor models and assessed the resultant factors' association with depression in a bereaved European trauma sample (N = 325). The participants were assessed for PTSD via the Harvard Trauma Questionnaire and depression via the Beck Depression Inventory. The five-factor model provided superior fit to the data compared with the existing four-factor models. In the dysphoric arousal model, depression was equally related to both dysphoric arousal and emotional numbing, whereas depression was more related to dysphoric arousal than to anxious arousal.

Brief communication: human cranial variation fits iterative founder effect model with African origin.

Science.gov (United States)

von Cramon-Taubadel, Noreen; Lycett, Stephen J

2008-05-01

Recent studies comparing craniometric and neutral genetic affinity matrices have concluded that, on average, human cranial variation fits a model of neutral expectation. While human craniometric and genetic data fit a model of isolation by geographic distance, it is not yet clear whether this is due to geographically mediated gene flow or human dispersal events. Recently, human genetic data have been shown to fit an iterative founder effect model of dispersal with an African origin, in line with the out-of-Africa replacement model for modern human origins, and Manica et al. (Nature 448 (2007) 346-349) have demonstrated that human craniometric data also fit this model. However, in contrast with the neutral model of cranial evolution suggested by previous studies, Manica et al. (2007) made the a priori assumption that cranial form has been subject to climatically driven natural selection and therefore correct for climate prior to conducting their analyses. Here we employ a modified theoretical and methodological approach to test whether human cranial variability fits the iterative founder effect model. In contrast with Manica et al. (2007) we employ size-adjusted craniometric variables, since climatic factors such as temperature have been shown to correlate with aspects of cranial size. Despite these differences, we obtain similar results to those of Manica et al. (2007), with up to 26% of global within-population craniometric variation being explained by geographic distance from sub-Saharan Africa. Comparative analyses using non-African origins do not yield significant results. The implications of these results are discussed in the light of the modern human origins debate. (c) 2007 Wiley-Liss, Inc.

Rapid world modeling: Fitting range data to geometric primitives

International Nuclear Information System (INIS)

Feddema, J.; Little, C.

1996-01-01

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

Kernel-density estimation and approximate Bayesian computation for flexible epidemiological model fitting in Python.

Science.gov (United States)

Irvine, Michael A; Hollingsworth, T Déirdre

2018-05-26

Fitting complex models to epidemiological data is a challenging problem: methodologies can be inaccessible to all but specialists, there may be challenges in adequately describing uncertainty in model fitting, the complex models may take a long time to run, and it can be difficult to fully capture the heterogeneity in the data. We develop an adaptive approximate Bayesian computation scheme to fit a variety of epidemiologically relevant data with minimal hyper-parameter tuning by using an adaptive tolerance scheme. We implement a novel kernel density estimation scheme to capture both dispersed and multi-dimensional data, and directly compare this technique to standard Bayesian approaches. We then apply the procedure to a complex individual-based simulation of lymphatic filariasis, a human parasitic disease. The procedure and examples are released alongside this article as an open access library, with examples to aid researchers to rapidly fit models to data. This demonstrates that an adaptive ABC scheme with a general summary and distance metric is capable of performing model fitting for a variety of epidemiological data. It also does not require significant theoretical background to use and can be made accessible to the diverse epidemiological research community. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Model-independent partial wave analysis using a massively-parallel fitting framework

Science.gov (United States)

Sun, L.; Aoude, R.; dos Reis, A. C.; Sokoloff, M.

2017-10-01

The functionality of GooFit, a GPU-friendly framework for doing maximum-likelihood fits, has been extended to extract model-independent {\\mathscr{S}}-wave amplitudes in three-body decays such as D + → h + h + h -. A full amplitude analysis is done where the magnitudes and phases of the {\\mathscr{S}}-wave amplitudes are anchored at a finite number of m 2(h + h -) control points, and a cubic spline is used to interpolate between these points. The amplitudes for {\\mathscr{P}}-wave and {\\mathscr{D}}-wave intermediate states are modeled as spin-dependent Breit-Wigner resonances. GooFit uses the Thrust library, with a CUDA backend for NVIDIA GPUs and an OpenMP backend for threads with conventional CPUs. Performance on a variety of platforms is compared. Executing on systems with GPUs is typically a few hundred times faster than executing the same algorithm on a single CPU.

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.

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.

Fitting direct covariance structures by the MSTRUCT modeling language of the CALIS procedure.

Science.gov (United States)

Yung, Yiu-Fai; Browne, Michael W; Zhang, Wei

2015-02-01

This paper demonstrates the usefulness and flexibility of the general structural equation modelling (SEM) approach to fitting direct covariance patterns or structures (as opposed to fitting implied covariance structures from functional relationships among variables). In particular, the MSTRUCT modelling language (or syntax) of the CALIS procedure (SAS/STAT version 9.22 or later: SAS Institute, 2010) is used to illustrate the SEM approach. The MSTRUCT modelling language supports a direct covariance pattern specification of each covariance element. It also supports the input of additional independent and dependent parameters. Model tests, fit statistics, estimates, and their standard errors are then produced under the general SEM framework. By using numerical and computational examples, the following tests of basic covariance patterns are illustrated: sphericity, compound symmetry, and multiple-group covariance patterns. Specification and testing of two complex correlation structures, the circumplex pattern and the composite direct product models with or without composite errors and scales, are also illustrated by the MSTRUCT syntax. It is concluded that the SEM approach offers a general and flexible modelling of direct covariance and correlation patterns. In conjunction with the use of SAS macros, the MSTRUCT syntax provides an easy-to-use interface for specifying and fitting complex covariance and correlation structures, even when the number of variables or parameters becomes large. © 2014 The British Psychological Society.

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

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

OpenAIRE

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

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 evaluat...

Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development.

Science.gov (United States)

Tøndel, Kristin; Niederer, Steven A; Land, Sander; Smith, Nicolas P

2014-05-20

Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input-output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on

Aerobic fitness is associated with greater white matter integrity in children

Directory of Open Access Journals (Sweden)

Laura eChaddock-Heyman

2014-08-01

Full Text Available Aerobic fitness has been found to play a positive role in brain and cognitive health of children. Yet, many of the neural biomarkers related to aerobic fitness remain unknown. Here, using diffusion tensor imaging (DTI, we demonstrated that higher aerobic fitness was related to greater estimates of white matter microstructure in children. Higher fit 9- and 10-year-old children showed greater fractional anisotropy (FA in sections of the corpus callosum, corona radiata, and superior longitudinal fasciculus, compared to lower fit children. The FA effects were primarily characterized by aerobic fitness differences in radial diffusivity (RD, thereby raising the possibility that estimates of myelination may vary as a function of individual differences in fitness during childhood. White matter structure may be another potential neural mechanism of aerobic fitness that assists in efficient communication between gray matter regions as well as the integration of regions into networks.

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

Science.gov (United States)

Armour, Cherie; Carragher, Natacha; Elhai, Jon D

2013-01-01

Since the initial inclusion of PTSD in the DSM nomenclature, PTSD symptomatology has been distributed across three symptom clusters. However, a wealth of empirical research has concluded that PTSD's latent structure is best represented by one of two four-factor models: Numbing or Dysphoria. Recently, a newly proposed five-factor Dysphoric Arousal model, which separates the DSM-IV's Arousal cluster into two factors of Anxious Arousal and Dysphoric Arousal, has gathered support across a variety of trauma samples. To date, the Dysphoric Arousal model has not been assessed using nationally representative epidemiological data. We employed confirmatory factor analysis to examine PTSD's latent structure in two independent population based surveys from American (NESARC) and Australia (NSWHWB). We specified and estimated the Numbing model, the Dysphoria model, and the Dysphoric Arousal model in both 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 structure using nationally representative epidemiological data in addition to single trauma specific samples. Copyright © 2012 Elsevier Ltd. All rights reserved.

Fractal Image Coding Based on a Fitting Surface

Directory of Open Access Journals (Sweden)

Sheng Bi

2014-01-01

Full Text Available A no-search fractal image coding method based on a fitting surface is proposed. In our research, an improved gray-level transform with a fitting surface is introduced. One advantage of this method is that the fitting surface is used for both the range and domain blocks and one set of parameters can be saved. Another advantage is that the fitting surface can approximate the range and domain blocks better than the previous fitting planes; this can result in smaller block matching errors and better decoded image quality. Since the no-search and quadtree techniques are adopted, smaller matching errors also imply less number of blocks matching which results in a faster encoding process. Moreover, by combining all the fitting surfaces, a fitting surface image (FSI is also proposed to speed up the fractal decoding. Experiments show that our proposed method can yield superior performance over the other three methods. Relative to range-averaged image, FSI can provide faster fractal decoding process. Finally, by combining the proposed fractal coding method with JPEG, a hybrid coding method is designed which can provide higher PSNR than JPEG while maintaining the same Bpp.

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.

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

ARA and ARI imperfect repair models: Estimation, goodness-of-fit and reliability prediction

International Nuclear Information System (INIS)

Toledo, Maria Luíza Guerra de; Freitas, Marta A.; Colosimo, Enrico A.; Gilardoni, Gustavo L.

2015-01-01

An appropriate maintenance policy is essential to reduce expenses and risks related to equipment failures. A fundamental aspect to be considered when specifying such policies is to be able to predict the reliability of the systems under study, based on a well fitted model. In this paper, the classes of models Arithmetic Reduction of Age and Arithmetic Reduction of Intensity are explored. Likelihood functions for such models are derived, and a graphical method is proposed for model selection. A real data set involving failures in trucks used by a Brazilian mining is analyzed considering models with different memories. Parameters, namely, shape and scale for Power Law Process, and the efficiency of repair were estimated for the best fitted model. Estimation of model parameters allowed us to derive reliability estimators to predict the behavior of the failure process. These results are a valuable information for the mining company and can be used to support decision making regarding preventive maintenance policy. - Highlights: • Likelihood functions for imperfect repair models are derived. • A goodness-of-fit technique is proposed as a tool for model selection. • Failures in trucks owned by a Brazilian mining are modeled. • Estimation allowed deriving reliability predictors to forecast the future failure process of the trucks

Person-fit to the Five Factor Model of personality

Czech Academy of Sciences Publication Activity Database

Allik, J.; Realo, A.; Mõttus, R.; Borkenau, P.; Kuppens, P.; Hřebíčková, Martina

2012-01-01

Roč. 71, č. 1 (2012), s. 35-45 ISSN 1421-0185 R&D Projects: GA ČR GAP407/10/2394 Institutional research plan: CEZ:AV0Z70250504 Keywords : Five Factor Model * cross - cultural comparison * person-fit Subject RIV: AN - Psychology Impact factor: 0.638, year: 2012

Study on fitness functions of genetic algorithm for dynamically correcting nuclide atmospheric diffusion model

International Nuclear Information System (INIS)

Ji Zhilong; Ma Yuanwei; Wang Dezhong

2014-01-01

Background: In radioactive nuclides atmospheric diffusion models, the empirical dispersion coefficients were deduced under certain experiment conditions, whose difference with nuclear accident conditions is a source of deviation. A better estimation of the radioactive nuclide's actual dispersion process could be done by correcting dispersion coefficients with observation data, and Genetic Algorithm (GA) is an appropriate method for this correction procedure. Purpose: This study is to analyze the fitness functions' influence on the correction procedure and the forecast ability of diffusion model. Methods: GA, coupled with Lagrange dispersion model, was used in a numerical simulation to compare 4 fitness functions' impact on the correction result. Results: In the numerical simulation, the fitness function with observation deviation taken into consideration stands out when significant deviation exists in the observed data. After performing the correction procedure on the Kincaid experiment data, a significant boost was observed in the diffusion model's forecast ability. Conclusion: As the result shows, in order to improve dispersion models' forecast ability using GA, observation data should be given different weight in the fitness function corresponding to their error. (authors)

Model Fitting for Predicted Precipitation in Darwin: Some Issues with Model Choice

Science.gov (United States)

Farmer, Jim

2010-01-01

In Volume 23(2) of the "Australian Senior Mathematics Journal," Boncek and Harden present an exercise in fitting a Markov chain model to rainfall data for Darwin Airport (Boncek & Harden, 2009). Days are subdivided into those with precipitation and precipitation-free days. The author abbreviates these labels to wet days and dry days.…

Introducing the fit-criteria assessment plot - A visualisation tool to assist class enumeration in group-based trajectory modelling.

Science.gov (United States)

Klijn, Sven L; Weijenberg, Matty P; Lemmens, Paul; van den Brandt, Piet A; Lima Passos, Valéria

2017-10-01

Background and objective Group-based trajectory modelling is a model-based clustering technique applied for the identification of latent patterns of temporal changes. Despite its manifold applications in clinical and health sciences, potential problems of the model selection procedure are often overlooked. The choice of the number of latent trajectories (class-enumeration), for instance, is to a large degree based on statistical criteria that are not fail-safe. Moreover, the process as a whole is not transparent. To facilitate class enumeration, we introduce a graphical summary display of several fit and model adequacy criteria, the fit-criteria assessment plot. Methods An R-code that accepts universal data input is presented. The programme condenses relevant group-based trajectory modelling output information of model fit indices in automated graphical displays. Examples based on real and simulated data are provided to illustrate, assess and validate fit-criteria assessment plot's utility. Results Fit-criteria assessment plot provides an overview of fit criteria on a single page, placing users in an informed position to make a decision. Fit-criteria assessment plot does not automatically select the most appropriate model but eases the model assessment procedure. Conclusions Fit-criteria assessment plot is an exploratory, visualisation tool that can be employed to assist decisions in the initial and decisive phase of group-based trajectory modelling analysis. Considering group-based trajectory modelling's widespread resonance in medical and epidemiological sciences, a more comprehensive, easily interpretable and transparent display of the iterative process of class enumeration may foster group-based trajectory modelling's adequate use.

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.

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.

Universal Rate Model Selector: A Method to Quickly Find the Best-Fit Kinetic Rate Model for an Experimental Rate Profile

Science.gov (United States)

2017-08-01

k2 – k1) 3.3 Universal Kinetic Rate Platform Development Kinetic rate models range from pure chemical reactions to mass transfer...14 8. The rate model that best fits the experimental data is a first-order or homogeneous catalytic reaction ...Avrami (7), and intraparticle diffusion (6) rate equations to name a few. A single fitting algorithm (kinetic rate model ) for a reaction does not

The global electroweak Standard Model fit after the Higgs discovery

CERN Document Server

Baak, Max

2013-01-01

We present an update of the global Standard Model (SM) fit to electroweak precision data under the assumption that the new particle discovered at the LHC is the SM Higgs boson. In this scenario all parameters entering the calculations of electroweak precision observalbes are known, allowing, for the first time, to over-constrain the SM at the electroweak scale and assert its validity. Within the SM the W boson mass and the effective weak mixing angle can be accurately predicted from the global fit. The results are compatible with, and exceed in precision, the direct measurements. An updated determination of the S, T and U parameters, which parametrize the oblique vacuum corrections, is given. The obtained values show good consistency with the SM expectation and no direct signs of new physics are seen. We conclude with an outlook to the global electroweak fit for a future e+e- collider.

Radial artery pulse waveform analysis based on curve fitting using discrete Fourier series.

Science.gov (United States)

Jiang, Zhixing; Zhang, David; Lu, Guangming

2018-04-19

Radial artery pulse diagnosis has been playing an important role in traditional Chinese medicine (TCM). For its non-invasion and convenience, the pulse diagnosis has great significance in diseases analysis of modern medicine. The practitioners sense the pulse waveforms in patients' wrist to make diagnoses based on their non-objective personal experience. With the researches of pulse acquisition platforms and computerized analysis methods, the objective study on pulse diagnosis can help the TCM to keep up with the development of modern medicine. In this paper, we propose a new method to extract feature from pulse waveform based on discrete Fourier series (DFS). It regards the waveform as one kind of signal that consists of a series of sub-components represented by sine and cosine (SC) signals with different frequencies and amplitudes. After the pulse signals are collected and preprocessed, we fit the average waveform for each sample using discrete Fourier series by least squares. The feature vector is comprised by the coefficients of discrete Fourier series function. Compared with the fitting method using Gaussian mixture function, the fitting errors of proposed method are smaller, which indicate that our method can represent the original signal better. The classification performance of proposed feature is superior to the other features extracted from waveform, liking auto-regression model and Gaussian mixture model. The coefficients of optimized DFS function, who is used to fit the arterial pressure waveforms, can obtain better performance in modeling the waveforms and holds more potential information for distinguishing different psychological states. Copyright © 2018 Elsevier B.V. All rights reserved.

Residuals and the Residual-Based Statistic for Testing Goodness of Fit of Structural Equation Models

Science.gov (United States)

Foldnes, Njal; Foss, Tron; Olsson, Ulf Henning

2012-01-01

The residuals obtained from fitting a structural equation model are crucial ingredients in obtaining chi-square goodness-of-fit statistics for the model. The authors present a didactic discussion of the residuals, obtaining a geometrical interpretation by recognizing the residuals as the result of oblique projections. This sheds light on the…

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.

Fitting Diffusion Item Response Theory Models for Responses and Response Times Using the R Package diffIRT

Directory of Open Access Journals (Sweden)

Dylan Molenaar

2015-08-01

Full Text Available In the psychometric literature, item response theory models have been proposed that explicitly take the decision process underlying the responses of subjects to psychometric test items into account. Application of these models is however hampered by the absence of general and flexible software to fit these models. In this paper, we present diffIRT, an R package that can be used to fit item response theory models that are based on a diffusion process. We discuss parameter estimation and model fit assessment, show the viability of the package in a simulation study, and illustrate the use of the package with two datasets pertaining to extraversion and mental rotation. In addition, we illustrate how the package can be used to fit the traditional diffusion model (as it has been originally developed in experimental psychology to data.

Sustained fitness gains and variability in fitness trajectories in the long-term evolution experiment with Escherichia coli

Science.gov (United States)

Lenski, Richard E.; Wiser, Michael J.; Ribeck, Noah; Blount, Zachary D.; Nahum, Joshua R.; Morris, J. Jeffrey; Zaman, Luis; Turner, Caroline B.; Wade, Brian D.; Maddamsetti, Rohan; Burmeister, Alita R.; Baird, Elizabeth J.; Bundy, Jay; Grant, Nkrumah A.; Card, Kyle J.; Rowles, Maia; Weatherspoon, Kiyana; Papoulis, Spiridon E.; Sullivan, Rachel; Clark, Colleen; Mulka, Joseph S.; Hajela, Neerja

2015-01-01

Many populations live in environments subject to frequent biotic and abiotic changes. Nonetheless, it is interesting to ask whether an evolving population's mean fitness can increase indefinitely, and potentially without any limit, even in a constant environment. A recent study showed that fitness trajectories of Escherichia coli populations over 50 000 generations were better described by a power-law model than by a hyperbolic model. According to the power-law model, the rate of fitness gain declines over time but fitness has no upper limit, whereas the hyperbolic model implies a hard limit. Here, we examine whether the previously estimated power-law model predicts the fitness trajectory for an additional 10 000 generations. To that end, we conducted more than 1100 new competitive fitness assays. Consistent with the previous study, the power-law model fits the new data better than the hyperbolic model. We also analysed the variability in fitness among populations, finding subtle, but significant, heterogeneity in mean fitness. Some, but not all, of this variation reflects differences in mutation rate that evolved over time. Taken together, our results imply that both adaptation and divergence can continue indefinitely—or at least for a long time—even in a constant environment. PMID:26674951

Superiority of Bessel function over Zernicke polynomial as base ...

Indian Academy of Sciences (India)

Abstract. Here we describe the superiority of Bessel function as base function for radial expan- sion over Zernicke polynomial in the tomographic reconstruction technique. The causes for the superiority have been described in detail. The superiority has been shown both with simulated data for Kadomtsev's model for ...

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

Science.gov (United States)

Friedrich, Péter; Vella, Michael; Gulyás, Attila I; Freund, Tamás F; Káli, Szabolcs

2014-01-01

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 problems 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 tool.

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

Double elevator weakening for unilateral congenital superior oblique palsy with ipsilateral superior rectus contracture and lax superior oblique tendon.

Science.gov (United States)

Khan, Arif O

2012-06-01

In unilateral congenital superior oblique palsy, a large hypertropia is sometimes associated with ipsilateral contracture of the superior rectus muscle and apparent overaction of the contralateral superior oblique. Ipsilateral double elevator weakening is one surgical approach; however, this procedure could compromise supraduction. We report a series of three consecutive patients who underwent ipsilateral superior rectus and inferior oblique recessions for unilateral superior oblique palsy. Intraoperatively, all three patients were found to have a lax ipsilateral superior oblique tendon. Postoperatively, all three patients had satisfactory correction of the hypertropia and abnormal head position with minimal supraduction defect. This procedure seems to be an acceptable initial surgical option for treating congenital superior oblique muscle palsy with ipsilateral contracture of the superior rectus muscle, even when the ipsilateral superior oblique tendon is lax. Copyright © 2012 American Association for Pediatric Ophthalmology and Strabismus. Published by Mosby, Inc. All rights reserved.

The universal Higgs fit

DEFF Research Database (Denmark)

Giardino, P. P.; Kannike, K.; Masina, I.

2014-01-01

We perform a state-of-the-art global fit to all Higgs data. We synthesise them into a 'universal' form, which allows to easily test any desired model. We apply the proposed methodology to extract from data the Higgs branching ratios, production cross sections, couplings and to analyse composite...... 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...... as an alternative to the Higgs, and disfavour fits with negative Yukawa couplings. We derive for the first time the SM Higgs boson mass from the measured rates, rather than from the peak positions, obtaining M-h = 124.4 +/- 1.6 GeV....

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.

PTSD's latent structure in Malaysian tsunami victims: assessing the newly proposed Dysphoric Arousal model.

Science.gov (United States)

Armour, Cherie; Raudzah Ghazali, Siti; Elklit, Ask

2013-03-30

The underlying latent structure of Posttraumatic Stress Disorder (PTSD) is widely researched. However, despite a plethora of factor analytic studies, no single model has consistently been shown as superior to alternative models. The two most often supported models are the Emotional Numbing and the Dysphoria models. However, a recently proposed five-factor Dysphoric Arousal model has been gathering support over and above existing models. Data for the current study were gathered from Malaysian Tsunami survivors (N=250). Three competing models (Emotional Numbing/Dysphoria/Dysphoric Arousal) were specified and estimated using Confirmatory Factor Analysis (CFA). The Dysphoria model provided superior fit to the data compared to the Emotional Numbing model. However, using chi-square difference tests, the Dysphoric Arousal model showed a superior fit compared to both the Emotional Numbing and Dysphoria models. In conclusion, the current results suggest that the Dysphoric Arousal model better represents PTSD's latent structure and that items measuring sleeping difficulties, irritability/anger and concentration difficulties form a separate, unique PTSD factor. These results are discussed in relation to the role of Hyperarousal in PTSD's on-going symptom maintenance and in relation to the DSM-5. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Feature extraction through least squares fit to a simple model

International Nuclear Information System (INIS)

Demuth, H.B.

1976-01-01

The Oak Ridge National Laboratory (ORNL) presented the Los Alamos Scientific Laboratory (LASL) with 18 radiographs of fuel rod test bundles. The problem is to estimate the thickness of the gap between some cylindrical rods and a flat wall surface. The edges of the gaps are poorly defined due to finite source size, x-ray scatter, parallax, film grain noise, and other degrading effects. The radiographs were scanned and the scan-line data were averaged to reduce noise and to convert the problem to one dimension. A model of the ideal gap, convolved with an appropriate point-spread function, was fit to the averaged data with a least squares program; and the gap width was determined from the final fitted-model parameters. The least squares routine did converge and the gaps obtained are of reasonable size. The method is remarkably insensitive to noise. This report describes the problem, the techniques used to solve it, and the results and conclusions. Suggestions for future work are also given

Does the Fit Between Competitive Strategy and Administrative Mechanisms Lead to Superior Performance?

OpenAIRE

Barth, Henrik

2000-01-01

At least two different administrative mechanisms are available for the small business manager to develop and pursue a competitive strategy. One refers to managerial skills needed to implement and follow the competitive strategy chosen by the firm. The other refers to the design of organisation structure i.e. how job tasks are divided, grouped and coordinated. This paper argues that the fit between the competitive strategy followed by a firm and the utilisation of the administrative mechanisms...

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.

Fitness cost

DEFF Research Database (Denmark)

Nielsen, Karen L.; Pedersen, Thomas M.; Udekwu, Klas I.

2012-01-01

phage types, predominantly only penicillin resistant. We investigated whether isolates of this epidemic were associated with a fitness cost, and we employed a mathematical model to ask whether these fitness costs could have led to the observed reduction in frequency. Bacteraemia isolates of S. aureus...... from Denmark have been stored since 1957. We chose 40 S. aureus isolates belonging to phage complex 83A, clonal complex 8 based on spa type, ranging in time of isolation from 1957 to 1980 and with varyous antibiograms, including both methicillin-resistant and -susceptible isolates. The relative fitness...... 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...

GOODNESS-OF-FIT TEST FOR THE ACCELERATED FAILURE TIME MODEL BASED ON MARTINGALE RESIDUALS

Czech Academy of Sciences Publication Activity Database

Novák, Petr

2013-01-01

Roč. 49, č. 1 (2013), s. 40-59 ISSN 0023-5954 R&D Projects: GA MŠk(CZ) 1M06047 Grant - others:GA MŠk(CZ) SVV 261315/2011 Keywords : accelerated failure time model * survival analysis * goodness-of-fit Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.563, year: 2013 http://library.utia.cas.cz/separaty/2013/SI/novak-goodness-of-fit test for the aft model based on martingale residuals.pdf

Comparison of Generalized Estimating Equations and Quadratic Inference Functions in superior versus inferior Ahmed Glaucoma Valve implantation

Directory of Open Access Journals (Sweden)

Razieh Khajeh-Kazemi

2011-01-01

Full Text Available Background: The celebrated generalized estimating equations (GEE approach is often used in longitudinal data analysis While this method behaves robustly against misspecification of the working correlation structure, it has some limitations on efficacy of estimators, goodness-of-fit tests and model selection criteria The quadratic inference functions (QIF is a new statistical methodology that overcomes these limitations Methods : We administered the use of QIF and GEE in comparing the superior and inferior Ahmed glaucoma valve (AGV implantation, while our focus was on the efficiency of estimation and using model selection criteria, we compared the effect of implant location on intraocular pressure (IOP in refractory glaucoma patients We modeled the relationship between IOP and implant location, patient′s sex and age, best corrected visual acuity, history of cataract surgery, preoperative IOP and months after surgery with assuming unstructured working correlation Results : 63 eyes of 63 patients were included in this study, 28 eyes in inferior group and 35 eyes in superior group The GEE analysis revealed that preoperative IOP has a significant effect on IOP (p = 0 011 However, QIF showed that preoperative IOP, months after surgery and squared months are significantly associated with IOP after surgery (p < 0 05 Overall, estimates from QIF are more efficient than GEE (RE = 1 272 Conclusions : In the case of unstructured working correlation, the QIF is more efficient than GEE There were no considerable difference between these locations, our results confirmed previously published works which mentioned it is better that glaucoma patients undergo superior AGV implantation

Assessing model fit in latent class analysis when asymptotics do not hold

NARCIS (Netherlands)

van Kollenburg, Geert H.; Mulder, Joris; Vermunt, Jeroen K.

2015-01-01

The application of latent class (LC) analysis involves evaluating the LC model using goodness-of-fit statistics. To assess the misfit of a specified model, say with the Pearson chi-squared statistic, a p-value can be obtained using an asymptotic reference distribution. However, asymptotic p-values

A sigmoidal fit for pressure-volume curves of idiopathic pulmonary fibrosis patients on mechanical ventilation: clinical implications

Directory of Open Access Journals (Sweden)

Juliana C. Ferreira

2011-01-01

Full Text Available OBJECTIVE: Respiratory pressure-volume curves fitted to exponential equations have been used to assess disease severity and prognosis in spontaneously breathing patients with idiopathic pulmonary fibrosis. Sigmoidal equations have been used to fit pressure-volume curves for mechanically ventilated patients but not for idiopathic pulmonary fibrosis patients. We compared a sigmoidal model and an exponential model to fit pressure-volume curves from mechanically ventilated patients with idiopathic pulmonary fibrosis. METHODS: Six idiopathic pulmonary fibrosis patients and five controls underwent inflation pressure-volume curves using the constant-flow technique during general anesthesia prior to open lung biopsy or thymectomy. We identified the lower and upper inflection points and fit the curves with an exponential equation, V = A-B.e-k.P, and a sigmoid equation, V = a+b/(1+e-(P-c/d. RESULTS: The mean lower inflection point for idiopathic pulmonary fibrosis patients was significantly higher (10.5 ± 5.7 cm H2O than that of controls (3.6 ± 2.4 cm H2O. The sigmoidal equation fit the pressure-volume curves of the fibrotic and control patients well, but the exponential equation fit the data well only when points below 50% of the inspiratory capacity were excluded. CONCLUSION: The elevated lower inflection point and the sigmoidal shape of the pressure-volume curves suggest that respiratory system compliance is decreased close to end-expiratory lung volume in idiopathic pulmonary fibrosis patients under general anesthesia and mechanical ventilation. The sigmoidal fit was superior to the exponential fit for inflation pressure-volume curves of anesthetized patients with idiopathic pulmonary fibrosis and could be useful for guiding mechanical ventilation during general anesthesia in this condition.

The effect of measurement quality on targeted structural model fit indices: A comment on Lance, Beck, Fan, and Carter (2016).

Science.gov (United States)

McNeish, Daniel; Hancock, Gregory R

2018-03-01

Lance, Beck, Fan, and Carter (2016) recently advanced 6 new fit indices and associated cutoff values for assessing data-model fit in the structural portion of traditional latent variable path models. The authors appropriately argued that, although most researchers' theoretical interest rests with the latent structure, they still rely on indices of global model fit that simultaneously assess both the measurement and structural portions of the model. As such, Lance et al. proposed indices intended to assess the structural portion of the model in isolation of the measurement model. Unfortunately, although these strategies separate the assessment of the structure from the fit of the measurement model, they do not isolate the structure's assessment from the quality of the measurement model. That is, even with a perfectly fitting measurement model, poorer quality (i.e., less reliable) measurements will yield a more favorable verdict regarding structural fit, whereas better quality (i.e., more reliable) measurements will yield a less favorable structural assessment. This phenomenon, referred to by Hancock and Mueller (2011) as the reliability paradox, affects not only traditional global fit indices but also those structural indices proposed by Lance et al. as well. Fortunately, as this comment will clarify, indices proposed by Hancock and Mueller help to mitigate this problem and allow the structural portion of the model to be assessed independently of both the fit of the measurement model as well as the quality of indicator variables contained therein. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

FitSKIRT: genetic algorithms to automatically fit dusty galaxies with a Monte Carlo radiative transfer code

Science.gov (United States)

De Geyter, G.; Baes, M.; Fritz, J.; Camps, P.

