Optimal inference with suboptimal models: addiction and active Bayesian inference.
Schwartenbeck, Philipp; FitzGerald, Thomas H B; Mathys, Christoph; Dolan, Ray; Wurst, Friedrich; Kronbichler, Martin; Friston, Karl
2015-02-01
When casting behaviour as active (Bayesian) inference, optimal inference is defined with respect to an agent's beliefs - based on its generative model of the world. This contrasts with normative accounts of choice behaviour, in which optimal actions are considered in relation to the true structure of the environment - as opposed to the agent's beliefs about worldly states (or the task). This distinction shifts an understanding of suboptimal or pathological behaviour away from aberrant inference as such, to understanding the prior beliefs of a subject that cause them to behave less 'optimally' than our prior beliefs suggest they should behave. Put simply, suboptimal or pathological behaviour does not speak against understanding behaviour in terms of (Bayes optimal) inference, but rather calls for a more refined understanding of the subject's generative model upon which their (optimal) Bayesian inference is based. Here, we discuss this fundamental distinction and its implications for understanding optimality, bounded rationality and pathological (choice) behaviour. We illustrate our argument using addictive choice behaviour in a recently described 'limited offer' task. Our simulations of pathological choices and addictive behaviour also generate some clear hypotheses, which we hope to pursue in ongoing empirical work. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
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…
Defining fitness in evolutionary models
Indian Academy of Sciences (India)
The analysis of evolutionary models requires an appropriate definition for fitness. In this paper, I review such definitions in relation to the five major dimensions by which models may be described, namely. finite versus infinite (or very large) population size,; type of environment (constant, fixed length, temporally stochastic, ...
Fitting and interpreting occupancy models.
Directory of Open Access Journals (Sweden)
Alan H Welsh
Full Text Available We show that occupancy models are more difficult to fit than is generally appreciated because the estimating equations often have multiple solutions, including boundary estimates which produce fitted probabilities of zero or one. The estimates are unstable when the data are sparse, making them difficult to interpret, and, even in ideal situations, highly variable. As a consequence, making accurate inference is difficult. When abundance varies over sites (which is the general rule in ecology because we expect spatial variance in abundance and detection depends on abundance, the standard analysis suffers bias (attenuation in detection, biased estimates of occupancy and potentially finding misleading relationships between occupancy and other covariates, asymmetric sampling distributions, and slow convergence of the sampling distributions to normality. The key result of this paper is that the biases are of similar magnitude to those obtained when we ignore non-detection entirely. The fact that abundance is subject to detection error and hence is not directly observable, means that we cannot tell when bias is present (or, equivalently, how large it is and we cannot adjust for it. This implies that we cannot tell which fit is better: the fit from the occupancy model or the fit ignoring the possibility of detection error. Therefore trying to adjust occupancy models for non-detection can be as misleading as ignoring non-detection completely. Ignoring non-detection can actually be better than trying to adjust for it.
Measured, modeled, and causal conceptions of fitness
Abrams, Marshall
2012-01-01
This paper proposes partial answers to the following questions: in what senses can fitness differences plausibly be considered causes of evolution?What relationships are there between fitness concepts used in empirical research, modeling, and abstract theoretical proposals? How does the relevance of different fitness concepts depend on research questions and methodological constraints? The paper develops a novel taxonomy of fitness concepts, beginning with type fitness (a property of a genotype or phenotype), token fitness (a property of a particular individual), and purely mathematical fitness. Type fitness includes statistical type fitness, which can be measured from population data, and parametric type fitness, which is an underlying property estimated by statistical type fitnesses. Token fitness includes measurable token fitness, which can be measured on an individual, and tendential token fitness, which is assumed to be an underlying property of the individual in its environmental circumstances. Some of the paper's conclusions can be outlined as follows: claims that fitness differences do not cause evolution are reasonable when fitness is treated as statistical type fitness, measurable token fitness, or purely mathematical fitness. Some of the ways in which statistical methods are used in population genetics suggest that what natural selection involves are differences in parametric type fitnesses. Further, it's reasonable to think that differences in parametric type fitness can cause evolution. Tendential token fitnesses, however, are not themselves sufficient for natural selection. Though parametric type fitnesses are typically not directly measurable, they can be modeled with purely mathematical fitnesses and estimated by statistical type fitnesses, which in turn are defined in terms of measurable token fitnesses. The paper clarifies the ways in which fitnesses depend on pragmatic choices made by researchers. PMID:23112804
Lifshitz, Fima; Pintos, Patricia M; Lezón, Christian E; Macri, Elisa V; Friedman, Silvia M; Boyer, Patricia M
2012-01-01
Previous studies performed in an experimental model of nutritional growth retardation (NGR) have observed metabolic adaptation. We hypothesized that changes in lipid-lipoprotein profile, glucose, and insulin levels occur, whereas overall body growth is reduced.The aim of this study was to assess serum lipid-lipoprotein profile, hepatogram, insulinemia and glycemia, and CVD risk markers in rats fed a suboptimal diet. Weanling male rats were assigned either to control (C) or NGR group. In this 4-week study, C rats were fed ad libitum a standard diet, and NGR rats received 80% of the amount of food consumed by C. Zoometric parameters, body fat content, serum lipid-lipoprotein profile, hepatogram, insulinemia, and glycemia were determined, and the cardiovascular disease (CVD) risk markers homeostasis model assessment-insulin resistance and homeostasis model assessment and β-cell function were calculated. Suboptimal food intake induced a significant decrease in body weight and length, which were accompanied by a reduction of 50% in body fat mass. Serum lipoproteins were significantly higher in NGR rats, with the exception of high-density lipoprotein cholesterol, which remained unchanged. Nutritional growth retardation rats had decreased triglycerides compared with C rats. No significant differences were detected in liver function parameters. The CVD risk markers homeostasis model assessment (HOMA)-insulin resistance and homeostasis model assessment and β-cell function were significantly lower in NGR rats. Mild chronic suboptimal nutrition in weanling male rats led to growth retardation and changes in the lipid-lipoprotein profile, glucose, and insulin levels while preserving the integrity of liver function. These data suggest a metabolic adaptation during suboptimal food intake, which ensures substrates flux to tissues that require constant energy-in detriment to body growth. The CVD risk markers suggested that mild chronic food restriction of approximately 20% could
Defining fitness in evolutionary models
Indian Academy of Sciences (India)
2008-12-23
Dec 23, 2008 ... While, the operational definitions of fitness may vary under different scenarios, they all have the .... The use of R0 as an operational metric of fitness implies a particular definition of the biological sce .... risk', and finally discussed by Gillespie (1974, 1977) in the context of variation in offspring number. Slatkin ...
Coaches as Fitness Role Models
Nichols, Randall; Zillifro, Traci D.; Nichols, Ronald; Hull, Ethan E.
2012-01-01
The lack of physical activity, low fitness levels, and elevated obesity rates as high as 32% of today's youth are well documented. Many strategies and grants have been developed at the national, regional, and local levels to help counteract these current trends. Strategies have been developed and implemented for schools, households (parents), and…
Are Physical Education Majors Models for Fitness?
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…
Extracting Actionability from Machine Learning Models by Sub-optimal Deterministic Planning
Lyu, Qiang; Chen, Yixin; Li, Zhaorong; Cui, Zhicheng; Chen, Ling; Zhang, Xing; Shen, Haihua
2016-01-01
A main focus of machine learning research has been improving the generalization accuracy and efficiency of prediction models. Many models such as SVM, random forest, and deep neural nets have been proposed and achieved great success. However, what emerges as missing in many applications is actionability, i.e., the ability to turn prediction results into actions. For example, in applications such as customer relationship management, clinical prediction, and advertisement, the users need not on...
LFLM (Local Fitting of Linear Models / Locally weighted Fitting of Linear Models)
DEFF Research Database (Denmark)
1997-01-01
LFLM (Local Fitting of Linear Models / Locally weighted Fitting of Linear Models) is an S-PLUS / R library for estimation in conditional parametric models. This class of models can briefly be described as linear models in which the parameters are replaced by smooth functions....
Induced subgraph searching for geometric model fitting
Xiao, Fan; Xiao, Guobao; Yan, Yan; Wang, Xing; Wang, Hanzi
2017-11-01
In this paper, we propose a novel model fitting method based on graphs to fit and segment multiple-structure data. In the graph constructed on data, each model instance is represented as an induced subgraph. Following the idea of pursuing the maximum consensus, the multiple geometric model fitting problem is formulated as searching for a set of induced subgraphs including the maximum union set of vertices. After the generation and refinement of the induced subgraphs that represent the model hypotheses, the searching process is conducted on the "qualified" subgraphs. Multiple model instances can be simultaneously estimated by solving a converted problem. Then, we introduce the energy evaluation function to determine the number of model instances in data. The proposed method is able to effectively estimate the number and the parameters of model instances in data severely corrupted by outliers and noises. Experimental results on synthetic data and real images validate the favorable performance of the proposed method compared with several state-of-the-art fitting methods.
Fitting models to correlated data (large samples)
Féménias, Jean-Louis
2004-03-01
The study of the ordered series of residuals of a fit proved to be useful in evaluating separately the pure experimental error and the model bias leading to a possible improvement of the modeling [J. Mol. Spectrosc. 217 (2003) 32]. In the present work this procedure is extended to homogeneous correlated data. This new method allows a separate estimation of pure experimental error, model bias, and data correlation; furthermore, it brings a new insight into the difference between goodness of fit and model relevance. It can be considered either as a study of 'random systematic errors' or as an extended approach of the Durbin-Watson problem [Biometrika 37 (1950) 409] taking into account the model error. In the present work an empirical approach is proposed for large samples ( n⩾500) where numerical tests are done showing the accuracy and the limits of the method.
Model fit after pairwise maximum likelihood
Directory of Open Access Journals (Sweden)
M. T. eBarendse
2016-04-01
Full Text Available Maximum likelihood factor analysis of discrete data within the structural equation modeling framework rests on the assumption that the observed discrete responses are manifestations of underlying continuous scores that are normally distributed. As maximizing the likelihood of multivariate response patterns is computationally very intensive, the sum of the log--likelihoods of the bivariate response patterns is maximized instead. Little is yet known about how to assess model fit when the analysis is based on such a pairwise maximum likelihood (PML of two--way contingency tables. We propose new fit criteria for the PML method and conduct a simulation study to evaluate their performance in model selection. With large sample sizes (500 or more, PML performs as well the robust weighted least squares analysis of polychoric correlations.
Fitting statistical models in bivariate allometry.
Packard, Gary C; Birchard, Geoffrey F; Boardman, Thomas J
2011-08-01
Several attempts have been made in recent years to formulate a general explanation for what appear to be recurring patterns of allometric variation in morphology, physiology, and ecology of both plants and animals (e.g. the Metabolic Theory of Ecology, the Allometric Cascade, the Metabolic-Level Boundaries hypothesis). However, published estimates for parameters in allometric equations often are inaccurate, owing to undetected bias introduced by the traditional method for fitting lines to empirical data. The traditional method entails fitting a straight line to logarithmic transformations of the original data and then back-transforming the resulting equation to the arithmetic scale. Because of fundamental changes in distributions attending transformation of predictor and response variables, the traditional practice may cause influential outliers to go undetected, and it may result in an underparameterized model being fitted to the data. Also, substantial bias may be introduced by the insidious rotational distortion that accompanies regression analyses performed on logarithms. Consequently, the aforementioned patterns of allometric variation may be illusions, and the theoretical explanations may be wide of the mark. Problems attending the traditional procedure can be largely avoided in future research simply by performing preliminary analyses on arithmetic values and by validating fitted equations in the arithmetic domain. The goal of most allometric research is to characterize relationships between biological variables and body size, and this is done most effectively with data expressed in the units of measurement. Back-transforming from a straight line fitted to logarithms is not a generally reliable way to estimate an allometric equation in the original scale. © 2010 The Authors. Biological Reviews © 2010 Cambridge Philosophical Society.
Exact Fit of Simple Finite Mixture Models
Directory of Open Access Journals (Sweden)
Dirk Tasche
2014-11-01
Full Text Available How to forecast next year’s portfolio-wide credit default rate based on last year’s default observations and the current score distribution? A classical approach to this problem consists of fitting a mixture of the conditional score distributions observed last year to the current score distribution. This is a special (simple case of a finite mixture model where the mixture components are fixed and only the weights of the components are estimated. The optimum weights provide a forecast of next year’s portfolio-wide default rate. We point out that the maximum-likelihood (ML approach to fitting the mixture distribution not only gives an optimum but even an exact fit if we allow the mixture components to vary but keep their density ratio fixed. From this observation we can conclude that the standard default rate forecast based on last year’s conditional default rates will always be located between last year’s portfolio-wide default rate and the ML forecast for next year. As an application example, cost quantification is then discussed. We also discuss how the mixture model based estimation methods can be used to forecast total loss. This involves the reinterpretation of an individual classification problem as a collective quantification problem.
Fit of Different Models for Multitrait-Multimethod Experiments.