2013-02-01

We present FitSKIRT, a method to efficiently fit radiative transfer models to UV/optical images of dusty galaxies. These images have the advantage that they have better spatial resolution compared to FIR/submm data. FitSKIRT uses the GAlib genetic algorithm library to optimize the output of the SKIRT Monte Carlo radiative transfer code. Genetic algorithms prove to be a valuable tool in handling the multi- dimensional search space as well as the noise induced by the random nature of the Monte Carlo radiative transfer code. FitSKIRT is tested on artificial images of a simulated edge-on spiral galaxy, where we gradually increase the number of fitted parameters. We find that we can recover all model parameters, even if all 11 model parameters are left unconstrained. Finally, we apply the FitSKIRT code to a V-band image of the edge-on spiral galaxy NGC 4013. This galaxy has been modeled previously by other authors using different combinations of radiative transfer codes and optimization methods. Given the different models and techniques and the complexity and degeneracies in the parameter space, we find reasonable agreement between the different models. We conclude that the FitSKIRT method allows comparison between different models and geometries in a quantitative manner and minimizes the need of human intervention and biasing. The high level of automation makes it an ideal tool to use on larger sets of observed data.

A scaled Lagrangian method for performing a least squares fit of a model to plant data

International Nuclear Information System (INIS)

Crisp, K.E.

1988-01-01

Due to measurement errors, even a perfect mathematical model will not be able to match all the corresponding plant measurements simultaneously. A further discrepancy may be introduced if an un-modelled change in conditions occurs within the plant which should have required a corresponding change in model parameters - e.g. a gradual deterioration in the performance of some component(s). Taking both these factors into account, what is required is that the overall discrepancy between the model predictions and the plant data is kept to a minimum. This process is known as 'model fitting', A method is presented for minimising any function which consists of the sum of squared terms, subject to any constraints. Its most obvious application is in the process of model fitting, where a weighted sum of squares of the differences between model predictions and plant data is the function to be minimised. When implemented within existing Central Electricity Generating Board computer models, it will perform a least squares fit of a model to plant data within a single job submission. (author)

The disconnected values model improves mental well-being and fitness in an employee wellness program.

Science.gov (United States)

Anshel, Mark H; Brinthaupt, Thomas M; Kang, Minsoo

2010-01-01

This study examined the effect of a 10-week wellness program on changes in physical fitness and mental well-being. The conceptual framework for this study was the Disconnected Values Model (DVM). According to the DVM, detecting the inconsistencies between negative habits and values (e.g., health, family, faith, character) and concluding that these "disconnects" are unacceptable promotes the need for health behavior change. Participants were 164 full-time employees at a university in the southeastern U.S. The program included fitness coaching and a 90-minute orientation based on the DVM. Multivariate Mixed Model analyses indicated significantly improved scores from pre- to post-intervention on selected measures of physical fitness and mental well-being. The results suggest that the Disconnected Values Model provides an effective cognitive-behavioral approach to generating health behavior change in a 10-week workplace wellness program.

GOSSIP: SED fitting code

Science.gov (United States)

Franzetti, Paolo; Scodeggio, Marco

2012-10-01

GOSSIP fits the electro-magnetic emission of an object (the SED, Spectral Energy Distribution) against synthetic models to find the simulated one that best reproduces the observed data. It builds-up the observed SED of an object (or a large sample of objects) combining magnitudes in different bands and eventually a spectrum; then it performs a chi-square minimization fitting procedure versus a set of synthetic models. The fitting results are used to estimate a number of physical parameters like the Star Formation History, absolute magnitudes, stellar mass and their Probability Distribution Functions.

Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications

Science.gov (United States)

W. Hasan, W. Z.

2018-01-01

The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system’s modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model. PMID:29351554

Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications.

Science.gov (United States)

Sabry, A H; W Hasan, W Z; Ab Kadir, M Z A; Radzi, M A M; Shafie, S

2018-01-01

The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.

Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications.

Directory of Open Access Journals (Sweden)

A H Sabry

Full Text Available The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.

III. The importance of physical activity and aerobic fitness for cognitive control and memory in children.

Science.gov (United States)

Chaddock-Heyman, Laura; Hillman, Charles H; Cohen, Neal J; Kramer, Arthur F

2014-12-01

In this chapter, we review literature that examines the association among physical activity, aerobic fitness, cognition, and the brain in elementary school children (ages 7-10 years). Specifically, physical activity and higher levels of aerobic fitness in children have been found to benefit brain structure, brain function, cognition, and school achievement. For example, higher fit children have larger brain volumes in the basal ganglia and hippocampus, which relate to superior performance on tasks of cognitive control and memory, respectively, when compared to their lower fit peers. Higher fit children also show superior brain function during tasks of cognitive control, better scores on tests of academic achievement, and higher performance on a real-world street crossing task, compared to lower fit and less active children. The cross-sectional findings are strengthened by a few randomized, controlled trials, which demonstrate that children randomly assigned to a physical activity intervention group show greater brain and cognitive benefits compared to a control group. Because these findings suggest that the developing brain is plastic and sensitive to lifestyle factors, we also discuss typical structural and functional brain maturation in children to provide context in which to interpret the effects of physical activity and aerobic fitness on the developing brain. This research is important because children are becoming increasingly sedentary, physically inactive, and unfit. An important goal of this review is to emphasize the importance of physical activity and aerobic fitness for the cognitive and brain health of today's youth. © 2014 The Society for Research in Child Development, Inc.

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).

The bystander effect model of Brenner and Sachs fitted to lung cancer data in 11 cohorts of underground miners, and equivalence of fit of a linear relative risk model with adjustment for attained age and age at exposure

International Nuclear Information System (INIS)

Little, M P

2004-01-01

Bystander effects following exposure to α-particles have been observed in many experimental systems, and imply that linearly extrapolating low dose risks from high dose data might materially underestimate risk. Brenner and Sachs (2002 Int. J. Radiat. Biol. 78 593-604; 2003 Health Phys. 85 103-8) have recently proposed a model of the bystander effect which they use to explain the inverse dose rate effect observed for lung cancer in underground miners exposed to radon daughters. In this paper we fit the model of the bystander effect proposed by Brenner and Sachs to 11 cohorts of underground miners, taking account of the covariance structure of the data and the period of latency between the development of the first pre-malignant cell and clinically overt cancer. We also fitted a simple linear relative risk model, with adjustment for age at exposure and attained age. The methods that we use for fitting both models are different from those used by Brenner and Sachs, in particular taking account of the covariance structure, which they did not, and omitting certain unjustifiable adjustments to the miner data. The fit of the original model of Brenner and Sachs (with 0 y period of latency) is generally poor, although it is much improved by assuming a 5 or 6 y period of latency from the first appearance of a pre-malignant cell to cancer. The fit of this latter model is equivalent to that of a linear relative risk model with adjustment for age at exposure and attained age. In particular, both models are capable of describing the observed inverse dose rate effect in this data set

Fitting measurement models to vocational interest data: are dominance models ideal?

Science.gov (United States)

Tay, Louis; Drasgow, Fritz; Rounds, James; Williams, Bruce A

2009-09-01

In this study, the authors examined the item response process underlying 3 vocational interest inventories: the Occupational Preference Inventory (C.-P. Deng, P. I. Armstrong, & J. Rounds, 2007), the Interest Profiler (J. Rounds, T. Smith, L. Hubert, P. Lewis, & D. Rivkin, 1999; J. Rounds, C. M. Walker, et al., 1999), and the Interest Finder (J. E. Wall & H. E. Baker, 1997; J. E. Wall, L. L. Wise, & H. E. Baker, 1996). Item response theory (IRT) dominance models, such as the 2-parameter and 3-parameter logistic models, assume that item response functions (IRFs) are monotonically increasing as the latent trait increases. In contrast, IRT ideal point models, such as the generalized graded unfolding model, have IRFs that peak where the latent trait matches the item. Ideal point models are expected to fit better because vocational interest inventories ask about typical behavior, as opposed to requiring maximal performance. Results show that across all 3 interest inventories, the ideal point model provided better descriptions of the response process. The importance of specifying the correct item response model for precise measurement is discussed. In particular, scores computed by a dominance model were shown to be sometimes illogical: individuals endorsing mostly realistic or mostly social items were given similar scores, whereas scores based on an ideal point model were sensitive to which type of items respondents endorsed.

Fitted HBT radii versus space-time variances in flow-dominated models

International Nuclear Information System (INIS)

Lisa, Mike; Frodermann, Evan; Heinz, Ulrich

2007-01-01

The inability of otherwise successful dynamical models to reproduce the 'HBT radii' extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the 'RHIC HBT Puzzle'. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source which can be directly computed from the emission function, without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models some of which exhibit significant deviations from simple Gaussian behaviour. By Fourier transforming the emission function we compute the 2-particle correlation function and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and measured HBT radii remain, we show that a more 'apples-to-apples' comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data. (author)

A goodness of fit statistic for the geometric distribution

OpenAIRE

Ferreira, J.A.

2003-01-01

textabstractWe propose a goodness of fit statistic for the geometric distribution and compare it in terms of power, via simulation, with the chi-square statistic. The statistic is based on the Lau-Rao theorem and can be seen as a discrete analogue of the total time on test statistic. The results suggest that the test based on the new statistic is generally superior to the chi-square test.

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

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

Directory of Open Access Journals (Sweden)

Mónica A Silva

Full Text Available 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 <5 km from the corresponding interpolated GPS position. Uncertainty in KF 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.

Phase fluctuations model for EM wave propagation through solar scintillation at superior solar conjunction

Science.gov (United States)

Xu, Guanjun; Song, Zhaohui

2017-04-01

Traveling solar wind disturbances have a significant influence on radio wave characteristics during the superior solar conjunction communication. This paper considers the impact of solar scintillation on phase fluctuations of electromagnetic (EM) wave propagation during the superior solar conjunction. Based on the Geometric Optics approximation, the close-form approximation model for phase fluctuations is developed. Both effects of anisotropic temporal variations function of plasma irregularities and their power spectrum are presented and analyzed numerically. It is found that phase fluctuations rapidly decrease with increasing Sun-Earth-Probe angle and decrease with increasing frequency at the rate of 1/f2. Moreover, the role of various features of the solar wind irregularities and their influence on the EM wave characteristic parameters is studied and discussed. Finally, we study the phase fluctuations of typical cases in order to better understand the impact of phase fluctuations in future deep space communication scenarios during solar conjunction periods.

The FIT Model - Fuel-cycle Integration and Tradeoffs

International Nuclear Information System (INIS)

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

2010-01-01

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 and 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 and 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.

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.

Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes

Science.gov (United States)

Leite, Walter L.; Stapleton, Laura M.

2011-01-01

In this study, the authors compared the likelihood ratio test and fit indexes for detection of misspecifications of growth shape in latent growth models through a simulation study and a graphical analysis. They found that the likelihood ratio test, MFI, and root mean square error of approximation performed best for detecting model misspecification…

Fitting the Fractional Polynomial Model to Non-Gaussian Longitudinal Data

Directory of Open Access Journals (Sweden)

Ji Hoon Ryoo

2017-08-01

Full Text Available As in cross sectional studies, longitudinal studies involve non-Gaussian data such as binomial, Poisson, gamma, and inverse-Gaussian distributions, and multivariate exponential families. A number of statistical tools have thus been developed to deal with non-Gaussian longitudinal data, including analytic techniques to estimate parameters in both fixed and random effects models. However, as yet growth modeling with non-Gaussian data is somewhat limited when considering the transformed expectation of the response via a linear predictor as a functional form of explanatory variables. In this study, we introduce a fractional polynomial model (FPM that can be applied to model non-linear growth with non-Gaussian longitudinal data and demonstrate its use by fitting two empirical binary and count data models. The results clearly show the efficiency and flexibility of the FPM for such applications.

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

Science.gov (United States)

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

2015-07-01

Tanned skin has been associated with perceptions of fitness and social desirability. Portrayal of models in magazines may reflect and perpetuate these perceptions. Limited research has investigated tanning shade gradations of models in men's versus women's fitness and muscle enthusiast magazines. Such findings are relevant in light of increased incidence and prevalence of melanoma in the United States. 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 (spring and summer, 2013) were utilized. Two independent reviewers rated tanning shade gradations of adult Caucasian male and female model images on magazines' covers, advertisements, and feature articles. Shade gradations were assessed using stock photographs of Caucasian models with varying levels of tanned skin on an 8-shade scale. A total of 4,683 images were evaluated. Darkest tanning shades were found among males in muscle enthusiast magazines and lightest among females in women's mainstream fitness magazines. By gender, male model images were 54% more likely to portray a darker tanning shade. In this study, images in men's (vs. women's) fitness and muscle enthusiast magazines portrayed Caucasian models with darker skin shades. Despite these magazines' fitness-related messages, pro-tanning images may promote attitudes and behaviors associated with higher skin cancer risk. To date, this is the first study to explore tanning shades in men's magazines of these genres. Further research is necessary to identify effects of exposure to these images among male readers. © The Author(s) 2014.

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.

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.

Persistent left superior vena cava with absent right superior vena cava: image findings

International Nuclear Information System (INIS)

Araujo Junior, Cyrillo Rodrigues de; Carvalho, Tarcisio Nunes; Fraguas Filho, Sergio Roberto; Costa, Marlos Augusto Bitencourt; Jacob, Beatriz Mahmud; Machado, Marcio Martins; Teixeira, Kim-Ir-Sen Santos; Ximenes, Carlos Alberto

2003-01-01

Persistent left superior vena cava absent right superior vena cava is a rare anomaly, with less than 150 cases reported in the literature. Congenitally persistent left superior vena cava is the most common variant of systemic venous return to the heart, resulting embryologically from failure of the left anterior cardinal vein to become obliterated. Its incidence varies from 0.3% in patients with otherwise normal heart to 4.3% in patients with congenital heart disease. In the majority of the patients, a right superior vena cava is present as well, but rarely the right anterior cardinal vein degenerates resulting in the absence of the normal right superior vena cava. The blood from the right side is carried by the persistent left superior vena cava to the right atrium through the coronary sinus. We report the case of a patient with a persistent left superior vena cava and absence of right superior vena cava identified by chance during a chest radiograph and computed tomography examination for investigation of chronic pulmonary obstructive disease. The patient had no congenital heart disease and the blood from the right side was drained by the persistent left superior vena cava into the right atrium through the coronary sinus. (author)

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DEFF Research Database (Denmark)

Ding, Tao; Li, Cheng; Huang, Can

2018-01-01

–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost......In order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master...... optimality. Numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods....

Self and Superior Assessment.

Science.gov (United States)

1986-06-01

model of the self-evaluation process as it differs from the evaluation process used by superiors. Symbolic Interactionism One view of self assessment is...supplied by the symbolic interactionists (Cooley, 1902; Head, 1934), who state that self perceptions are generated largely from individuals...disagreements remained even immediately after an appraisal interview in which a great deal of feedback was given. Research on the symbolic interactionist

Marginal and internal fit of heat pressed versus CAD/CAM fabricated all-ceramic onlays after exposure to thermo-mechanical fatigue

Science.gov (United States)

Guess, Petra C.; Vagopoulou, Thaleia; Zhang, Yu; Wolkewitz, Martin; Strub, Joerg R.

2015-01-01

Objectives The aim of the study was to evaluate the marginal and internal fit of heat-pressed and CAD/CAM fabricated all-ceramic onlays before and after luting as well as after thermo-mechanical fatigue. Materials and Methods Seventy-two caries-free, extracted human mandibular molars were randomly divided into three groups (n=24/group). All teeth received an onlay preparation with a mesio-occlusal-distal inlay cavity and an occlusal reduction of all cusps. Teeth were restored with heat-pressed IPS-e.max-Press* (IP, *Ivoclar-Vivadent) and Vita-PM9 (VP, Vita-Zahnfabrik) as well as CAD/CAM fabricated IPS-e.max-CAD* (IC, Cerec 3D/InLab/Sirona) all-ceramic materials. After cementation with a dual-polymerizing resin cement (VariolinkII*), all restorations were subjected to mouth-motion fatigue (98N, 1.2 million cycles; 5°C/55°C). Marginal fit discrepancies were examined on epoxy replicas before and after luting as well as after fatigue at 200x magnification. Internal fit was evaluated by multiple sectioning technique. For the statistical analysis, a linear model was fitted with accounting for repeated measurements. Results Adhesive cementation of onlays resulted in significantly increased marginal gap values in all groups, whereas thermo-mechanical fatigue had no effect. Marginal gap values of all test groups were equal after fatigue exposure. Internal discrepancies of CAD/CAM fabricated restorations were significantly higher than both press manufactured onlays. Conclusions Mean marginal gap values of the investigated onlays before and after luting as well as after fatigue were within the clinically acceptable range. Marginal fit was not affected by the investigated heat-press versus CAD/CAM fabrication technique. Press fabrication resulted in a superior internal fit of onlays as compared to the CAD/CAM technique. Clinical Relevance Clinical requirements of 100 μm for marginal fit were fulfilled by the heat-press as well as by the CAD/CAM fabricated all-ceramic onlays

A Data-Driven Method for Selecting Optimal Models Based on Graphical Visualisation of Differences in Sequentially Fitted ROC Model Parameters

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K S Mwitondi

2013-05-01

Full Text Available Differences in modelling techniques and model performance assessments typically impinge on the quality of knowledge extraction from data. We propose an algorithm for determining optimal patterns in data by separately training and testing three decision tree models in the Pima Indians Diabetes and the Bupa Liver Disorders datasets. Model performance is assessed using ROC curves and the Youden Index. Moving differences between sequential fitted parameters are then extracted, and their respective probability density estimations are used to track their variability using an iterative graphical data visualisation technique developed for this purpose. Our results show that the proposed strategy separates the groups more robustly than the plain ROC/Youden approach, eliminates obscurity, and minimizes over-fitting. Further, the algorithm can easily be understood by non-specialists and demonstrates multi-disciplinary compliance.

Fast fitting of non-Gaussian state-space models to animal movement data via Template Model Builder

DEFF Research Database (Denmark)

Albertsen, Christoffer Moesgaard; Whoriskey, Kim; Yurkowski, David

2015-01-01

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...... 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....

Log-normal frailty models fitted as Poisson generalized linear mixed models.

Science.gov (United States)

Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver

2016-12-01

The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Multiple organ definition in CT using a Bayesian approach for 3D model fitting

Science.gov (United States)

Boes, Jennifer L.; Weymouth, Terry E.; Meyer, Charles R.

1995-08-01

Organ definition in computed tomography (CT) is of interest for treatment planning and response monitoring. We present a method for organ definition using a priori information about shape encoded in a set of biometric organ models--specifically for the liver and kidney-- that accurately represents patient population shape information. Each model is generated by averaging surfaces from a learning set of organ shapes previously registered into a standard space defined by a small set of landmarks. The model is placed in a specific patient's data set by identifying these landmarks and using them as the basis for model deformation; this preliminary representation is then iteratively fit to the patient's data based on a Bayesian formulation of the model's priors and CT edge information, yielding a complete organ surface. We demonstrate this technique using a set of fifteen abdominal CT data sets for liver surface definition both before and after the addition of a kidney model to the fitting; we demonstrate the effectiveness of this tool for organ surface definition in this low-contrast domain.

Veia cava superior esquerda anômala com ausência de veia cava superior direita: achados de imagem Persistent left superior vena cava with absent right superior vena cava: image findings

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Cyrillo Rodrigues de Araújo Júnior

2003-10-01

Full Text Available A persistência da veia cava superior esquerda com ausência da veia cava superior direita é uma anomalia rara, com menos de 150 casos descritos na literatura. A não-obliteração e regressão da veia cardinal anterior esquerda durante o desenvolvimento embriológico promove uma variação sistêmica de retorno venoso ao coração, com persistência da veia cava superior esquerda. Sua incidência varia de 0,3% em pacientes sem alterações cardíacas congênitas concomitantes a 4,3% naqueles com cardiopatias. Na maioria das vezes coexiste a veia cava superior direita, porém se houver regressão e degeneração da veia cardinal anterior direita, implicará a sua ausência e a drenagem venosa para o coração será feita pela veia cava superior esquerda ao átrio direito, através do seio coronariano. Mostramos um caso de um paciente submetido a radiografia de tórax e tomografia computadorizada para avaliação de doença pulmonar obstrutiva crônica, tendo como achado a persistência da veia cava superior esquerda com ausência da direita, sem qualquer cardiopatia associada e com a drenagem cardíaca sendo feita, através do seio coronariano, para o átrio direito.Persistent left superior vena cava with absent right superior vena cava is a rare anomaly, with less than 150 cases reported in the literature. Congenitally persistent left superior vena cava is the most common variant of systemic venous return to the heart, resulting embryologically from failure of the left anterior cardinal vein to become obliterated. Its incidence varies from 0.3% in patients with otherwise normal heart to 4.3% in patients with congenital heart disease. In the majority of the patients, a right superior vena cava is present as well, but rarely the right anterior cardinal vein degenerates resulting in the absence of the normal right superior vena cava. The blood from the right side is carried by the persistent left superior vena cava to the right atrium through the

Reconstructed Ancestral Enzymes Impose a Fitness Cost upon Modern Bacteria Despite Exhibiting Favourable Biochemical Properties.

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Hobbs, Joanne K; Prentice, Erica J; Groussin, Mathieu; Arcus, Vickery L

2015-10-01

Ancestral sequence reconstruction has been widely used to study historical enzyme evolution, both from biochemical and cellular perspectives. Two properties of reconstructed ancestral proteins/enzymes are commonly reported--high thermostability and high catalytic activity--compared with their contemporaries. Increased protein stability is associated with lower aggregation rates, higher soluble protein abundance and a greater capacity to evolve, and therefore, these proteins could be considered "superior" to their contemporary counterparts. In this study, we investigate the relationship between the favourable in vitro biochemical properties of reconstructed ancestral enzymes and the organismal fitness they confer in vivo. We have previously reconstructed several ancestors of the enzyme LeuB, which is essential for leucine biosynthesis. Our initial fitness experiments revealed that overexpression of ANC4, a reconstructed LeuB that exhibits high stability and activity, was only able to partially rescue the growth of a ΔleuB strain, and that a strain complemented with this enzyme was outcompeted by strains carrying one of its descendants. When we expanded our study to include five reconstructed LeuBs and one contemporary, we found that neither in vitro protein stability nor the catalytic rate was correlated with fitness. Instead, fitness showed a strong, negative correlation with estimated evolutionary age (based on phylogenetic relationships). Our findings suggest that, for reconstructed ancestral enzymes, superior in vitro properties do not translate into organismal fitness in vivo. The molecular basis of the relationship between fitness and the inferred age of ancestral LeuB enzymes is unknown, but may be related to the reconstruction process. We also hypothesise that the ancestral enzymes may be incompatible with the other, contemporary enzymes of the metabolic network.

The 'fitting problem' in cosmology

International Nuclear Information System (INIS)

Ellis, G.F.R.; Stoeger, W.

1987-01-01

The paper considers the best way to fit an idealised exactly homogeneous and isotropic universe model to a realistic ('lumpy') universe; whether made explicit or not, some such approach of necessity underlies the use of the standard Robertson-Walker models as models of the real universe. Approaches based on averaging, normal coordinates and null data are presented, the latter offering the best opportunity to relate the fitting procedure to data obtainable by astronomical observations. (author)

A fitting LEGACY – modelling Kepler's best stars

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Aarslev Magnus J.

2017-01-01

Full Text Available The LEGACY sample represents the best solar-like stars observed in the Kepler mission[5, 8]. The 66 stars in the sample are all on the main sequence or only slightly more evolved. They each have more than one year's observation data in short cadence, allowing for precise extraction of individual frequencies. Here we present model fits using a modified ASTFIT procedure employing two different near-surface-effect corrections, one by Christensen-Dalsgaard[4] and a newer correction proposed by Ball & Gizon[1]. We then compare the results obtained using the different corrections. We find that using the latter correction yields lower masses and significantly lower χ2 values for a large part of the sample.

Inclusion of the fitness sharing technique in an evolutionary algorithm to analyze the fitness landscape of the genetic code adaptability.

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Santos, José; Monteagudo, Ángel

2017-03-27

The canonical code, although prevailing in complex genomes, is not universal. It was shown the canonical genetic code superior robustness compared to random codes, but it is not clearly determined how it evolved towards its current form. The error minimization theory considers the minimization of point mutation adverse effect as the main selection factor in the evolution of the code. We have used simulated evolution in a computer to search for optimized codes, which helps to obtain information about the optimization level of the canonical code in its evolution. A genetic algorithm searches for efficient codes in a fitness landscape that corresponds with the adaptability of possible hypothetical genetic codes. The lower the effects of errors or mutations in the codon bases of a hypothetical code, the more efficient or optimal is that code. The inclusion of the fitness sharing technique in the evolutionary algorithm allows the extent to which the canonical genetic code is in an area corresponding to a deep local minimum to be easily determined, even in the high dimensional spaces considered. The analyses show that the canonical code is not in a deep local minimum and that the fitness landscape is not a multimodal fitness landscape with deep and separated peaks. Moreover, the canonical code is clearly far away from the areas of higher fitness in the landscape. Given the non-presence of deep local minima in the landscape, although the code could evolve and different forces could shape its structure, the fitness landscape nature considered in the error minimization theory does not explain why the canonical code ended its evolution in a location which is not an area of a localized deep minimum of the huge fitness landscape.

Pictorial Superiority Effect

Science.gov (United States)

Nelson, Douglas L.; And Others

1976-01-01

Pictures generally show superior recognition relative to their verbal labels. This experiment was designed to link this pictorial superiority effect to sensory or meaning codes associated with the two types of symbols. (Editor)

Marginal and internal fit of cobalt-chromium copings fabricated using the conventional and the direct metal laser sintering techniques: A comparative in vitro study

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Sujana Ullattuthodi

2017-01-01

Conclusions: Within the limitations of this in vitro study, it was concluded that the internal fit of conventional copings was superior to that of the DMLS copings. Marginal fit of the copings fabricated by two different techniques had no significant difference.

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...

Development and design of a late-model fitness test instrument based on LabView

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Xie, Ying; Wu, Feiqing

2010-12-01

Undergraduates are pioneers of China's modernization program and undertake the historic mission of rejuvenating our nation in the 21st century, whose physical fitness is vital. A smart fitness test system can well help them understand their fitness and health conditions, thus they can choose more suitable approaches and make practical plans for exercising according to their own situation. following the future trends, a Late-model fitness test Instrument based on LabView has been designed to remedy defects of today's instruments. The system hardware consists of fives types of sensors with their peripheral circuits, an acquisition card of NI USB-6251 and a computer, while the system software, on the basis of LabView, includes modules of user register, data acquisition, data process and display, and data storage. The system, featured by modularization and an open structure, is able to be revised according to actual needs. Tests results have verified the system's stability and reliability.

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.

Fitting N-mixture models to count data with unmodeled heterogeneity: Bias, diagnostics, and alternative approaches

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Duarte, Adam; Adams, Michael J.; Peterson, James T.

2018-01-01

Monitoring animal populations is central to wildlife and fisheries management, and the use of N-mixture models toward these efforts has markedly increased in recent years. Nevertheless, relatively little work has evaluated estimator performance when basic assumptions are violated. Moreover, diagnostics to identify when bias in parameter estimates from N-mixture models is likely is largely unexplored. We simulated count data sets using 837 combinations of detection probability, number of sample units, number of survey occasions, and type and extent of heterogeneity in abundance or detectability. We fit Poisson N-mixture models to these data, quantified the bias associated with each combination, and evaluated if the parametric bootstrap goodness-of-fit (GOF) test can be used to indicate bias in parameter estimates. We also explored if assumption violations can be diagnosed prior to fitting N-mixture models. In doing so, we propose a new model diagnostic, which we term the quasi-coefficient of variation (QCV). N-mixture models performed well when assumptions were met and detection probabilities were moderate (i.e., ≥0.3), and the performance of the estimator improved with increasing survey occasions and sample units. However, the magnitude of bias in estimated mean abundance with even slight amounts of unmodeled heterogeneity was substantial. The parametric bootstrap GOF test did not perform well as a diagnostic for bias in parameter estimates when detectability and sample sizes were low. The results indicate the QCV is useful to diagnose potential bias and that potential bias associated with unidirectional trends in abundance or detectability can be diagnosed using Poisson regression. This study represents the most thorough assessment to date of assumption violations and diagnostics when fitting N-mixture models using the most commonly implemented error distribution. Unbiased estimates of population state variables are needed to properly inform management decision

Decision making on fitness landscapes

Science.gov (United States)

Arthur, R.; Sibani, P.

2017-04-01

We discuss fitness landscapes and how they can be modified to account for co-evolution. We are interested in using the landscape as a way to model rational decision making in a toy economic system. We develop a model very similar to the Tangled Nature Model of Christensen et al. that we call the Tangled Decision Model. This is a natural setting for our discussion of co-evolutionary fitness landscapes. We use a Monte Carlo step to simulate decision making and investigate two different decision making procedures.

Decision Making on Fitness Landscapes

DEFF Research Database (Denmark)

Arthur, Rudy; Sibani, Paolo

2017-01-01

We discuss fitness landscapes and how they can be modified to account for co-evolution. We are interested in using the landscape as a way to model rational decision making in a toy economic system. We develop a model very similar to the Tangled Nature Model of Christensen et. al. that we call...... the Tangled Decision Model. This is a natural setting for our discussion of co-evolutionary fitness landscapes. We use a Monte Carlo step to simulate decision making and investigate two different decision making procedures....

Assessing a moderating effect and the global fit of a PLS model on online trading

Directory of Open Access Journals (Sweden)

Juan J. García-Machado

2017-12-01

Full Text Available This paper proposes a PLS Model for the study of Online Trading. Traditional investing has experienced a revolution due to the rise of e-trading services that enable investors to use Internet conduct secure trading. On the hand, model results show that there is a positive, direct and statistically significant relationship between personal outcome expectations, perceived relative advantage, shared vision and economy-based trust with the quality of knowledge. On the other hand, trading frequency and portfolio performance has also this relationship. After including the investor’s income and financial wealth (IFW as moderating effect, the PLS model was enhanced, and we found that the interaction term is negative and statistically significant, so, higher IFW levels entail a weaker relationship between trading frequency and portfolio performance and vice-versa. Finally, with regard to the goodness of overall model fit measures, they showed that the model is fit for SRMR and dG measures, so it is likely that the model is true.