Corten, Irmgard W.; Saris, Willem E.; Coenders, Germa; van der Veld, William; Aalberts, Chris E.; Kornelis, Charles
2002-01-01
Compared different models suggested for the analysis of multitrait multimethod (MTMM) experiments for their fit to 87 data sets collected in the United States. The fit of models based on polychoric correlations is much worse than the fit of models based on product moment correlations, but in both cases a model that assumes additive method effects…
A fitting LEGACY - modelling Kepler's best stars
Aarslev, Magnus J.; Christensen-Dalsgaard, Jørgen; Lund, Mikkel N.; Silva Aguirre, Victor; Gough, Douglas
2017-10-01
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.
Pritchard, Tony; Hansen, Andrew; Scarboro, Shot; Melnic, Irina
2015-01-01
The purpose of this study was to investigate changes in fitness levels, content knowledge, physical activity levels, and participants' perceptions following the implementation of the sport education fitness model (SEFM) at a high school. Thirty-two high school students participated in 20 lessons using the SEFM. Aerobic capacity, muscular…
Hyper-Fit: Fitting Linear Models to Multidimensional Data with Multivariate Gaussian Uncertainties
Robotham, A. S. G.; Obreschkow, D.
2015-09-01
Astronomical data is often uncertain with errors that are heteroscedastic (different for each data point) and covariant between different dimensions. Assuming that a set of D-dimensional data points can be described by a (D - 1)-dimensional plane with intrinsic scatter, we derive the general likelihood function to be maximised to recover the best fitting model. Alongside the mathematical description, we also release the hyper-fit package for the R statistical language (http://github.com/asgr/hyper.fit) and a user-friendly web interface for online fitting (http://hyperfit.icrar.org). The hyper-fit package offers access to a large number of fitting routines, includes visualisation tools, and is fully documented in an extensive user manual. Most of the hyper-fit functionality is accessible via the web interface. In this paper, we include applications to toy examples and to real astronomical data from the literature: the mass-size, Tully-Fisher, Fundamental Plane, and mass-spin-morphology relations. In most cases, the hyper-fit solutions are in good agreement with published values, but uncover more information regarding the fitted model.
Model-Free CUSUM Methods for Person Fit
Armstrong, Ronald D.; Shi, Min
2009-01-01
This article demonstrates the use of a new class of model-free cumulative sum (CUSUM) statistics to detect person fit given the responses to a linear test. The fundamental statistic being accumulated is the likelihood ratio of two probabilities. The detection performance of this CUSUM scheme is compared to other model-free person-fit statistics…
Automated Model Fit Method for Diesel Engine Control Development
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
Blanquart, François; Bataillon, Thomas
2016-06-01
The fitness landscape defines the relationship between genotypes and fitness in a given environment and underlies fundamental quantities such as the distribution of selection coefficient and the magnitude and type of epistasis. A better understanding of variation in landscape structure across species and environments is thus necessary to understand and predict how populations will adapt. An increasing number of experiments investigate the properties of fitness landscapes by identifying mutations, constructing genotypes with combinations of these mutations, and measuring the fitness of these genotypes. Yet these empirical landscapes represent a very small sample of the vast space of all possible genotypes, and this sample is often biased by the protocol used to identify mutations. Here we develop a rigorous statistical framework based on Approximate Bayesian Computation to address these concerns and use this flexible framework to fit a broad class of phenotypic fitness models (including Fisher's model) to 26 empirical landscapes representing nine diverse biological systems. Despite uncertainty owing to the small size of most published empirical landscapes, the inferred landscapes have similar structure in similar biological systems. Surprisingly, goodness-of-fit tests reveal that this class of phenotypic models, which has been successful so far in interpreting experimental data, is a plausible in only three of nine biological systems. More precisely, although Fisher's model was able to explain several statistical properties of the landscapes-including the mean and SD of selection and epistasis coefficients-it was often unable to explain the full structure of fitness landscapes. Copyright © 2016 by the Genetics Society of America.
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.
HDFITS: Porting the FITS data model to HDF5
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.
On the Measurement of Model Fit for Sparse Categorical Data
Kraus, Katrin
2012-01-01
This thesis consists of four papers that deal with several aspects of the measurement of model fit for categorical data. In all papers, special attention is paid to situations with sparse data. The first paper concerns the computational burden of calculating Pearson's goodness-of-fit statistic for situations where many response patterns have observed frequencies that equal zero. A simple solution is presented that allows for the computation of the total value of Pearson's goodness-of-fit stat...
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.
Two Strategies for Fitting Real Data to Rasch Polytomous Models.
Rojas Tejada, Antonio J.; Gonzalez Gomez, Andres; Padilla Garcia, Jose L.; Perez Melendez, Cristino
2002-01-01
Studied the results provided by two strategies for fitting data to Latent Trait Theory models, Total-Persons-Items (TPI) and Total-Items-Persons (TIP). To assess these strategies, 30 items measuring religious attitudes were administered to 821 persons. Results show that TPI maximizes the number of persons with good fit, and TIP maximizes the…
BEST FIT MODEL FOR YIELD CURVE ESTIMATION
Directory of Open Access Journals (Sweden)
Zdravka Aljinović
2012-12-01
Full Text Available Yield curve represents a relationship between the rate of return and maturity of certain securities. A range of activities on the market is determined by the abovementioned relationship; therefore its significance is unquestionable. Besides that, its shape reflects the shape of the economy, i.e. it can predict recession. These are the reasons why it is very important to properly and accurately estimate the yield curve. There are various models evolved for its estimation; however the most used are parametric models: Nelson-Siegel model and Svensson model. In this paper the yield curves are estimated on Croatian financial market, based on weekly data in years 2011 and 2012 both with Nelson-Siegel and Svensson model, and the obtained results are compared.
An Algorithm for Optimally Fitting a Wiener Model
Directory of Open Access Journals (Sweden)
Lucas P. Beverlin
2011-01-01
Full Text Available The purpose of this work is to present a new methodology for fitting Wiener networks to datasets with a large number of variables. Wiener networks have the ability to model a wide range of data types, and their structures can yield parameters with phenomenological meaning. There are several challenges to fitting such a model: model stiffness, the nonlinear nature of a Wiener network, possible overfitting, and the large number of parameters inherent with large input sets. This work describes a methodology to overcome these challenges by using several iterative algorithms under supervised learning and fitting subsets of the parameters at a time. This methodology is applied to Wiener networks that are used to predict blood glucose concentrations. The predictions of validation sets from models fit to four subjects using this methodology yielded a higher correlation between observed and predicted observations than other algorithms, including the Gauss-Newton and Levenberg-Marquardt algorithms.
A person fit test for IRT models for polytomous items
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
Fitting polytomous Rasch models in SAS
DEFF Research Database (Denmark)
Christensen, Karl Bang
2006-01-01
The item parameters of a polytomous Rasch model can be estimated using marginal and conditional approaches. This paper describes how this can be done in SAS (V8.2) for three item parameter estimation procedures: marginal maximum likelihood estimation, conditional maximum likelihood estimation...
A Note on Recurring Misconceptions When Fitting Nonlinear Mixed Models.
Harring, Jeffrey R; Blozis, Shelley A
2016-01-01
Nonlinear mixed-effects (NLME) models are used when analyzing continuous repeated measures data taken on each of a number of individuals where the focus is on characteristics of complex, nonlinear individual change. Challenges with fitting NLME models and interpreting analytic results have been well documented in the statistical literature. However, parameter estimates as well as fitted functions from NLME analyses in recent articles have been misinterpreted, suggesting the need for clarification of these issues before these misconceptions become fact. These misconceptions arise from the choice of popular estimation algorithms, namely, the first-order linearization method (FO) and Gaussian-Hermite quadrature (GHQ) methods, and how these choices necessarily lead to population-average (PA) or subject-specific (SS) interpretations of model parameters, respectively. These estimation approaches also affect the fitted function for the typical individual, the lack-of-fit of individuals' predicted trajectories, and vice versa.
A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit
Kim, K. Han; Young, Karen S.; Bernal, Yaritza; Boppana, Abhishektha; Vu, Linh Q.; Benson, Elizabeth A.; Jarvis, Sarah; Rajulu, Sudhakar L.
2016-01-01
Suboptimal suit fit is a known risk factor for crewmember shoulder injury. Suit fit assessment is however prohibitively time consuming and cannot be generalized across wide variations of body shapes and poses. In this work, we have developed a new design tool based on the statistical analysis of body shape scans. This tool is aimed at predicting the skin deformation and shape variations for any body size and shoulder pose for a target population. This new process, when incorporated with CAD software, will enable virtual suit fit assessments, predictively quantifying the contact volume, and clearance between the suit and body surface at reduced time and cost.
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.
Directory of Open Access Journals (Sweden)
Marion Jaud
2016-06-01
Full Text Available For monitoring purposes and in the context of geomorphological research, Unmanned Aerial Vehicles (UAV appear to be a promising solution to provide multi-temporal Digital Surface Models (DSMs and orthophotographs. There are a variety of photogrammetric software tools available for UAV-based data. The objective of this study is to investigate the level of accuracy that can be achieved using two of these software tools: Agisoft PhotoScan® Pro and an open-source alternative, IGN© MicMac®, in sub-optimal survey conditions (rugged terrain, with a large variety of morphological features covering a range of roughness sizes, poor GPS reception. A set of UAV images has been taken by a hexacopter drone above the Rivière des Remparts, a river on Reunion Island. This site was chosen for its challenging survey conditions: the topography of the study area (i involved constraints on the flight plan; (ii implied errors on some GPS measurements; (iii prevented an optimal distribution of the Ground Control Points (GCPs and; (iv was very complex to reconstruct. Several image processing tests are performed with different scenarios in order to analyze the sensitivity of each software package to different parameters (image quality, numbers of GCPs, etc.. When computing the horizontal and vertical errors within a control region on a set of ground reference targets, both methods provide rather similar results. A precision up to 3–4 cm is achievable with these software packages. The DSM quality is also assessed over the entire study area comparing PhotoScan DSM and MicMac DSM with a Terrestrial Laser Scanner (TLS point cloud. PhotoScan and MicMac DSM are also compared at the scale of particular features. Both software packages provide satisfying results: PhotoScan is more straightforward to use but its source code is not open; MicMac is recommended for experimented users as it is more flexible.
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 ...
Inclusive fitness arguments in genetic models of behaviour.
Taylor, P D
1996-01-01
My purpose here is to provide a coherent account of inclusive fitness techniques, accessible to a mathematically literate graduate student in evolutionary biology, and to relate these to standard one-locus genetic models. I begin in Sect. 2 with a general formulation of evolutionary stability; in Sect. 3 and Sect. 4 I interpret the basic stability conditions within genetic and inclusive fitness models. In Sect. 5 I extend these concepts to the case of a class-structured population, and in Sect. 6 I illustrate these notions with a sex ratio example. In Sect. 7 I give a proof of the result that under additive gene action and weak selection, an inclusive fitness argument is able to verify an important stability condition (2.5) for one-locus genetic models. Most of these results have been published.
Canonical fitness model for simple scale-free graphs
Flegel, F.; Sokolov, I. M.
2012-01-01
We consider a fitness model assumed to generate simple graphs with power-law heavy-tailed degree sequence: P(k) \\propto k^{-1-\\alpha} with 0 < \\alpha < 1, in which the corresponding distributions do not posses a mean. We discuss the situations in which the model is used to produce a multigraph and examine what happens if the multiple edges are merged to a single one and thus a simple graph is built. We give the relation between the (normalized) fitness parameter r and the expected degree \
[How to fit and interpret multilevel models using SPSS].
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.
Assessing fit in Bayesian models for spatial processes
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.
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
The Gold Medal Fitness Program: A Model for Teacher Change
Wright, Jan; Konza, Deslea; Hearne, Doug; Okely, Tony
2008-01-01
Background: Following the 2000 Sydney Olympics, the NSW Premier, Mr Bob Carr, launched a school-based initiative in NSW government primary schools called the "Gold Medal Fitness Program" to encourage children to be fitter and more active. The Program was introduced into schools through a model of professional development, "Quality…
Suboptimal Criterion Learning in Static and Dynamic Environments.
Directory of Open Access Journals (Sweden)
Elyse H Norton
2017-01-01
Full Text Available Humans often make decisions based on uncertain sensory information. Signal detection theory (SDT describes detection and discrimination decisions as a comparison of stimulus "strength" to a fixed decision criterion. However, recent research suggests that current responses depend on the recent history of stimuli and previous responses, suggesting that the decision criterion is updated trial-by-trial. The mechanisms underpinning criterion setting remain unknown. Here, we examine how observers learn to set a decision criterion in an orientation-discrimination task under both static and dynamic conditions. To investigate mechanisms underlying trial-by-trial criterion placement, we introduce a novel task in which participants explicitly set the criterion, and compare it to a more traditional discrimination task, allowing us to model this explicit indication of criterion dynamics. In each task, stimuli were ellipses with principal orientations drawn from two categories: Gaussian distributions with different means and equal variance. In the covert-criterion task, observers categorized a displayed ellipse. In the overt-criterion task, observers adjusted the orientation of a line that served as the discrimination criterion for a subsequently presented ellipse. We compared performance to the ideal Bayesian learner and several suboptimal models that varied in both computational and memory demands. Under static and dynamic conditions, we found that, in both tasks, observers used suboptimal learning rules. In most conditions, a model in which the recent history of past samples determines a belief about category means fit the data best for most observers and on average. Our results reveal dynamic adjustment of discrimination criterion, even after prolonged training, and indicate how decision criteria are updated over time.
Evolution models with lethal mutations on symmetric or random fitness landscapes.
Kirakosyan, Zara; Saakian, David B; Hu, Chin-Kun
2010-07-01
We calculate the mean fitness for evolution models, when the fitness is a function of the Hamming distance from a reference sequence, and there is a probability that this fitness is nullified (Eigen model case) or tends to the negative infinity (Crow-Kimura model case). We calculate the mean fitness of these models. The mean fitness is calculated also for the random fitnesses with logarithmic-normal distribution, reasonably describing sometimes the situation with RNA viruses.
Survival model construction guided by fit and predictive strength.
Chauvel, Cécile; O'Quigley, John
2017-06-01
Survival model construction can be guided by goodness-of-fit techniques as well as measures of predictive strength. Here, we aim to bring together these distinct techniques within the context of a single framework. The goal is how to best characterize and code the effects of the variables, in particular time dependencies, when taken either singly or in combination with other related covariates. Simple graphical techniques can provide an immediate visual indication as to the goodness-of-fit but, in cases of departure from model assumptions, will point in the direction of a more involved and richer alternative model. These techniques appear to be intuitive. This intuition is backed up by formal theorems that underlie the process of building richer models from simpler ones. Measures of predictive strength are used in conjunction with these goodness-of-fit techniques and, again, formal theorems show that these measures can be used to help identify models closest to the unknown non-proportional hazards mechanism that we can suppose generates the observations. Illustrations from studies in breast cancer show how these tools can be of help in guiding the practical problem of efficient model construction for survival data. © 2016, The International Biometric Society.
Status of the global electroweak fit of the Standard Model
Höcker, Andreas
2009-01-01
Results from the global Standard Model fit to electroweak precision data, including newest Tevatron measurements, are reviewed and discussed. The complete fit using also the constraints from the direct Higgs boson searches yields an upper limit on the Higgs mass of 153 GeV at 95% CL. The top mass is indirectly determined to be (177.2 +10.5 -7.8) GeV and (179.5 +8.8 -5.2) GeV for fits including or not the constraints from the direct Higgs searches, respectively. Using the 3NLO perturbative prediction of the massless QCD Adler function, the strong coupling constant at the Z-mass scale is determined to be alpha_s(MZ)=0.1193 +- 0.0028 +- 0.0001, which is in excellent agreement with the 3NLO result from hadronic tau decays. The perspectives of the electroweak fit for forthcoming and proposed future collider projects are discussed. The available constraints on the Higgs mass are convolved with the high-scale behaviour of the Higgs quartic coupling to derive likelihoods for the survival of the Standard Model versus ...
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......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 productivity types fit the data well compared to the homogeneous model....
Accumulation and modeling of particles in drinking water pipe fittings
Directory of Open Access Journals (Sweden)
K. Neilands
2012-09-01
Full Text Available The effect of pipe fittings (mainly T-pieces on particle accumulation in drinking water distribution networks were shown in this work. The online measurements of flow and turbidity for cast iron, polyethylene and polyvinyl chloride pipe sections were linked with analysis of pipe geometry. Up to 0.29 kg of the total amount mobilized in T-pieces ranging from DN 100/100–DN 250/250. The accumulated amount of particles in fittings was defined as J and introduced into the existing turbidity model PODDS (prediction of discoloration in distribution systems proposed by Boxall et al. (2001 which describes the erosion of particles leading to discoloration events in drinking water network viz sections of straight pipes. However, this work does not interpret mobilization of particles in pipe fittings which have been considered in this article. T-pieces were the object of this study and depending of the diameter or daily flow velocity, the coefficient J varied from 1.16 to 8.02. The study showed that pipe fittings act as catchment areas for particle accumulation in drinking water networks.
Atmospheric Turbulence Modeling for Aerospace Vehicles: Fractional Order Fit
Kopasakis, George (Inventor)
2015-01-01
An improved model for simulating atmospheric disturbances is disclosed. A scale Kolmogorov spectral may be scaled to convert the Kolmogorov spectral into a finite energy von Karman spectral and a fractional order pole-zero transfer function (TF) may be derived from the von Karman spectral. Fractional order atmospheric turbulence may be approximated with an integer order pole-zero TF fit, and the approximation may be stored in memory.
Fitting rainfall interception models to forest ecosystems of Mexico
Návar, José
2017-05-01
Models that accurately predict forest interception are essential both for water balance studies and for assessing watershed responses to changes in land use and the long-term climate variability. This paper compares the performance of four rainfall interception models-the sparse Gash (1995), Rutter et al. (1975), Liu (1997) and two new models (NvMxa and NvMxb)-using data from four spatially extensive, structurally diverse forest ecosystems in Mexico. Ninety-eight case studies measuring interception in tropical dry (25), arid/semi-arid (29), temperate (26), and tropical montane cloud forests (18) were compiled and analyzed. Coefficients derived from raw data or published statistical relationships were used as model input to evaluate multi-storm forest interception at the case study scale. On average empirical data showed that, tropical montane cloud, temperate, arid/semi-arid and tropical dry forests intercepted 14%, 18%, 22% and 26% of total precipitation, respectively. The models performed well in predicting interception, with mean deviations between measured and modeled interception as a function of total precipitation (ME) generally 0.66. Model fitting precision was dependent on the forest ecosystem. Arid/semi-arid forests exhibited the smallest, while tropical montane cloud forest displayed the largest ME deviations. Improved agreement between measured and modeled data requires modification of in-storm evaporation rate in the Liu; the canopy storage in the sparse Gash model; and the throughfall coefficient in the Rutter and the NvMx models. This research concludes on recommending the wide application of rainfall interception models with some caution as they provide mixed results. The extensive forest interception data source, the fitting and testing of four models, the introduction of a new model, and the availability of coefficient values for all four forest ecosystems are an important source of information and a benchmark for future investigations in this
Goodness-of-fit of multilevel latent class models for categorical data
Nagelkerke, E.; Oberski, D.L.; Vermunt, J.K.
2016-01-01
In the context of multilevel latent class models, the goodness-of-fit depends on multiple aspects, among which are two local independence assumptions. However, because of the lack of local fit statistics, the model and any issues relating to model fit can only be inspected jointly through global fit
Fitting stratified proportional odds models by amalgamating conditional likelihoods.
Mukherjee, Bhramar; Ahn, Jaeil; Liu, Ivy; Rathouz, Paul J; Sánchez, Brisa N
2008-10-30
Classical methods for fitting a varying intercept logistic regression model to stratified data are based on the conditional likelihood principle to eliminate the stratum-specific nuisance parameters. When the outcome variable has multiple ordered categories, a natural choice for the outcome model is a stratified proportional odds or cumulative logit model. However, classical conditioning techniques do not apply to the general K-category cumulative logit model (K>2) with varying stratum-specific intercepts as there is no reduction due to sufficiency; the nuisance parameters remain in the conditional likelihood. We propose a methodology to fit stratified proportional odds model by amalgamating conditional likelihoods obtained from all possible binary collapsings of the ordinal scale. The method allows for categorical and continuous covariates in a general regression framework. We provide a robust sandwich estimate of the variance of the proposed estimator. For binary exposures, we show equivalence of our approach to the estimators already proposed in the literature. The proposed recipe can be implemented very easily in standard software. We illustrate the methods via three real data examples related to biomedical research. Simulation results comparing the proposed method with a random effects model on the stratification parameters are also furnished. Copyright 2008 John Wiley & Sons, Ltd.
Modeling of differentiated physical fitness in school children
Directory of Open Access Journals (Sweden)
V.G. Arefiev
2014-01-01
Full Text Available Purpose: to develop a model of physical fitness training for schoolgirls to surrender standard- tives of physical culture (for example, high jump with a running start. Objectives of the study - to determine the relationship between the levels of development of motor skills and results in the high jump with a running start. Also calculate simple regression equation between them. Material : The study involved 416 school - prostrate aged 10-17. Results : It was found that the greatest influence on the effectiveness of the jump exerts a level of "explosive" force the leg muscles (30,4-47,9 %. The relative influence of mobility power 15,4-23,9 %. The share accounted speed 8,6-15,8 %. Impact indicators flexibility and endurance is 7,6-12,4 % and 4,4-7,2 %. Conclusions : The selection of exercises and methods advantageously carried out after comparing models of physical fitness and the actual state of development of motor characteristics. This makes it possible to determine the quantitative information about the shortcomings of physical fitness of each student (group and specify the direction of future work.
RFA: R-Squared Fitting Analysis Model for Power Attack
Directory of Open Access Journals (Sweden)
An Wang
2017-01-01
Full Text Available Correlation Power Analysis (CPA introduced by Brier et al. in 2004 is an important method in the side-channel attack and it enables the attacker to use less cost to derive secret or private keys with efficiency over the last decade. In this paper, we propose R-squared fitting model analysis (RFA which is more appropriate for nonlinear correlation analysis. This model can also be applied to other side-channel methods such as second-order CPA and collision-correlation power attack. Our experiments show that the RFA-based attacks bring significant advantages in both time complexity and success rate.
Two Dimensional Projection Pursuit Applied to Gaussian Mixture Model Fitting
Directory of Open Access Journals (Sweden)
Natella Likhterov
2003-08-01
Full Text Available In this paper we seek a Gaussian mixture model (GMM of an n-variate probability density function. Usually the parameters of GMMs are determined by a maximum likelihood (ML criterion. A practical deficiency of ML fitting of GMMs is poor performance when dealing with high-dimensional data since a large sample size is needed to match the accuracy that is possible in low dimensions. We propose a method to fit the GMM to multivariate data which is based on the two-dimensional projection pursuit (PP method. By means of simulations we compare the proposed method with a one-dimensional PP method for GMM. We conclude that a combination of one- and twodimensional PP methods could be useful in some applications.
Chempy: A flexible chemical evolution model for abundance fitting
Rybizki, J.; Just, A.; Rix, H.-W.; Fouesneau, M.
2017-02-01
Chempy models Galactic chemical evolution (GCE); it is a parametrized open one-zone model within a Bayesian framework. A Chempy model is specified by a set of 5-10 parameters that describe the effective galaxy evolution along with the stellar and star-formation physics: e.g. the star-formation history (SFH), the feedback efficiency, the stellar initial mass function (IMF) and the incidence of supernova of type Ia (SN Ia). Chempy can sample the posterior probability distribution in the full model parameter space and test data-model matches for different nucleosynthetic yield sets, performing essentially as a chemical evolution fitting tool. Chempy can be used to confront predictions from stellar nucleosynthesis with complex abundance data sets and to refine the physical processes governing the chemical evolution of stellar systems.
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.
Issues in Evaluating Model Fit With Missing Data
Davey, Adam
2005-01-01
Effects of incomplete data on fit indexes remain relatively unexplored. We evaluate a wide set of fit indexes (?[squared], root mean squared error of appproximation, Normed Fit Index [NFI], Tucker-Lewis Index, comparative fit index, gamma-hat, and McDonald's Centrality Index) varying conditions of sample size (100-1,000 in increments of 50),…
Empirical fitness models for hepatitis C virus immunogen design.
Hart, Gregory R; Ferguson, Andrew L
2015-11-24
Hepatitis C virus (HCV) afflicts 170 million people worldwide, 2%-3% of the global population, and kills 350 000 each year. Prophylactic vaccination offers the most realistic and cost effective hope of controlling this epidemic in the developing world where expensive drug therapies are not available. Despite 20 years of research, the high mutability of the virus and lack of knowledge of what constitutes effective immune responses have impeded development of an effective vaccine. Coupling data mining of sequence databases with spin glass models from statistical physics, we have developed a computational approach to translate clinical sequence databases into empirical fitness landscapes quantifying the replicative capacity of the virus as a function of its amino acid sequence. These landscapes explicitly connect viral genotype to phenotypic fitness, and reveal vulnerable immunological targets within the viral proteome that can be exploited to rationally design vaccine immunogens. We have recovered the empirical fitness landscape for the HCV RNA-dependent RNA polymerase (protein NS5B) responsible for viral genome replication, and validated the predictions of our model by demonstrating excellent accord with experimental measurements and clinical observations. We have used our landscapes to perform exhaustive in silico screening of 16.8 million T-cell immunogen candidates to identify 86 optimal formulations. By reducing the search space of immunogen candidates by over five orders of magnitude, our approach can offer valuable savings in time, expense, and labor for experimental vaccine development and accelerate the search for a HCV vaccine. HCV-hepatitis C virus, HLA-human leukocyte antigen, CTL-cytotoxic T lymphocyte, NS5B-nonstructural protein 5B, MSA-multiple sequence alignment, PEG-IFN-pegylated interferon.