Keep Using My Health Apps: Discover Users' Perception of Health and Fitness Apps with the UTAUT2 Model.

Science.gov (United States)

Yuan, Shupei; Ma, Wenjuan; Kanthawala, Shaheen; Peng, Wei

2015-09-01

Health and fitness applications (apps) are one of the major app categories in the current mobile app market. Few studies have examined this area from the users' perspective. This study adopted the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) Model to examine the predictors of the users' intention to adopt health and fitness apps. A survey (n=317) was conducted with college-aged smartphone users at a Midwestern university in the United States. Performance expectancy, hedonic motivations, price value, and habit were significant predictors of users' intention of continued usage of health and fitness apps. However, effort expectancy, social influence, and facilitating conditions were not found to predict users' intention of continued usage of health and fitness apps. This study extends the UTATU2 Model to the mobile apps domain and provides health professions, app designers, and marketers with the insights of user experience in terms of continuously using health and fitness apps.

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; Govorkova, Elena A

2015-04-01

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. Influenza B viruses are important human respiratory pathogens contributing to a significant portion

Phylogenetic tree reconstruction accuracy and model fit when proportions of variable sites change across the tree.

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Shavit Grievink, Liat; Penny, David; Hendy, Michael D; Holland, Barbara R

2010-05-01

Commonly used phylogenetic models assume a homogeneous process through time in all parts of the tree. However, it is known that these models can be too simplistic as they do not account for nonhomogeneous lineage-specific properties. In particular, it is now widely recognized that as constraints on sequences evolve, the proportion and positions of variable sites can vary between lineages causing heterotachy. The extent to which this model misspecification affects tree reconstruction is still unknown. Here, we evaluate the effect of changes in the proportions and positions of variable sites on model fit and tree estimation. We consider 5 current models of nucleotide sequence evolution in a Bayesian Markov chain Monte Carlo framework as well as maximum parsimony (MP). We show that for a tree with 4 lineages where 2 nonsister taxa undergo a change in the proportion of variable sites tree reconstruction under the best-fitting model, which is chosen using a relative test, often results in the wrong tree. In this case, we found that an absolute test of model fit is a better predictor of tree estimation accuracy. We also found further evidence that MP is not immune to heterotachy. In addition, we show that increased sampling of taxa that have undergone a change in proportion and positions of variable sites is critical for accurate tree reconstruction.

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.

UROX 2.0: an interactive tool for fitting atomic models into electron-microscopy reconstructions

International Nuclear Information System (INIS)

Siebert, Xavier; Navaza, Jorge

2009-01-01

UROX is software designed for the interactive fitting of atomic models into electron-microscopy reconstructions. The main features of the software are presented, along with a few examples. Electron microscopy of a macromolecular structure can lead to three-dimensional reconstructions with resolutions that are typically in the 30–10 Å range and sometimes even beyond 10 Å. Fitting atomic models of the individual components of the macromolecular structure (e.g. those obtained by X-ray crystallography or nuclear magnetic resonance) into an electron-microscopy map allows the interpretation of the latter at near-atomic resolution, providing insight into the interactions between the components. Graphical software is presented that was designed for the interactive fitting and refinement of atomic models into electron-microscopy reconstructions. Several characteristics enable it to be applied over a wide range of cases and resolutions. Firstly, calculations are performed in reciprocal space, which results in fast algorithms. This allows the entire reconstruction (or at least a sizeable portion of it) to be used by taking into account the symmetry of the reconstruction both in the calculations and in the graphical display. Secondly, atomic models can be placed graphically in the map while the correlation between the model-based electron density and the electron-microscopy reconstruction is computed and displayed in real time. The positions and orientations of the models are refined by a least-squares minimization. Thirdly, normal-mode calculations can be used to simulate conformational changes between the atomic model of an individual component and its corresponding density within a macromolecular complex determined by electron microscopy. These features are illustrated using three practical cases with different symmetries and resolutions. The software, together with examples and user instructions, is available free of charge at http://mem.ibs.fr/UROX/

Fitness, Sleep-Disordered Breathing, Symptoms of Depression, and Cognition in Inactive Overweight Children: Mediation Models.

Science.gov (United States)

Stojek, Monika M K; Montoya, Amanda K; Drescher, Christopher F; Newberry, Andrew; Sultan, Zain; Williams, Celestine F; Pollock, Norman K; Davis, Catherine L

We used mediation models to examine the mechanisms underlying the relationships among physical fitness, sleep-disordered breathing (SDB), symptoms of depression, and cognitive functioning. We conducted a cross-sectional secondary analysis of the cohorts involved in the 2003-2006 project PLAY (a trial of the effects of aerobic exercise on health and cognition) and the 2008-2011 SMART study (a trial of the effects of exercise on cognition). A total of 397 inactive overweight children aged 7-11 received a fitness test, standardized cognitive test (Cognitive Assessment System, yielding Planning, Attention, Simultaneous, Successive, and Full Scale scores), and depression questionnaire. Parents completed a Pediatric Sleep Questionnaire. We used bootstrapped mediation analyses to test whether SDB mediated the relationship between fitness and depression and whether SDB and depression mediated the relationship between fitness and cognition. Fitness was negatively associated with depression ( B = -0.041; 95% CI, -0.06 to -0.02) and SDB ( B = -0.005; 95% CI, -0.01 to -0.001). SDB was positively associated with depression ( B = 0.99; 95% CI, 0.32 to 1.67) after controlling for fitness. The relationship between fitness and depression was mediated by SDB (indirect effect = -0.005; 95% CI, -0.01 to -0.0004). The relationship between fitness and the attention component of cognition was independently mediated by SDB (indirect effect = 0.058; 95% CI, 0.004 to 0.13) and depression (indirect effect = -0.071; 95% CI, -0.01 to -0.17). SDB mediates the relationship between fitness and depression, and SDB and depression separately mediate the relationship between fitness and the attention component of cognition.

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.

Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle.

Science.gov (United States)

Ayres, D R; Pereira, R J; Boligon, A A; Silva, F F; Schenkel, F S; Roso, V M; Albuquerque, L G

2013-12-01

Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals. © 2013 Blackwell Verlag GmbH.

Comparison of actual oxygen delivery kinetics to those predicted by mathematical modeling following stage 1 palliation just prior to superior cavopulmonary anastomosis.

Science.gov (United States)

Yuki, Koichi; DiNardo, James A

2015-02-01

Optimizing systemic oxygen delivery (DO2) and hemodynamics in children with hypoplastic left heart syndrome (HLHS) is a clinical challenge. Mathematical modeling of the HLHS circulation has been used to determine the relationship between oxygen kinetic parameters and DO2 and to determine how DO2 might be optimized. The model demonstrates that neither arterial oxygen saturation (SaO2) nor mixed venous oxygen saturation (SvO2) alone accurately predicts DO2. Oxygen delivery kinetics predicted by previously described mathematical modeling were compared with actual patients' hemodynamic data. We sought to determine which patient derived parameters correlated best with DO2. Patients with HLHS who underwent cardiac catheterization prior to surgery to create a superior cavopulmonary anastomosis from 2007 to 2011 were identified. Hemodynamic data obtained were compared with the data derived from the mathematical model. Correlations between SaO2, SvO2, SaO2-SvO2, SaO2/(SaO2-SvO2), pulmonary-to-systemic blood flow ratio (Qp/Qs), and DO2 were evaluated using both linear and nonlinear analyses, and R(2) was calculated. Patients' data fit most aspects of the mathematical model. DO2 had the best correlation with SaO2/(SaO2-SvO2; R(2) = 0.8755) followed by SaO2 -SvO2 (R(2) = 0.8063), while SaO2 or SvO2 alone did not demonstrate a significant correlation as predicated by the mathematical model (R(2) = 0.09564 and 0.4831, respectively). SaO2/(SaO2 -SvO2) would be useful clinically to track changes in DO2 that occur with changes in patient condition or with interventions. © 2014 John Wiley & Sons Ltd.

QUANTIFYING THE SHORT LIFETIME WITH TCSPC-FLIM: FIRST MOMENT VERSUS FITTING METHODS

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LINGLING XU

2013-10-01

Full Text Available Combing the time-correlated single photon counting (TCSPC with fluorescence lifetime imaging microscopy (FLIM provides promising opportunities in revealing important information on the microenvironment of cells and tissues, but the applications are thus far mainly limited by the accuracy and precision of the TCSPC-FLIM technique. Here we present a comprehensive investigation on the performance of two data analysis methods, the first moment (M1 method and the conventional least squares (Fitting method, in quantifying fluorescence lifetime. We found that the M1 method is more superior than the Fitting method when the lifetime is short (70 ~ 400 ps or the signal intensity is weak (<103 photons.

Testing the validity of stock-recruitment curve fits

International Nuclear Information System (INIS)

Christensen, S.W.; Goodyear, C.P.

1988-01-01

The utilities relied heavily on the Ricker stock-recruitment model as the basis for quantifying biological compensation in the Hudson River power case. They presented many fits of the Ricker model to data derived from striped bass catch and effort records compiled by the National Marine Fisheries Service. Based on this curve-fitting exercise, a value of 4 was chosen for the parameter alpha in the Ricker model, and this value was used to derive the utilities' estimates of the long-term impact of power plants on striped bass populations. A technique was developed and applied to address a single fundamental question: if the Ricker model were applicable to the Hudson River striped bass population, could the estimates of alpha from the curve-fitting exercise be considered reliable. The technique involved constructing a simulation model that incorporated the essential biological features of the population and simulated the characteristics of the available actual catch-per-unit-effort data through time. The ability or failure to retrieve the known parameter values underlying the simulation model via the curve-fitting exercise was a direct test of the reliability of the results of fitting stock-recruitment curves to the real data. The results demonstrated that estimates of alpha from the curve-fitting exercise were not reliable. The simulation-modeling technique provides an effective way to identify whether or not particular data are appropriate for use in fitting such models. 39 refs., 2 figs., 3 tabs

Describing the Process of Adopting Nutrition and Fitness Apps: Behavior Stage Model Approach.

Science.gov (United States)

König, Laura M; Sproesser, Gudrun; Schupp, Harald T; Renner, Britta

2018-03-13

Although mobile technologies such as smartphone apps are promising means for motivating people to adopt a healthier lifestyle (mHealth apps), previous studies have shown low adoption and continued use rates. Developing the means to address this issue requires further understanding of mHealth app nonusers and adoption processes. This study utilized a stage model approach based on the Precaution Adoption Process Model (PAPM), which proposes that people pass through qualitatively different motivational stages when adopting a behavior. To establish a better understanding of between-stage transitions during app adoption, this study aimed to investigate the adoption process of nutrition and fitness app usage, and the sociodemographic and behavioral characteristics and decision-making style preferences of people at different adoption stages. Participants (N=1236) were recruited onsite within the cohort study Konstanz Life Study. Use of mobile devices and nutrition and fitness apps, 5 behavior adoption stages of using nutrition and fitness apps, preference for intuition and deliberation in eating decision-making (E-PID), healthy eating style, sociodemographic variables, and body mass index (BMI) were assessed. Analysis of the 5 behavior adoption stages showed that stage 1 ("unengaged") was the most prevalent motivational stage for both nutrition and fitness app use, with half of the participants stating that they had never thought about using a nutrition app (52.41%, 533/1017), whereas less than one-third stated they had never thought about using a fitness app (29.25%, 301/1029). "Unengaged" nonusers (stage 1) showed a higher preference for an intuitive decision-making style when making eating decisions, whereas those who were already "acting" (stage 4) showed a greater preference for a deliberative decision-making style (F 4,1012 =21.83, Pdigital interventions. This study highlights that new user groups might be better reached by apps designed to address a more intuitive

Modelling job support, job fit, job role and job satisfaction for school of nursing sessional academic staff.

Science.gov (United States)

Cowin, Leanne S; Moroney, Robyn

2018-01-01

Sessional academic staff are an important part of nursing education. Increases in casualisation of the academic workforce continue and satisfaction with the job role is an important bench mark for quality curricula delivery and influences recruitment and retention. This study examined relations between four job constructs - organisation fit, organisation support, staff role and job satisfaction for Sessional Academic Staff at a School of Nursing by creating two path analysis models. A cross-sectional correlational survey design was utilised. Participants who were currently working as sessional or casual teaching staff members were invited to complete an online anonymous survey. The data represents a convenience sample of Sessional Academic Staff in 2016 at a large school of Nursing and Midwifery in Australia. After psychometric evaluation of each of the job construct measures in this study we utilised Structural Equation Modelling to better understand the relations of the variables. The measures used in this study were found to be both valid and reliable for this sample. Job support and job fit are positively linked to job satisfaction. Although the hypothesised model did not meet model fit standards, a new 'nested' model made substantive sense. This small study explored a new scale for measuring academic job role, and demonstrated how it promotes the constructs of job fit and job supports. All four job constructs are important in providing job satisfaction - an outcome that in turn supports staffing stability, retention, and motivation.

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.

Permutation tests for goodness-of-fit testing of mathematical models to experimental data.

Science.gov (United States)

Fişek, M Hamit; Barlas, Zeynep

2013-03-01

This paper presents statistical procedures for improving the goodness-of-fit testing of theoretical models to data obtained from laboratory experiments. We use an experimental study in the expectation states research tradition which has been carried out in the "standardized experimental situation" associated with the program to illustrate the application of our procedures. We briefly review the expectation states research program and the fundamentals of resampling statistics as we develop our procedures in the resampling context. The first procedure we develop is a modification of the chi-square test which has been the primary statistical tool for assessing goodness of fit in the EST research program, but has problems associated with its use. We discuss these problems and suggest a procedure to overcome them. The second procedure we present, the "Average Absolute Deviation" test, is a new test and is proposed as an alternative to the chi square test, as being simpler and more informative. The third and fourth procedures are permutation versions of Jonckheere's test for ordered alternatives, and Kendall's tau(b), a rank order correlation coefficient. The fifth procedure is a new rank order goodness-of-fit test, which we call the "Deviation from Ideal Ranking" index, which we believe may be more useful than other rank order tests for assessing goodness-of-fit of models to experimental data. The application of these procedures to the sample data is illustrated in detail. We then present another laboratory study from an experimental paradigm different from the expectation states paradigm - the "network exchange" paradigm, and describe how our procedures may be applied to this data set. Copyright © 2012 Elsevier Inc. All rights reserved.

Sequential fitting-and-separating reflectance components for analytical bidirectional reflectance distribution function estimation.

Science.gov (United States)

Lee, Yu; Yu, Chanki; Lee, Sang Wook

2018-01-10

We present a sequential fitting-and-separating algorithm for surface reflectance components that separates individual dominant reflectance components and simultaneously estimates the corresponding bidirectional reflectance distribution function (BRDF) parameters from the separated reflectance values. We tackle the estimation of a Lafortune BRDF model, which combines a nonLambertian diffuse reflection and multiple specular reflectance components with a different specular lobe. Our proposed method infers the appropriate number of BRDF lobes and their parameters by separating and estimating each of the reflectance components using an interval analysis-based branch-and-bound method in conjunction with iterative K-ordered scale estimation. The focus of this paper is the estimation of the Lafortune BRDF model. Nevertheless, our proposed method can be applied to other analytical BRDF models such as the Cook-Torrance and Ward models. Experiments were carried out to validate the proposed method using isotropic materials from the Mitsubishi Electric Research Laboratories-Massachusetts Institute of Technology (MERL-MIT) BRDF database, and the results show that our method is superior to a conventional minimization algorithm.

THE HERSCHEL ORION PROTOSTAR SURVEY: SPECTRAL ENERGY DISTRIBUTIONS AND FITS USING A GRID OF PROTOSTELLAR MODELS

Energy Technology Data Exchange (ETDEWEB)

Furlan, E. [Infrared Processing and Analysis Center, California Institute of Technology, 770 S. Wilson Ave., Pasadena, CA 91125 (United States); Fischer, W. J. [Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771 (United States); Ali, B. [Space Science Institute, 4750 Walnut Street, Boulder, CO 80301 (United States); Stutz, A. M. [Max-Planck-Institut für Astronomie, Königstuhl 17, D-69117 Heidelberg (Germany); Stanke, T. [ESO, Karl-Schwarzschild-Strasse 2, D-85748 Garching bei München (Germany); Tobin, J. J. [National Radio Astronomy Observatory, Charlottesville, VA 22903 (United States); Megeath, S. T.; Booker, J. [Ritter Astrophysical Research Center, Department of Physics and Astronomy, University of Toledo, 2801 W. Bancroft Street, Toledo, OH 43606 (United States); Osorio, M. [Instituto de Astrofísica de Andalucía, CSIC, Camino Bajo de Huétor 50, E-18008 Granada (Spain); Hartmann, L.; Calvet, N. [Department of Astronomy, University of Michigan, 500 Church Street, Ann Arbor, MI 48109 (United States); Poteet, C. A. [New York Center for Astrobiology, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, NY 12180 (United States); Manoj, P. [Department of Astronomy and Astrophysics, Tata Institute of Fundamental Research, Homi Bhabha Road, Colaba, Mumbai 400005 (India); Watson, D. M. [Department of Physics and Astronomy, University of Rochester, Rochester, NY 14627 (United States); Allen, L., E-mail: furlan@ipac.caltech.edu [National Optical Astronomy Observatory, 950 N. Cherry Avenue, Tucson, AZ 85719 (United States)

2016-05-01

We present key results from the Herschel Orion Protostar Survey: 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 submillimeter photometry from APEX, our SEDs cover 1.2–870 μ m and sample the peak of the protostellar envelope emission at ∼100 μ 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 30,400 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 constraints on protostellar envelope properties. We find that most protostars, and in particular the flat-spectrum sources, are well fit. The median envelope density and median inclination angle decrease from Class 0 to Class I to flat-spectrum protostars, despite the broad range in best-fit parameters in each of the three categories. We also discuss degeneracies in our model parameters. Our results confirm that the different protostellar classes generally correspond to an evolutionary sequence with a decreasing envelope infall rate, but the inclination angle also plays a role in the appearance, and thus interpretation, of the SEDs.

Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy

Science.gov (United States)

Nabizadeh, Nooshin; John, Nigel

2014-03-01

Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

Anticipating mismatches of HIT investments: Developing a viability-fit model for e-health services.

Science.gov (United States)

Mettler, Tobias

2016-01-01

Albeit massive investments in the recent years, the impact of health information technology (HIT) has been controversial and strongly disputed by both research and practice. While many studies are concerned with the development of new or the refinement of existing measurement models for assessing the impact of HIT adoption (ex post), this study presents an initial attempt to better understand the factors affecting viability and fit of HIT and thereby underscores the importance of also having instruments for managing expectations (ex ante). We extend prior research by undertaking a more granular investigation into the theoretical assumptions of viability and fit constructs. In doing so, we use a mixed-methods approach, conducting qualitative focus group discussions and a quantitative field study to improve and validate a viability-fit measurement instrument. Our findings suggest two issues for research and practice. First, the results indicate that different stakeholders perceive HIT viability and fit of the same e-health services very unequally. Second, the analysis also demonstrates that there can be a great discrepancy between the organizational viability and individual fit of a particular e-health service. The findings of this study have a number of important implications such as for health policy making, HIT portfolios, and stakeholder communication. Copyright © 2015. Published by Elsevier Ireland Ltd.

Magnetic resonance imaging evaluation of meniscoid superior labrum: normal variant or superior labral tear

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Marcelo Novelino Simão

Full Text Available Abstract Objective: The objective of this study was to determine the incidence of a "meniscoid" superior labrum. Materials and Methods: This was a retrospective analysis of 582 magnetic resonance imaging examinations of shoulders. Of those 582 examinations, 110 were excluded, for a variety of reasons, and the final analysis therefore included 472 cases. Consensus readings were performed by three musculoskeletal radiologists using specific criteria to diagnose meniscoid labra. Results: A meniscoid superior labrum was identified in 48 (10.2% of the 472 cases evaluated. Arthroscopic proof was available in 21 cases (43.8%. In 10 (47.6% of those 21 cases, the operative report did not include the mention a superior labral tear, thus suggesting the presence of a meniscoid labrum. In only one of those cases were there specific comments about a mobile superior labrum (i.e., meniscoid labrum. In the remaining 11 (52.4%, surgical correlation demonstrated superior labral tears. Conclusion: A meniscoid superior labrum is not an infrequent finding. Depending upon assumptions and the requirement of surgical proof, the prevalence of a meniscoid superior labrum in this study was between 2.1% (surgically proven and 4.8% (projected. However, superior labral tears are just as common and are often confused with meniscoid labra.

Amino acids intake and physical fitness among adolescents.

Science.gov (United States)

Gracia-Marco, Luis; Bel-Serrat, Silvia; Cuenca-Garcia, Magdalena; Gonzalez-Gross, Marcela; Pedrero-Chamizo, Raquel; Manios, Yannis; Marcos, Ascensión; Molnar, Denes; Widhalm, Kurt; Polito, Angela; Vanhelst, Jeremy; Hagströmer, Maria; Sjöström, Michael; Kafatos, Anthony; de Henauw, Stefaan; Gutierrez, Ángel; Castillo, Manuel J; Moreno, Luis A

2017-06-01

The aim was to investigate whether there was an association between amino acid (AA) intake and physical fitness and if so, to assess whether this association was independent of carbohydrates intake. European adolescents (n = 1481, 12.5-17.5 years) were measured. Intake was assessed via two non-consecutive 24-h dietary recalls. Lower and upper limbs muscular fitness was assessed by standing long jump and handgrip strength tests, respectively. Cardiorespiratory fitness was assessed by the 20-m shuttle run test. Physical activity was objectively measured. Socioeconomic status was obtained via questionnaires. Lower limbs muscular fitness seems to be positively associated with tryptophan, histidine and methionine intake in boys, regardless of centre, age, socioeconomic status, physical activity and total energy intake (model 1). However, these associations disappeared once carbohydrates intake was controlled for (model 2). In girls, only proline intake seems to be positively associated with lower limbs muscular fitness (model 2) while cardiorespiratory fitness seems to be positively associated with leucine (model 1) and proline intake (models 1 and 2). None of the observed significant associations remained significant once multiple testing was controlled for. In conclusion, we failed to detect any associations between any of the evaluated AAs and physical fitness after taking into account the effect of multiple testing.

Fitting the two-compartment model in DCE-MRI by linear inversion.

Science.gov (United States)

Flouri, Dimitra; Lesnic, Daniel; Sourbron, Steven P

2016-09-01

Model fitting of dynamic contrast-enhanced-magnetic resonance imaging-MRI data with nonlinear least squares (NLLS) methods is slow and may be biased by the choice of initial values. The aim of this study was to develop and evaluate a linear least squares (LLS) method to fit the two-compartment exchange and -filtration models. A second-order linear differential equation for the measured concentrations was derived where model parameters act as coefficients. Simulations of normal and pathological data were performed to determine calculation time, accuracy and precision under different noise levels and temporal resolutions. Performance of the LLS was evaluated by comparison against the NLLS. The LLS method is about 200 times faster, which reduces the calculation times for a 256 × 256 MR slice from 9 min to 3 s. For ideal data with low noise and high temporal resolution the LLS and NLLS were equally accurate and precise. The LLS was more accurate and precise than the NLLS at low temporal resolution, but less accurate at high noise levels. The data show that the LLS leads to a significant reduction in calculation times, and more reliable results at low noise levels. At higher noise levels the LLS becomes exceedingly inaccurate compared to the NLLS, but this may be improved using a suitable weighting strategy. Magn Reson Med 76:998-1006, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Robustly Fitting and Forecasting Dynamical Data With Electromagnetically Coupled Artificial Neural Network: A Data Compression Method.

Science.gov (United States)

Wang, Ziyin; Liu, Mandan; Cheng, Yicheng; Wang, Rubin

2017-06-01

In this paper, a dynamical recurrent artificial neural network (ANN) is proposed and studied. Inspired from a recent research in neuroscience, we introduced nonsynaptic coupling to form a dynamical component of the network. We mathematically proved that, with adequate neurons provided, this dynamical ANN model is capable of approximating any continuous dynamic system with an arbitrarily small error in a limited time interval. Its extreme concise Jacobian matrix makes the local stability easy to control. We designed this ANN for fitting and forecasting dynamic data and obtained satisfied results in simulation. The fitting performance is also compared with those of both the classic dynamic ANN and the state-of-the-art models. Sufficient trials and the statistical results indicated that our model is superior to those have been compared. Moreover, we proposed a robust approximation problem, which asking the ANN to approximate a cluster of input-output data pairs in large ranges and to forecast the output of the system under previously unseen input. Our model and learning scheme proposed in this paper have successfully solved this problem, and through this, the approximation becomes much more robust and adaptive to noise, perturbation, and low-order harmonic wave. This approach is actually an efficient method for compressing massive external data of a dynamic system into the weight of the ANN.

The regression-calibration method for fitting generalized linear models with additive measurement error

OpenAIRE

James W. Hardin; Henrik Schmeidiche; Raymond J. Carroll

2003-01-01

This paper discusses and illustrates the method of regression calibration. This is a straightforward technique for fitting models with additive measurement error. We present this discussion in terms of generalized linear models (GLMs) following the notation defined in Hardin and Carroll (2003). Discussion will include specified measurement error, measurement error estimated by replicate error-prone proxies, and measurement error estimated by instrumental variables. The discussion focuses on s...

Analyzing fit in CSR strategy research in state-owned enterprises: Indonesia context

Energy Technology Data Exchange (ETDEWEB)

Saracoglu, B.O.

2016-07-01

Purpose: We attempted to empirically examine the fitness level of enterprises CSR strategy and its context with contingency and configuration approach. Furthermore, we used 213 CSR managers of state-owned enterprises in Indonesia as samples Design/methodology/approach: We used the purposive sampling technique to examine the data, also the contingency and configuration approach are measured with regression Euclidean distance. Findings: The result of the configuration and contingency approach has shown fit between CSR strategy and elements of contingency such as socialization tactic and time orientation. This condition also emerges on proactive CSR strategy and reactive CSR strategy, However, there are limitations of this study: an existence of the influence of the situation and condition when this study takes time; there is a concern on the result of not generalizing population, also the organizational performance only considered the size of organizational performance from non financial measure. Research limitation: (a) respondents’ answers are highly influenced by situation and condition when the study takes time. Although validity and reliability tests has shown the right outcome, there is still a possibility of a bias, (b) state-owned enterprises in Indonesia are represented by CSR manager samples with purposive technique so there is a concern on the result for not generalizing population, (c) this research only used primary data through questionnaires. It would be better to combine both primary and secondary data for future researches, (d) organizational performance only considered the size of organizational performance from non financial measure. Originality/value: There is a methodological contribution in testing the fit of a relationship, both contingency and configuration are superior in terms of research method which used Euclidean distance, and used multivariate fit and bivariate fit linear regression. This research model used systematic approach by

Analyzing fit in CSR strategy research in state-owned entreprises: Indonesia context

Directory of Open Access Journals (Sweden)

Muafi Muafi

2016-03-01

Full Text Available Purpose: We attempted to empirically examine the fitness level of enterprises CSR strategy and its context with contingency and configuration approach. Furthermore, we used 213 CSR managers of state-owned enterprises in Indonesia as samples Design/methodology/approach: We used the purposive sampling technique to examine the data, also the contingency and configuration approach are measured with regression Euclidean distance. Findings: The result of the configuration and contingency approach has shown fit between CSR strategy and elements of contingency such as socialization tactic and time orientation. This condition also emerges on proactive CSR strategy and reactive CSR strategy, However, there are limitations of this study: an existence of the influence of the situation and condition when this study takes time; there is a concern on the result of not generalizing population, also the organizational performance only considered the size of organizational performance from non financial measure. Research limitation: (a respondents’ answers are highly influenced by situation and condition when the study takes time. Although validity and reliability tests has shown the right outcome, there is still a possibility of a bias, (b state-owned companies in Indonesia are represented by CSR manager samples or PKBL with purposive technique so there is a concern on the result for not generalizing population, (c this research only used primary data through questionnaires. It would be better to combine both primary and secondary data for future researches, (d  organizational performance only considered the size of organizational performance from non financial measure. Originality/value: There is a methodological contribution in testing the fit of a relationship, both contingency and configuration are superior in terms of research method which used Euclidean distance, and used multivariate fit and bivariate fit linear regression. This research model used

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

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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.

FIREFLY (Fitting IteRativEly For Likelihood analYsis): a full spectral fitting code

Science.gov (United States)

Wilkinson, David M.; Maraston, Claudia; Goddard, Daniel; Thomas, Daniel; Parikh, Taniya

2017-12-01

We present a new spectral fitting code, FIREFLY, for deriving the stellar population properties of stellar systems. FIREFLY is a chi-squared minimization fitting code that fits combinations of single-burst stellar population models to spectroscopic data, following an iterative best-fitting process controlled by the Bayesian information criterion. No priors are applied, rather all solutions within a statistical cut are retained with their weight. Moreover, no additive or multiplicative polynomials are employed to adjust the spectral shape. This fitting freedom is envisaged in order to map out the effect of intrinsic spectral energy distribution degeneracies, such as age, metallicity, dust reddening on galaxy properties, and to quantify the effect of varying input model components on such properties. Dust attenuation is included using a new procedure, which was tested on Integral Field Spectroscopic data in a previous paper. The fitting method is extensively tested with a comprehensive suite of mock galaxies, real galaxies from the Sloan Digital Sky Survey and Milky Way globular clusters. We also assess the robustness of the derived properties as a function of signal-to-noise ratio (S/N) and adopted wavelength range. We show that FIREFLY is able to recover age, metallicity, stellar mass, and even the star formation history remarkably well down to an S/N ∼ 5, for moderately dusty systems. Code and results are publicly available.1

FITTING OF PARAMETRIC BUILDING MODELS TO OBLIQUE AERIAL IMAGES

Directory of Open Access Journals (Sweden)

U. S. Panday

2012-09-01

Full Text Available In literature and in photogrammetric workstations many approaches and systems to automatically reconstruct buildings from remote sensing data are described and available. Those building models are being used for instance in city modeling or in cadastre context. If a roof overhang is present, the building walls cannot be estimated correctly from nadir-view aerial images or airborne laser scanning (ALS data. This leads to inconsistent building outlines, which has a negative influence on visual impression, but more seriously also represents a wrong legal boundary in the cadaster. Oblique aerial images as opposed to nadir-view images reveal greater detail, enabling to see different views of an object taken from different directions. Building walls are visible from oblique images directly and those images are used for automated roof overhang estimation in this research. A fitting algorithm is employed to find roof parameters of simple buildings. It uses a least squares algorithm to fit projected wire frames to their corresponding edge lines extracted from the images. Self-occlusion is detected based on intersection result of viewing ray and the planes formed by the building whereas occlusion from other objects is detected using an ALS point cloud. Overhang and ground height are obtained by sweeping vertical and horizontal planes respectively. Experimental results are verified with high resolution ortho-images, field survey, and ALS data. Planimetric accuracy of 1cm mean and 5cm standard deviation was obtained, while buildings' orientation were accurate to mean of 0.23° and standard deviation of 0.96° with ortho-image. Overhang parameters were aligned to approximately 10cm with field survey. The ground and roof heights were accurate to mean of – 9cm and 8cm with standard deviations of 16cm and 8cm with ALS respectively. The developed approach reconstructs 3D building models well in cases of sufficient texture. More images should be acquired for

Realization of computer-controlled CAMAC model through the technology of virtual instrument

International Nuclear Information System (INIS)

Le Yi; Li Cheng; Liao Juanjuan; Zhou Xin

1997-01-01

The author is to introduce virtual instrument system and basic features of its typical software development platform, and show this system's superiority and fitness to physical experiments by the example of the CAMAC model ADC2249A, which is often used in nuclear physics experiments

Detection of superior genotype of fatty acid synthase in Korean native cattle by an environment-adjusted statistical model

Directory of Open Access Journals (Sweden)

Jea-Young Lee

2017-06-01

Full Text Available Objective This study examines the genetic factors influencing the phenotypes (four economic traits:oleic acid [C18:1], monounsaturated fatty acids, carcass weight, and marbling score of Hanwoo. Methods To enhance the accuracy of the genetic analysis, the study proposes a new statistical model that excludes environmental factors. A statistically adjusted, analysis of covariance model of environmental and genetic factors was developed, and estimated environmental effects (covariate effects of age and effects of calving farms were excluded from the model. Results The accuracy was compared before and after adjustment. The accuracy of the best single nucleotide polymorphism (SNP in C18:1 increased from 60.16% to 74.26%, and that of the two-factor interaction increased from 58.69% to 87.19%. Also, superior SNPs and SNP interactions were identified using the multifactor dimensionality reduction method in Table 1 to 4. Finally, high- and low-risk genotypes were compared based on their mean scores for each trait. Conclusion The proposed method significantly improved the analysis accuracy and identified superior gene-gene interactions and genotypes for each of the four economic traits of Hanwoo.