Empirical fitness models for hepatitis C virus immunogen design
Hart, Gregory R.; Ferguson, Andrew L.
2015-12-01
Hepatitis C virus (HCV) afflicts 170 million people worldwide, 2%-3% of the global population, and kills 350 000 each year. Prophylactic vaccination offers the most realistic and cost effective hope of controlling this epidemic in the developing world where expensive drug therapies are not available. Despite 20 years of research, the high mutability of the virus and lack of knowledge of what constitutes effective immune responses have impeded development of an effective vaccine. Coupling data mining of sequence databases with spin glass models from statistical physics, we have developed a computational approach to translate clinical sequence databases into empirical fitness landscapes quantifying the replicative capacity of the virus as a function of its amino acid sequence. These landscapes explicitly connect viral genotype to phenotypic fitness, and reveal vulnerable immunological targets within the viral proteome that can be exploited to rationally design vaccine immunogens. We have recovered the empirical fitness landscape for the HCV RNA-dependent RNA polymerase (protein NS5B) responsible for viral genome replication, and validated the predictions of our model by demonstrating excellent accord with experimental measurements and clinical observations. We have used our landscapes to perform exhaustive in silico screening of 16.8 million T-cell immunogen candidates to identify 86 optimal formulations. By reducing the search space of immunogen candidates by over five orders of magnitude, our approach can offer valuable savings in time, expense, and labor for experimental vaccine development and accelerate the search for a HCV vaccine. Abbreviations: HCV—hepatitis C virus, HLA—human leukocyte antigen, CTL—cytotoxic T lymphocyte, NS5B—nonstructural protein 5B, MSA—multiple sequence alignment, PEG-IFN—pegylated interferon.
Loeb, M L G; Zink, A G
2006-05-01
Individuals within complex social groups often experience reduced reproduction owing to coercive or suppressive actions of other group members. However, the nature of social and ecological environments that favour individual acceptance of such costs of sociality is not well understood. Taxa with short periods of direct social interaction, such as some communal egg layers, are interesting models for study of the cost of social interaction because opportunities to control reproduction of others are limited to brief periods of reproduction. To understand the conditions under which communal egg layers are in fitness conflict and thus likely to influence each other's reproduction, we develop an optimality model involving a brood guarding 'host' and a nonguarding disperser, or 'egg dumper'. The model shows that when, where intermediate-sized broods have highest survival, lifetime inclusive fitnesses of hosts and dumpers are often optimized with different numbers of dumped eggs. We hypothesize that resolution of this conflict may involve attempts by one party to manipulate the other's reproduction. To test model predictions we used a lace bug (Heteroptera: Tingidae) that shows both hosts and egg dumpers as well as increased offspring survival in response to communal egg laying. We found that egg-dumping lace bugs oviposit a number of eggs that very closely matches predicted fitness optimum for hosts rather than predicted optimum of dumpers. This result suggests that dumpers pay a social cost for communal egg laying, a cost that may occur through host suppression of dumper reproduction. Although dumper allocation of eggs is thus sub-optimal for dumpers, previous models show that the decision to egg dump is nevertheless evolutionarily stable, possibly because hosts permit just enough dumper oviposition to encourage commitment to the behaviour.
The FIT Model - Fuel-cycle Integration and Tradeoffs
Energy Technology Data Exchange (ETDEWEB)
Steven J. Piet; Nick R. Soelberg; Samuel E. Bays; Candido Pereira; Layne F. Pincock; Eric L. Shaber; Meliisa C Teague; Gregory M Teske; Kurt G Vedros
2010-09-01
All mass streams from fuel separation and fabrication are products that must meet some set of product criteria – fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the “system losses study” team that developed it [Shropshire2009, Piet2010] are an initial step by the FCR&D program toward a global analysis that accounts for the requirements and capabilities of each component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R&D needs and set longer-term goals. The question originally posed to the “system losses study” was the cost of separation, fuel fabrication, waste management, etc. versus the separation efficiency. In other words, are the costs associated with marginal reductions in separations losses (or improvements in product recovery) justified by the gains in the performance of other systems? We have learned that that is the wrong question. The right question is: how does one adjust the compositions and quantities of all mass streams, given uncertain product criteria, to balance competing objectives including cost? FIT is a method to analyze different fuel cycles using common bases to determine how chemical performance changes in one part of a fuel cycle (say used fuel cooling times or separation efficiencies) affect other parts of the fuel cycle. FIT estimates impurities in fuel and waste via a rough estimate of physics and mass balance for a set of technologies. If feasibility is an issue for a set, as it is for “minimum fuel treatment” approaches such as melt refining and AIROX, it can help to make an estimate of how performances would have to change to achieve feasibility.
A shooting approach to suboptimal control
Hull, David G.; Sheen, Jyh-Jong
1991-01-01
The shooting method is used to solve the suboptimal control problem where the control history is assumed to be piecewise linear. Suboptimal solutions can be obtained without difficulty and can lead to accurate approximate controls and good starting multipliers for the regular shooting method by increasing the number of nodes. Optimal planar launch trajectories are presented for the advanced launch system.
Fitting of Parametric Building Models to Oblique Aerial Images
Panday, U. S.; Gerke, M.
2011-09-01
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 completeness of
Item level diagnostics and model - data fit in item response theory ...
African Journals Online (AJOL)
... when using BILOG-MG V3.0. Five items fitted 2-parameter models in IRTPRO. It was recommended that the use of more than one IRT software programme offers more useful information for the choice of model that fit the data. KEYWORDS: Item Level, Diagnostics, Statistics, Model - Data Fit, Item Response Theory (IRT).
Global fits of GUT-scale SUSY models with GAMBIT
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.
A bipartite fitness model for online music streaming services
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.
A Simulated Annealing based Optimization Algorithm for Automatic Variogram Model Fitting
Soltani-Mohammadi, Saeed; Safa, Mohammad
2016-09-01
Fitting a theoretical model to an experimental variogram is an important issue in geostatistical studies because if the variogram model parameters are tainted with uncertainty, the latter will spread in the results of estimations and simulations. Although the most popular fitting method is fitting by eye, in some cases use is made of the automatic fitting method on the basis of putting together the geostatistical principles and optimization techniques to: 1) provide a basic model to improve fitting by eye, 2) fit a model to a large number of experimental variograms in a short time, and 3) incorporate the variogram related uncertainty in the model fitting. Effort has been made in this paper to improve the quality of the fitted model by improving the popular objective function (weighted least squares) in the automatic fitting. Also, since the variogram model function (£) and number of structures (m) too affect the model quality, a program has been provided in the MATLAB software that can present optimum nested variogram models using the simulated annealing method. Finally, to select the most desirable model from among the single/multi-structured fitted models, use has been made of the cross-validation method, and the best model has been introduced to the user as the output. In order to check the capability of the proposed objective function and the procedure, 3 case studies have been presented.
Fitness voter model: Damped oscillations and anomalous consensus.
Woolcock, Anthony; Connaughton, Colm; Merali, Yasmin; Vazquez, Federico
2017-09-01
We study the dynamics of opinion formation in a heterogeneous voter model on a complete graph, in which each agent is endowed with an integer fitness parameter k≥0, in addition to its + or - opinion state. The evolution of the distribution of k-values and the opinion dynamics are coupled together, so as to allow the system to dynamically develop heterogeneity and memory in a simple way. When two agents with different opinions interact, their k-values are compared, and with probability p the agent with the lower value adopts the opinion of the one with the higher value, while with probability 1-p the opposite happens. The agent that keeps its opinion (winning agent) increments its k-value by one. We study the dynamics of the system in the entire 0≤p≤1 range and compare with the case p=1/2, in which opinions are decoupled from the k-values and the dynamics is equivalent to that of the standard voter model. When 0≤p<1/2, agents with higher k-values are less persuasive, and the system 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 1/2
model, although it still scales linearly with N. The p=1 case is special, with a relaxation to coexistence that scales as t^{-2.73} and a consensus time that scales as
A Fitness Index model for Italian adolescents living in Southern Italy: the ASSO project.
Bianco, Antonino; Mammina, Caterina; Jemni, Monèm; Filippi, Anna R; Patti, Antonino; Thomas, Ewan; Paoli, Antonio; Palma, Antonio; Tabacchi, Garden
2016-11-01
Strong relations between physical fitness and health in adolescents have been established in the last decades. The main objectives of the present investigation were to assess major physical fitness components in a sample of Italian school adolescents, comparing them with international data, and providing a Fitness Index model derived from percentile cut-off values of five considered physical fitness components. A total of 644 school pupils (15.9±1.1 years; M: N.=399; F: N.=245) were tested using the ASSO-Fitness Test Battery (FTB), a tool developed within the Adolescents and Surveillance System for the Obesity prevention project, which included the handgrip, standing broad-jump, sit-up to exhaustion, 4×10-m shuttle run and 20-m shuttle run tests. Stratified percentile values and related smoothed curves were obtained. The method of principal components analysis (PCA) was applied to the considered five fitness components to derive a continuous fitness level score (the Fit-Score). A Likert-type scale on the Fit-Score values was applied to obtain an intuitive classification of the individual level of fitness: very poor (Xfitness levels compared to girls. They also showed an incremental trend amongst fitness levels with age in all physical components. These results could be overlapped with those related to European adolescents. Data revealed high correlations (r>0.5) between the Fit-Score and all the fitness components. The median Fit-Score was equal to 33 for females and 53 for males (in a scale from 0 to 100). The ASSO-FTB allowed the assessment of health-related fitness components in a convenient sample of Italian adolescents and provided a Fitness Index model incorporating all these components for an intuitive classification of fitness levels. If this model is confirmed, the monitoring of these variables will allow early detection of health-related issues in a mass population, thus giving the opportunity to plan appropriate interventions.
Fitting a code-red virus spread model: An account of putting theory into practice
Kolesnichenko, A.V.; Haverkort, Boudewijn R.H.M.; Remke, Anne Katharina Ingrid; de Boer, Pieter-Tjerk
This paper is about fitting a model for the spreading of a computer virus to measured data, contributing not only the fitted model, but equally important, an account of the process of getting there. Over the last years, there has been an increased interest in epidemic models to study the speed of
The FITS model office ergonomics program: a model for best practice.
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.
Revisiting the Global Electroweak Fit of the Standard Model and Beyond with Gfitter
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...
Modelling population dynamics model formulation, fitting and assessment using state-space methods
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.
Suboptimal glycemic control in type 2 diabetes
DEFF Research Database (Denmark)
Nefs, Giesje; Pouwer, F; Denollet, J
2012-01-01
, clinical, lifestyle and psychological factors between 2005 and 2009. The Edinburgh Depression Scale was used to assess symptoms of depressed mood, anhedonia and anxiety. Suboptimal glycemic control was defined as HbA(1c) values ≥7%, with 29.8% of the sample (n=1718) scoring above this cut......-off. In univariate logistic regression analyses, anhedonia was significantly associated with suboptimal glycemic control (OR 1.29, 95% CI 1.09-1.52), while both depressed mood (OR 1.04, 0.88-1.22) and anxiety (OR 0.99, 0.83-1.19) were not. The association between anhedonia and glycemic control remained after...
Counseling as a Stochastic Process: Fitting a Markov Chain Model to Initial Counseling Interviews
Lichtenberg, James W.; Hummel, Thomas J.
1976-01-01
The goodness of fit of a first-order Markov chain model to six counseling interviews was assessed by using chi-square tests of homogeneity and simulating sampling distributions of selected process characteristics against which the same characteristics in the actual interviews were compared. The model fit four of the interviews. Presented at AERA,…
Percentile Analysis for Goodness-of-Fit Comparisons of Models to Data
2014-07-01
McClelland , 2009). A common way of assessing the fit of a model to data is to employ statistical goodness-of-fit measures. One such measure is the...Fourth Annual Conference of the Cognitive Science Society. McClelland , J. (2009). The place of modeling in cognitive science. Topics in Cognitive
Using a Person-Environment Fit Model to Predict Job Involvement and Organizational Commitment.
Blau, Gary J.
1987-01-01
Using a sample of registered nurses (N=228) from a large urban hospital, this longitudinal study tested the applicability of a person-environment fit model for predicting job involvement and organizational commitment. Results indicated the proposed person-environment fit model is useful for predicting job involvement, but not organizational…
Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.
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.
A Simulated Annealing based Optimization Algorithm for Automatic Variogram Model Fitting
National Research Council Canada - National Science Library
Saeed Soltani-Mohammadi; Mohammad Safa
2016-01-01
Fitting a theoretical model to an experimental variogram is an important issue in geostatistical studies because if the variogram model parameters are tainted with uncertainty, the latter will spread...
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.
Identifying best-fitting inputs in health-economic model calibration: a Pareto frontier approach.
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.
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
-plot models. In this article, we propose the computation of two R-2, R-2-adjusted, prediction error sums of squares (PRESS), and R-2-prediction statistics to measure the adequacy of fit for the WP and the SP submodels in a split-plot design. This is complemented with the graphical analysis of the two types...... of errors to check for any violation of the underlying assumptions and the adequacy of fit of split-plot models. Using examples, we show how computing two measures of model adequacy of fit for each split-plot design model is appropriate and useful as they reveal whether the correct WP and SP effects have...
Moment-Based Probability Modeling and Extreme Response Estimation, The FITS Routine Version 1.2
Energy Technology Data Exchange (ETDEWEB)
MANUEL,LANCE; KASHEF,TINA; WINTERSTEIN,STEVEN R.
1999-11-01
This report documents the use of the FITS routine, which provides automated fits of various analytical, commonly used probability models from input data. It is intended to complement the previously distributed FITTING routine documented in RMS Report 14 (Winterstein et al., 1994), which implements relatively complex four-moment distribution models whose parameters are fit with numerical optimization routines. Although these four-moment fits can be quite useful and faithful to the observed data, their complexity can make them difficult to automate within standard fitting algorithms. In contrast, FITS provides more robust (lower moment) fits of simpler, more conventional distribution forms. For each database of interest, the routine estimates the distribution of annual maximum response based on the data values and the duration, T, over which they were recorded. To focus on the upper tails of interest, the user can also supply an arbitrary lower-bound threshold, {chi}{sub low}, above which a shifted distribution model--exponential or Weibull--is fit.
A life-history model of human fitness indicators.
Sefcek, Jon A; Figueredo, Aurelio José
2010-01-01
Recent adaptationist accounts of human mental and physical health have reinvigorated the debate over the evolution of human intelligence. In the tradition of strong inference the current study was developed to determine whether either Miller's (1998, 2000a) Fitness Indicator Theory or Rushton's (1985, 2000) Differential-K Theory better accounts for general intelligence ("g") in an undergraduate university population (N=192). Owing to the lengthy administration time of the test materials, a newly developed 18-item short form of the Ravens Advanced Progressive Matrices (APM-18; Sefcek, Miller, and Figueredo 2007) was used. A significant, positive relationship between K and F (r = .31, p or = .05 and r = .11, p > or = .05, respectively). Though generally contrary to both hypotheses, these results may be explained in relation to antagonistic pleiotropy and a potential failure to derive correct predictions for within-species comparisons directly from the results of between-species comparisons.
Lee, Young-Sun; Wollack, James A.; Douglas, Jeffrey
2009-01-01
The purpose of this study was to assess the model fit of a 2PL through comparison with the nonparametric item characteristic curve (ICC) estimation procedures. Results indicate that three nonparametric procedures implemented produced ICCs that are similar to that of the 2PL for items simulated to fit the 2PL. However for misfitting items,…
A Comparison of Two New Indices for the Assessment of Fit of Structural Equation Models.
Goffin, Richard D.
1993-01-01
Two recent indices of fit, the Relative Noncentrality Index (RNI) (R. P. McDonald and H. W. Marsh, 1990) and the Comparative Fit Index (P. M. Bentler, 1990), are shown to be algebraically equivalent in most applications, although one condition in which the RNI may be advantageous for model comparison is identified. (SLD)
Diploid biological evolution models with general smooth fitness landscapes and recombination.
Saakian, David B; Kirakosyan, Zara; Hu, Chin-Kun
2008-06-01
Using a Hamilton-Jacobi equation approach, we obtain analytic equations for steady-state population distributions and mean fitness functions for Crow-Kimura and Eigen-type diploid biological evolution models with general smooth hypergeometric fitness landscapes. Our numerical solutions of diploid biological evolution models confirm the analytic equations obtained. We also study the parallel diploid model for the simple case of recombination and calculate the variance of distribution, which is consistent with numerical results.
Finite Genome Length Corrections for the Mean Fitness and Gene Probabilities in Evolution Models
Kirakosyan, Zara; Saakian, David B.; Hu, Chin-Kun
2011-07-01
Using the Hamilton-Jacobi equation approach to study genomes of length L, we obtain 1/ L corrections for the steady state population distributions and mean fitness functions for horizontal gene transfer model, as well as for the diploid evolution model with general fitness landscapes. Our numerical solutions confirm the obtained analytic equations. Our method could be applied to the general case of nonlinear Markov models.
Finite population size effects in quasispecies models with single-peak fitness landscape
Saakian, David B.; Deem, Michael W.; Hu, Chin Kun
2012-01-01
We consider finite population size effects for Crow-Kimura and Eigen quasispecies models with single peak fitness landscape. We formulate accurately the iteration procedure for the finite population models, then derive Hamilton-Jacobi equation (HJE) to describe the dynamic of the probability distribution. The steady state solution of HJE gives the variance of the mean fitness. Our results are useful for understanding population sizes of virus in which the infinite population models can give r...
MCMC estimation and some fit analysis of multidimensional IRT models
Beguin, Anton; Glas, Cornelis A.W.
2001-01-01
A Bayesian procedure to estimate the three-parameter normal ogive model and a generalization of the procedure to a model with multidimensional ability parameters are presented. The procedure is a generalization of a procedure by Albert (1992) for estimating the two-parameter normal ogive model. The
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...... of the flexible regression models to analyze competing risks data when non-proportionality is present in the data....
Alternative Models of Person-Environment Fit: Prediction of Morale in Three Homes for the Aged.
Kahana, Eva; And Others
1980-01-01
Tests alternative theoretical models of environment-individual interaction. Findings point to the importance of person-environment fit in the areas of congregation, impulse control, and segregation in explaining morale. (Author)
SPSS macros to compare any two fitted values from a regression model.
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.
Fitting firepower score models to the battle of Kursk data
Gozel, Ramazan
2000-01-01
Approved for public release; distribution is unlimited. This thesis applies several Firepower Score attrition algorithms to real data. These algorithms are used in highly aggregated combat models to predict attrition and movement rates. The quality of the available historical data for validation of attrition models is poor. Most accessible battle data contain only starting sizes and casualties, sometimes only for one side. A detailed database of the Battle of Kursk of World War II, the lar...
Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits
Kopasakis, George
2015-01-01
Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.
Fitness model for the Italian interbank money market
de Masi, G.; Iori, G.; Caldarelli, G.
2006-12-01
We use the theory of complex networks in order to quantitatively characterize the formation of communities in a particular financial market. The system is composed by different banks exchanging on a daily basis loans and debts of liquidity. Through topological analysis and by means of a model of network growth we can determine the formation of different group of banks characterized by different business strategy. The model based on Pareto’s law makes no use of growth or preferential attachment and it reproduces correctly all the various statistical properties of the system. We believe that this network modeling of the market could be an efficient way to evaluate the impact of different policies in the market of liquidity.
Information Theoretic Tools for Parameter Fitting in Coarse Grained Models
Kalligiannaki, Evangelia
2015-01-07
We study the application of information theoretic tools for model reduction in the case of systems driven by stochastic dynamics out of equilibrium. The model/dimension reduction is considered by proposing parametrized coarse grained dynamics and finding the optimal parameter set for which the relative entropy rate with respect to the atomistic dynamics is minimized. The minimization problem leads to a generalization of the force matching methods to non equilibrium systems. A multiplicative noise example reveals the importance of the diffusion coefficient in the optimization problem.
Reducing uncertainty based on model fitness: Application to a ...
African Journals Online (AJOL)
A weakness of global sensitivity and uncertainty analysis methodologies is the often subjective definition of prior parameter probability distributions, especially ... The reservoir representing the central part of the wetland, where flood waters separate into several independent distributaries, is a keystone area within the model.
Reducing uncertainty based on model fitness: Application to a ...
African Journals Online (AJOL)
2015-01-07
Jan 7, 2015 ... This general methodology is applied to a reservoir model of the Okavango ... local or global and global methods can be based on regression, ..... fdet) empirically represent rooting depth and simulate a linear .... work, we apply an enhanced version of FAST, the extended ..... John Wiley & Sons, Ltd., Sussex,.
Design of spatial experiments: Model fitting and prediction
Energy Technology Data Exchange (ETDEWEB)
Fedorov, V.V.
1996-03-01
The main objective of the paper is to describe and develop model oriented methods and algorithms for the design of spatial experiments. Unlike many other publications in this area, the approach proposed here is essentially based on the ideas of convex design theory.
Fitting Meta-Analytic Structural Equation Models with Complex Datasets
Wilson, Sandra Jo; Polanin, Joshua R.; Lipsey, Mark W.
2016-01-01
A modification of the first stage of the standard procedure for two-stage meta-analytic structural equation modeling for use with large complex datasets is presented. This modification addresses two common problems that arise in such meta-analyses: (a) primary studies that provide multiple measures of the same construct and (b) the correlation…
Extended Langmuir model fitting to the filter column adsorption data ...
African Journals Online (AJOL)
Leachate samples collected at different depths of WQD column were analyzed for concentrations of zinc and copper ions using atomic absorption spectrometer. The removal efficiency was around 94% and 92% for zinc and copper respectively using column depth of 1 M at a flow rate of 12 ml/min. The adsorption model ...
Adaptation in tunably rugged fitness landscapes: the rough Mount Fuji model.
Neidhart, Johannes; Szendro, Ivan G; Krug, Joachim
2014-10-01
Much of the current theory of adaptation is based on Gillespie's mutational landscape model (MLM), which assumes that the fitness values of genotypes linked by single mutational steps are independent random variables. On the other hand, a growing body of empirical evidence shows that real fitness landscapes, while possessing a considerable amount of ruggedness, are smoother than predicted by the MLM. In the present article we propose and analyze a simple fitness landscape model with tunable ruggedness based on the rough Mount Fuji (RMF) model originally introduced by Aita et al. in the context of protein evolution. We provide a comprehensive collection of results pertaining to the topographical structure of RMF landscapes, including explicit formulas for the expected number of local fitness maxima, the location of the global peak, and the fitness correlation function. The statistics of single and multiple adaptive steps on the RMF landscape are explored mainly through simulations, and the results are compared to the known behavior in the MLM model. Finally, we show that the RMF model can explain the large number of second-step mutations observed on a highly fit first-step background in a recent evolution experiment with a microvirid bacteriophage. Copyright © 2014 by the Genetics Society of America.
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
Goodness-of-fit tests in mixed models
Claeskens, Gerda
2009-05-12
Mixed models, with both random and fixed effects, are most often estimated on the assumption that the random effects are normally distributed. In this paper we propose several formal tests of the hypothesis that the random effects and/or errors are normally distributed. Most of the proposed methods can be extended to generalized linear models where tests for non-normal distributions are of interest. Our tests are nonparametric in the sense that they are designed to detect virtually any alternative to normality. In case of rejection of the null hypothesis, the nonparametric estimation method that is used to construct a test provides an estimator of the alternative distribution. © 2009 Sociedad de Estadística e Investigación Operativa.
Li, Tongyun; Xie, Chao; Jiao, Hong
2017-06-01
This article explored the application of the posterior predictive model checking (PPMC) method in assessing fit for unidimensional polytomous item response theory (IRT) models, specifically the divide-by-total models (e.g., the generalized partial credit model). Previous research has primarily focused on using PPMC in model checking for unidimensional and multidimensional IRT models for dichotomous data, and has paid little attention to polytomous models. A Monte Carlo simulation was conducted to investigate the performance of PPMC in detecting different sources of misfit for the partial credit model family. Results showed that the PPMC method, in combination with appropriate discrepancy measures, had adequate power in detecting different sources of misfit for the partial credit model family. Global odds ratio and item total correlation exhibited specific patterns in detecting the absence of the slope parameter, whereas Yen's Q1 was found to be promising in the detection of misfit caused by the constant category intersection parameter constraint across items. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Fitting measurement models to vocational interest data: are dominance models ideal?
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.
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.
Some Statistics for Assessing Person-Fit Based on Continuous-Response Models
Ferrando, Pere Joan
2010-01-01
This article proposes several statistics for assessing individual fit based on two unidimensional models for continuous responses: linear factor analysis and Samejima's continuous response model. Both models are approached using a common framework based on underlying response variables and are formulated at the individual level as fixed regression…
A simple model of group selection that cannot be analyzed with inclusive fitness
van Veelen, M.; Luo, S.; Simon, B.
2014-01-01
A widespread claim in evolutionary theory is that every group selection model can be recast in terms of inclusive fitness. Although there are interesting classes of group selection models for which this is possible, we show that it is not true in general. With a simple set of group selection models,
Stochastic point process modelling of rainfall. I. Single-site fitting and validation
Cowpertwait, P. S. P.; O'Connell, P. E.; Metcalfe, A. V.; Mawdsley, J. A.