Fitting the Probability Distribution Functions to Model Particulate Matter Concentrations

International Nuclear Information System (INIS)

El-Shanshoury, Gh.I.

2017-01-01

The main objective of this study is to identify the best probability distribution and the plotting position formula for modeling the concentrations of Total Suspended Particles (TSP) as well as the Particulate Matter with an aerodynamic diameter<10 μm (PM 10 ). The best distribution provides the estimated probabilities that exceed the threshold limit given by the Egyptian Air Quality Limit value (EAQLV) as well the number of exceedance days is estimated. The standard limits of the EAQLV for TSP and PM 10 concentrations are 24-h average of 230 μg/m 3 and 70 μg/m 3 , respectively. Five frequency distribution functions with seven formula of plotting positions (empirical cumulative distribution functions) are compared to fit the average of daily TSP and PM 10 concentrations in year 2014 for Ain Sokhna city. The Quantile-Quantile plot (Q-Q plot) is used as a method for assessing how closely a data set fits a particular distribution. A proper probability distribution that represents the TSP and PM 10 has been chosen based on the statistical performance indicator values. The results show that Hosking and Wallis plotting position combined with Frechet distribution gave the highest fit for TSP and PM 10 concentrations. Burr distribution with the same plotting position follows Frechet distribution. The exceedance probability and days over the EAQLV are predicted using Frechet distribution. In 2014, the exceedance probability and days for TSP concentrations are 0.052 and 19 days, respectively. Furthermore, the PM 10 concentration is found to exceed the threshold limit by 174 days

Using geometry to improve model fitting and experiment design for glacial isostasy

Science.gov (United States)

Kachuck, S. B.; Cathles, L. M.

2017-12-01

As scientists we routinely deal with models, which are geometric objects at their core - the manifestation of a set of parameters as predictions for comparison with observations. When the number of observations exceeds the number of parameters, the model is a hypersurface (the model manifold) in the space of all possible predictions. The object of parameter fitting is to find the parameters corresponding to the point on the model manifold as close to the vector of observations as possible. But the geometry of the model manifold can make this difficult. By curving, ending abruptly (where, for instance, parameters go to zero or infinity), and by stretching and compressing the parameters together in unexpected directions, it can be difficult to design algorithms that efficiently adjust the parameters. Even at the optimal point on the model manifold, parameters might not be individually resolved well enough to be applied to new contexts. In our context of glacial isostatic adjustment, models of sparse surface observations have a broad spread of sensitivity to mixtures of the earth's viscous structure and the surface distribution of ice over the last glacial cycle. This impedes precise statements about crucial geophysical processes, such as the planet's thermal history or the climates that controlled the ice age. We employ geometric methods developed in the field of systems biology to improve the efficiency of fitting (geodesic accelerated Levenberg-Marquardt) and to identify the maximally informative sources of additional data to make better predictions of sea levels and ice configurations (optimal experiment design). We demonstrate this in particular in reconstructions of the Barents Sea Ice Sheet, where we show that only certain kinds of data from the central Barents have the power to distinguish between proposed models.

vFitness: a web-based computing tool for improving estimation of in vitro HIV-1 fitness experiments

Directory of Open Access Journals (Sweden)

Demeter Lisa

2010-05-01

Full Text Available Abstract Background The replication rate (or fitness between viral variants has been investigated in vivo and in vitro for human immunodeficiency virus (HIV. HIV fitness plays an important role in the development and persistence of drug resistance. The accurate estimation of viral fitness relies on complicated computations based on statistical methods. This calls for tools that are easy to access and intuitive to use for various experiments of viral fitness. Results Based on a mathematical model and several statistical methods (least-squares approach and measurement error models, a Web-based computing tool has been developed for improving estimation of virus fitness in growth competition assays of human immunodeficiency virus type 1 (HIV-1. Conclusions Unlike the two-point calculation used in previous studies, the estimation here uses linear regression methods with all observed data in the competition experiment to more accurately estimate relative viral fitness parameters. The dilution factor is introduced for making the computational tool more flexible to accommodate various experimental conditions. This Web-based tool is implemented in C# language with Microsoft ASP.NET, and is publicly available on the Web at http://bis.urmc.rochester.edu/vFitness/.

Fitted Hanbury-Brown Twiss radii versus space-time variances in flow-dominated models

Science.gov (United States)

Frodermann, Evan; Heinz, Ulrich; Lisa, Michael Annan

2006-04-01

The inability of otherwise successful dynamical models to reproduce the Hanbury-Brown Twiss (HBT) radii extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the RHIC HBT Puzzle. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source that can be directly computed from the emission function without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models, some of which exhibit significant deviations from simple Gaussian behavior. By Fourier transforming the emission function, we compute the two-particle correlation function, and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and the measured HBT radii remain, we show that a more apples-to-apples comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data.

Fitted Hanbury-Brown-Twiss radii versus space-time variances in flow-dominated models

International Nuclear Information System (INIS)

Frodermann, Evan; Heinz, Ulrich; Lisa, Michael Annan

2006-01-01

The inability of otherwise successful dynamical models to reproduce the Hanbury-Brown-Twiss (HBT) radii extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the RHIC HBT Puzzle. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source that can be directly computed from the emission function without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models, some of which exhibit significant deviations from simple Gaussian behavior. By Fourier transforming the emission function, we compute the two-particle correlation function, and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and the measured HBT radii remain, we show that a more apples-to-apples comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data

Worm plot to diagnose fit in quantile regression

NARCIS (Netherlands)

Buuren, S. van

2007-01-01

The worm plot is a series of detrended Q-Q plots, split by covariate levels. The worm plot is a diagnostic tool for visualizing how well a statistical model fits the data, for finding locations at which the fit can be improved, and for comparing the fit of different models. This paper shows how the

Worm plot to diagnose fit in quantile regression

NARCIS (Netherlands)

Buuren, S. van

2007-01-01

The worm plot is a series of detrended Q-Q plots, split by covariate levels. The worm plot is a diagnostic tool for visualizing how well a statistical model fits the data, for finding locations at which the fit can be improved, and for comparing the fit of different models. This paper shows how

Development and Analysis of Volume Multi-Sphere Method Model Generation using Electric Field Fitting

Science.gov (United States)

Ingram, G. J.

Electrostatic modeling of spacecraft has wide-reaching applications such as detumbling space debris in the Geosynchronous Earth Orbit regime before docking, servicing and tugging space debris to graveyard orbits, and Lorentz augmented orbits. The viability of electrostatic actuation control applications relies on faster-than-realtime characterization of the electrostatic interaction. The Volume Multi-Sphere Method (VMSM) seeks the optimal placement and radii of a small number of equipotential spheres to accurately model the electrostatic force and torque on a conducting space object. Current VMSM models tuned using force and torque comparisons with commercially available finite element software are subject to the modeled probe size and numerical errors of the software. This work first investigates fitting of VMSM models to Surface-MSM (SMSM) generated electrical field data, removing modeling dependence on probe geometry while significantly increasing performance and speed. A proposed electric field matching cost function is compared to a force and torque cost function, the inclusion of a self-capacitance constraint is explored and 4 degree-of-freedom VMSM models generated using electric field matching are investigated. The resulting E-field based VMSM development framework is illustrated on a box-shaped hub with a single solar panel, and convergence properties of select models are qualitatively analyzed. Despite the complex non-symmetric spacecraft geometry, elegantly simple 2-sphere VMSM solutions provide force and torque fits within a few percent.

Interaction between age and aerobic fitness in determining heart rate dynamics

International Nuclear Information System (INIS)

McNarry, M A; Lewis, M J

2012-01-01

Heart rate variability (HRV) and phase-rectified signal averaging (PRSA) estimates of heart rate dynamics are diminished in older people compared with younger people. However, it is not fully elucidated whether these differences are related to age per se or to the concomitant influence of aerobic fitness. Aerobic fitness (peak oxygen uptake, gas exchange threshold, oxygen uptake kinetics, exercise economy) was assessed in 70 healthy adults (41 male) aged 18–57 years. Participants also underwent a 24 h, ambulatory ECG for the derivation of HRV and PRSA variables. HRV was most sensitive to age and aerobic fitness when measured during the morning period (6 am–12 pm). HRV and PRSA were both diminished with age and were higher in aerobically superior participants. The decline in HRV with age was predominantly attributable to age itself (33%), with aerobic fitness representing an additional modulating factor. The present study also provides tentative evidence that assessment of the influence of aerobic fitness should not rely on .VO 2peak alone. These findings demonstrate that age per se is an important factor in determining HRV. However, given the clinical importance of diminished HRV and the immutable nature of aging, the potential significance of physical activity/training to enhance cardiac regulatory function should not be underestimated. (paper)

Prediction of Pressing Quality for Press-Fit Assembly Based on Press-Fit Curve and Maximum Press-Mounting Force

Directory of Open Access Journals (Sweden)

Bo You

2015-01-01

Full Text Available In order to predict pressing quality of precision press-fit assembly, press-fit curves and maximum press-mounting force of press-fit assemblies were investigated by finite element analysis (FEA. The analysis was based on a 3D Solidworks model using the real dimensions of the microparts and the subsequent FEA model that was built using ANSYS Workbench. The press-fit process could thus be simulated on the basis of static structure analysis. To verify the FEA results, experiments were carried out using a press-mounting apparatus. The results show that the press-fit curves obtained by FEA agree closely with the curves obtained using the experimental method. In addition, the maximum press-mounting force calculated by FEA agrees with that obtained by the experimental method, with the maximum deviation being 4.6%, a value that can be tolerated. The comparison shows that the press-fit curve and max press-mounting force calculated by FEA can be used for predicting the pressing quality during precision press-fit assembly.

Direct fit of a theoretical model of phase transition in oscillatory finger motions.

NARCIS (Netherlands)

Newell, K.M.; Molenaar, P.C.M.

2003-01-01

This paper presents a general method to fit the Schoner-Haken-Kelso (SHK) model of human movement phase transitions directly to time series data. A robust variant of the extended Kalman filter technique is applied to the data of a single subject. The options of covariance resetting and iteration

Complex growing networks with intrinsic vertex fitness

International Nuclear Information System (INIS)

Bedogne, C.; Rodgers, G. J.

2006-01-01

One of the major questions in complex network research is to identify the range of mechanisms by which a complex network can self organize into a scale-free state. In this paper we investigate the interplay between a fitness linking mechanism and both random and preferential attachment. In our models, each vertex is assigned a fitness x, drawn from a probability distribution ρ(x). In Model A, at each time step a vertex is added and joined to an existing vertex, selected at random, with probability p and an edge is introduced between vertices with fitnesses x and y, with a rate f(x,y), with probability 1-p. Model B differs from Model A in that, with probability p, edges are added with preferential attachment rather than randomly. The analysis of Model A shows that, for every fixed fitness x, the network's degree distribution decays exponentially. In Model B we recover instead a power-law degree distribution whose exponent depends only on p, and we show how this result can be generalized. The properties of a number of particular networks are examined

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

The picture superiority effect in associative recognition.

Science.gov (United States)

Hockley, William E

2008-10-01

The picture superiority effect has been well documented in tests of item recognition and recall. The present study shows that the picture superiority effect extends to associative recognition. In three experiments, students studied lists consisting of random pairs of concrete words and pairs of line drawings; then they discriminated between intact (old) and rearranged (new) pairs of words and pictures at test. The discrimination advantage for pictures over words was seen in a greater hit rate for intact picture pairs, but there was no difference in the false alarm rates for the two types of stimuli. That is, there was no mirror effect. The same pattern of results was found when the test pairs consisted of the verbal labels of the pictures shown at study (Experiment 4), indicating that the hit rate advantage for picture pairs represents an encoding benefit. The results have implications for theories of the picture superiority effect and models of associative recognition.

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) . © 2015 John Wiley & Sons Ltd/London School of Economics.

Measuring Quasar Spin via X-ray Continuum Fitting

Science.gov (United States)

Jenkins, Matthew; Pooley, David; Rappaport, Saul; Steiner, Jack

2018-01-01

We have identified several quasars whose X-ray spectra appear very soft. When fit with power-law models, the best-fit indices are greater than 3. This is very suggestive of thermal disk emission, indicating that the X-ray spectrum is dominated by the disk component. Galactic black hole binaries in such states have been successfully fit with disk-blackbody models to constrain the inner radius, which also constrains the spin of the black hole. We have fit those models to XMM-Newton spectra of several of our identified soft X-ray quasars to place constraints on the spins of the supermassive black holes.

RATES OF FITNESS DECLINE AND REBOUND SUGGEST PERVASIVE EPISTASIS

Science.gov (United States)

Perfeito, L; Sousa, A; Bataillon, T; Gordo, I

2014-01-01

Unraveling the factors that determine the rate of adaptation is a major question in evolutionary biology. One key parameter is the effect of a new mutation on fitness, which invariably depends on the environment and genetic background. The fate of a mutation also depends on population size, which determines the amount of drift it will experience. Here, we manipulate both population size and genotype composition and follow adaptation of 23 distinct Escherichia coli genotypes. These have previously accumulated mutations under intense genetic drift and encompass a substantial fitness variation. A simple rule is uncovered: the net fitness change is negatively correlated with the fitness of the genotype in which new mutations appear—a signature of epistasis. We find that Fisher's geometrical model can account for the observed patterns of fitness change and infer the parameters of this model that best fit the data, using Approximate Bayesian Computation. We estimate a genomic mutation rate of 0.01 per generation for fitness altering mutations, albeit with a large confidence interval, a mean fitness effect of mutations of −0.01, and an effective number of traits nine in mutS− E. coli. This framework can be extended to confront a broader range of models with data and test different classes of fitness landscape models. PMID:24372601

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.

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

Fitness

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... gov home http://www.girlshealth.gov/ Home Fitness Fitness Want to look and feel your best? Physical ... are? Check out this info: What is physical fitness? top Physical fitness means you can do everyday ...

Hamiltonian inclusive fitness: a fitter fitness concept.

Science.gov (United States)

Costa, James T

2013-01-01

In 1963-1964 W. D. Hamilton introduced the concept of inclusive fitness, the only significant elaboration of Darwinian fitness since the nineteenth century. I discuss the origin of the modern fitness concept, providing context for Hamilton's discovery of inclusive fitness in relation to the puzzle of altruism. While fitness conceptually originates with Darwin, the term itself stems from Spencer and crystallized quantitatively in the early twentieth century. Hamiltonian inclusive fitness, with Price's reformulation, provided the solution to Darwin's 'special difficulty'-the evolution of caste polymorphism and sterility in social insects. Hamilton further explored the roles of inclusive fitness and reciprocation to tackle Darwin's other difficulty, the evolution of human altruism. The heuristically powerful inclusive fitness concept ramified over the past 50 years: the number and diversity of 'offspring ideas' that it has engendered render it a fitter fitness concept, one that Darwin would have appreciated.

Fitting the Phenomenological MSSM

CERN Document Server

AbdusSalam, S S; Quevedo, F; Feroz, F; Hobson, M

2010-01-01

We perform a global Bayesian fit of the phenomenological minimal supersymmetric standard model (pMSSM) to current indirect collider and dark matter data. The pMSSM contains the most relevant 25 weak-scale MSSM parameters, which are simultaneously fit using `nested sampling' Monte Carlo techniques in more than 15 years of CPU time. We calculate the Bayesian evidence for the pMSSM and constrain its parameters and observables in the context of two widely different, but reasonable, priors to determine which inferences are robust. We make inferences about sparticle masses, the sign of the $\\mu$ parameter, the amount of fine tuning, dark matter properties and the prospects for direct dark matter detection without assuming a restrictive high-scale supersymmetry breaking model. We find the inferred lightest CP-even Higgs boson mass as an example of an approximately prior independent observable. This analysis constitutes the first statistically convergent pMSSM global fit to all current data.

CRAPONE, Optical Model Potential Fit of Neutron Scattering Data

International Nuclear Information System (INIS)

Fabbri, F.; Fratamico, G.; Reffo, G.

2004-01-01

1 - Description of problem or function: Automatic search for local and non-local optical potential parameters for neutrons. Total, elastic, differential elastic cross sections, l=0 and l=1 strength functions and scattering length can be considered. 2 - Method of solution: A fitting procedure is applied to different sets of experimental data depending on the local or non-local approximation chosen. In the non-local approximation the fitting procedure can be simultaneously performed over the whole energy range. The best fit is obtained when a set of parameters is found where CHI 2 is at its minimum. The solution of the system equations is obtained by diagonalization of the matrix according to the Jacobi method

State Authenticity as Fit to Environment: The Implications of Social Identity for Fit, Authenticity, and Self-Segregation.

Science.gov (United States)

Schmader, Toni; Sedikides, Constantine

2017-10-01

People seek out situations that "fit," but the concept of fit is not well understood. We introduce State Authenticity as Fit to the Environment (SAFE), a conceptual framework for understanding how social identities motivate the situations that people approach or avoid. Drawing from but expanding the authenticity literature, we first outline three types of person-environment fit: self-concept fit, goal fit, and social fit. Each type of fit, we argue, facilitates cognitive fluency, motivational fluency, and social fluency that promote state authenticity and drive approach or avoidance behaviors. Using this model, we assert that contexts subtly signal social identities in ways that implicate each type of fit, eliciting state authenticity for advantaged groups but state inauthenticity for disadvantaged groups. Given that people strive to be authentic, these processes cascade down to self-segregation among social groups, reinforcing social inequalities. We conclude by mapping out directions for research on relevant mechanisms and boundary conditions.

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

Estimation and prediction of maximum daily rainfall at Sagar Island using best fit probability models

Science.gov (United States)

Mandal, S.; Choudhury, B. U.

2015-07-01

Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.

Testing the goodness of fit of selected infiltration models on soils with different land use histories

International Nuclear Information System (INIS)

Mbagwu, J.S.C.

1993-10-01

Six infiltration models, some obtained by reformulating the fitting parameters of the classical Kostiakov (1932) and Philip (1957) equations, were investigated for their ability to describe water infiltration into highly permeable sandy soils from the Nsukka plains of SE Nigeria. The models were Kostiakov, Modified Kostiakov (A), Modified Kostiakov (B), Philip, Modified Philip (A) and Modified Philip (B). Infiltration data were obtained from double ring infiltrometers on field plots established on a Knadic Paleustult (Nkpologu series) to investigate the effects of land use on soil properties and maize yield. The treatments were; (i) tilled-mulched (TM), (ii) tilled-unmulched (TU), (iii) untilled-mulched (UM), (iv) untilled-unmulched (UU) and (v) continuous pasture (CP). Cumulative infiltration was highest on the TM and lowest on the CP plots. All estimated model parameters obtained by the best fit of measured data differed significantly among the treatments. Based on the magnitude of R 2 values, the Kostiakov, Modified Kostiakov (A), Philip and Modified Philip (A) models provided best predictions of cumulative infiltration as a function of time. Comparing experimental with model-predicted cumulative infiltration showed, however, that on all treatments the values predicted by the classical Kostiakov, Philip and Modified Philip (A) models deviated most from experimental data. The other models produced values that agreed very well with measured data. Considering the eases of determining the fitting parameters it is proposed that on soils with high infiltration rates, either Modified Kostiakov model (I = Kt a + Ict) or Modified Philip model (I St 1/2 + Ict), (where I is cumulative infiltration, K, the time coefficient, t, time elapsed, 'a' the time exponent, Ic the equilibrium infiltration rate and S, the soil water sorptivity), be used for routine characterization of the infiltration process. (author). 33 refs, 3 figs 6 tabs

A bivariate contaminated binormal model for robust fitting of proper ROC curves to a pair of correlated, possibly degenerate, ROC datasets.

Science.gov (United States)

Zhai, Xuetong; Chakraborty, Dev P

2017-06-01

The objective was to design and implement a bivariate extension to the contaminated binormal model (CBM) to fit paired receiver operating characteristic (ROC) datasets-possibly degenerate-with proper ROC curves. Paired datasets yield two correlated ratings per case. Degenerate datasets have no interior operating points and proper ROC curves do not inappropriately cross the chance diagonal. The existing method, developed more than three decades ago utilizes a bivariate extension to the binormal model, implemented in CORROC2 software, which yields improper ROC curves and cannot fit degenerate datasets. CBM can fit proper ROC curves to unpaired (i.e., yielding one rating per case) and degenerate datasets, and there is a clear scientific need to extend it to handle paired datasets. In CBM, nondiseased cases are modeled by a probability density function (pdf) consisting of a unit variance peak centered at zero. Diseased cases are modeled with a mixture distribution whose pdf consists of two unit variance peaks, one centered at positive μ with integrated probability α, the mixing fraction parameter, corresponding to the fraction of diseased cases where the disease was visible to the radiologist, and one centered at zero, with integrated probability (1-α), corresponding to disease that was not visible. It is shown that: (a) for nondiseased cases the bivariate extension is a unit variances bivariate normal distribution centered at (0,0) with a specified correlation ρ 1 ; (b) for diseased cases the bivariate extension is a mixture distribution with four peaks, corresponding to disease not visible in either condition, disease visible in only one condition, contributing two peaks, and disease visible in both conditions. An expression for the likelihood function is derived. A maximum likelihood estimation (MLE) algorithm, CORCBM, was implemented in the R programming language that yields parameter estimates and the covariance matrix of the parameters, and other statistics

Building Customer Churn Prediction Models in Fitness Industry with Machine Learning Methods

OpenAIRE

Shan, Min

2017-01-01

With the rapid growth of digital systems, churn management has become a major focus within customer relationship management in many industries. Ample research has been conducted for churn prediction in different industries with various machine learning methods. This thesis aims to combine feature selection and supervised machine learning methods for defining models of churn prediction and apply them on fitness industry. Forward selection is chosen as feature selection methods. Support Vector ...

Different fits satisfy different needs: linking person-environment fit to employee commitment and performance using self-determination theory.

Science.gov (United States)

Greguras, Gary J; Diefendorff, James M

2009-03-01

Integrating and expanding upon the person-environment fit (PE fit) and the self-determination theory literatures, the authors hypothesized and tested a model in which the satisfaction of the psychological needs for autonomy, relatedness, and competence partially mediated the relations between different types of perceived PE fit (i.e., person-organization fit, person-group fit, and job demands-abilities fit) with employee affective organizational commitment and overall job performance. Data from 163 full-time working employees and their supervisors were collected across 3 time periods. Results indicate that different types of PE fit predicted different types of psychological need satisfaction and that psychological need satisfaction predicted affective commitment and performance. Further, person-organization fit and demands-abilities fit also evidenced direct effects on employee affective commitment. These results begin to explicate the processes through which different types of PE fit relate to employee attitudes and behaviors. (c) 2009 APA, all rights reserved.

Why do employees follow their superiors' instructions? Identification of the reasons to comply with superiors' will in a group of Polish employees.

Science.gov (United States)

Wójcik, Aleksandra; Merecz-Kot, Dorota; Andysz, Aleksandra

2015-01-01

Managers influence the way organization works as well as the functioning of subordinates - in the context of their work life but non-professional functioning as well e.g., attitude towards work-life balance or taking care of health. We focused on the superior-subordinate relation, referring to social power bases theory by Raven. We identified the reasons why subordinates decide to follow their superiors' orders and determined specific styles of compliance with superiors' will. Understanding why employees listen to their superiors may be valuable in the context of supporting healthy organizational climate and atmosphere of co-operation or communicating values - for example, as regards taking care of own health. We discussed the results referring to the issue of influencing employees in the context of their health behavior. The research involved 100 Polish employees, aged 28 years old on average, who filled in the Interpersonal Power Inventory by Raven et al. for subordinates in a Polish adaptation by Zaleski. The questionnaire includes 11 subscales referring to power bases. Based on the cluster analysis results, we recognized people who complied because of: all kinds of power bases (typical for 46% of the respondents); the respect for superiors' professionalism (34%); and formal/objective reasons (20%). Employees differ in terms of their styles of compliance. Their motives to comply with superiors' instructions constitute compilations of power bases. The superiors' awareness of the reasons why their employees decide to follow orders is necessary for successful management. It may motivate employees to work but also to take care of their own health. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

Fit reduced GUTS models online: From theory to practice.

Science.gov (United States)

Baudrot, Virgile; Veber, Philippe; Gence, Guillaume; Charles, Sandrine

2018-05-20

Mechanistic modeling approaches, such as the toxicokinetic-toxicodynamic (TKTD) framework, are promoted by international institutions such as the European Food Safety Authority and the Organization for Economic Cooperation and Development to assess the environmental risk of chemical products generated by human activities. TKTD models can encompass a large set of mechanisms describing the kinetics of compounds inside organisms (e.g., uptake and elimination) and their effect at the level of individuals (e.g., damage accrual, recovery, and death mechanism). Compared to classical dose-response models, TKTD approaches have many advantages, including accounting for temporal aspects of exposure and toxicity, considering data points all along the experiment and not only at the end, and making predictions for untested situations as realistic exposure scenarios. Among TKTD models, the general unified threshold model of survival (GUTS) is within the most recent and innovative framework but is still underused in practice, especially by risk assessors, because specialist programming and statistical skills are necessary to run it. Making GUTS models easier to use through a new module freely available from the web platform MOSAIC (standing for MOdeling and StAtistical tools for ecotoxIClogy) should promote GUTS operability in support of the daily work of environmental risk assessors. This paper presents the main features of MOSAIC_GUTS: uploading of the experimental data, GUTS fitting analysis, and LCx estimates with their uncertainty. These features will be exemplified from literature data. Integr Environ Assess Manag 2018;00:000-000. © 2018 SETAC. © 2018 SETAC.

An investigation of forecast horizon and observation fit’s influence on an econometric rate forecast model in the liner shipping industry

DEFF Research Database (Denmark)

Nielsen, Peter; Jiang, Liping; Rytter, Niels Gorm Malý

2014-01-01

This paper evaluates the influence of forecast horizon and observation fit on the robustness and performance of a specific freight rate forecast model used in the liner shipping industry. In the first stage of the research, a forecast model used to predict container freight rate development...... of the forecast horizon and observation fit and their interactions on the forecast model's performance. The results underline the complicated nature of creating a suitable forecast model by balancing business needs, a desire to fit a good model and achieve high accuracy. There is strong empirical evidence from...... this study; that a robust model is preferable, that overfitting is a true danger, and that a balance must be achieved between forecast horizon and the number of observations used to fit the model. In addition, methodological guidance has also been provided on how to test, design, and choose the superior...

The Picture Superiority Effect and Biological Education.

Science.gov (United States)

Reid, D. J.

1984-01-01

Discusses learning behaviors where the "picture superiority effect" (PSE) seems to be most effective in biology education. Also considers research methodology and suggests a new research model which allows a more direct examination of the strategies learners use when matching up picture and text in efforts to "understand"…

Reverse total shoulder glenoid baseplate stability with superior glenoid bone loss.

Science.gov (United States)

Martin, Elise J; Duquin, Thomas R; Ehrensberger, Mark T

2017-10-01

Superior wear of the glenoid bone is common in patients with rotator cuff arthropathy. This can become a treatment challenge for patients who require shoulder arthroplasty. In reverse shoulder arthroplasty (RSA), glenoid bone loss may affect the stability of baseplate fixation. The primary purpose of this biomechanical laboratory study was to assess the initial fixation stability of RSA glenosphere baseplates in the presence of variable amounts of superior glenoid bone loss. High-density solid rigid polyurethane foam (30 pounds/cubic foot) was machined to model the glenoid with variable superior defects that provided different levels of support (100%, 90%, 75%, and 50%) for the glenosphere baseplate. The samples were cyclically loaded (0-750 N at 1 Hz for 5000 cycles) at a 60° glenohumeral angle. The micromotion and migration of the baseplate were calculated from displacement data captured during the loading tests with an array of 3 linear variable differential transformers mounted around the baseplate. Micromotion was significantly greater in samples with 50% defects compared with those with smaller defects. Migration was significantly greater after testing for all defect sizes. Initial fixation of RSA glenosphere baseplates was significantly reduced in models with 50% bone loss on the superior edge compared with models with less bone loss in this high-density bone foam model. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

SU-E-J-85: Leave-One-Out Perturbation (LOOP) Fitting Algorithm for Absolute Dose Film Calibration

International Nuclear Information System (INIS)

Chu, A; Ahmad, M; Chen, Z; Nath, R; Feng, W

2014-01-01

Purpose: To introduce an outliers-recognition fitting routine for film dosimetry. It cannot only be flexible with any linear and non-linear regression but also can provide information for the minimal number of sampling points, critical sampling distributions and evaluating analytical functions for absolute film-dose calibration. Methods: The technique, leave-one-out (LOO) cross validation, is often used for statistical analyses on model performance. We used LOO analyses with perturbed bootstrap fitting called leave-one-out perturbation (LOOP) for film-dose calibration . Given a threshold, the LOO process detects unfit points (“outliers”) compared to other cohorts, and a bootstrap fitting process follows to seek any possibilities of using perturbations for further improvement. After that outliers were reconfirmed by a traditional t-test statistics and eliminated, then another LOOP feedback resulted in the final. An over-sampled film-dose- calibration dataset was collected as a reference (dose range: 0-800cGy), and various simulated conditions for outliers and sampling distributions were derived from the reference. Comparisons over the various conditions were made, and the performance of fitting functions, polynomial and rational functions, were evaluated. Results: (1) LOOP can prove its sensitive outlier-recognition by its statistical correlation to an exceptional better goodness-of-fit as outliers being left-out. (2) With sufficient statistical information, the LOOP can correct outliers under some low-sampling conditions that other “robust fits”, e.g. Least Absolute Residuals, cannot. (3) Complete cross-validated analyses of LOOP indicate that the function of rational type demonstrates a much superior performance compared to the polynomial. Even with 5 data points including one outlier, using LOOP with rational function can restore more than a 95% value back to its reference values, while the polynomial fitting completely failed under the same conditions

SU-E-J-85: Leave-One-Out Perturbation (LOOP) Fitting Algorithm for Absolute Dose Film Calibration

Energy Technology Data Exchange (ETDEWEB)

Chu, A; Ahmad, M; Chen, Z; Nath, R [Yale New Haven Hospital/School of Medicine Yale University, New Haven, CT (United States); Feng, W [New York Presbyterian Hospital, Tenafly, NJ (United States)

2014-06-01

Purpose: To introduce an outliers-recognition fitting routine for film dosimetry. It cannot only be flexible with any linear and non-linear regression but also can provide information for the minimal number of sampling points, critical sampling distributions and evaluating analytical functions for absolute film-dose calibration. Methods: The technique, leave-one-out (LOO) cross validation, is often used for statistical analyses on model performance. We used LOO analyses with perturbed bootstrap fitting called leave-one-out perturbation (LOOP) for film-dose calibration . Given a threshold, the LOO process detects unfit points (“outliers”) compared to other cohorts, and a bootstrap fitting process follows to seek any possibilities of using perturbations for further improvement. After that outliers were reconfirmed by a traditional t-test statistics and eliminated, then another LOOP feedback resulted in the final. An over-sampled film-dose- calibration dataset was collected as a reference (dose range: 0-800cGy), and various simulated conditions for outliers and sampling distributions were derived from the reference. Comparisons over the various conditions were made, and the performance of fitting functions, polynomial and rational functions, were evaluated. Results: (1) LOOP can prove its sensitive outlier-recognition by its statistical correlation to an exceptional better goodness-of-fit as outliers being left-out. (2) With sufficient statistical information, the LOOP can correct outliers under some low-sampling conditions that other “robust fits”, e.g. Least Absolute Residuals, cannot. (3) Complete cross-validated analyses of LOOP indicate that the function of rational type demonstrates a much superior performance compared to the polynomial. Even with 5 data points including one outlier, using LOOP with rational function can restore more than a 95% value back to its reference values, while the polynomial fitting completely failed under the same conditions

Thermodynamic models for determination of solid–liquid equilibrium of the 6-benzyladenine in pure and binary organic solvents

International Nuclear Information System (INIS)

Li, Tao; Deng, Renlun; Wu, Gang; Gu, Pengfei; Hu, Yonghong; Yang, Wenge; Yu, Yemin; Zhang, Yuhao; Yang, Chen

2017-01-01

Highlights: • The solubility increased with increasing temperature. • Data were fitted using the modified Apelblat equation and other models in pure solvents. • Data were fitted using the modified Apelblat equation and other models in binary solvent mixture. - Abstract: Data on corresponding solid–liquid equilibrium of 6-benzyladenine in different solvents are essential for a preliminary study of industrial applications. In this paper, the solid–liquid equilibrium of 6-benzyladenine in methanol, ethanol, 1-butanol, acetone, acetonitrile, ethyl acetate, dimethyl formamide and tetrahydrofuran pure solvents and (dimethyl formamide + actone) mixture solvents was explored within the temperature range from (278.15 to 333.15) K under 0.1 MPa. For the temperature range investigated, the solubility of 6-benzyladenine in the solvents increased with increasing temperature. The solubility of 6-benzyladenine in dimethyl formamide is superior to other selected pure solvents. The modified Apelblat model, the Buchowski-Ksiazaczak λh model, and the ideal model were adopted to describe and predict the change tendency of solubility. Computational results showed that the modified Apelblat model has more advantages than the other two models. The solubility results were fitted using a modified Apelblat equation, a variant of the combined nearly ideal binary solvent/Redich-Kister (CNIBS/R-K) model, Jouyban-Acree model and Ma model in (dimethyl formamide + acetone) binary solvent mixture. Computational results showed that the modified Apelblat model is superior to the other equations.

AMS-02 fits dark matter

Science.gov (United States)

Balázs, Csaba; Li, Tong

2016-05-01

In this work we perform a comprehensive statistical analysis of the AMS-02 electron, positron fluxes and the antiproton-to-proton ratio in the context of a simplified dark matter model. We include known, standard astrophysical sources and a dark matter component in the cosmic ray injection spectra. To predict the AMS-02 observables we use propagation parameters extracted from observed fluxes of heavier nuclei and the low energy part of the AMS-02 data. We assume that the dark matter particle is a Majorana fermion coupling to third generation fermions via a spin-0 mediator, and annihilating to multiple channels at once. The simultaneous presence of various annihilation channels provides the dark matter model with additional flexibility, and this enables us to simultaneously fit all cosmic ray spectra using a simple particle physics model and coherent astrophysical assumptions. Our results indicate that AMS-02 observations are not only consistent with the dark matter hypothesis within the uncertainties, but adding a dark matter contribution improves the fit to the data. Assuming, however, that dark matter is solely responsible for this improvement of the fit, it is difficult to evade the latest CMB limits in this model.

AMS-02 fits dark matter

Energy Technology Data Exchange (ETDEWEB)

Balázs, Csaba; Li, Tong [ARC Centre of Excellence for Particle Physics at the Tera-scale,School of Physics and Astronomy, Monash University, Melbourne, Victoria 3800 (Australia)

2016-05-05

In this work we perform a comprehensive statistical analysis of the AMS-02 electron, positron fluxes and the antiproton-to-proton ratio in the context of a simplified dark matter model. We include known, standard astrophysical sources and a dark matter component in the cosmic ray injection spectra. To predict the AMS-02 observables we use propagation parameters extracted from observed fluxes of heavier nuclei and the low energy part of the AMS-02 data. We assume that the dark matter particle is a Majorana fermion coupling to third generation fermions via a spin-0 mediator, and annihilating to multiple channels at once. The simultaneous presence of various annihilation channels provides the dark matter model with additional flexibility, and this enables us to simultaneously fit all cosmic ray spectra using a simple particle physics model and coherent astrophysical assumptions. Our results indicate that AMS-02 observations are not only consistent with the dark matter hypothesis within the uncertainties, but adding a dark matter contribution improves the fit to the data. Assuming, however, that dark matter is solely responsible for this improvement of the fit, it is difficult to evade the latest CMB limits in this model.

A History of Regression and Related Model-Fitting in the Earth Sciences (1636?-2000)

International Nuclear Information System (INIS)

Howarth, Richard J.

2001-01-01

The (statistical) modeling of the behavior of a dependent variate as a function of one or more predictors provides examples of model-fitting which span the development of the earth sciences from the 17th Century to the present. The historical development of these methods and their subsequent application is reviewed. Bond's predictions (c. 1636 and 1668) of change in the magnetic declination at London may be the earliest attempt to fit such models to geophysical data. Following publication of Newton's theory of gravitation in 1726, analysis of data on the length of a 1 o meridian arc, and the length of a pendulum beating seconds, as a function of sin 2 (latitude), was used to determine the ellipticity of the oblate spheroid defining the Figure of the Earth. The pioneering computational methods of Mayer in 1750, Boscovich in 1755, and Lambert in 1765, and the subsequent independent discoveries of the principle of least squares by Gauss in 1799, Legendre in 1805, and Adrain in 1808, and its later substantiation on the basis of probability theory by Gauss in 1809 were all applied to the analysis of such geodetic and geophysical data. Notable later applications include: the geomagnetic survey of Ireland by Lloyd, Sabine, and Ross in 1836, Gauss's model of the terrestrial magnetic field in 1838, and Airy's 1845 analysis of the residuals from a fit to pendulum lengths, from which he recognized the anomalous character of measurements of gravitational force which had been made on islands. In the early 20th Century applications to geological topics proliferated, but the computational burden effectively held back applications of multivariate analysis. Following World War II, the arrival of digital computers in universities in the 1950s facilitated computation, and fitting linear or polynomial models as a function of geographic coordinates, trend surface analysis, became popular during the 1950-60s. The inception of geostatistics in France at this time by Matheron had its

A Sport Education Fitness Season's Impact on Students' Fitness Levels, Knowledge, and In-Class Physical Activity.

Science.gov (United States)

Ward, Jeffery Kurt; Hastie, Peter A; Wadsworth, Danielle D; Foote, Shelby; Brock, Sheri J; Hollett, Nikki

2017-09-01

The purpose of this study was to determine the extent to which a sport education season of fitness could provide students with recommended levels of in-class moderate-to-vigorous physical activity (MVPA) while also increasing students' fitness knowledge and fitness achievement. One hundred and sixty-six 5th-grade students (76 boys, 90 girls) participated in a 20-lesson season called "CrossFit Challenge" during a 4-week period. The Progressive Aerobic Cardiovascular Endurance Run, push-ups, and curl-ups tests of the FITNESSGRAM® were used to assess fitness at pretest and posttest, while fitness knowledge was assessed through a validated, grade-appropriate test of health-related fitness knowledge (HRF). Physical activity was measured with Actigraph GT3X triaxial accelerometers. Results indicated a significant time effect for all fitness tests and the knowledge test. Across the entire season, the students spent an average of 54.5% of lesson time engaged in MVPA, irrespective of the type of lesson (instruction, free practice, or competition). The results suggest that configuring the key principles of sport education within a unit of fitness is an efficient model for providing students with the opportunity to improve fitness skill and HRF knowledge while attaining recommended levels of MVPA.

Superior cervical gangliectomy induces non-exudative age-related macular degeneration in mice

Directory of Open Access Journals (Sweden)

Hernán H. Dieguez

2018-02-01

Full Text Available Non-exudative age-related macular degeneration, a prevalent cause of blindness, is a progressive and degenerative disease characterized by alterations in Bruch's membrane, retinal pigment epithelium, and photoreceptors exclusively localized in the macula. Although experimental murine models exist, the vast majority take a long time to develop retinal alterations and, in general, these alterations are ubiquitous, with many resulting from non-eye-specific genetic manipulations; additionally, most do not always reproduce the hallmarks of human age-related macular degeneration. Choroid vessels receive sympathetic innervation from the superior cervical ganglion, which, together with the parasympathetic system, regulates blood flow into the choroid. Choroid blood flow changes have been involved in age-related macular degeneration development and progression. At present, no experimental models take this factor into account. The aim of this work was to analyze the effect of superior cervical gangliectomy (also known as ganglionectomy on the choroid, Bruch's membrane, retinal pigment epithelium and retina. Adult male C57BL/6J mice underwent unilateral superior cervical gangliectomy and a contralateral sham procedure. Although superior cervical gangliectomy induced ubiquitous choroid and choriocapillaris changes, it induced Bruch's membrane thickening, loss of retinal pigment epithelium melanin content and retinoid isomerohydrolase, the appearance of drusen-like deposits, and retinal pigment epithelium and photoreceptor atrophy, exclusively localized in the temporal side. Moreover, superior cervical gangliectomy provoked a localized increase in retinal pigment epithelium and photoreceptor apoptosis, and a decline in photoreceptor electroretinographic function. Therefore, superior cervical gangliectomy recapitulated the main features of human non-exudative age-related macular degeneration, and could become a new experimental model of dry age

Sex differences in emotion recognition: Evidence for a small overall female superiority on facial disgust.

Science.gov (United States)

Connolly, Hannah L; Lefevre, Carmen E; Young, Andrew W; Lewis, Gary J

2018-05-21

Although it is widely believed that females outperform males in the ability to recognize other people's emotions, this conclusion is not well supported by the extant literature. The current study sought to provide a strong test of the female superiority hypothesis by investigating sex differences in emotion recognition for five basic emotions using stimuli well-calibrated for individual differences assessment, across two expressive domains (face and body), and in a large sample (N = 1,022: Study 1). We also assessed the stability and generalizability of our findings with two independent replication samples (N = 303: Study 2, N = 634: Study 3). In Study 1, we observed that females were superior to males in recognizing facial disgust and sadness. In contrast, males were superior to females in recognizing bodily happiness. The female superiority for recognition of facial disgust was replicated in Studies 2 and 3, and this observation also extended to an independent stimulus set in Study 2. No other sex differences were stable across studies. These findings provide evidence for the presence of sex differences in emotion recognition ability, but show that these differences are modest in magnitude and appear to be limited to facial disgust. We discuss whether this sex difference may reflect human evolutionary imperatives concerning reproductive fitness and child care. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The More, the Better? Curvilinear Effects of Job Autonomy on Well-Being From Vitamin Model and PE-Fit Theory Perspectives.

Science.gov (United States)

Stiglbauer, Barbara; Kovacs, Carrie

2017-12-28

In organizational psychology research, autonomy is generally seen as a job resource with a monotone positive relationship with desired occupational outcomes such as well-being. However, both Warr's vitamin model and person-environment (PE) fit theory suggest that negative outcomes may result from excesses of some job resources, including autonomy. Thus, the current studies used survey methodology to explore cross-sectional relationships between environmental autonomy, person-environment autonomy (mis)fit, and well-being. We found that autonomy and autonomy (mis)fit explained between 6% and 22% of variance in well-being, depending on type of autonomy (scheduling, method, or decision-making) and type of (mis)fit operationalization (atomistic operationalization through the separate assessment of actual and ideal autonomy levels vs. molecular operationalization through the direct assessment of perceived autonomy (mis)fit). Autonomy (mis)fit (PE-fit perspective) explained more unique variance in well-being than environmental autonomy itself (vitamin model perspective). Detrimental effects of autonomy excess on well-being were most evident for method autonomy and least consistent for decision-making autonomy. We argue that too-much-of-a-good-thing effects of job autonomy on well-being exist, but suggest that these may be dependent upon sample characteristics (range of autonomy levels), type of operationalization (molecular vs. atomistic fit), autonomy facet (method, scheduling, or decision-making), as well as individual and organizational moderators. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Global fits of GUT-scale SUSY models with GAMBIT

Science.gov (United States)

Athron, Peter; Balázs, Csaba; 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; de Austri, Roberto Ruiz; Saavedra, Aldo; Savage, Christopher; Scott, Pat; Serra, Nicola; Weniger, Christoph; White, Martin

2017-12-01

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 avoiding all other constraints. We find high-likelihood regions of parameter space featuring light stops and charginos, making them potentially detectable in the near future at the LHC. We also show that tonne-scale direct detection will play a largely complementary role, probing large parts of the remaining viable parameter space, including essentially all models with multi-TeV neutralinos.

Global fits of GUT-scale SUSY models with GAMBIT

Energy Technology Data Exchange (ETDEWEB)

Athron, Peter [Monash University, School of Physics and Astronomy, Melbourne, VIC (Australia); Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); Balazs, Csaba [Monash University, School of Physics and Astronomy, Melbourne, VIC (Australia); Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); Bringmann, Torsten; Dal, Lars A.; Krislock, Abram; Raklev, Are [University of Oslo, Department of Physics, Oslo (Norway); Buckley, Andy [University of Glasgow, SUPA, School of Physics and Astronomy, Glasgow (United Kingdom); Chrzaszcz, Marcin [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); H. Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, Krakow (Poland); Conrad, Jan; Edsjoe, Joakim; Farmer, Ben [AlbaNova University Centre, Oskar Klein Centre for Cosmoparticle Physics, Stockholm (Sweden); Stockholm University, Department of Physics, Stockholm (Sweden); Cornell, Jonathan M. [McGill University, Department of Physics, Montreal, QC (Canada); Jackson, Paul; White, Martin [Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); University of Adelaide, Department of Physics, Adelaide, SA (Australia); Kvellestad, Anders; Savage, Christopher [NORDITA, Stockholm (Sweden); Mahmoudi, Farvah [Univ Lyon, Univ Lyon 1, CNRS, ENS de Lyon, Centre de Recherche Astrophysique de Lyon UMR5574, Saint-Genis-Laval (France); Theoretical Physics Department, CERN, Geneva (Switzerland); Martinez, Gregory D. [University of California, Physics and Astronomy Department, Los Angeles, CA (United States); Putze, Antje [LAPTh, Universite de Savoie, CNRS, Annecy-le-Vieux (France); Rogan, Christopher [Harvard University, Department of Physics, Cambridge, MA (United States); Ruiz de Austri, Roberto [IFIC-UV/CSIC, Instituto de Fisica Corpuscular, Valencia (Spain); Saavedra, Aldo [Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); The University of Sydney, Faculty of Engineering and Information Technologies, Centre for Translational Data Science, School of Physics, Camperdown, NSW (Australia); Scott, Pat [Imperial College London, Department of Physics, Blackett Laboratory, London (United Kingdom); Serra, Nicola [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); Weniger, Christoph [University of Amsterdam, GRAPPA, Institute of Physics, Amsterdam (Netherlands); Collaboration: The GAMBIT Collaboration

2017-12-15

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 avoiding all other constraints. We find high-likelihood regions of parameter space featuring light stops and charginos, making them potentially detectable in the near future at the LHC. We also show that tonne-scale direct detection will play a largely complementary role, probing large parts of the remaining viable parameter space, including essentially all models with multi-TeV neutralinos. (orig.)

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...

A classical regression framework for mediation analysis: fitting one model to estimate mediation effects.

Science.gov (United States)

Saunders, Christina T; Blume, Jeffrey D

2017-10-26

Mediation analysis explores the degree to which an exposure's effect on an outcome is diverted through a mediating variable. We describe a classical regression framework for conducting mediation analyses in which estimates of causal mediation effects and their variance are obtained from the fit of a single regression model. The vector of changes in exposure pathway coefficients, which we named the essential mediation components (EMCs), is used to estimate standard causal mediation effects. Because these effects are often simple functions of the EMCs, an analytical expression for their model-based variance follows directly. Given this formula, it is instructive to revisit the performance of routinely used variance approximations (e.g., delta method and resampling methods). Requiring the fit of only one model reduces the computation time required for complex mediation analyses and permits the use of a rich suite of regression tools that are not easily implemented on a system of three equations, as would be required in the Baron-Kenny framework. Using data from the BRAIN-ICU study, we provide examples to illustrate the advantages of this framework and compare it with the existing approaches. © The Author 2017. Published by Oxford University Press.

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.

A Monte Carlo-adjusted goodness-of-fit test for parametric models describing spatial point patterns

KAUST Repository

Dao, Ngocanh; Genton, Marc G.

2014-01-01

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

Fitness function and nonunique solutions in x-ray reflectivity curve fitting: crosserror between surface roughness and mass density

International Nuclear Information System (INIS)

Tiilikainen, J; Bosund, V; Mattila, M; Hakkarainen, T; Sormunen, J; Lipsanen, H

2007-01-01

Nonunique solutions of the x-ray reflectivity (XRR) curve fitting problem were studied by modelling layer structures with neural networks and designing a fitness function to handle the nonidealities of measurements. Modelled atomic-layer-deposited aluminium oxide film structures were used in the simulations to calculate XRR curves based on Parratt's formalism. This approach reduced the dimensionality of the parameter space and allowed the use of fitness landscapes in the study of nonunique solutions. Fitness landscapes, where the height in a map represents the fitness value as a function of the process parameters, revealed tracks where the local fitness optima lie. The tracks were projected on the physical parameter space thus allowing the construction of the crosserror equation between weakly determined parameters, i.e. between the mass density and the surface roughness of a layer. The equation gives the minimum error for the other parameters which is a consequence of the nonuniqueness of the solution if noise is present. Furthermore, the existence of a possible unique solution in a certain parameter range was found to be dependent on the layer thickness and the signal-to-noise ratio

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.

Fitness of allozyme variants in Drosophila pseudoobscura. II. Selection at the Est-5, Odh and Mdh-2 loci

Energy Technology Data Exchange (ETDEWEB)

Marinkovic, D; Ayala, F J

1975-01-01

We have studied the effects on fitness of allelic variation at three gene loci (Est-5, Odh, and Mdh-2) coding for enzymes in Drosophila pseudoobscura. Genotype has a significant effect on fitness for all six parameters measured (female fecundity, male mating capacity, egg-to-adult survival under near-optimal and under competitive conditions, and rate of development under near-optimal and under competitive conditions). No single genotype is best for all six fitness parameters; rather, genotypes with superior performance during a certain stage of the life-cycle may have low fitness at some other stage, or in different environmental conditions. Heterozygotes are sometimes best when all fitness parameters are considered. There are significant interactions between loci. The various forms of balancing selection uncovered in our experiments may account for the polymorphisms occurring in natural populations of D. pseudoobscura at the three loci studied. (auth)

A rat model system to study complex disease risks, fitness, aging, and longevity.

Science.gov (United States)

Koch, Lauren Gerard; Britton, Steven L; Wisløff, Ulrik

2012-02-01

The association between low exercise capacity and all-cause morbidity and mortality is statistically strong yet mechanistically unresolved. By connecting clinical observation with a theoretical base, we developed a working hypothesis that variation in capacity for oxygen metabolism is the central mechanistic determinant between disease and health (aerobic hypothesis). As an unbiased test, we show that two-way artificial selective breeding of rats for low and high intrinsic endurance exercise capacity also produces rats that differ for numerous disease risks, including the metabolic syndrome, cardiovascular complications, premature aging, and reduced longevity. This contrasting animal model system may prove to be translationally superior relative to more widely used simplistic models for understanding geriatric biology and medicine. Copyright © 2012 Elsevier Inc. All rights reserved.

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

Neural network hydrological modelling: on questions of over-fitting, over-training and over-parameterisation

Science.gov (United States)

Abrahart, R. J.; Dawson, C. W.; Heppenstall, A. J.; See, L. M.

2009-04-01

The most critical issue in developing a neural network model is generalisation: how well will the preferred solution perform when it is applied to unseen datasets? The reported experiments used far-reaching sequences of model architectures and training periods to investigate the potential damage that could result from the impact of several interrelated items: (i) over-fitting - a machine learning concept related to exceeding some optimal architectural size; (ii) over-training - a machine learning concept related to the amount of adjustment that is applied to a specific model - based on the understanding that too much fine-tuning might result in a model that had accommodated random aspects of its training dataset - items that had no causal relationship to the target function; and (iii) over-parameterisation - a statistical modelling concept that is used to restrict the number of parameters in a model so as to match the information content of its calibration dataset. The last item in this triplet stems from an understanding that excessive computational complexities might permit an absurd and false solution to be fitted to the available material. Numerous feedforward multilayered perceptrons were trialled and tested. Two different methods of model construction were also compared and contrasted: (i) traditional Backpropagation of Error; and (ii) state-of-the-art Symbiotic Adaptive Neuro-Evolution. Modelling solutions were developed using the reported experimental set ups of Gaume & Gosset (2003). The models were applied to a near-linear hydrological modelling scenario in which past upstream and past downstream discharge records were used to forecast current discharge at the downstream gauging station [CS1: River Marne]; and a non-linear hydrological modelling scenario in which past river discharge measurements and past local meteorological records (precipitation and evaporation) were used to forecast current discharge at the river gauging station [CS2: Le Sauzay].

Universality Classes of Interaction Structures for NK Fitness Landscapes

Science.gov (United States)

Hwang, Sungmin; Schmiegelt, Benjamin; Ferretti, Luca; Krug, Joachim

2018-02-01

Kauffman's NK-model is a paradigmatic example of a class of stochastic models of genotypic fitness landscapes that aim to capture generic features of epistatic interactions in multilocus systems. Genotypes are represented as sequences of L binary loci. The fitness assigned to a genotype is a sum of contributions, each of which is a random function defined on a subset of k ≤ L loci. These subsets or neighborhoods determine the genetic interactions of the model. Whereas earlier work on the NK model suggested that most of its properties are robust with regard to the choice of neighborhoods, recent work has revealed an important and sometimes counter-intuitive influence of the interaction structure on the properties of NK fitness landscapes. Here we review these developments and present new results concerning the number of local fitness maxima and the statistics of selectively accessible (that is, fitness-monotonic) mutational pathways. In particular, we develop a unified framework for computing the exponential growth rate of the expected number of local fitness maxima as a function of L, and identify two different universality classes of interaction structures that display different asymptotics of this quantity for large k. Moreover, we show that the probability that the fitness landscape can be traversed along an accessible path decreases exponentially in L for a large class of interaction structures that we characterize as locally bounded. Finally, we discuss the impact of the NK interaction structures on the dynamics of evolution using adaptive walk models.

Statistical topography of fitness landscapes

OpenAIRE

Franke, Jasper

2011-01-01

Fitness landscapes are generalized energy landscapes that play an important conceptual role in evolutionary biology. These landscapes provide a relation between the genetic configuration of an organism and that organism’s adaptive properties. In this work, global topographical features of these fitness landscapes are investigated using theoretical models. The resulting predictions are compared to empirical landscapes. It is shown that these landscapes allow, at least with respe...

Superior cervical gangliectomy induces non-exudative age-related macular degeneration in mice.

Science.gov (United States)

Dieguez, Hernán H; Romeo, Horacio E; González Fleitas, María F; Aranda, Marcos L; Milne, Georgia A; Rosenstein, Ruth E; Dorfman, Damián

2018-02-07

Non-exudative age-related macular degeneration, a prevalent cause of blindness, is a progressive and degenerative disease characterized by alterations in Bruch's membrane, retinal pigment epithelium, and photoreceptors exclusively localized in the macula. Although experimental murine models exist, the vast majority take a long time to develop retinal alterations and, in general, these alterations are ubiquitous, with many resulting from non-eye-specific genetic manipulations; additionally, most do not always reproduce the hallmarks of human age-related macular degeneration. Choroid vessels receive sympathetic innervation from the superior cervical ganglion, which, together with the parasympathetic system, regulates blood flow into the choroid. Choroid blood flow changes have been involved in age-related macular degeneration development and progression. At present, no experimental models take this factor into account. The aim of this work was to analyze the effect of superior cervical gangliectomy (also known as ganglionectomy) on the choroid, Bruch's membrane, retinal pigment epithelium and retina. Adult male C57BL/6J mice underwent unilateral superior cervical gangliectomy and a contralateral sham procedure. Although superior cervical gangliectomy induced ubiquitous choroid and choriocapillaris changes, it induced Bruch's membrane thickening, loss of retinal pigment epithelium melanin content and retinoid isomerohydrolase, the appearance of drusen-like deposits, and retinal pigment epithelium and photoreceptor atrophy, exclusively localized in the temporal side. Moreover, superior cervical gangliectomy provoked a localized increase in retinal pigment epithelium and photoreceptor apoptosis, and a decline in photoreceptor electroretinographic function. Therefore, superior cervical gangliectomy recapitulated the main features of human non-exudative age-related macular degeneration, and could become a new experimental model of dry age-related macular degeneration, and

Fitting a defect non-linear model with or without prior, distinguishing nuclear reaction products as an example

Science.gov (United States)

Helgesson, P.; Sjöstrand, H.

2017-11-01

Fitting a parametrized function to data is important for many researchers and scientists. If the model is non-linear and/or defect, it is not trivial to do correctly and to include an adequate uncertainty analysis. This work presents how the Levenberg-Marquardt algorithm for non-linear generalized least squares fitting can be used with a prior distribution for the parameters and how it can be combined with Gaussian processes to treat model defects. An example, where three peaks in a histogram are to be distinguished, is carefully studied. In particular, the probability r1 for a nuclear reaction to end up in one out of two overlapping peaks is studied. Synthetic data are used to investigate effects of linearizations and other assumptions. For perfect Gaussian peaks, it is seen that the estimated parameters are distributed close to the truth with good covariance estimates. This assumes that the method is applied correctly; for example, prior knowledge should be implemented using a prior distribution and not by assuming that some parameters are perfectly known (if they are not). It is also important to update the data covariance matrix using the fit if the uncertainties depend on the expected value of the data (e.g., for Poisson counting statistics or relative uncertainties). If a model defect is added to the peaks, such that their shape is unknown, a fit which assumes perfect Gaussian peaks becomes unable to reproduce the data, and the results for r1 become biased. It is, however, seen that it is possible to treat the model defect with a Gaussian process with a covariance function tailored for the situation, with hyper-parameters determined by leave-one-out cross validation. The resulting estimates for r1 are virtually unbiased, and the uncertainty estimates agree very well with the underlying uncertainty.

Fitting a defect non-linear model with or without prior, distinguishing nuclear reaction products as an example.

Science.gov (United States)

Helgesson, P; Sjöstrand, H

2017-11-01

Fitting a parametrized function to data is important for many researchers and scientists. If the model is non-linear and/or defect, it is not trivial to do correctly and to include an adequate uncertainty analysis. This work presents how the Levenberg-Marquardt algorithm for non-linear generalized least squares fitting can be used with a prior distribution for the parameters and how it can be combined with Gaussian processes to treat model defects. An example, where three peaks in a histogram are to be distinguished, is carefully studied. In particular, the probability r 1 for a nuclear reaction to end up in one out of two overlapping peaks is studied. Synthetic data are used to investigate effects of linearizations and other assumptions. For perfect Gaussian peaks, it is seen that the estimated parameters are distributed close to the truth with good covariance estimates. This assumes that the method is applied correctly; for example, prior knowledge should be implemented using a prior distribution and not by assuming that some parameters are perfectly known (if they are not). It is also important to update the data covariance matrix using the fit if the uncertainties depend on the expected value of the data (e.g., for Poisson counting statistics or relative uncertainties). If a model defect is added to the peaks, such that their shape is unknown, a fit which assumes perfect Gaussian peaks becomes unable to reproduce the data, and the results for r 1 become biased. It is, however, seen that it is possible to treat the model defect with a Gaussian process with a covariance function tailored for the situation, with hyper-parameters determined by leave-one-out cross validation. The resulting estimates for r 1 are virtually unbiased, and the uncertainty estimates agree very well with the underlying uncertainty.