1996-02-01
A Newman-Scott clustered point process model for rainfall is developed for use in storm sewer rehabilitation studies in the UK, where predictions are needed of the frequency of system overloading for existing and upgraded conditions. In the first part of this two-part paper, a flexible model fitting procedure is presented which involves matching approximately a chosen set of historical rainfall statistics, which exceeds in number the set of parameters. In fitting the model to hourly data, it is found that wet and dry spell transition probabilities should be included in the chosen set of statistics rather than lag 1 autocorrelations, as they improve the model's fit to the historical dry spell sequences. In fitting the model to daily data, estimates of the variances of sub-daily rainfall totals derived from regional regression relationships are used to ensure that sub-daily totals generated by the fitted model exhibit the desired statistical behaviour. A number of validation checks are carried out on simulated time series, which include visual comparisons with historical series, and comparisons of crossing properties and of the distributions of daily annual maximum rainfalls. Overall, the results support the use of the model for its intended application.
ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks
Directory of Open Access Journals (Sweden)
David R. Hunter
2008-12-01
Full Text Available We describe some of the capabilities of the ergm package and the statistical theory underlying it. This package contains tools for accomplishing three important, and inter-related, tasks involving exponential-family random graph models (ERGMs: estimation, simulation, and goodness of fit. More precisely, ergm has the capability of approximating a maximum likelihood estimator for an ERGM given a network data set; simulating new network data sets from a fitted ERGM using Markov chain Monte Carlo; and assessing how well a fitted ERGM does at capturing characteristics of a particular network data set.
Model-based fitting of compression settings using narrowband stimuli
DEFF Research Database (Denmark)
Kowalewski, Borys; Fereczkowski, Michal; MacDonald, Ewen
Most state-of-the-art hearing aids apply multi-channel dynamic-range compression (DRC). Studies using speech intelligibility as an outcome measure have shown mixed results in terms of the benefits of compression over linear amplification (e.g. Davies-Venn et al. 2009; Goedegebure et al. 2001, 2002...... present a compression design that has been optimized, within the framework of a computational model, for improving the performance of (aided) hearing impaired listeners in temporal and spectral resolution-related tasks...... the individual hearing-impaired listeners rely on. Therefore, it is difficult to disentangle them when speech recognition is used as an outcome measure. Edwards (2002) suggested using a set of relatively simple outcome measures, based on narrowband signals, for the evaluation of hearing-aid signal processing. We...
Shekhar, Karthik; Ruberman, Claire F; Ferguson, Andrew L; Barton, John P; Kardar, Mehran; Chakraborty, Arup K
2013-12-01
Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses.
Shekhar, Karthik; Ferguson, Andrew L; Barton, John P; Kardar, Mehran; Chakraborty, Arup K
2013-01-01
Mutational escape from vaccine induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of non-equilibrium viral evolution driven by patient-specific immune responses, and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory \\'{a} la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our f...
Shekhar, Karthik; Ruberman, Claire F.; Ferguson, Andrew L.; Barton, John P.; Kardar, Mehran; Chakraborty, Arup K.
2013-12-01
Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses.
Martin, Guillaume; Roques, Lionel
2016-01-01
Various models describe asexual evolution by mutation, selection, and drift. Some focus directly on fitness, typically modeling drift but ignoring or simplifying both epistasis and the distribution of mutation effects (traveling wave models). Others follow the dynamics of quantitative traits determining fitness (Fisher’s geometric model), imposing a complex but fixed form of mutation effects and epistasis, and often ignoring drift. In all cases, predictions are typically obtained in high or low mutation rate limits and for long-term stationary regimes, thus losing information on transient behaviors and the effect of initial conditions. Here, we connect fitness-based and trait-based models into a single framework, and seek explicit solutions even away from stationarity. The expected fitness distribution is followed over time via its cumulant generating function, using a deterministic approximation that neglects drift. In several cases, explicit trajectories for the full fitness distribution are obtained for arbitrary mutation rates and standing variance. For nonepistatic mutations, especially with beneficial mutations, this approximation fails over the long term but captures the early dynamics, thus complementing stationary stochastic predictions. The approximation also handles several diminishing returns epistasis models (e.g., with an optimal genotype); it can be applied at and away from equilibrium. General results arise at equilibrium, where fitness distributions display a “phase transition” with mutation rate. Beyond this phase transition, in Fisher’s geometric model, the full trajectory of fitness and trait distributions takes a simple form; robust to the details of the mutant phenotype distribution. Analytical arguments are explored regarding why and when the deterministic approximation applies. PMID:27770037
Optimisation of ionic models to fit tissue action potentials: application to 3D atrial modelling.
Al Abed, Amr; Guo, Tianruo; Lovell, Nigel H; Dokos, Socrates
2013-01-01
A 3D model of atrial electrical activity has been developed with spatially heterogeneous electrophysiological properties. The atrial geometry, reconstructed from the male Visible Human dataset, included gross anatomical features such as the central and peripheral sinoatrial node (SAN), intra-atrial connections, pulmonary veins, inferior and superior vena cava, and the coronary sinus. Membrane potentials of myocytes from spontaneously active or electrically paced in vitro rabbit cardiac tissue preparations were recorded using intracellular glass microelectrodes. Action potentials of central and peripheral SAN, right and left atrial, and pulmonary vein myocytes were each fitted using a generic ionic model having three phenomenological ionic current components: one time-dependent inward, one time-dependent outward, and one leakage current. To bridge the gap between the single-cell ionic models and the gross electrical behaviour of the 3D whole-atrial model, a simplified 2D tissue disc with heterogeneous regions was optimised to arrive at parameters for each cell type under electrotonic load. Parameters were then incorporated into the 3D atrial model, which as a result exhibited a spontaneously active SAN able to rhythmically excite the atria. The tissue-based optimisation of ionic models and the modelling process outlined are generic and applicable to image-based computer reconstruction and simulation of excitable tissue.
Optimisation of Ionic Models to Fit Tissue Action Potentials: Application to 3D Atrial Modelling
Lovell, Nigel H.; Dokos, Socrates
2013-01-01
A 3D model of atrial electrical activity has been developed with spatially heterogeneous electrophysiological properties. The atrial geometry, reconstructed from the male Visible Human dataset, included gross anatomical features such as the central and peripheral sinoatrial node (SAN), intra-atrial connections, pulmonary veins, inferior and superior vena cava, and the coronary sinus. Membrane potentials of myocytes from spontaneously active or electrically paced in vitro rabbit cardiac tissue preparations were recorded using intracellular glass microelectrodes. Action potentials of central and peripheral SAN, right and left atrial, and pulmonary vein myocytes were each fitted using a generic ionic model having three phenomenological ionic current components: one time-dependent inward, one time-dependent outward, and one leakage current. To bridge the gap between the single-cell ionic models and the gross electrical behaviour of the 3D whole-atrial model, a simplified 2D tissue disc with heterogeneous regions was optimised to arrive at parameters for each cell type under electrotonic load. Parameters were then incorporated into the 3D atrial model, which as a result exhibited a spontaneously active SAN able to rhythmically excite the atria. The tissue-based optimisation of ionic models and the modelling process outlined are generic and applicable to image-based computer reconstruction and simulation of excitable tissue. PMID:23935704
Optimisation of Ionic Models to Fit Tissue Action Potentials: Application to 3D Atrial Modelling
Directory of Open Access Journals (Sweden)
Amr Al Abed
2013-01-01
Full Text Available A 3D model of atrial electrical activity has been developed with spatially heterogeneous electrophysiological properties. The atrial geometry, reconstructed from the male Visible Human dataset, included gross anatomical features such as the central and peripheral sinoatrial node (SAN, intra-atrial connections, pulmonary veins, inferior and superior vena cava, and the coronary sinus. Membrane potentials of myocytes from spontaneously active or electrically paced in vitro rabbit cardiac tissue preparations were recorded using intracellular glass microelectrodes. Action potentials of central and peripheral SAN, right and left atrial, and pulmonary vein myocytes were each fitted using a generic ionic model having three phenomenological ionic current components: one time-dependent inward, one time-dependent outward, and one leakage current. To bridge the gap between the single-cell ionic models and the gross electrical behaviour of the 3D whole-atrial model, a simplified 2D tissue disc with heterogeneous regions was optimised to arrive at parameters for each cell type under electrotonic load. Parameters were then incorporated into the 3D atrial model, which as a result exhibited a spontaneously active SAN able to rhythmically excite the atria. The tissue-based optimisation of ionic models and the modelling process outlined are generic and applicable to image-based computer reconstruction and simulation of excitable tissue.
Effect of Using Suboptimal Alignments in Template-Based Protein Structure Prediction
Chen, Hao; Kihara, Daisuke
2010-01-01
Computational protein structure prediction remains a challenging task in protein bioinformatics. In the recent years, the importance of template-based structure prediction is increasing due to the growing number of protein structures solved by the structural genomics projects. To capitalize the significant efforts and investments paid on the structural genomics projects, it is urgent to establish effective ways to use the solved structures as templates by developing methods for exploiting remotely related proteins that cannot be simply identified by homology. In this work, we examine the effect of employing suboptimal alignments in template-based protein structure prediction. We showed that suboptimal alignments are often more accurate than the optimal one, and such accurate suboptimal alignments can occur even at a very low rank of the alignment score. Suboptimal alignments contain a significant number of correct amino acid residue contacts. Moreover, suboptimal alignments can improve template-based models when used as input to Modeller. Finally, we employ suboptimal alignments for handling a contact potential in a probabilistic way in a threading program, SUPRB. The probabilistic contacts strategy outperforms the partly thawed approach which only uses the optimal alignment in defining residue contacts and also the reranking strategy, which uses the contact potential in reranking alignments. The comparison with existing methods in the template-recognition test shows that SUPRB is very competitive and outperform existing methods. PMID:21058297
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.
A soluble model of evolution and extinction dynamics in a rugged fitness landscape
Sibani, Paolo
1997-01-01
We consider a continuum version of a previously introduced and numerically studied model of macroevolution (PRL 75, 2055, (1995)) in which agents evolve by an optimization process in a rugged fitness landscape and die due to their competitive interactions. We first formulate dynamical equations for the fitness distribution and the survival probability. Secondly we analytically derive the $t^{-2}$ law which characterizes the life time distribution of biological genera. Thirdly we discuss other...
Zhang, Yichen; Tan, Jonathan C.
2018-01-01
We present a continuum radiative transfer model grid for fitting observed spectral energy distributions (SEDs) of massive protostars. The model grid is based on the paradigm of core accretion theory for massive star formation with pre-assembled gravitationally bound cores as initial conditions. In particular, following the turbulent core model, initial core properties are set primarily by their mass and the pressure of their ambient clump. We then model the evolution of the protostar and its surround structures in a self-consistent way. The model grid contains about 9000 SEDs with four free parameters: initial core mass, the mean surface density of the environment, the protostellar mass, and the inclination. The model grid is used to fit observed SEDs via {χ }2 minimization, with the foreground extinction additionally estimated. We demonstrate the fitting process and results using the example of massive protostar G35.20-0.74. Compared with other SED model grids currently used for massive star formation studies, the properties of the protostar and its surrounding structures are more physically connected in our model grid, which reduces the dimensionality of the parameter spaces and the total number of models. This excludes possible fitting of models that are physically unrealistic or are not internally self-consistent in the context of the turbulent core model. Thus, this model grid serves not only as a fitting tool to estimate properties of massive protostars, but also as a test of core accretion theory. The SED model grid is publicly released with this paper.
Voxel-based multimodel fitting method for modeling time activity curves in SPECT images.
Sarrut, David; Halty, Adrien; Badel, Jean-Noel; Ferrer, Ludovic; Bardiès, Manuel
2017-12-01
Estimating the biodistribution and the pharmacokinetics from time-sequence SPECT images on a per-voxel basis is useful for studying activity nonuniformity or computing absorbed dose distributions by convolution of voxel kernels or Monte-Carlo radiation transport. Current approaches are either region-based, thus assuming uniform activity within the region, or voxel-based but using the same fitting model for all voxels. We propose a voxel-based multimodel fitting method (VoMM) that estimates a fitting function for each voxel by automatically selecting the most appropriate model among a predetermined set with Akaike criteria. This approach can be used to compute the time integrated activity (TIA) for all voxels in the image. To control fitting optimization that may fail due to excessive image noise, an approximated version based on trapezoid integration, named restricted method, is also studied. From this comparison, the number of failed fittings within images was estimated and analyzed. Numerical experiments were used to quantify uncertainties and feasibility was demonstrated with real patient data. Regarding numerical experiments, root mean square errors of TIA obtained with VoMM were similar to those obtained with bi-exponential fitting functions, and were lower ( 10%) than with single model approaches that consider the same fitting function for all voxels. Failure rates were lower with VoMM and restricted approaches than with single-model methods. On real clinical data, VoMM was able to fit 90% of the voxels and led to less failed fits than single-model approaches. On regions of interest (ROI) analysis, the difference between ROI-based and voxel-based TIA estimations was low, less than 4%. However, the computation of the mean residence time exhibited larger differences, up to 25%. The proposed voxel-based multimodel fitting method, VoMM, is feasible on patient data. VoMM leads organ-based TIA estimations similar to conventional ROI-based method. However, for
Gentry, Marcia
2010-01-01
This article presents the author's brief comment on Hisham B. Ghassib's "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?" Ghassib (2010) takes the reader through an interesting history of human innovation and processes and situates his theory within a productivist model. The deliberate attention to…
A fungal growth model fitted to carbon-limited dynamics of Rhizoctonia solani
Jeger, M.J.; Lamour, A.; Gilligan, C.A.; Otten, W.