Tratamento da síndrome da veia cava superior Treatment of superior vena cava syndrome

Directory of Open Access Journals (Sweden)

Luís Marcelo Inaco Cirino

2005-12-01

Full Text Available A veia cava superior é formada pela união das duas veias inominadas, direita e esquerda, e localiza-se no mediastino médio, à direita da artéria aorta e anteriormente à traquéia. A síndrome da veia cava superior representa um conjunto de sinais (dilatação das veias do pescoço, pletora facial, edema de membros superiores, cianose e sintomas (cefaléia, dispnéia, tosse, edema de membro superior, ortopnéia e disfagia decorrentes da obstrução do fluxo sanguíneo através da veia cava superior em direção ao átrio direito. A obstrução pode ser causada por compressão extrínseca, invasão tumoral, trombose ou por dificuldade do retorno venoso ao coração secundária a doenças intra-atriais ou intraluminais. Aproximadamente 73% a 97% dos casos de síndrome da veia cava superior ocorrem durante a evolução de processos malignos intratorácicos. A maioria dos pacientes com a síndrome secundária a neoplasias malignas é tratada sem necessidade de cirurgia, através de radioterapia ou quimioterapia, ou através da colocação de stents endoluminais. Quando a síndrome é de etiologia benigna, o tratamento é feito através de medidas clínicas (anticoagulação, elevação da cabeça, etc. ou, em casos refratários, através de angioplastia, colocação de stents endoluminais e cirurgia.The superior vena cava is formed by the union of the right and left brachiocephalic veins. It is located in the middle mediastinum, to the right of the aorta and anterior to the trachea. Superior vena cava syndrome consists of a group of signs (dilation of the veins in the neck, facial swelling, edema of the upper limbs, and cyanosis and symptoms (headache, dyspnea, cough, orthopnea and dysphagia caused by the obstruction of blood flow through the superior vena cava to the right atrium. This obstruction can be caused by extrinsic compression, tumor invasion or thrombosis. Such obstruction may also occur as a result of insufficient venous return

Kompetisi Stasiun Televisi Swasta Nasional Berdasarkan Superiority Direction dan Superiority Magnitude

Directory of Open Access Journals (Sweden)

Anastasia Winanti Riesardhy

2013-11-01

Full Text Available Abstract: Uses and gratification theory is employed particularly as the teoritical frame of the research to examine the extent to which ten national television stations compete to satisfy Indonesian audiences. In particular, two main concepts of that theory namely audiences “gratification sought and gratifications obtained, are broken down and counted based on superiority direction and superiority magnitude. In general, the findings show that those televisions have satisfied their audiences, although in terms of gratifications to dispersal motives, they haven’t satisfied as much as it was expected. Significant competition occurs between TRANSTV and TRANS7, RCTI and SCTV, and TVONE and METROTV. TVONE become the most satisfiyng television station. Abstrak: Teori Uses & Gratification menjadi dasar penelitian ini untuk mengukur bagaimana kompetisi yang terjadi di antara sepuluh stasiun televisi yang bersiaran secara nasional di Indonesia. Aplikasi dari teori tersebut dimunculkan dalam konsep kepuasan yang diharapkan dan kepuasan yang diperoleh ketika menonton acara televisi dan didasarkan pada penghitungan superiority direction dan superiority magnitude. Sepuluh stasiun televisi yang diteliti telah dapat memuaskan audiensnya, meskipun untuk kepuasan atas motif pengalihan masih belum dapat melampaui kepuasan yang diharapkan. Kompetisi yang signifikan terjadi antara TRANSTV dengan TRANS7, RCTI dengan SCTV serta TVONE dengan METROTV. TVONE menjadi stasiun televisi yang menduduki peringkat pertama dalam memberikan kepuasan tertinggi kepada audiens.

Maximum likelihood fitting of FROC curves under an initial-detection-and-candidate-analysis model

International Nuclear Information System (INIS)

Edwards, Darrin C.; Kupinski, Matthew A.; Metz, Charles E.; Nishikawa, Robert M.

2002-01-01

We have developed a model for FROC curve fitting that relates the observer's FROC performance not to the ROC performance that would be obtained if the observer's responses were scored on a per image basis, but rather to a hypothesized ROC performance that the observer would obtain in the task of classifying a set of 'candidate detections' as positive or negative. We adopt the assumptions of the Bunch FROC model, namely that the observer's detections are all mutually independent, as well as assumptions qualitatively similar to, but different in nature from, those made by Chakraborty in his AFROC scoring methodology. Under the assumptions of our model, we show that the observer's FROC performance is a linearly scaled version of the candidate analysis ROC curve, where the scaling factors are just given by the FROC operating point coordinates for detecting initial candidates. Further, we show that the likelihood function of the model parameters given observational data takes on a simple form, and we develop a maximum likelihood method for fitting a FROC curve to this data. FROC and AFROC curves are produced for computer vision observer datasets and compared with the results of the AFROC scoring method. Although developed primarily with computer vision schemes in mind, we hope that the methodology presented here will prove worthy of further study in other applications as well

Superiorized algorithm for reconstruction of CT images from sparse-view and limited-angle polyenergetic data

Science.gov (United States)

Humphries, T.; Winn, J.; Faridani, A.

2017-08-01

Recent work in CT image reconstruction has seen increasing interest in the use of total variation (TV) and related penalties to regularize problems involving reconstruction from undersampled or incomplete data. Superiorization is a recently proposed heuristic which provides an automatic procedure to ‘superiorize’ an iterative image reconstruction algorithm with respect to a chosen objective function, such as TV. Under certain conditions, the superiorized algorithm is guaranteed to find a solution that is as satisfactory as any found by the original algorithm with respect to satisfying the constraints of the problem; this solution is also expected to be superior with respect to the chosen objective. Most work on superiorization has used reconstruction algorithms which assume a linear measurement model, which in the case of CT corresponds to data generated from a monoenergetic x-ray beam. Many CT systems generate x-rays from a polyenergetic spectrum, however, in which the measured data represent an integral of object attenuation over all energies in the spectrum. This inconsistency with the linear model produces the well-known beam hardening artifacts, which impair analysis of CT images. In this work we superiorize an iterative algorithm for reconstruction from polyenergetic data, using both TV and an anisotropic TV (ATV) penalty. We apply the superiorized algorithm in numerical phantom experiments modeling both sparse-view and limited-angle scenarios. In our experiments, the superiorized algorithm successfully finds solutions which are as constraints-compatible as those found by the original algorithm, with significantly reduced TV and ATV values. The superiorized algorithm thus produces images with greatly reduced sparse-view and limited angle artifacts, which are also largely free of the beam hardening artifacts that would be present if a superiorized version of a monoenergetic algorithm were used.

Quantifying and Reducing Curve-Fitting Uncertainty in Isc

Energy Technology Data Exchange (ETDEWEB)

Campanelli, Mark; Duck, Benjamin; Emery, Keith

2015-06-14

Current-voltage (I-V) curve measurements of photovoltaic (PV) devices are used to determine performance parameters and to establish traceable calibration chains. Measurement standards specify localized curve fitting methods, e.g., straight-line interpolation/extrapolation of the I-V curve points near short-circuit current, Isc. By considering such fits as statistical linear regressions, uncertainties in the performance parameters are readily quantified. However, the legitimacy of such a computed uncertainty requires that the model be a valid (local) representation of the I-V curve and that the noise be sufficiently well characterized. Using more data points often has the advantage of lowering the uncertainty. However, more data points can make the uncertainty in the fit arbitrarily small, and this fit uncertainty misses the dominant residual uncertainty due to so-called model discrepancy. Using objective Bayesian linear regression for straight-line fits for Isc, we investigate an evidence-based method to automatically choose data windows of I-V points with reduced model discrepancy. We also investigate noise effects. Uncertainties, aligned with the Guide to the Expression of Uncertainty in Measurement (GUM), are quantified throughout.

Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution

Science.gov (United States)

Yunus, R. M.; Hasan, M. M.; Zubairi, Y. Z.

2017-09-01

In this study, the Tweedie distribution was used to fit the monthly rainfall data from 24 monitoring stations of Peninsula Malaysia for the period from January, 2008 to April, 2015. The aim of the study is to determine whether the distributions within the Tweedie family fit well the monthly Malaysian rainfall data. Within the Tweedie family, the gamma distribution is generally used for fitting the rainfall totals, however the Poisson-gamma distribution is more useful to describe two important features of rainfall pattern, which are the occurrences (dry months) and the amount (wet months). First, the appropriate distribution of the monthly rainfall was identified within the Tweedie family for each station. Then, the Tweedie Generalised Linear Model (GLM) with no explanatory variable was used to model the monthly rainfall data. Graphical representation was used to assess model appropriateness. The QQ plots of quantile residuals show that the Tweedie models fit the monthly rainfall data better for majority of the stations in the west coast and mid land than those in the east coast of Peninsula. This significant finding suggests that the best fitted distribution depends on the geographical location of the monitoring station. In this paper, a simple model is developed for generating synthetic rainfall data for use in various areas, including agriculture and irrigation. We have showed that the data that were simulated using the Tweedie distribution have fairly similar frequency histogram to that of the actual data. Both the mean number of rainfall events and mean amount of rain for a month were estimated simultaneously for the case that the Poisson gamma distribution fits the data reasonably well. Thus, this work complements previous studies that fit the rainfall amount and the occurrence of rainfall events separately, each to a different distribution.

A Bayesian Approach to Person Fit Analysis in Item Response Theory Models. Research Report.

Science.gov (United States)

Glas, Cees A. W.; Meijer, Rob R.

A Bayesian approach to the evaluation of person fit in item response theory (IRT) models is presented. In a posterior predictive check, the observed value on a discrepancy variable is positioned in its posterior distribution. In a Bayesian framework, a Markov Chain Monte Carlo procedure can be used to generate samples of the posterior distribution…

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.

A CAD System for Evaluating Footwear Fit

Science.gov (United States)

Savadkoohi, Bita Ture; de Amicis, Raffaele

With the great growth in footwear demand, the footwear manufacturing industry, for achieving commercial success, must be able to provide the footwear that fulfills consumer's requirement better than it's competitors. Accurate fitting for shoes is an important factor in comfort and functionality. Footwear fitter measurement have been using manual measurement for a long time, but the development of 3D acquisition devices and the advent of powerful 3D visualization and modeling techniques, automatically analyzing, searching and interpretation of the models have now made automatic determination of different foot dimensions feasible. In this paper, we proposed an approach for finding footwear fit within the shoe last data base. We first properly aligned the 3D models using "Weighted" Principle Component Analysis (WPCA). After solving the alignment problem we used an efficient algorithm for cutting the 3D model in order to find the footwear fit from shoe last data base.

Information Superiority through Data Warehousing

National Research Council Canada - National Science Library

Warner, Neil

2001-01-01

.... A precursor to a knowledge edge is Information Superiority. Within most current Command Support Systems minimal integration and fusion of data is undertaken to provide the basis of information superiority...

The Many Null Distributions of Person Fit Indices.

Science.gov (United States)

Molenaar, Ivo W.; Hoijtink, Herbert

1990-01-01

Statistical properties of person fit indices are reviewed as indicators of the extent to which a person's score pattern is in agreement with a measurement model. Distribution of a fit index and ability-free fit evaluation are discussed. The null distribution was simulated for a test of 20 items. (SLD)

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

Black Versus Gray T-Shirts: Comparison of Spectrophotometric and Other Biophysical Properties of Physical Fitness Uniforms and Modeled Heat Strain and Thermal Comfort

Science.gov (United States)

2016-09-01

PROPERTIES OF PHYSICAL FITNESS UNIFORMS AND MODELED HEAT STRAIN AND THERMAL COMFORT DISCLAIMER The opinions or assertions contained herein are the...SHIRTS: COMPARISON OF SPECTROPHOTOMETRIC AND OTHER BIOPHYSICAL PROPERTIES OF PHYSICAL FITNESS UNIFORMS AND MODELED HEAT STRAIN AND THERMAL COMFORT ...the impact of the environment on the wearer. To model these impacts on human thermal sensation (e.g., thermal comfort ) and thermoregulatory

Virtual Suit Fit Assessment Using Body Shape Model

Data.gov (United States)

National Aeronautics and Space Administration — Shoulder injury is one of the most serious risks for crewmembers in long-duration spaceflight. While suboptimal suit fit and contact pressures between the shoulder...

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. Copyright © 2016 Elsevier B.V. All rights reserved.

Two-Stage Method Based on Local Polynomial Fitting for a Linear Heteroscedastic Regression Model and Its Application in Economics

Directory of Open Access Journals (Sweden)

Liyun Su

2012-01-01

Full Text Available We introduce the extension of local polynomial fitting to the linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to nonparametric technique of local polynomial estimation, we do not need to know the heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we focus on comparison of parameters and reach an optimal fitting. Besides, we verify the asymptotic normality of parameters based on numerical simulations. Finally, this approach is applied to a case of economics, and it indicates that our method is surely effective in finite-sample situations.

Convolution based profile fitting

International Nuclear Information System (INIS)

Kern, A.; Coelho, A.A.; Cheary, R.W.

2002-01-01

Full text: In convolution based profile fitting, profiles are generated by convoluting functions together to form the observed profile shape. For a convolution of 'n' functions this process can be written as, Y(2θ)=F 1 (2θ)x F 2 (2θ)x... x F i (2θ)x....xF n (2θ). In powder diffractometry the functions F i (2θ) can be interpreted as the aberration functions of the diffractometer, but in general any combination of appropriate functions for F i (2θ) may be used in this context. Most direct convolution fitting methods are restricted to combinations of F i (2θ) that can be convoluted analytically (e.g. GSAS) such as Lorentzians, Gaussians, the hat (impulse) function and the exponential function. However, software such as TOPAS is now available that can accurately convolute and refine a wide variety of profile shapes numerically, including user defined profiles, without the need to convolute analytically. Some of the most important advantages of modern convolution based profile fitting are: 1) virtually any peak shape and angle dependence can normally be described using minimal profile parameters in laboratory and synchrotron X-ray data as well as in CW and TOF neutron data. This is possible because numerical convolution and numerical differentiation is used within the refinement procedure so that a wide range of functions can easily be incorporated into the convolution equation; 2) it can use physically based diffractometer models by convoluting the instrument aberration functions. This can be done for most laboratory based X-ray powder diffractometer configurations including conventional divergent beam instruments, parallel beam instruments, and diffractometers used for asymmetric diffraction. It can also accommodate various optical elements (e.g. multilayers and monochromators) and detector systems (e.g. point and position sensitive detectors) and has already been applied to neutron powder diffraction systems (e.g. ANSTO) as well as synchrotron based

Fitting outbreak models to data from many small norovirus outbreaks

Directory of Open Access Journals (Sweden)

Eamon B. O’Dea

2014-03-01

Full Text Available Infectious disease often occurs in small, independent outbreaks in populations with varying characteristics. Each outbreak by itself may provide too little information for accurate estimation of epidemic model parameters. Here we show that using standard stochastic epidemic models for each outbreak and allowing parameters to vary between outbreaks according to a linear predictor leads to a generalized linear model that accurately estimates parameters from many small and diverse outbreaks. By estimating initial growth rates in addition to transmission rates, we are able to characterize variation in numbers of initially susceptible individuals or contact patterns between outbreaks. With simulation, we find that the estimates are fairly robust to the data being collected at discrete intervals and imputation of about half of all infectious periods. We apply the method by fitting data from 75 norovirus outbreaks in health-care settings. Our baseline regression estimates are 0.0037 transmissions per infective-susceptible day, an initial growth rate of 0.27 transmissions per infective day, and a symptomatic period of 3.35 days. Outbreaks in long-term-care facilities had significantly higher transmission and initial growth rates than outbreaks in hospitals.

Minimal see-saw model predicting best fit lepton mixing angles

International Nuclear Information System (INIS)

King, Stephen F.

2013-01-01

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 e ,ν μ ,ν τ ) proportional to (0,1,1) and the right-handed neutrino mainly responsible for the solar neutrino mass has couplings to (ν e ,ν μ ,ν 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 4 family symmetry model of leptons, together with Z 3 and Z 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 2 /m 3 . The model predicts the lepton mixing angles θ 12 ≈34 ∘ ,θ 23 ≈41 ∘ ,θ 13 ≈9.5 ∘ , 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 ∘

GENFIT - a generic track-fitting toolkit

Energy Technology Data Exchange (ETDEWEB)

Rauch, Johannes [Technische Universitaet Muenchen (Germany); Schlueter, Tobias [Ludwig-Maximilians-Universitaet Muenchen (Germany)

2014-07-01

GENFIT is an experiment-independent track-fitting toolkit, which combines fitting algorithms, track representations, and measurement geometries into a modular framework. We report on a significantly improved version of GENFIT, based on experience gained in the Belle II, PANDA, and FOPI experiments. Improvements concern the implementation of additional track-fitting algorithms, enhanced implementations of Kalman fitters, enhanced visualization capabilities, and additional implementations of measurement types suited for various kinds of tracking detectors. The data model has been revised, allowing for efficient track merging, smoothing, residual calculation and alignment.

New ROOT Graphical User Interfaces for fitting

International Nuclear Information System (INIS)

Maline, D Gonzalez; Moneta, L; Antcheva, I

2010-01-01

ROOT, as a scientific data analysis framework, provides extensive capabilities via Graphical User Interfaces (GUI) for performing interactive analysis and visualizing data objects like histograms and graphs. A new interface for fitting has been developed for performing, exploring and comparing fits on data point sets such as histograms, multi-dimensional graphs or trees. With this new interface, users can build interactively the fit model function, set parameter values and constraints and select fit and minimization methods with their options. Functionality for visualizing the fit results is as well provided, with the possibility of drawing residuals or confidence intervals. Furthermore, the new fit panel reacts as a standalone application and it does not prevent users from interacting with other windows. We will describe in great detail the functionality of this user interface, covering as well new capabilities provided by the new fitting and minimization tools introduced recently in the ROOT framework.

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.

A Comparison of Competing Models for Understanding Industrial Organization’s Acceptance of Cloud Services

Directory of Open Access Journals (Sweden)

Shui-Lien Chen

2018-03-01

Full Text Available Cloud computing is the next generation in computing, and the next natural step in the evolution of on-demand information technology services and products. However, only a few studies have addressed the adoption of cloud computing from an organizational perspective, which have not proven whether the research model is the best-fitting model. The purpose of this paper is to construct research competing models (RCMs and determine the best-fitting model for understanding industrial organization’s acceptance of cloud services. This research integrated the technology acceptance model and the principle of model parsimony to develop four cloud service adoption RCMs with enterprise usage intention being used as a proxy for actual behavior, and then compared the RCMs using structural equation modeling (SEM. Data derived from a questionnaire-based survey of 227 firms in Taiwan were tested against the relationships through SEM. Based on the empirical study, the results indicated that, although all four RCMs had a high goodness of fit, in both nested and non-nested structure comparisons, research competing model A (Model A demonstrated superior performance and was the best-fitting model. This study introduced a model development strategy that can most accurately explain and predict the behavioral intention of organizations to adopt cloud services.

Innovation Rather than Improvement: A Solvable High-Dimensional Model Highlights the Limitations of Scalar Fitness

Science.gov (United States)

Tikhonov, Mikhail; Monasson, Remi

2018-01-01

Much of our understanding of ecological and evolutionary mechanisms derives from analysis of low-dimensional models: with few interacting species, or few axes defining "fitness". It is not always clear to what extent the intuition derived from low-dimensional models applies to the complex, high-dimensional reality. For instance, most naturally occurring microbial communities are strikingly diverse, harboring a large number of coexisting species, each of which contributes to shaping the environment of others. Understanding the eco-evolutionary interplay in these systems is an important challenge, and an exciting new domain for statistical physics. Recent work identified a promising new platform for investigating highly diverse ecosystems, based on the classic resource competition model of MacArthur. Here, we describe how the same analytical framework can be used to study evolutionary questions. Our analysis illustrates how, at high dimension, the intuition promoted by a one-dimensional (scalar) notion of fitness can become misleading. Specifically, while the low-dimensional picture emphasizes organism cost or efficiency, we exhibit a regime where cost becomes irrelevant for survival, and link this observation to generic properties of high-dimensional geometry.

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.

A bipartite fitness model for online music streaming services

Science.gov (United States)

Pongnumkul, Suchit; Motohashi, Kazuyuki

2018-01-01

This paper proposes an evolution model and an analysis of the behavior of music consumers on online music streaming services. While previous studies have observed power-law degree distributions of usage in online music streaming services, the underlying behavior of users has not been well understood. Users and songs can be described using a bipartite network where an edge exists between a user node and a song node when the user has listened that song. The growth mechanism of bipartite networks has been used to understand the evolution of online bipartite networks Zhang et al. (2013). Existing bipartite models are based on a preferential attachment mechanism László Barabási and Albert (1999) in which the probability that a user listens to a song is proportional to its current popularity. This mechanism does not allow for two types of real world phenomena. First, a newly released song with high quality sometimes quickly gains popularity. Second, the popularity of songs normally decreases as time goes by. Therefore, this paper proposes a new model that is more suitable for online music services by adding fitness and aging functions to the song nodes of the bipartite network proposed by Zhang et al. (2013). Theoretical analyses are performed for the degree distribution of songs. Empirical data from an online streaming service, Last.fm, are used to confirm the degree distribution of the object nodes. Simulation results show improvements from a previous model. Finally, to illustrate the application of the proposed model, a simplified royalty cost model for online music services is used to demonstrate how the changes in the proposed parameters can affect the costs for online music streaming providers. Managerial implications are also discussed.

Comparative Evaluation of Conventional and Accelerated Castings on Marginal Fit and Surface Roughness

Science.gov (United States)

Jadhav, Vivek Dattatray; Motwani, Bhagwan K.; Shinde, Jitendra; Adhapure, Prasad

2017-01-01

Aims: The aim of this study was to evaluate the marginal fit and surface roughness of complete cast crowns made by a conventional and an accelerated casting technique. Settings and Design: This study was divided into three parts. In Part I, the marginal fit of full metal crowns made by both casting techniques in the vertical direction was checked, in Part II, the fit of sectional metal crowns in the horizontal direction made by both casting techniques was checked, and in Part III, the surface roughness of disc-shaped metal plate specimens made by both casting techniques was checked. Materials and Methods: A conventional technique was compared with an accelerated technique. In Part I of the study, the marginal fit of the full metal crowns as well as in Part II, the horizontal fit of sectional metal crowns made by both casting techniques was determined, and in Part III, the surface roughness of castings made with the same techniques was compared. Statistical Analysis Used: The results of the t-test and independent sample test do not indicate statistically significant differences in the marginal discrepancy detected between the two casting techniques. Results: For the marginal discrepancy and surface roughness, crowns fabricated with the accelerated technique were significantly different from those fabricated with the conventional technique. Conclusions: Accelerated casting technique showed quite satisfactory results, but the conventional technique was superior in terms of marginal fit and surface roughness. PMID:29042726

Cardiorespiratory fitness modifies the relationship between myocardial function and cerebral blood flow in older adults.

Science.gov (United States)

Johnson, Nathan F; Gold, Brian T; Bailey, Alison L; Clasey, Jody L; Hakun, Jonathan G; White, Matthew; Long, Doug E; Powell, David K

2016-05-01

A growing body of evidence indicates that cardiorespiratory fitness attenuates some age-related cerebral declines. However, little is known about the role that myocardial function plays in this relationship. Brain regions with high resting metabolic rates, such as the default mode network (DMN), may be especially vulnerable to age-related declines in myocardial functions affecting cerebral blood flow (CBF). This study explored the relationship between a measure of myocardial mechanics, global longitudinal strain (GLS), and CBF to the DMN. In addition, we explored how cardiorespiratory affects this relationship. Participants were 30 older adults between the ages of 59 and 69 (mean age=63.73years, SD=2.8). Results indicated that superior cardiorespiratory fitness and myocardial mechanics were positively associated with DMN CBF. Moreover, results of a mediation analysis revealed that the relationship between GLS and DMN CBF was accounted for by individual differences in fitness. Findings suggest that benefits of healthy heart function to brain function are modified by fitness. Copyright © 2015 Elsevier Inc. All rights reserved.

ACCELERATED FITTING OF STELLAR SPECTRA

Energy Technology Data Exchange (ETDEWEB)

Ting, Yuan-Sen; Conroy, Charlie [Harvard–Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Rix, Hans-Walter [Max Planck Institute for Astronomy, Königstuhl 17, D-69117 Heidelberg (Germany)

2016-07-20

Stellar spectra are often modeled and fitted by interpolating within a rectilinear grid of synthetic spectra to derive the stars’ labels: stellar parameters and elemental abundances. However, the number of synthetic spectra needed for a rectilinear grid grows exponentially with the label space dimensions, precluding the simultaneous and self-consistent fitting of more than a few elemental abundances. Shortcuts such as fitting subsets of labels separately can introduce unknown systematics and do not produce correct error covariances in the derived labels. In this paper we present a new approach—Convex Hull Adaptive Tessellation (chat)—which includes several new ideas for inexpensively generating a sufficient stellar synthetic library, using linear algebra and the concept of an adaptive, data-driven grid. A convex hull approximates the region where the data lie in the label space. A variety of tests with mock data sets demonstrate that chat can reduce the number of required synthetic model calculations by three orders of magnitude in an eight-dimensional label space. The reduction will be even larger for higher dimensional label spaces. In chat the computational effort increases only linearly with the number of labels that are fit simultaneously. Around each of these grid points in the label space an approximate synthetic spectrum can be generated through linear expansion using a set of “gradient spectra” that represent flux derivatives at every wavelength point with respect to all labels. These techniques provide new opportunities to fit the full stellar spectra from large surveys with 15–30 labels simultaneously.

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...... distribution of the simulated random effects coincides with the assumed random effects distribution. In practice, the specified model depends on some unknown parameter which is replaced by an estimate. We obtain a correction for this by deriving the asymptotic distribution of the empirical distribution...

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...... distribution of the simulated random effects coincides with the assumed random effects distribution. In practice the specified model depends on some unknown parameter which is replaced by an estimate. We obtain a correction for this by deriving the asymptotic distribution of the empirical distribution function...

Introduction: Occam’s Razor (SOT - Fit for Purpose workshop introduction)

Science.gov (United States)

Mathematical models provide important, reproducible, and transparent information for risk-based decision making. However, these models must be constructed to fit the needs of the problem to be solved. A “fit for purpose” model is an abstraction of a complicated problem that allow...

VizieR Online Data Catalog: GRB prompt emission fitted with the DREAM model (Ahlgren+, 2015)

Science.gov (United States)

Ahlgren, B.; Larsson, J.; Nymark, T.; Ryde, F.; Pe'Er, A.

2018-01-01

We illustrate the application of the DREAM model by fitting it to two different, bright Fermi GRBs; GRB 090618 and GRB 100724B. While GRB 090618 is well fitted by a Band function, GRB 100724B was the first example of a burst with a significant additional BB component (Guiriec et al. 2011ApJ...727L..33G). GRB 090618 is analysed using Gamma-ray Burst Monitor (GBM) data (Meegan et al. 2009ApJ...702..791M) from the NaI and BGO detectors. For GRB 100724B, we used GBM data from the NaI and BGO detectors as well as Large Area Telescope Low Energy (LAT-LLE) data. For both bursts we selected NaI detectors seeing the GRB at an off-axis angle lower than 60° and the BGO detector as being the best aligned of the two BGO detectors. The spectra were fitted in the energy ranges 8-1000 keV (NaI), 200-40000 keV (BGO) and 30-1000 MeV (LAT-LLE). (2 data files).

Human X-chromosome inactivation pattern distributions fit a model of genetically influenced choice better than models of completely random choice

Science.gov (United States)

Renault, Nisa K E; Pritchett, Sonja M; Howell, Robin E; Greer, Wenda L; Sapienza, Carmen; Ørstavik, Karen Helene; Hamilton, David C

2013-01-01

In eutherian mammals, one X-chromosome in every XX somatic cell is transcriptionally silenced through the process of X-chromosome inactivation (XCI). Females are thus functional mosaics, where some cells express genes from the paternal X, and the others from the maternal X. The relative abundance of the two cell populations (X-inactivation pattern, XIP) can have significant medical implications for some females. In mice, the ‘choice' of which X to inactivate, maternal or paternal, in each cell of the early embryo is genetically influenced. In humans, the timing of XCI choice and whether choice occurs completely randomly or under a genetic influence is debated. Here, we explore these questions by analysing the distribution of XIPs in large populations of normal females. Models were generated to predict XIP distributions resulting from completely random or genetically influenced choice. Each model describes the discrete primary distribution at the onset of XCI, and the continuous secondary distribution accounting for changes to the XIP as a result of development and ageing. Statistical methods are used to compare models with empirical data from Danish and Utah populations. A rigorous data treatment strategy maximises information content and allows for unbiased use of unphased XIP data. The Anderson–Darling goodness-of-fit statistics and likelihood ratio tests indicate that a model of genetically influenced XCI choice better fits the empirical data than models of completely random choice. PMID:23652377

Burlington Northern Taconite Transshipment Facility, Duluth-Superior Harbor, Superior Wisconsin. Environmental Assessment Report.

Science.gov (United States)

1975-03-01

the Federal Government declared the Duluth- Superior area to be economically depressed . The reason given was the "consistant and chronic unemployment...include dogwood, sumac, arrowwood, blueberry, highbush cranberry , elderberry, wild grape, buttonbrush, snowberry and partridgeberry. Aquatic and...water for the proposed greenbelt areas and as dust sup- pression spray. 10.003 The depressed economy of the Duluth-Superior area would benefit by the

Ajuste de modelos estocásticos lineares e não-lineares para a descrição do perfil longitudinal de árvores Fitting linear and nonlinear stochastic models to describe longitudinal tree profile

Directory of Open Access Journals (Sweden)

Leonardo Machado Pires

2007-10-01

Full Text Available Os modelos polinomiais são mais difundidos no meio florestal brasileiro na descrição do perfil de árvores devido à sua facilidade de ajuste e precisão. O mesmo não ocorre com os modelos não-lineares, os quais possuem maior dificuldade de ajuste. Dentre os modelos não-lineares clássicos, na descrição do perfil, podem-se citar o de Gompertz, o Logístico e o de Weibull. Portanto, este estudo visou comparar os modelos lineares e não lineares para a descrição do perfil de árvores. As medidas de comparação foram o coeficiente de determinação (R², o erro-padrão residual (s yx, o coeficiente de determinação corrigido (R²ajustado, o gráfico dos resíduos e a facilidade de ajuste. Os resultados ressaltaram que, dentre os modelos não-lineares, o que obteve melhor desempenho, de forma geral, foi o modelo Logístico, apesar de o modelo de Gompertz ser melhor em termos de erro-padrão residual. Nos modelos lineares, o polinômio proposto por Pires & Calegario foi superior aos demais. Ao comparar os modelos não-lineares com os lineares, o modelo Logístico foi melhor em razão, principalmente, do fato de o comportamento dos dados ser não-linear, à baixa correlação entre os parâmetros e à fácil interpretação deles, facilitando a convergência e o ajuste.Polynomial models are most commonly used in Brazilian forestry for taper modeling due to its straightforwardly fitting and precision. The use of nonlinear regression classic models, like Gompertz, Logistic and Weibull, is not very common in Brazil. Therefore, this study aimed to verify the best nonlinear and linear models, and among these the best model to describe the longitudinal tree profile. The comparison measures were: R², syx, R²adjusted, residual graphics and fitting convergence. The results pointed out that among the non-linear models the best behavior, in general, was given by the Logistic model, although the Gompertz model was superior compared with the Weibull

Comments on Ghassib's "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?"

Science.gov (United States)

McCluskey, Ken W.

2010-01-01

This article presents the author's comments on Hisham B. Ghassib's "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?" Ghassib's article focuses on the transformation of science from pre-modern times to the present. Ghassib (2010) notes that, unlike in an earlier era when the economy depended on static…

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...

Non-linear least squares curve fitting of a simple theoretical model to radioimmunoassay dose-response data using a mini-computer

International Nuclear Information System (INIS)

Wilkins, T.A.; Chadney, D.C.; Bryant, J.; Palmstroem, S.H.; Winder, R.L.

1977-01-01

Using the simple univalent antigen univalent-antibody equilibrium model the dose-response curve of a radioimmunoassay (RIA) may be expressed as a function of Y, X and the four physical parameters of the idealised system. A compact but powerful mini-computer program has been written in BASIC for rapid iterative non-linear least squares curve fitting and dose interpolation with this function. In its simplest form the program can be operated in an 8K byte mini-computer. The program has been extensively tested with data from 10 different assay systems (RIA and CPBA) for measurement of drugs and hormones ranging in molecular size from thyroxine to insulin. For each assay system the results have been analysed in terms of (a) curve fitting biases and (b) direct comparison with manual fitting. In all cases the quality of fitting was remarkably good in spite of the fact that the chemistry of each system departed significantly from one or more of the assumptions implicit in the model used. A mathematical analysis of departures from the model's principal assumption has provided an explanation for this somewhat unexpected observation. The essential features of this analysis are presented in this paper together with the statistical analyses of the performance of the program. From these and the results obtained to date in the routine quality control of these 10 assays, it is concluded that the method of curve fitting and dose interpolation presented in this paper is likely to be of general applicability. (orig.) [de

Fits combining hyperon semileptonic decays and magnetic moments and CVC

International Nuclear Information System (INIS)

Bohm, A.; Kielanowski, P.

1982-10-01

We have performed a test of CVC by determining the baryon charges and magnetic moments from the hyperon semileptonic data. Then CVC was applied in order to make a joint fit of all baryon semileptonic decay data and baryon magnetic moments for the spectrum generating group (SG) model as well as for the conventional (cabibbo and magnetic moments in nuclear magnetons) model. The SG model gives a very good fit with chi 2 /n/sub D/ = 25/20 approximately equals 21% C.L. whereas the conventional model gives a fit with chi 2 /n/sub D/ = 244/20

Two Aspects of the Simplex Model: Goodness of Fit to Linear Growth Curve Structures and the Analysis of Mean Trends.

Science.gov (United States)

Mandys, Frantisek; Dolan, Conor V.; Molenaar, Peter C. M.

1994-01-01

Studied the conditions under which the quasi-Markov simplex model fits a linear growth curve covariance structure and determined when the model is rejected. Presents a quasi-Markov simplex model with structured means and gives an example. (SLD)

Determining Mission Statement Effectiveness from a Fit Perspective

Directory of Open Access Journals (Sweden)

Toh Seong-Yuen

2017-08-01

Full Text Available The purpose of this paper is to study the relationship between the organization's mission statement and its outcomes from a fit perspective in the alignment of the organization's structural and cultural elements. Based on an extension of Campbell's (1991 mission model by combination of ideas from two schools of thought in mission statement studies (structural and cultural, the authors introduce the concept of “fit” to show how it contributes towards a new mission statement model. The results show that both alignments are important to create a fit situation in order to positively impact organization outcomes. Based on Cohen (1988, the detected effect size of .322 is considered large. The managerial implication is that there should be more focus on managing organisational alignment to support a fit situation as this is instrumental to mission statement effectiveness. The originality of this study stems from the idea that while past studies develop model based on ideas from within the confine of a particular school of thought, this study is one of the first to combine ideas from both the structural and cultural schools of thought by extending Campbell's (1991 mission model using the fit perspective.

The fitting parameters extraction of conversion model of the low dose rate effect in bipolar devices

International Nuclear Information System (INIS)

Bakerenkov, Alexander

2011-01-01

The Enhanced Low Dose Rate Sensitivity (ELDRS) in bipolar devices consists of in base current degradation of NPN and PNP transistors increase as the dose rate is decreased. As a result of almost 20-year studying, the some physical models of effect are developed, being described in detail. Accelerated test methods, based on these models use in standards. The conversion model of the effect, that allows to describe the inverse S-shaped excess base current dependence versus dose rate, was proposed. This paper presents the problem of conversion model fitting parameters extraction.

Quantifying and Reducing Curve-Fitting Uncertainty in Isc: Preprint

Energy Technology Data Exchange (ETDEWEB)

Campanelli, Mark; Duck, Benjamin; Emery, Keith

2015-09-28

Current-voltage (I-V) curve measurements of photovoltaic (PV) devices are used to determine performance parameters and to establish traceable calibration chains. Measurement standards specify localized curve fitting methods, e.g., straight-line interpolation/extrapolation of the I-V curve points near short-circuit current, Isc. By considering such fits as statistical linear regressions, uncertainties in the performance parameters are readily quantified. However, the legitimacy of such a computed uncertainty requires that the model be a valid (local) representation of the I-V curve and that the noise be sufficiently well characterized. Using more data points often has the advantage of lowering the uncertainty. However, more data points can make the uncertainty in the fit arbitrarily small, and this fit uncertainty misses the dominant residual uncertainty due to so-called model discrepancy. Using objective Bayesian linear regression for straight-line fits for Isc, we investigate an evidence-based method to automatically choose data windows of I-V points with reduced model discrepancy. We also investigate noise effects. Uncertainties, aligned with the Guide to the Expression of Uncertainty in Measurement (GUM), are quantified throughout.

Marginal and internal fit of cobalt-chromium copings fabricated using the conventional and the direct metal laser sintering techniques: A comparative in vitro study.

Science.gov (United States)

Ullattuthodi, Sujana; Cherian, Kandathil Phillip; Anandkumar, R; Nambiar, M Sreedevi

2017-01-01

This in vitro study seeks to evaluate and compare the marginal and internal fit of cobalt-chromium copings fabricated using the conventional and direct metal laser sintering (DMLS) techniques. A master model of a prepared molar tooth was made using cobalt-chromium alloy. Silicone impression of the master model was made and thirty standardized working models were then produced; twenty working models for conventional lost-wax technique and ten working models for DMLS technique. A total of twenty metal copings were fabricated using two different production techniques: conventional lost-wax method and DMLS; ten samples in each group. The conventional and DMLS copings were cemented to the working models using glass ionomer cement. Marginal gap of the copings were measured at predetermined four points. The die with the cemented copings are standardized-sectioned with a heavy duty lathe. Then, each sectioned samples were analyzed for the internal gap between the die and the metal coping using a metallurgical microscope. Digital photographs were taken at ×50 magnification and analyzed using measurement software. Statistical analysis was done by unpaired t -test and analysis of variance (ANOVA). The results of this study reveal that no significant difference was present in the marginal gap of conventional and DMLS copings ( P > 0.05) by means of ANOVA. The mean values of internal gap of DMLS copings were significantly greater than that of conventional copings ( P < 0.05). Within the limitations of this in vitro study, it was concluded that the internal fit of conventional copings was superior to that of the DMLS copings. Marginal fit of the copings fabricated by two different techniques had no significant difference.

Superior oblique luxation and trochlear luxation as new concepts in superior oblique muscle weakening surgery

NARCIS (Netherlands)

Mombaerts, I.; Koornneef, L.; Everhard-Halm, Y. S.; Hughes, D. S.; Maillette de Buy Wenniger-Prick, L. J.

1995-01-01

We used superior oblique luxation and trochlear luxation as new surgical procedures to treat acquired Brown's syndrome and superior oblique muscle overaction. We studied nine patients (11 eyes) who underwent trochlear surgery between 1988 and 1993. Four patients had acquired Brown's syndrome and

Electrical stimulation of superior colliculus affects strabismus angle in monkey models for strabismus

Science.gov (United States)

Upadhyaya, Suraj; Meng, Hui

2017-01-01

Disruption of binocular vision during the critical period for development leads to eye misalignment in humans and in monkey models. We have previously suggested that disruption within a vergence circuit could be the neural basis for strabismus. Electrical stimulation in the rostral superior colliculus (rSC) leads to vergence eye movements in normal monkeys. Therefore, the purpose of this study was to investigate the effect of SC stimulation on eye misalignment in strabismic monkeys. Electrical stimulation was delivered to 51 sites in the intermediate and deep layers of the SC (400 Hz, 0.5-s duration, 10–40 μA) in 3 adult optical prism-reared strabismic monkeys. Scleral search coils were used to measure movements of both eyes during a fixation task. Staircase saccades with horizontal and vertical components were elicited by stimulation as predicted from the SC topographic map. Electrical stimulation also resulted in significant changes in horizontal strabismus angle, i.e., a shift toward exotropia/esotropia depending on stimulation site. Electrically evoked saccade vector amplitude in the two eyes was not significantly different (P > 0.05; paired t-test) but saccade direction differed. However, saccade disconjugacy accounted for only ~50% of the change in horizontal misalignment while disconjugate postsaccadic movements accounted for the other ~50% of the change in misalignment due to electrical stimulation. In summary, our data suggest that electrical stimulation of the SC of strabismic monkeys produces a change in horizontal eye alignment that is due to a combination of disconjugate saccadic eye movements and disconjugate postsaccadic movements. NEW & NOTEWORTHY Electrical stimulation of the superior colliculus in strabismic monkeys results in a change in eye misalignment. These data support the notion of developmental disruption of vergence circuits leading to maintenance of eye misalignment in strabismus. PMID:28031397

Theoretically unprejudiced fits to proton scattering

International Nuclear Information System (INIS)

Kobos, A.M.; Mackintosh, R.S.

1979-01-01

By using a spline interpolation method applied to all components of the proton optical potential we have fitted elastic scattering from 40 Ca and from 16 O at a range of energies. The potentials are highly oscillatory and we have shown that similar oscillations are found when the spline fitting procedure is applied to pseudo-data generated from potentials of known l-dependence. Moreover, we show how to find an l-independent potential equivalent to one that is l-dependent and we find that it is oscillatory and that various characteristic features of empirical spline fit potentials can be explained. Thus, by fitting the data with model indenpendt l-independent potentials we have found support for the contention that the nucleon optical potential should be viewed as being l-dependent. This work may be regarded as an example of the kind of physical information that can be gained by pursuing exact fits to proton elastic scattering data

A comparison of approaches in fitting continuum SEDs

International Nuclear Information System (INIS)

Liu Yao; Wang Hong-Chi; Madlener David; Wolf Sebastian

2013-01-01

We present a detailed comparison of two approaches, the use of a pre-calculated database and simulated annealing (SA), for fitting the continuum spectral energy distribution (SED) of astrophysical objects whose appearance is dominated by surrounding dust. While pre-calculated databases are commonly used to model SED data, only a few studies to date employed SA due to its unclear accuracy and convergence time for this specific problem. From a methodological point of view, different approaches lead to different fitting quality, demand on computational resources and calculation time. We compare the fitting quality and computational costs of these two approaches for the task of SED fitting to provide a guide to the practitioner to find a compromise between desired accuracy and available resources. To reduce uncertainties inherent to real datasets, we introduce a reference model resembling a typical circumstellar system with 10 free parameters. We derive the SED of the reference model with our code MC3 D at 78 logarithmically distributed wavelengths in the range [0.3 μm, 1.3 mm] and use this setup to simulate SEDs for the database and SA. Our result directly demonstrates the applicability of SA in the field of SED modeling, since the algorithm regularly finds better solutions to the optimization problem than a pre-calculated database. As both methods have advantages and shortcomings, a hybrid approach is preferable. While the database provides an approximate fit and overall probability distributions for all parameters deduced using Bayesian analysis, SA can be used to improve upon the results returned by the model grid.

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  

Adaptive memory: young children show enhanced retention of fitness-related information.

Science.gov (United States)

Aslan, Alp; Bäuml, Karl-Heinz T

2012-01-01

Evolutionary psychologists propose that human cognition evolved through natural selection to solve adaptive problems related to survival and reproduction, with its ultimate function being the enhancement of reproductive fitness. Following this proposal and the evolutionary-developmental view that ancestral selection pressures operated not only on reproductive adults, but also on pre-reproductive children, the present study examined whether young children show superior memory for information that is processed in terms of its survival value. In two experiments, we found such survival processing to enhance retention in 4- to 10-year-old children, relative to various control conditions that also required deep, meaningful processing but were not related to survival. These results suggest that, already in very young children, survival processing is a special and extraordinarily effective form of memory encoding. The results support the functional-evolutionary proposal that young children's memory is "tuned" to process and retain fitness-related information. Copyright © 2011 Elsevier B.V. All rights reserved.

LOCO with Constraints and Improved Fitting Technique

International Nuclear Information System (INIS)

Not Available

2007-01-01

LOCO has been a powerful beam-based diagnostics and optics control method for storage rings and synchrotrons worldwide ever since it was established at NSLS by J. Safranek. This method measures the orbit response matrix and optionally the dispersion function of the machine. The data are then fitted to a lattice model by adjusting parameters such as quadrupole and skew quadrupole strengths in the model, BPM gains and rolls, corrector gains and rolls of the measurement system. Any abnormality of the machine that affects the machine optics can then be identified. The resulting lattice model is equivalent to the real machine lattice as seen by the BPMs. Since there are usually two or more BPMs per betatron period in modern circular accelerators, the model is often a very accurate representation of the real machine. According to the fitting result, one can correct the machine lattice to the design lattice by changing the quadrupole and skew quadrupole strengths. LOCO is so important that it is routinely performed at many electron storage rings to guarantee machine performance, especially after the Matlab-based LOCO code became available. However, for some machines, LOCO is not easy to carry out. In some cases, LOCO fitting converges to an unrealistic solution with large changes to the quadrupole strengths ΔK. The quadrupole gradient changes can be so large that the resulting lattice model fails to find a closed orbit and subsequent iterations become impossible. In cases when LOCO converges, the solution can have ΔK that is larger than realistic and often along with a spurious zigzag pattern between adjacent quadrupoles. This degeneracy behavior of LOCO is due to the correlation between the fitting parameters - usually between neighboring quadrupoles. The fitting scheme is therefore less restrictive over certain patterns of changes to these quadrupoles with which the correlated quadrupoles fight each other and the net effect is very inefficient χ 2 reduction, i

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≤psystem approaches exponentially fast to the consensus state of the initial majority opinion. The 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 1/2system initially relaxes to a state with an even coexistence of opinions, but eventually reaches consensus by finite-size fluctuations. The approach to the coexistence state is monotonic for 1/2oscillations around the coexistence value. The final approach to coexistence is approximately a power law t^{-b(p)} in both regimes, where the exponent b increases with p. Also, τ increases respect to the standard voter 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∼N^{β}, with β≃1.45.

Alternate superior Julia sets

International Nuclear Information System (INIS)

Yadav, Anju; Rani, Mamta

2015-01-01

Alternate Julia sets have been studied in Picard iterative procedures. The purpose of this paper is to study the quadratic and cubic maps using superior iterates to obtain Julia sets with different alternate structures. Analytically, graphically and computationally it has been shown that alternate superior Julia sets can be connected, disconnected and totally disconnected, and also fattier than the corresponding alternate Julia sets. A few examples have been studied by applying different type of alternate structures

Fitness of crop-wild hybrid sunflower under competitive conditions: implications for crop-to-wild introgression.

Science.gov (United States)

Mercer, Kristin L; Emry, D Jason; Snow, Allison A; Kost, Matthew A; Pace, Brian A; Alexander, Helen M

2014-01-01

Understanding the likelihood and extent of introgression of novel alleles in hybrid zones requires comparison of lifetime fitness of parents and hybrid progeny. However, fitness differences among cross types can vary depending on biotic conditions, thereby influencing introgression patterns. Based on past work, we predicted that increased competition would enhance introgression between cultivated and wild sunflower (Helianthus annuus) by reducing fitness advantages of wild plants. To test this prediction, we established a factorial field experiment in Kansas, USA where we monitored the fitness of four cross types (Wild, F1, F2, and BCw hybrids) under different levels of interspecific and intraspecific competition. Intraspecific manipulations consisted both of density of competitors and of frequency of crop-wild hybrids. We recorded emergence of overwintered seeds, survival to reproduction, and numbers of seeds produced per reproductive plant. We also calculated two compound fitness measures: seeds produced per emerged seedling and seeds produced per planted seed. Cross type and intraspecific competition affected emergence and survival to reproduction, respectively. Further, cross type interacted with competitive treatments to influence all other fitness traits. More intense competition treatments, especially related to density of intraspecific competitors, repeatedly reduced the fitness advantage of wild plants when considering seeds produced per reproductive plant and per emerged seedling, and F2 plants often became indistinguishable from the wilds. Wild fitness remained superior when seedling emergence was also considered as part of fitness, but the fitness of F2 hybrids relative to wild plants more than quadrupled with the addition of interspecific competitors and high densities of intraspecific competitors. Meanwhile, contrary to prediction, lower hybrid frequency reduced wild fitness advantage. These results emphasize the importance of taking a full life cycle

Fitness of crop-wild hybrid sunflower under competitive conditions: implications for crop-to-wild introgression.

Directory of Open Access Journals (Sweden)

Kristin L Mercer

Full Text Available Understanding the likelihood and extent of introgression of novel alleles in hybrid zones requires comparison of lifetime fitness of parents and hybrid progeny. However, fitness differences among cross types can vary depending on biotic conditions, thereby influencing introgression patterns. Based on past work, we predicted that increased competition would enhance introgression between cultivated and wild sunflower (Helianthus annuus by reducing fitness advantages of wild plants. To test this prediction, we established a factorial field experiment in Kansas, USA where we monitored the fitness of four cross types (Wild, F1, F2, and BCw hybrids under different levels of interspecific and intraspecific competition. Intraspecific manipulations consisted both of density of competitors and of frequency of crop-wild hybrids. We recorded emergence of overwintered seeds, survival to reproduction, and numbers of seeds produced per reproductive plant. We also calculated two compound fitness measures: seeds produced per emerged seedling and seeds produced per planted seed. Cross type and intraspecific competition affected emergence and survival to reproduction, respectively. Further, cross type interacted with competitive treatments to influence all other fitness traits. More intense competition treatments, especially related to density of intraspecific competitors, repeatedly reduced the fitness advantage of wild plants when considering seeds produced per reproductive plant and per emerged seedling, and F2 plants often became indistinguishable from the wilds. Wild fitness remained superior when seedling emergence was also considered as part of fitness, but the fitness of F2 hybrids relative to wild plants more than quadrupled with the addition of interspecific competitors and high densities of intraspecific competitors. Meanwhile, contrary to prediction, lower hybrid frequency reduced wild fitness advantage. These results emphasize the importance of taking

Fitness of Crop-Wild Hybrid Sunflower under Competitive Conditions: Implications for Crop-to-Wild Introgression

Science.gov (United States)

Mercer, Kristin L.; Emry, D. Jason; Snow, Allison A.; Kost, Matthew A.; Pace, Brian A.; Alexander, Helen M.

2014-01-01

Understanding the likelihood and extent of introgression of novel alleles in hybrid zones requires comparison of lifetime fitness of parents and hybrid progeny. However, fitness differences among cross types can vary depending on biotic conditions, thereby influencing introgression patterns. Based on past work, we predicted that increased competition would enhance introgression between cultivated and wild sunflower (Helianthus annuus) by reducing fitness advantages of wild plants. To test this prediction, we established a factorial field experiment in Kansas, USA where we monitored the fitness of four cross types (Wild, F1, F2, and BCw hybrids) under different levels of interspecific and intraspecific competition. Intraspecific manipulations consisted both of density of competitors and of frequency of crop-wild hybrids. We recorded emergence of overwintered seeds, survival to reproduction, and numbers of seeds produced per reproductive plant. We also calculated two compound fitness measures: seeds produced per emerged seedling and seeds produced per planted seed. Cross type and intraspecific competition affected emergence and survival to reproduction, respectively. Further, cross type interacted with competitive treatments to influence all other fitness traits. More intense competition treatments, especially related to density of intraspecific competitors, repeatedly reduced the fitness advantage of wild plants when considering seeds produced per reproductive plant and per emerged seedling, and F2 plants often became indistinguishable from the wilds. Wild fitness remained superior when seedling emergence was also considered as part of fitness, but the fitness of F2 hybrids relative to wild plants more than quadrupled with the addition of interspecific competitors and high densities of intraspecific competitors. Meanwhile, contrary to prediction, lower hybrid frequency reduced wild fitness advantage. These results emphasize the importance of taking a full life cycle

Sacroiliac joint stability: Finite element analysis of implant number, orientation, and superior implant length.

Science.gov (United States)

Lindsey, Derek P; Kiapour, Ali; Yerby, Scott A; Goel, Vijay K

2018-03-18

To analyze how various implants placement variables affect sacroiliac (SI) joint range of motion. An experimentally validated finite element model of the lumbar spine and pelvis was used to simulate a fusion of the SI joint using various placement configurations of triangular implants (iFuse Implant System ® ). Placement configurations were varied by changing implant orientation, superior implant length, and number of implants. The range of motion of the SI joint was calculated using a constant moment of 10 N-m with a follower load of 400 N. The changes in motion were compared between the treatment groups to assess how the different variables affected the overall motion of the SI joint. Transarticular placement of 3 implants with superior implants that end in the middle of the sacrum resulted in the greatest reduction in range of motion (flexion/extension = 73%, lateral bending = 42%, axial rotation = 72%). The range of motions of the SI joints were reduced with use of transarticular orientation (9%-18%) when compared with an inline orientation. The use of a superior implant that ended mid-sacrum resulted in median reductions of (8%-14%) when compared with a superior implant that ended in the middle of the ala. Reducing the number of implants, resulted in increased SI joint range of motions for the 1 and 2 implant models of 29%-133% and 2%-39%, respectively, when compared with the 3 implant model. Using a validated finite element model we demonstrated that placement of 3 implants across the SI joint using a transarticular orientation with superior implant reaching the sacral midline resulted in the most stable construct. Additional clinical studies may be required to confirm these results.

Physical Work Demands and Fitness

DEFF Research Database (Denmark)

Larsen, Mette Korshøj

. The effects were evaluated with objective physiological or diurnal data in an intention-to-treat analysis using multi-adjusted mixed models. The results indicated that the intervention led to several improvements in risk factors for cardiovascular disease, e.g. enhanced cardiorespiratory fitness, reduced...... exposed to high relative aerobic workloads obtained more pronounced increases of resting and 24-hour ambulatory blood pressure, an unaltered cardiorespiratory fitness and a reduced sleeping heart rate. The enhanced resting and 24-hour ambulatory blood pressure may be explained as a potential...

The role of social capital and community belongingness for exercise adherence: An exploratory study of the CrossFit gym model.

Science.gov (United States)

Whiteman-Sandland, Jessica; Hawkins, Jemma; Clayton, Debbie

2016-08-01

This is the first study to measure the 'sense of community' reportedly offered by the CrossFit gym model. A cross-sectional study adapted Social Capital and General Belongingness scales to compare perceptions of a CrossFit gym and a traditional gym. CrossFit gym members reported significantly higher levels of social capital (both bridging and bonding) and community belongingness compared with traditional gym members. However, regression analysis showed neither social capital, community belongingness, nor gym type was an independent predictor of gym attendance. Exercise and health professionals may benefit from evaluating further the 'sense of community' offered by gym-based exercise programmes.

Covariances for neutron cross sections calculated using a regional model based on local-model fits to experimental data

Energy Technology Data Exchange (ETDEWEB)

Smith, D.L.; Guenther, P.T.

1983-11-01

We suggest a procedure for estimating uncertainties in neutron cross sections calculated with a nuclear model descriptive of a specific mass region. It applies standard error propagation techniques, using a model-parameter covariance matrix. Generally, available codes do not generate covariance information in conjunction with their fitting algorithms. Therefore, we resort to estimating a relative covariance matrix a posteriori from a statistical examination of the scatter of elemental parameter values about the regional representation. We numerically demonstrate our method by considering an optical-statistical model analysis of a body of total and elastic scattering data for the light fission-fragment mass region. In this example, strong uncertainty correlations emerge and they conspire to reduce estimated errors to some 50% of those obtained from a naive uncorrelated summation in quadrature. 37 references.

Covariances for neutron cross sections calculated using a regional model based on local-model fits to experimental data

International Nuclear Information System (INIS)

Smith, D.L.; Guenther, P.T.

1983-11-01

We suggest a procedure for estimating uncertainties in neutron cross sections calculated with a nuclear model descriptive of a specific mass region. It applies standard error propagation techniques, using a model-parameter covariance matrix. Generally, available codes do not generate covariance information in conjunction with their fitting algorithms. Therefore, we resort to estimating a relative covariance matrix a posteriori from a statistical examination of the scatter of elemental parameter values about the regional representation. We numerically demonstrate our method by considering an optical-statistical model analysis of a body of total and elastic scattering data for the light fission-fragment mass region. In this example, strong uncertainty correlations emerge and they conspire to reduce estimated errors to some 50% of those obtained from a naive uncorrelated summation in quadrature. 37 references

Modelling the association between weight status and social deprivation in English school children: Can physical activity and fitness affect the relationship?

Science.gov (United States)

Nevill, Alan M; Duncan, Michael J; Lahart, Ian; Sandercock, Gavin

2016-11-01

The association between being overweight/obese and deprivation is a serious concern in English schoolchildren. To model this association incorporating known confounders and to discover whether physical fitness and physical activity may reduce or eliminate this association. Cross-sectional data were collected between 2007-2009, from 8053 10-16 year old children from the East-of-England Healthy Heart Study. Weight status was assessed using waist circumference (cm) and body mass (kg). Deprivation was measured using the Index of Multiple Deprivation (IMD). Confounding variables used in the proportional, allometric models were hip circumference, stature, age and sex. Children's fitness levels were assessed using predicted VO 2 max (20-metre shuttle-run test) and physical activity was estimated using the Physical Activity Questionnaire for Adolescents or Children. A strong association was found between both waist circumference and body mass and the IMD. These associations persisted after controlling for all confounding variables. When the children's physical activity and fitness levels were added to the models, the association was either greatly reduced or, in the case of body mass, absent. To reduce deprivation inequalities in children's weight-status, health practitioners should focus on increasing physical fitness via physical activity in areas of greater deprivation.

On the fit of models to covariances and methodology to the Bulletin.

Science.gov (United States)

Bentler, P M

1992-11-01

It is noted that 7 of the 10 top-cited articles in the Psychological Bulletin deal with methodological topics. One of these is the Bentler-Bonett (1980) article on the assessment of fit in covariance structure models. Some context is provided on the popularity of this article. In addition, a citation study of methodology articles appearing in the Bulletin since 1978 was carried out. It verified that publications in design, evaluation, measurement, and statistics continue to be important to psychological research. Some thoughts are offered on the role of the journal in making developments in these areas more accessible to psychologists.

Experimental Rugged Fitness Landscape in Protein Sequence Space

Science.gov (United States)

Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

2006-01-01

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12–130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7×104-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18–24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region. PMID:17183728

Experimental rugged fitness landscape in protein sequence space.

Science.gov (United States)

Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

2006-12-20

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4)-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

Experimental rugged fitness landscape in protein sequence space.

Directory of Open Access Journals (Sweden)

Yuuki Hayashi

Full Text Available The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1 the dependence of stationary fitness on library size, which increased gradually, and (2 the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

A hands-on approach for fitting long-term survival models under the GAMLSS framework.

Science.gov (United States)

de Castro, Mário; Cancho, Vicente G; Rodrigues, Josemar

2010-02-01

In many data sets from clinical studies there are patients insusceptible to the occurrence of the event of interest. Survival models which ignore this fact are generally inadequate. The main goal of this paper is to describe an application of the generalized additive models for location, scale, and shape (GAMLSS) framework to the fitting of long-term survival models. In this work the number of competing causes of the event of interest follows the negative binomial distribution. In this way, some well known models found in the literature are characterized as particular cases of our proposal. The model is conveniently parameterized in terms of the cured fraction, which is then linked to covariates. We explore the use of the gamlss package in R as a powerful tool for inference in long-term survival models. The procedure is illustrated with a numerical example. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

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.

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

International Nuclear Information System (INIS)

Singh, N. S. S.; Muthuvalu, M. S.; Asirvadam, V. S.

2014-01-01

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

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 effect-site concentrations tested ranged from 1 to 76 ng/mL and from 5 to 80 ng/mL for midazolam and alfentanil, respectively. Midazolam and alfentanil had synergistic effects in colonoscopy and EGD, but additivity was observed in the intersession group. Adequate prediction rates were 84% to 85% in the intersession group, 84% to 88% during colonoscopy, and 82% to 87% during EGD. The reduced Greco and Fixed alfentanil concentration required for 50% of the patients to achieve targeted response Hierarchy models performed better with comparable predictive strength. The reduced Greco model had the lowest AICc with strong correlation in all 3 phases of endoscopy. Dynamic, rather than fixed, γ and γalf in the Hierarchy model improved model 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

Estimation of error components in a multi-error linear regression model, with an application to track fitting

International Nuclear Information System (INIS)

Fruehwirth, R.

1993-01-01

We present an estimation procedure of the error components in a linear regression model with multiple independent stochastic error contributions. After solving the general problem we apply the results to the estimation of the actual trajectory in track fitting with multiple scattering. (orig.)