2008-01-01
Here, a quasi-steady-state approximation was used to simplify a mathematical model for fungal growth in carbon-limiting systems, and this was fitted to growth dynamics of the soil-borne plant pathogen and saprotroph Rhizoctonia solani. The model identified a criterion for invasion into
Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes
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…
Assessing model fit in latent class analysis when asymptotics do not hold
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
The transtheoretical model and exercise behaviour of members in fitness clubs
Middelkamp, P.J.C.; Steenbergen, B.
2015-01-01
Introduction: The transtheoretical model of behaviour change (TTM) is often used to understand changes in health related behaviour, like exercise. The applicability of this model to exercise behaviour of the 140 million members in fitness clubs worldwide has never been systematically reviewed. The
The Congruence Myth: An Analysis of the Efficacy of the Person-Environment Fit Model.
Tinsley, Howard E. A.
2000-01-01
A research review supports the validity of the person-environment fit (PEF) model in vocational psychology; however, sampling inadequacies have influenced results. One PEF example, Holland's hexagonal model, is unsupported due to lack of commensurate measurement; most hexagonal congruence indices are invalid. (Contains 110 references.) (SK)
Optimization-Based Model Fitting for Latent Class and Latent Profile Analyses
Huang, Guan-Hua; Wang, Su-Mei; Hsu, Chung-Chu
2011-01-01
Statisticians typically estimate the parameters of latent class and latent profile models using the Expectation-Maximization algorithm. This paper proposes an alternative two-stage approach to model fitting. The first stage uses the modified k-means and hierarchical clustering algorithms to identify the latent classes that best satisfy the…
DEFF Research Database (Denmark)
Nielsen, Karen L.; Pedersen, Thomas M.; Udekwu, Klas I.
2012-01-01
found significantly independent negative correlations between fitness and the presence of mecA or streptomycin resistance. Mathematical modelling confirmed that fitness costs of the magnitude carried by these isolates could result in the disappearance of MRSA prevalence during a time span similar...... 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...... 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...
Modelling metabolic evolution on phenotypic fitness landscapes: a case study on C4 photosynthesis.
Heckmann, David
2015-12-01
How did the complex metabolic systems we observe today evolve through adaptive evolution? The fitness landscape is the theoretical framework to answer this question. Since experimental data on natural fitness landscapes is scarce, computational models are a valuable tool to predict landscape topologies and evolutionary trajectories. Careful assumptions about the genetic and phenotypic features of the system under study can simplify the design of such models significantly. The analysis of C4 photosynthesis evolution provides an example for accurate predictions based on the phenotypic fitness landscape of a complex metabolic trait. The C4 pathway evolved multiple times from the ancestral C3 pathway and models predict a smooth 'Mount Fuji' landscape accordingly. The modelled phenotypic landscape implies evolutionary trajectories that agree with data on modern intermediate species, indicating that evolution can be predicted based on the phenotypic fitness landscape. Future directions will have to include structural changes of metabolic fitness landscape structure with changing environments. This will not only answer important evolutionary questions about reversibility of metabolic traits, but also suggest strategies to increase crop yields by engineering the C4 pathway into C3 plants. © 2015 Authors; published by Portland Press Limited.
The Predicting Model of E-commerce Site Based on the Ideas of Curve Fitting
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.
On Suboptimal Solution of Antagonistic Matrix Games
Directory of Open Access Journals (Sweden)
Goryashko Alexander
2017-01-01
Full Text Available The paper examines resource allocation games such as Colonel Blotto and Colonel Lotto games with the goal to develop tractable method for building suboptimal solution in mixed strategies of these games without solving the relevant optimization problem. The foundation of proposed method lies in the specific combinatorial properties of the partition games. It turned out that as far as distribution of resource along battlefield is concerned that pure strategies participating in ε-optimal solution possessed specific structure. Numerical experiments showed that these specific structural peculiarities can be easily reproduced utilizing previously found combinatorial properties of partition. As a result, we get ε-optimal solution of partition games and support set mixed strategies can be computed in polynomial time.
A goodness-of-fit test for occupancy models with correlated within-season revisits
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
Ranger, Jochen; Kuhn, Jörg-Tobias; Szardenings, Carsten
2017-05-01
Cognitive psychometric models embed cognitive process models into a latent trait framework in order to allow for individual differences. Due to their close relationship to the response process the models allow for profound conclusions about the test takers. However, before such a model can be used its fit has to be checked carefully. In this manuscript we give an overview over existing tests of model fit and show their relation to the generalized moment test of Newey (Econometrica, 53, 1985, 1047) and Tauchen (J. Econometrics, 30, 1985, 415). We also present a new test, the Hausman test of misspecification (Hausman, Econometrica, 46, 1978, 1251). The Hausman test consists of a comparison of two estimates of the same item parameters which should be similar if the model holds. The performance of the Hausman test is evaluated in a simulation study. In this study we illustrate its application to two popular models in cognitive psychometrics, the Q-diffusion model and the D-diffusion model (van der Maas, Molenaar, Maris, Kievit, & Boorsboom, Psychol Rev., 118, 2011, 339; Molenaar, Tuerlinckx, & van der Maas, J. Stat. Softw., 66, 2015, 1). We also compare the performance of the test to four alternative tests of model fit, namely the M2 test (Molenaar et al., J. Stat. Softw., 66, 2015, 1), the moment test (Ranger et al., Br. J. Math. Stat. Psychol., 2016) and the test for binned time (Ranger & Kuhn, Psychol. Test. Asess. , 56, 2014b, 370). The simulation study indicates that the Hausman test is superior to the latter tests. The test closely adheres to the nominal Type I error rate and has higher power in most simulation conditions. © 2017 The British Psychological Society.
Evaluation of graphical diagnostics for assessing goodness of fit of logistic regression models.
Pavan Kumar, Venkata V; Duffull, Stephen B
2011-04-01
The aim of the current work was to evaluate graphical diagnostics for assessment of the fit of logistic regression models. Assessment of goodness of fit of a model to the data set is essential to ensure the model provides an acceptable description of the binary variables seen. For logistic regression the most common diagnostic used for this purpose is binning the data and comparing the empirical probability of the occurrence of a dependent variable with the model predicted probability against the mean covariate value in the bin. Although intuitively appealing this method, which we term simple binning, may not have consistent properties for diagnosing model problems. In this report we describe and evaluate two different diagnostic procedures, random binning and simplified Bayes marginal model plots. These procedures were assessed via simulation under three different designs. Design 1: studies which were balanced on binary variables and a continuous covariate. Design 2: studies that were balanced on binary variables but unbalanced on the continuous covariate. Design 3: studies that were unbalanced on both the binary variables and the covariate. Each simulated study consisted of 500 individuals. Thirty studies were simulated. The covariate of interest was dose which could range from 0 to 20 units. The data were simulated with the dose being related to the outcome according to an E (max) model on the logit scale. A logit E (max) model (correct model) and a logit linear model (wrong model) were fitted to all data sets. The performance of the above diagnostics, in addition to simple binning, was compared. For all designs the proposed diagnostics performed at least as well and in many instances better than simple binning. In case of design 1 random binning and simple binning are identical. In the case of designs 2 and 3 random binning and simplified Bayes marginal model plots were superior in assessing the model fit when compared to simple binning. For the examples tested
Soluble Model of Evolution and Extinction Dynamics in a Rugged Fitness Landscape
Sibani, Paolo
1997-08-01
We consider a continuum version of a previously introduced and numerically studied model of macroevolution [P. Sibani, M. R. Schimdt, and P. Alstrøm, Phys. Rev. Lett. 75, 2055 (1995)] in which agents evolve by an optimization process in a rugged fitness landscape and die due to their competitive interactions. We first formulate dynamical equations for the fitness distribution and the survival probability. Secondly, we analytically derive the t-2 law which characterizes the lifetime distribution of biological genera. Thirdly, we discuss other dynamical properties of the model as the rate of extinction and conclude with a brief discussion.
Robustness of fit indices to outliers and leverage observations in structural equation modeling.
Yuan, Ke-Hai; Zhong, Xiaoling
2013-06-01
Normal-distribution-based maximum likelihood (NML) is the most widely used method in structural equation modeling (SEM), although practical data tend to be nonnormally distributed. The effect of nonnormally distributed data or data contamination on the normal-distribution-based likelihood ratio (LR) statistic is well understood due to many analytical and empirical studies. In SEM, fit indices are used as widely as the LR statistic. In addition to NML, robust procedures have been developed for more efficient and less biased parameter estimates with practical data. This article studies the effect of outliers and leverage observations on fit indices following NML and two robust methods. Analysis and empirical results indicate that good leverage observations following NML and one of the robust methods lead most fit indices to give more support to the substantive model. While outliers tend to make a good model superficially bad according to many fit indices following NML, they have little effect on those following the two robust procedures. Implications of the results to data analysis are discussed, and recommendations are provided regarding the use of estimation methods and interpretation of fit indices. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
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.
Interventions via Social Influence for Emergent Suboptimal Restraint Use
Directory of Open Access Journals (Sweden)
Ziad KOBTI
2013-08-01
Full Text Available Although restraint use has increased primarily in developed countries, vehicle accident-related injuries and deaths continue to be a problem. Alongside lack of restraint use, studies involving suboptimal restraint use have gained recent popularity. In this study we investigate the use of social influence forinterventions to counter emerging suboptimal restraint use in groups of agents.A multi-agent simulation model is provided where dominant individuals use randomly assigned influence rates to repeatedly alter the knowledge of lessinfluential group members. Cultural influence is implemented via a cultural algorithm and used to simulate individuals affected by beliefs in the community. Objectives include investigating the emergence of patterns of restraint selection and use as well as interventions targeted at more influential agents. Results demonstrate that prominent patterns of behaviour similar to the influentialmembers of the groups do emerge. Furthermore, interventions targeted at influential group members outperform interventions targeted at a percentage of the population at large. Interventions succeed at some level both in the presence and absence of cultural influence.
Local and omnibus goodness-of-fit tests in classical measurement error models
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.
Comparison of Three Measures to Promote National Fitness in China by Mathematical Modeling
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Pan Tang
2014-01-01
Full Text Available In this paper we established a mathematical model for national fitness in China. Based on a questionnaire and data of the General Administration of Sport of China and the National Bureau of Statistics of China, the dynamics for three classes of people are expressed by a system of three-dimensional ordinary equations. Model parameters are estimated from the data. This study indicated that national fitness put out by the Chinese government is reasonable. By finding the key parameter, the best measure to promote national fitness is put forward. In order to increase the number of people who frequently participate in sport exercise in a short period of time, if only one measure can be chosen, guiding people who never take part in physical exercise will be the best measure.
Minimal plus one point designs for testing lack of fit for some sigmoid curve models.
Su, Ying; Raghavarao, Damaraju
2013-03-11
D-optimal designs for nonlinear models are often minimally supported. They have been frequently criticized for their inability to test for lack of fit. We construct alternative designs to address this issue for some commonly used sigmoid curves, including logistic, probit, and Gompertz models with two, three, or four parameters. For each model, we compare five nonminimally supported designs in terms of their efficiency, and propose designs that are both statistically efficient and practically convenient for practitioners.
The FIT 2.0 Model - Fuel-cycle Integration and Tradeoffs
Energy Technology Data Exchange (ETDEWEB)
Steven J. Piet; Nick R. Soelberg; Layne F. Pincock; Eric L. Shaber; Gregory M Teske
2011-06-01
All mass streams from fuel separation and fabrication are products that must meet some set of product criteria – fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the “system losses study” team that developed it [Shropshire2009, Piet2010b] are steps by the Fuel Cycle Technology program toward an analysis that accounts for the requirements and capabilities of each fuel cycle component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R&D needs and set longer-term goals. This report describes FIT 2, an update of the original FIT model.[Piet2010c] FIT is a method to analyze different fuel cycles; in particular, to determine how changes in one part of a fuel cycle (say, fuel burnup, cooling, or separation efficiencies) chemically affect other parts of the fuel cycle. FIT provides the following: Rough estimate of physics and mass balance feasibility of combinations of technologies. If feasibility is an issue, it provides an estimate of how performance would have to change to achieve feasibility. Estimate of impurities in fuel and impurities in waste as function of separation performance, fuel fabrication, reactor, uranium source, etc.
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.
Velasco, Jose; Pizarro, Daniel; Macias-Guarasa, Javier
2012-01-01
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. PMID:23202021
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…
Fit Gap Analysis – The Role of Business Process Reference Models
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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.