Spreadsheets, Graphing Calculators and the Line of Best Fit

Directory of Open Access Journals (Sweden)

Bernie O'Sullivan

2003-07-01

One technique that can now be done, almost mindlessly, is the line of best fit. Both the graphing calculator and the Excel spreadsheet produce models for collected data that appear to be very good fits, but upon closer scrutiny, are revealed to be quite poor. This article will examine one such case. I will couch the paper within the framework of a very good classroom investigation that will help generate students’ understanding of the basic principles of curve fitting and will enable them to produce a very accurate model of collected data by combining the technology of the graphing calculator and the spreadsheet.

Fitting Nonlinear Ordinary Differential Equation Models with Random Effects and Unknown Initial Conditions Using the Stochastic Approximation Expectation-Maximization (SAEM) Algorithm.

Science.gov (United States)

Chow, Sy-Miin; Lu, Zhaohua; Sherwood, Andrew; Zhu, Hongtu

2016-03-01

The past decade has evidenced the increased prevalence of irregularly spaced longitudinal data in social sciences. Clearly lacking, however, are modeling tools that allow researchers to fit dynamic models to irregularly spaced data, particularly data that show nonlinearity and heterogeneity in dynamical structures. We consider the issue of fitting multivariate nonlinear differential equation models with random effects and unknown initial conditions to irregularly spaced data. A stochastic approximation expectation-maximization algorithm is proposed and its performance is evaluated using a benchmark nonlinear dynamical systems model, namely, the Van der Pol oscillator equations. The empirical utility of the proposed technique is illustrated using a set of 24-h ambulatory cardiovascular data from 168 men and women. Pertinent methodological challenges and unresolved issues are discussed.

GMTR: two-dimensional geo-fit multitarget retrieval model for michelson interferometer for passive atmospheric sounding/environmental satellite observations.

Science.gov (United States)

Carlotti, Massimo; Brizzi, Gabriele; Papandrea, Enzo; Prevedelli, Marco; Ridolfi, Marco; Dinelli, Bianca Maria; Magnani, Luca

2006-02-01

We present a new retrieval model designed to analyze the observations of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), which is on board the ENVironmental SATellite (ENVISAT). The new geo-fit multitarget retrieval model (GMTR) implements the geo-fit two-dimensional inversion for the simultaneous retrieval of several targets including a set of atmospheric constituents that are not considered by the ground processor of the MIPAS experiment. We describe the innovative solutions adopted in the inversion algorithm and the main functionalities of the corresponding computer code. The performance of GMTR is compared with that of the MIPAS ground processor in terms of accuracy of the retrieval products. Furthermore, we show the capability of GMTR to resolve the horizontal structures of the atmosphere. The new retrieval model is implemented in an optimized computer code that is distributed by the European Space Agency as "open source" in a package that includes a full set of auxiliary data for the retrieval of 28 atmospheric targets.

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.

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...

Exploiting the information content of hydrological ''outliers'' for goodness-of-fit testing

Directory of Open Access Journals (Sweden)

F. Laio

2010-10-01

Full Text Available Validation of probabilistic models based on goodness-of-fit tests is an essential step for the frequency analysis of extreme events. The outcome of standard testing techniques, however, is mainly determined by the behavior of the hypothetical model, F_X(x, in the central part of the distribution, while the behavior in the tails of the distribution, which is indeed very relevant in hydrological applications, is relatively unimportant for the results of the tests. The maximum-value test, originally proposed as a technique for outlier detection, is a suitable, but seldom applied, technique that addresses this problem. The test is specifically targeted to verify if the maximum (or minimum values in the sample are consistent with the hypothesis that the distribution F_X(x is the real parent distribution. The application of this test is hindered by the fact that the critical values for the test should be numerically obtained when the parameters of F_X(x are estimated on the same sample used for verification, which is the standard situation in hydrological applications. We propose here a simple, analytically explicit, technique to suitably account for this effect, based on the application of censored L-moments estimators of the parameters. We demonstrate, with an application that uses artificially generated samples, the superiority of this modified maximum-value test with respect to the standard version of the test. We also show that the test has comparable or larger power with respect to other goodness-of-fit tests (e.g., chi-squared test, Anderson-Darling test, Fung and Paul test, in particular when dealing with small samples (sample size lower than 20–25 and when the parent distribution is similar to the distribution being tested.

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.

CUSUM-based person-fit statistics for adaptive testing

NARCIS (Netherlands)

van Krimpen-Stoop, Edith; Meijer, R.R.

2001-01-01

Item scores that do not fit an assumed item response theory model may cause the latent trait value to be inaccurately estimated. Several person-fit statistics for detecting nonfitting score patterns for paper-and-pencil tests have been proposed. In the context of computerized adaptive tests (CAT),

CUSUM-based person-fit statistics for adaptive testing

NARCIS (Netherlands)

van Krimpen-Stoop, Edith; Meijer, R.R.

1999-01-01

Item scores that do not fit an assumed item response theory model may cause the latent trait value to be estimated inaccurately. Several person-fit statistics for detecting nonfitting score patterns for paper-and-pencil tests have been proposed. In the context of computerized adaptive tests (CAT),

Isochrone Fitting of Hubble Photometry in UV–VIS–IR Bands

Science.gov (United States)

Barker, Hallie; Paust, Nathaniel E. Q.

2018-03-01

We present new isochrone fits to color–magnitude diagrams from Hubble Space Telescope Wide Field Camera 3 and Advanced Camera for Surveys photometry of the globular clusters M13 and M80 in five bands from the ultraviolet to near-infrared. Isochrone fits to the photometry using the Dartmouth Stellar Evolution Program (DSEP), the PAdova and TRieste Stellar Evolution Code (PARSEC), and MESA Isochrones and Stellar Tracks (MIST) are examined to study the isochrone morphology. Additionally, cluster ages, extinctions, and distances are found from the visible-infrared color–magnitude diagrams. We conduct careful qualitative analysis on the inconsistencies of the fits across twelve color combinations of the five observed bands, and find that the (F606W‑F814W) color generally produces very good fits, but that there are large discrepancies when the data is fit using colors including UV bands for all three models. We also find that the best fits in the UV are achieved using MIST isochrones, but that they require metallicities that are lower than the other two models, as well published spectroscopic values. Finally, we directly compare DSEP and PARSEC by performing isochrone-isochrone fitting, and find that, for globular cluster aged populations, similar appearing PARSEC isochrones are on average 1.5 Gyr younger than DSEP isochrones. We find that the two models become less discrepant at lower metallicities.

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...

Fitting the e+e- → e+e- lineshape

International Nuclear Information System (INIS)

Martinez, M.; Miquel, R.

1992-01-01

The implications of different treatments of the e + e - →e + e - cross sections in the context of Z parameter fitting are discussed. We show that fitting with a complete description of the process might become important for an accurate determination of the Z parameters. A fitting formula describing the integrated cross section in terms of the Z parameters is presented. This formula agrees with the most accurate calculations in the Standard Model to within 1 per mil. (orig.)

Exploring the Influence of Neighborhood Characteristics on Burglary Risks: A Bayesian Random Effects Modeling Approach

Directory of Open Access Journals (Sweden)

Hongqiang Liu

2016-06-01

Full Text Available A Bayesian random effects modeling approach was used to examine the influence of neighborhood characteristics on burglary risks in Jianghan District, Wuhan, China. This random effects model is essentially spatial; a spatially structured random effects term and an unstructured random effects term are added to the traditional non-spatial Poisson regression model. Based on social disorganization and routine activity theories, five covariates extracted from the available data at the neighborhood level were used in the modeling. Three regression models were fitted and compared by the deviance information criterion to identify which model best fit our data. A comparison of the results from the three models indicates that the Bayesian random effects model is superior to the non-spatial models in fitting the data and estimating regression coefficients. Our results also show that neighborhoods with above average bar density and department store density have higher burglary risks. Neighborhood-specific burglary risks and posterior probabilities of neighborhoods having a burglary risk greater than 1.0 were mapped, indicating the neighborhoods that should warrant more attention and be prioritized for crime intervention and reduction. Implications and limitations of the study are discussed in our concluding section.

Time Series Modelling of Syphilis Incidence in China from 2005 to 2012.

Science.gov (United States)

Zhang, Xingyu; Zhang, Tao; Pei, Jiao; Liu, Yuanyuan; Li, Xiaosong; Medrano-Gracia, Pau

2016-01-01

The infection rate of syphilis in China has increased dramatically in recent decades, becoming a serious public health concern. Early prediction of syphilis is therefore of great importance for heath planning and management. In this paper, we analyzed surveillance time series data for primary, secondary, tertiary, congenital and latent syphilis in mainland China from 2005 to 2012. Seasonality and long-term trend were explored with decomposition methods. Autoregressive integrated moving average (ARIMA) was used to fit a univariate time series model of syphilis incidence. A separate multi-variable time series for each syphilis type was also tested using an autoregressive integrated moving average model with exogenous variables (ARIMAX). The syphilis incidence rates have increased three-fold from 2005 to 2012. All syphilis time series showed strong seasonality and increasing long-term trend. Both ARIMA and ARIMAX models fitted and estimated syphilis incidence well. All univariate time series showed highest goodness-of-fit results with the ARIMA(0,0,1)×(0,1,1) model. Time series analysis was an effective tool for modelling the historical and future incidence of syphilis in China. The ARIMAX model showed superior performance than the ARIMA model for the modelling of syphilis incidence. Time series correlations existed between the models for primary, secondary, tertiary, congenital and latent syphilis.

FITS: a function-fitting program

Energy Technology Data Exchange (ETDEWEB)

Balestrini, S.J.; Chezem, C.G.

1982-01-01

FITS is an iterating computer program that adjusts the parameters of a function to fit a set of data points according to the least squares criterion and then lists and plots the results. The function can be programmed or chosen from a library that is provided. The library can be expanded to include up to 99 functions. A general plotting routine, contained in the program but useful in its own right, is described separately in an Appendix.

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

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...... on the performance of the fuel cell.The two parameters are shown to be key elements in adjusting thethree-dimensional model to fit measured polarization curves.Results from the proposed model are compared to single cellmeasurements on a test MEA from IRD Fuel Cells.......A three-dimensional, computational fluid dynamics (CFD) model of a PEM fuel cell is presented. The model consists ofstraight channels, porous gas diffusion layers, porous catalystlayers and a membrane. In this computational domain, most ofthe transport phenomena which govern the performance of the...

Using a qualitative approach for understanding hospital-affiliated integrated clinical and fitness facilities: characteristics and members' experiences.

Science.gov (United States)

Yang, Jingzhen; Kingsbury, Diana; Nichols, Matthew; Grimm, Kristin; Ding, Kele; Hallam, Jeffrey

2015-06-19

With health care shifting away from the traditional sick care model, many hospitals are integrating fitness facilities and programs into their clinical services in order to support health promotion and disease prevention at the community level. Through a series of focus groups, the present study assessed characteristics of hospital-affiliated integrated facilities located in Northeast Ohio, United States and members' experiences with respect to these facilities. Adult members were invited to participate in a focus group using a recruitment flyer. A total of 6 focus groups were conducted in 2013, each lasting one hour, ranging from 5 to 12 participants per group. The responses and discussions were recorded and transcribed verbatim, then analyzed independently by research team members. Major themes were identified after consensus was reached. The participants' average age was 57, with 56.8% currently under a doctor's care. Four major themes associated with integrated facilities and members' experiences emerged across the six focus groups: 1) facility/program, 2) social atmosphere, 3) provider, and 4) member. Within each theme, several sub-themes were also identified. A key feature of integrated facilities is the availability of clinical and fitness services "under one roof". Many participants remarked that they initially attended physical therapy, becoming members of the fitness facility afterwards, or vice versa. The participants had favorable views of and experiences with the superior physical environment and atmosphere, personal attention, tailored programs, and knowledgeable, friendly, and attentive staff. In particular, participants favored the emphasis on preventive care and the promotion of holistic health and wellness. These results support the integration of wellness promotion and programming with traditional medical care and call for the further evaluation of such a model with regard to participants' health outcomes.

Segmental acetabular rim defects, bone loss, oversizing, and press fit cup in total hip arthroplasty evaluated with a probabilistic finite element analysis.

Science.gov (United States)

Amirouche, Farid; Solitro, Giovanni F; Walia, Amit; Gonzalez, Mark; Bobko, Aimee

2017-08-01

Management of segmental rim defects and bone mineral density (BMD) loss in the elderly prior to total hip replacement is unclear within classification systems for acetabular bone loss. In this study, our objectives were (1) to understand how a reduction in BMD in the elderly affects the oversizing of a press-fit cup for primary fixation and (2) to evaluate whether the location of the segmental defect affected cup fixation. A finite element (FE) model was used to simulate and evaluate cup insertion and fixation in the context of segmental rim defects. We focused on the distribution of patients over age 70 and used BMD (estimated from CT) as a proxy for aging's implications on THR and used probabilistic FE analysis to understand how BMD loss affects oversizing of a press-fit cup. A cup oversized by 1.10 ± 0.28 mm provides sufficient fixation and lower stresses at the cup-bone interface for elderly patients. Defects in the anterior column and posterior column both required the same mean insertion force for cup seating of 84% (taken as an average of 2 anterior column and 2 posterior column defects) compared to the control configuration, which was 5% greater than the insertion force for a superior rim defect and 12% greater than the insertion force for an inferior rim defect. A defect along the superior or inferior rim had a minimal effect on cup fixation, while a defect in the columns created cup instability and increased stress at the defect location.

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

Effects of High-Intensity Interval Training versus Continuous Training on Physical Fitness, Cardiovascular Function and Quality of Life in Heart Failure Patients.

Directory of Open Access Journals (Sweden)

Nathalie M M Benda

Full Text Available Physical fitness is an important prognostic factor in heart failure (HF. To improve fitness, different types of exercise have been explored, with recent focus on high-intensity interval training (HIT. We comprehensively compared effects of HIT versus continuous training (CT in HF patients NYHA II-III on physical fitness, cardiovascular function and structure, and quality of life, and hypothesize that HIT leads to superior improvements compared to CT.Twenty HF patients (male:female 19:1, 64±8 yrs, ejection fraction 38±6% were allocated to 12-weeks of HIT (10*1-minute at 90% maximal workload-alternated by 2.5 minutes at 30% maximal workload or CT (30 minutes at 60-75% of maximal workload. Before and after intervention, we examined physical fitness (incremental cycling test, cardiac function and structure (echocardiography, vascular function and structure (ultrasound and quality of life (SF-36, Minnesota living with HF questionnaire (MLHFQ.Training improved maximal workload, peak oxygen uptake (VO2peak related to the predicted VO2peak, oxygen uptake at the anaerobic threshold, and maximal oxygen pulse (all P<0.05, whilst no differences were present between HIT and CT (N.S.. We found no major changes in resting cardiovascular function and structure. SF-36 physical function score improved after training (P<0.05, whilst SF-36 total score and MLHFQ did not change after training (N.S..Training induced significant improvements in parameters of physical fitness, although no evidence for superiority of HIT over CT was demonstrated. No major effect of training was found on cardiovascular structure and function or quality of life in HF patients NYHA II-III.Nederlands Trial Register NTR3671.

Fitness for duty: A tried-and-true model for decision making

International Nuclear Information System (INIS)

Horn, G.L.

1989-01-01

The US Nuclear Regulatory Commission (NRC) rules and regulations pertaining to fitness for duty specify development of programs designed to ensure that nuclear power plant personnel are not under the influence of legal or illegal substances that cause mental or physical impairment of work performance such that public safety is compromised. These regulations specify the type of decision loop to employ in determining the employee's movement through the process of initial restriction of access to the point at which his access authorization is restores. Suggestions are also offered to determine the roles that various components of the organization should take in the decision loop. This paper discusses some implications and labor concerns arising from the suggested role of employee assistance programs (EAPs) in the decision loop for clinical assessment and return-to-work evaluation of chemical testing failures. A model for a decision loop addressing some of the issues raised is presented. The proposed model has been implemented in one nuclear facility and has withstood the scrutiny of an NRC audit

Superior versus inferior Ahmed glaucoma valve implantation.

Science.gov (United States)

Pakravan, Mohammad; Yazdani, Shahin; Shahabi, Camelia; Yaseri, Mehdi

2009-02-01

To compare the efficacy and safety of Ahmed glaucoma valve (AGV) (New World Medical Inc., Rancho Cucamonga, CA) implantation in the superior versus inferior quadrants. Prospective parallel cohort study. A total of 106 eyes of 106 patients with refractory glaucoma. Consecutive patients with refractory glaucoma underwent AGV implantation in the superior or inferior quadrants. Main outcome measures included intraocular pressure (IOP) and rate of complications. Other outcome measures included best corrected visual acuity (BCVA), number of glaucoma medications, and success rate (defined as at least 30% IOP reduction and 5glaucoma surgery, phthisis bulbi, or loss of light perception. Of a total of 106 eyes, 58 and 48 eyes underwent AGV implantation in the superior and inferior quadrants, respectively. Baseline characteristics were comparable in the study groups, except for preoperative IOP, which was higher in the superior group (P = 0.01). Patients were followed for a mean period of 10.6+/-8.49 months and 10.58+/-6.75 months in the superior and inferior groups, respectively (P = 0.477). BCVA was comparable between the groups at all postoperative visits (P>0.122). After 1 year, statistically significant but comparable IOP reduction from baseline (Pglaucoma medications was comparable after 1 year (1.3+/-1.2 vs. 1.9+/-0.8 for superior and inferior implants, respectively, P = 0.256). Success rates were also similar at 1 year: 27 eyes (81.8%) versus 20 eyes (95.2%) for superior and inferior implants, respectively (P = 0.227). However, the overall rate of complications, such as implant exposure necessitating removal, cosmetically unappealing appearance, and endophthalmitis, was higher in the inferior group: 12 eyes (25%) versus 3 eyes (5.2%) for superior and inferior groups, respectively, (P = 0.004). Superior and inferior AGV implants have similar intermediate efficacy in terms of IOP reduction, decrease in number of glaucoma medications, and preservation of vision. However

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.

Exploring the fitness landscape of poliovirus

Science.gov (United States)

Bianco, Simone; Acevedo, Ashely; Andino, Raul; Tang, Chao

2012-02-01

RNA viruses are known to display extraordinary adaptation capabilities to different environments, due to high mutation rates. Their very dynamical evolution is captured by the quasispecies concept, according to which the viral population forms a swarm of genetic variants linked through mutation, which cooperatively interact at a functional level and collectively contribute to the characteristics of the population. The description of the viral fitness landscape becomes paramount towards a more thorough understanding of the virus evolution and spread. The high mutation rate, together with the cooperative nature of the quasispecies, makes it particularly challenging to explore its fitness landscape. I will present an investigation of the dynamical properties of poliovirus fitness landscape, through both the adoption of new experimental techniques and theoretical models.

Probabilistic model fitting for spatio-temporal variability studies of precipitation: the Sara-Brut system - a case study

International Nuclear Information System (INIS)

Dorado Delgado, Jennifer; Burbano Criollo, Juan Carlos; Molina Tabares, Jose Manuel; Carvajal Escobar, Yesid; Aristizabal, Hector Fabio

2006-01-01

In this study, space and time variability of monthly and annual rainfall was analyzed for the downstream influence zone of a Colombian supply-regulation reservoir, Sara-Brut, located on the Cauca valley department. Monthly precipitation data from 18 gauge stations and for a 29-year record (1975-2003) were used. These data were processed by means of time series completion, consistency analyses and sample statistics computations. Theoretical probabilistic distribution models such as Gumbel, normal, lognormal and wake by, and other empirical distributions such as Weibull and Landwehr were applied in order to fit the historical precipitation data set. The fit standard error (FSE) was used to test the goodness of fit of the theoretical distribution models and to choose the best of this probabilistic function. The wake by approach showed the best goodness of fit in 89% of the total gauges taken into account. Time variability was analyzed by means of wake by estimated values of monthly and annual precipitation associated with return periods of 1,052, 1,25, 2, 10, 20 and 50 years. Precipitation space variability is presents by means of ArcGis v8.3 and using krigging as interpolation method. In general terms the results obtained from this study show significant distribution variability in precipitation over the whole area, and particularity, the formation of dry and humid nucleus over the northeastern strip and microclimates at the southwestern and central zone of the study area were observed, depending on the season of year. The mentioned distribution pattern is likely caused by the influence of pacific wind streams, which come from the Andean western mountain range. It is expected that the results from this work be helpful for future planning and hydrologic project design

Self-Fitting Hearing Aids

Directory of Open Access Journals (Sweden)

Gitte Keidser

2016-04-01

Full Text Available A self-contained, self-fitting hearing aid (SFHA is a device that enables the user to perform both threshold measurements leading to a prescribed hearing aid setting and fine-tuning, without the need for audiological support or access to other equipment. The SFHA has been proposed as a potential solution to address unmet hearing health care in developing countries and remote locations in the developed world and is considered a means to lower cost and increase uptake of hearing aids in developed countries. This article reviews the status of the SFHA and the evidence for its feasibility and challenges and predicts where it is heading. Devices that can be considered partly or fully self-fitting without audiological support were identified in the direct-to-consumer market. None of these devices are considered self-contained as they require access to other hardware such as a proprietary interface, computer, smartphone, or tablet for manipulation. While there is evidence that self-administered fitting processes can provide valid and reliable results, their success relies on user-friendly device designs and interfaces and easy-to-interpret instructions. Until these issues have been sufficiently addressed, optional assistance with the self-fitting process and on-going use of SFHAs is recommended. Affordability and a sustainable delivery system remain additional challenges for the SFHA in developing countries. Future predictions include a growth in self-fitting products, with most future SFHAs consisting of earpieces that connect wirelessly with a smartphone and providers offering assistance through a telehealth infrastructure, and the integration of SFHAs into the traditional hearing health-care model.

Estimating the fitness cost and benefit of cefixime resistance in Neisseria gonorrhoeae to inform prescription policy: A modelling study.

Directory of Open Access Journals (Sweden)

Lilith K Whittles

2017-10-01

Full Text Available Gonorrhoea is one of the most common bacterial sexually transmitted infections in England. Over 41,000 cases were recorded in 2015, more than half of which occurred in men who have sex with men (MSM. As the bacterium has developed resistance to each first-line antibiotic in turn, we need an improved understanding of fitness benefits and costs of antibiotic resistance to inform control policy and planning. Cefixime was recommended as a single-dose treatment for gonorrhoea from 2005 to 2010, during which time resistance increased, and subsequently declined.We developed a stochastic compartmental model representing the natural history and transmission of cefixime-sensitive and cefixime-resistant strains of Neisseria gonorrhoeae in MSM in England, which was applied to data on diagnoses and prescriptions between 2008 and 2015. We estimated that asymptomatic carriers play a crucial role in overall transmission dynamics, with 37% (95% credible interval CrI 24%-52% of infections remaining asymptomatic and untreated, accounting for 89% (95% CrI 82%-93% of onward transmission. The fitness cost of cefixime resistance in the absence of cefixime usage was estimated to be such that the number of secondary infections caused by resistant strains is only about half as much as for the susceptible strains, which is insufficient to maintain persistence. However, we estimated that treatment of cefixime-resistant strains with cefixime was unsuccessful in 83% (95% CrI 53%-99% of cases, representing a fitness benefit of resistance. This benefit was large enough to counterbalance the fitness cost when 31% (95% CrI 26%-36% of cases were treated with cefixime, and when more than 55% (95% CrI 44%-66% of cases were treated with cefixime, the resistant strain had a net fitness advantage over the susceptible strain. Limitations include sparse data leading to large intervals on key model parameters and necessary assumptions in the modelling of a complex epidemiological process

Absent right superior caval vein in situs solitus

DEFF Research Database (Denmark)

Lytzen, Rebekka; Sundberg, Karin; Vejlstrup, Niels

2015-01-01

Introduction In up to 0.07% of the general population, the right anterior cardinal vein obliterates and the left remains open, creating an absent right superior caval vein and a persistent left superior caval vein. Absent right superior caval vein is associated with additional congenital heart...... disease in about half the patients. We wished to study the consequences of absent right superior caval vein as an incidental finding on prenatal ultrasonic malformation screening. Material and methods This is a retrospective case series study of all foetuses diagnosed with absent right superior caval vein...... no postnatal complications. All children were found to have healthy hearts at follow-up. CONCLUSIONS: In all cases, the findings proved to be a benign condition with no clinical manifestations or complications. Although isolated absent right superior caval vein does not seem to affect the outcome, associated...

Damage Identification of Bridge Based on Chebyshev Polynomial Fitting and Fuzzy Logic without Considering Baseline Model Parameters

Directory of Open Access Journals (Sweden)

Yu-Bo Jiao

2015-01-01

Full Text Available The paper presents an effective approach for damage identification of bridge based on Chebyshev polynomial fitting and fuzzy logic systems without considering baseline model data. The modal curvature of damaged bridge can be obtained through central difference approximation based on displacement modal shape. Depending on the modal curvature of damaged structure, Chebyshev polynomial fitting is applied to acquire the curvature of undamaged one without considering baseline parameters. Therefore, modal curvature difference can be derived and used for damage localizing. Subsequently, the normalized modal curvature difference is treated as input variable of fuzzy logic systems for damage condition assessment. Numerical simulation on a simply supported bridge was carried out to demonstrate the feasibility of the proposed method.

TASK-TECHNOLOGY FIT AND PERSON-JOB FIT: A BEAUTY CONTEST TO IMPROVE THE SUCCESS OF INFORMATION SYSTEMS

OpenAIRE

Suryani, Woro Dwi; Sumiyana, Sumiyana

2015-01-01

This study raises the issue that information system success could be enhanced by complementingother factors. This study investigates the success of information systems by inducing2the task-technology fit (TTF) and person-job fit (PJF) into the DeLone and McLean model. Thisstudy aims to examine, among the two induced factors, which one is able to explain andimprove the success of the information systems implementation.The results of this study indicate that the TTF explains the models’ goodnes...

A new three-dimensional track fit with multiple scattering

International Nuclear Information System (INIS)

Berger, Niklaus; Kozlinskiy, Alexandr; Kiehn, Moritz; Schöning, André

2017-01-01

Modern semiconductor detectors allow for charged particle tracking with ever increasing position resolution. Due to the reduction of the spatial hit uncertainties, multiple Coulomb scattering in the detector layers becomes the dominant source for tracking uncertainties. In this case long distance effects can be ignored for the momentum measurement, and the track fit can consequently be formulated as a sum of independent fits to hit triplets. In this paper we present an analytical solution for a three-dimensional triplet(s) fit in a homogeneous magnetic field based on a multiple scattering model. Track fitting of hit triplets is performed using a linearization ansatz. The momentum resolution is discussed for a typical spectrometer setup. Furthermore the track fit is compared with other track fits for two different pixel detector geometries, namely the Mu3e experiment at PSI and a typical high-energy collider experiment. For a large momentum range the triplets fit provides a significantly better performance than a single helix fit. The triplets fit is fast and can easily be parallelized, which makes it ideal for the implementation on parallel computing architectures.

A new three-dimensional track fit with multiple scattering

Energy Technology Data Exchange (ETDEWEB)

Berger, Niklaus; Kozlinskiy, Alexandr [Physikalisches Institut, Heidelberg University, Heidelberg (Germany); Institut für Kernphysik and PRISMA cluster of excellence, Mainz University, Mainz (Germany); Kiehn, Moritz; Schöning, André [Physikalisches Institut, Heidelberg University, Heidelberg (Germany)

2017-02-01

Modern semiconductor detectors allow for charged particle tracking with ever increasing position resolution. Due to the reduction of the spatial hit uncertainties, multiple Coulomb scattering in the detector layers becomes the dominant source for tracking uncertainties. In this case long distance effects can be ignored for the momentum measurement, and the track fit can consequently be formulated as a sum of independent fits to hit triplets. In this paper we present an analytical solution for a three-dimensional triplet(s) fit in a homogeneous magnetic field based on a multiple scattering model. Track fitting of hit triplets is performed using a linearization ansatz. The momentum resolution is discussed for a typical spectrometer setup. Furthermore the track fit is compared with other track fits for two different pixel detector geometries, namely the Mu3e experiment at PSI and a typical high-energy collider experiment. For a large momentum range the triplets fit provides a significantly better performance than a single helix fit. The triplets fit is fast and can easily be parallelized, which makes it ideal for the implementation on parallel computing architectures.

The FitTrack Index as fitness indicator: A pilot study | van Rensburg ...

African Journals Online (AJOL)

Conclusions: These results suggest that the web-based FitTrack Index may be considered an appropriate tool to evaluate exercise capacity and cardiovascular fitness in healthy individuals following an aerobic training programme. Keywords: Aerobic fitness, Exercise ability, Recreational fitness, Cardiovascular fitness, ...

FITS: a function-fitting program

Energy Technology Data Exchange (ETDEWEB)

Balestrini, S.J.; Chezem, C.G.

1982-08-01

FITS is an iterating computer program that adjusts the parameters of a function to fit a set of data points according to the least squares criterion and then lists and plots the results. The function can be programmed or chosen from a library that is provided. The library can be expanded to include up to 99 functions. A general plotting routine, contained in the program but useful in its own right, is described separately in Appendix A. An example problem file and its solution is given in Appendix B.

Person-organization fit and turnover intention: exploring the mediating effect of work engagement and the moderating effect of demand-ability fit.

Science.gov (United States)

Peng, Jui-Chen; Lee, Yin-Ling; Tseng, Mei-Man

2014-03-01

Person-organization (P-O) fit is an important influencing factor on the intentions and attitudes of hospital nurses. The authors used a motivation-mechanism approach to conceptualize work engagement as a mediator and demand-ability (D-A) fit as a moderator to elicit the role of P-O fit in the turnover intention of nurses. This article explores whether the work engagement of nurses mediates the relationship between P-O fit and turnover intention and examines whether D-A fit moderates this relationship. The sample comprised 349 nurses working for two regional hospitals in Yilan County, Taiwan. Linear regression modeling analysis was conducted to test the proposed hypotheses. Results indicate that P-O fit has a negative effect on participant turnover intention. In addition, the work engagement of participants was found to mediate the impact of P-O fit on turnover intention. A new significant interactive relationship was discovered such that high D-A fit strengthened the negative relationship between P-O fit and turnover intention. The work engagement of professional nurses has attracted increasing attention in the literature on fit, particularly with regard to the linkage between P-O and fit-turnover intention. This study enhances the understanding of the function of P-O fit by considering perceived D-A fit. Nurse turnover is the main reason for the current shortage of nurses in Taiwan. Therefore, if the cognitive values of nurses and the organizational culture fit with hospital value systems, common values may facilitate a higher degree of nurse work engagement and, in turn, decrease turnover intention. In addition, recruiting employees with high D-A fit may help hospitals enhance the negative relationship between P-O fit and nurse turnover intention.