Small-sample robust estimators of noncentrality-based and incremental model fit
Boomsma, Anne; Herzog, W.
2009-01-01
Traditional estimators of fit measures based on the noncentral chi-square distribution (root mean square error of approximation [RMSEA], Steiger's , etc.) tend to overreject acceptable models when the sample size is small. To handle this problem, it is proposed to employ Bartlett's (1950), Yuan's
Universal Screening for Emotional and Behavioral Problems: Fitting a Population-Based Model
Schanding, G. Thomas, Jr.; Nowell, Kerri P.
2013-01-01
Schools have begun to adopt a population-based method to conceptualizing assessment and intervention of students; however, little empirical evidence has been gathered to support this shift in service delivery. The present study examined the fit of a population-based model in identifying students' behavioral and emotional functioning using a…
Direct fit of a theoretical model of phase transition in oscillatory finger motions.
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
Flexible Fitting of Atomic Models into Cryo-EM Density Maps Guided by Helix Correspondences.
Dou, Hang; Burrows, Derek W; Baker, Matthew L; Ju, Tao
2017-06-20
Although electron cryo-microscopy (cryo-EM) has recently achieved resolutions of better than 3 Å, at which point molecular modeling can be done directly from the density map, analysis and annotation of a cryo-EM density map still primarily rely on fitting atomic or homology models to the density map. In this article, we present, to our knowledge, a new method for flexible fitting of known or modeled protein structures into cryo-EM density maps. Unlike existing methods that are guided by local density gradients, our method is guided by correspondences between the α-helices in the density map and model, and does not require an initial rigid-body fitting step. Compared with current methods on both simulated and experimental density maps, our method not only achieves greater accuracy for proteins with large deformations but also runs as fast or faster than many of the other flexible fitting routines. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Examining Creative Performance in the Workplace through a Person-Environment Fit Model.
Puccio, Gerard J.; Talbot, Reginald J.; Joniak, Andrew J.
2000-01-01
A modified version of Kirton's Adaptor-Innovator Inventory was used to operationalize the person-environment fit model and a self-report measure was used to assess creative productivity in 40 British adults. Results indicate that style match between the individual and the environment was associated with higher levels of product novelty and…
Predictability of evolutionary trajectories in fitness landscapes.
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Alexander E Lobkovsky
2011-12-01
Full Text Available Experimental studies on enzyme evolution show that only a small fraction of all possible mutation trajectories are accessible to evolution. However, these experiments deal with individual enzymes and explore a tiny part of the fitness landscape. We report an exhaustive analysis of fitness landscapes constructed with an off-lattice model of protein folding where fitness is equated with robustness to misfolding. This model mimics the essential features of the interactions between amino acids, is consistent with the key paradigms of protein folding and reproduces the universal distribution of evolutionary rates among orthologous proteins. We introduce mean path divergence as a quantitative measure of the degree to which the starting and ending points determine the path of evolution in fitness landscapes. Global measures of landscape roughness are good predictors of path divergence in all studied landscapes: the mean path divergence is greater in smooth landscapes than in rough ones. The model-derived and experimental landscapes are significantly smoother than random landscapes and resemble additive landscapes perturbed with moderate amounts of noise; thus, these landscapes are substantially robust to mutation. The model landscapes show a deficit of suboptimal peaks even compared with noisy additive landscapes with similar overall roughness. We suggest that smoothness and the substantial deficit of peaks in the fitness landscapes of protein evolution are fundamental consequences of the physics of protein folding.
Predictability of evolutionary trajectories in fitness landscapes.
Lobkovsky, Alexander E; Wolf, Yuri I; Koonin, Eugene V
2011-12-01
Experimental studies on enzyme evolution show that only a small fraction of all possible mutation trajectories are accessible to evolution. However, these experiments deal with individual enzymes and explore a tiny part of the fitness landscape. We report an exhaustive analysis of fitness landscapes constructed with an off-lattice model of protein folding where fitness is equated with robustness to misfolding. This model mimics the essential features of the interactions between amino acids, is consistent with the key paradigms of protein folding and reproduces the universal distribution of evolutionary rates among orthologous proteins. We introduce mean path divergence as a quantitative measure of the degree to which the starting and ending points determine the path of evolution in fitness landscapes. Global measures of landscape roughness are good predictors of path divergence in all studied landscapes: the mean path divergence is greater in smooth landscapes than in rough ones. The model-derived and experimental landscapes are significantly smoother than random landscapes and resemble additive landscapes perturbed with moderate amounts of noise; thus, these landscapes are substantially robust to mutation. The model landscapes show a deficit of suboptimal peaks even compared with noisy additive landscapes with similar overall roughness. We suggest that smoothness and the substantial deficit of peaks in the fitness landscapes of protein evolution are fundamental consequences of the physics of protein folding.
Mann, Jaclyn K; Barton, John P; Ferguson, Andrew L; Omarjee, Saleha; Walker, Bruce D; Chakraborty, Arup; Ndung'u, Thumbi
2014-08-01
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, and
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
A κ-deformed model of growing complex networks with fitness
Stella, Massimo; Brede, Markus
2014-08-01
The Barabási-Bianconi (BB) fitness model can be solved by a mapping between the original network growth model to an idealized bosonic gas. The well-known transition to Bose-Einstein condensation in the latter then corresponds to the emergence of “super-hubs” in the network model. Motivated by the preservation of the scale-free property, thermodynamic stability and self-duality, we generalize the original extensive mapping of the BB fitness model by using the nonextensive Kaniadakis κ-distribution. Through numerical simulation and mean-field calculations we show that deviations from extensivity do not compromise qualitative features of the phase transition. Analysis of the critical temperature yields a monotonically decreasing dependence on the nonextensive parameter κ.
Directory of Open Access Journals (Sweden)
Rita Yi Man Li
2012-03-01
Full Text Available Entrepreneurs have always born the risk of running their business. They reap a profit in return for their risk taking and work. Housing developers are no different. In many countries, such as Australia, the United Kingdom and the United States, they interpret the tastes of the buyers and provide the dwellings they develop with basic fittings such as floor and wall coverings, bathroom fittings and kitchen cupboards. In mainland China, however, in most of the developments, units or houses are sold without floor or wall coverings, kitchen or bathroom fittings. What is the motive behind this choice? This paper analyses the factors affecting housing developers’ decisions to provide fittings based on 1701 housing developments in Hangzhou, Chongqing and Hangzhou using a Probit model. The results show that developers build a higher proportion of bare units in mainland China when: 1 there is shortage of housing; 2 land costs are high so that the comparative costs of providing fittings become relatively low.
The transtheoretical model and exercise behaviour of members in fitness clubs
Middelkamp, P.J.C.; Steenbergen, B.
2015-01-01
Introduction: The transtheoretical model of behaviour change (TTM) is often used to understand changes in health related behaviour, like exercise. The applicability of this model to exercise behaviour of the 140 million members in fitness clubs worldwide has never been systematically reviewed. The purpose of this paper is to review current TTM studies on exercise behaviour of this specific population. Methods: A systematic literature review was performed using three kinds of databases. In tot...
A mathematical model of actin filament turnover for fitting FRAP data.
Halavatyi, Aliaksandr A; Nazarov, Petr V; Al Tanoury, Ziad; Apanasovich, Vladimir V; Yatskou, Mikalai; Friederich, Evelyne
2010-03-01
A novel mathematical model of the actin dynamics in living cells under steady-state conditions has been developed for fluorescence recovery after photobleaching (FRAP) experiments. As opposed to other FRAP fitting models, which use the average lifetime of actins in filaments and the actin turnover rate as fitting parameters, our model operates with unbiased actin association/dissociation rate constants and accounts for the filament length. The mathematical formalism is based on a system of stochastic differential equations. The derived equations were validated on synthetic theoretical data generated by a stochastic simulation algorithm adapted for the simulation of FRAP experiments. Consistent with experimental findings, the results of this work showed that (1) fluorescence recovery is a function of the average filament length, (2) the F-actin turnover and the FRAP are accelerated in the presence of actin nucleating proteins, (3) the FRAP curves may exhibit both a linear and non-linear behaviour depending on the parameters of actin polymerisation, and (4) our model resulted in more accurate parameter estimations of actin dynamics as compared with other FRAP fitting models. Additionally, we provide a computational tool that integrates the model and that can be used for interpretation of FRAP data on actin cytoskeleton.
Kunina-Habenicht, Olga; Rupp, Andre A.; Wilhelm, Oliver
2012-01-01
Using a complex simulation study we investigated parameter recovery, classification accuracy, and performance of two item-fit statistics for correct and misspecified diagnostic classification models within a log-linear modeling framework. The basic manipulated test design factors included the number of respondents (1,000 vs. 10,000), attributes (3…
A flexible, interactive software tool for fitting the parameters of neuronal models
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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
Quantitative fit assessment of tibial nail designs using 3D computer modelling.
Schmutz, B; Rathnayaka, K; Wullschleger, M E; Meek, J; Schuetz, M A
2010-02-01
Intramedullary nailing is the standard fixation method for displaced diaphyseal fractures of the tibia in adults. The bends in modern tibial nails allow for an easier insertion, enhance the 'bone-nail construct' stability, and reduce axial malalignments of the main fragments. Anecdotal clinical evidence indicates that current nail designs do not fit optimally for patients of Asian origin. The aim of this study was to develop a method to quantitatively assess the anatomical fitting of two different nail designs for Asian tibiae by utilising 3D computer modelling. We used 3D models of two different tibial nail designs (ETN (Expert Tibia Nail) and ETN-Proximal-Bend, Synthes), and 20 CT-based 3D cortex models of Japanese cadaver tibiae. With the aid of computer graphical methods, the 3D nail models were positioned inside the medullary cavity of the intact 3D tibia models. The anatomical fitting between nail and bone was assessed by the extent of the nail protrusion from the medullary cavity into the cortical bone, in a real bone this might lead to axial malalignments of the main fragments. The fitting was quantified in terms of the total surface area, and the maximum distance by which the nail was protruding into the cortex of the virtual bone model. In all 20 bone models, the total area of the nail protruding from the medullary cavity was smaller for the ETN-Proximal-Bend (average 540 mm(2)) compared to the ETN (average 1044 mm(2)). Also, the maximum distance of the nail protruding from the medullary cavity was smaller for the ETN-Proximal-Bend (average 1.2mm) compared to the ETN (average 2.7 mm). The differences were statistically significant (p<0.05) for both the total surface area and the maximum distance measurements. By utilising computer graphical methods it was possible to conduct a quantitative fit assessment of different nail designs. The ETN-Proximal-Bend shows a statistical significantly better intramedullary fit with less cortical protrusion than the
Analysis and fit of stellar spectra using a mega-database of CMFGEN models
Fierro-Santillán, Celia; Zsargó, Janos; Klapp, Jaime; Díaz-Azuara, Santiago Alfredo; Arrieta, Anabel; Arias, Lorena
2017-11-01
We present a tool for analysis and fit of stellar spectra using a mega database of 15,000 atmosphere models for OB stars. We have developed software tools, which allow us to find the model that best fits to an observed spectrum, comparing equivalent widths and line ratios in the observed spectrum with all models of the database. We use the Hα, Hβ, Hγ, and Hδ lines as criterion of stellar gravity and ratios of He II λ4541/He I λ4471, He II λ4200/(He I+He II λ4026), He II λ4541/He I λ4387, and He II λ4200/He I λ4144 as criterion of T eff.
Fitting a mixture model by expectation maximization to discover motifs in biopolymers
Energy Technology Data Exchange (ETDEWEB)
Bailey, T.L.; Elkan, C. [Univ. of California, La Jolla, CA (United States)
1994-12-31
The algorithm described in this paper discovers one or more motifs in a collection of DNA or protein sequences by using the technique of expectation maximization to fit a two-component finite mixture model to the set of sequences. Multiple motifs are found by fitting a mixture model to the data, probabilistically erasing the occurrences of the motif thus found, and repeating the process to find successive motifs. The algorithm requires only a set of unaligned sequences and a number specifying the width of the motifs as input. It returns a model of each motif and a threshold which together can be used as a Bayes-optimal classifier for searching for occurrences of the motif in other databases. The algorithm estimates how many times each motif occurs in each sequence in the dataset and outputs an alignment of the occurrences of the motif. The algorithm is capable of discovering several different motifs with differing numbers of occurrences in a single dataset.
unmarked: An R package for fitting hierarchical models of wildlife occurrence and abundance
Fiske, Ian J.; Chandler, Richard B.
2011-01-01
Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientific questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mechanisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unified modeling interface. The R package unmarked provides such a unified modeling framework, including tools for data exploration, model fitting, model criticism, post-hoc analysis, and model comparison.
unmarked: An R Package for Fitting Hierarchical Models of Wildlife Occurrence and Abundance
Directory of Open Access Journals (Sweden)
Ian J. Fiske
2011-08-01
Full Text Available Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientific questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mechanisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unified modeling interface. The R package unmarked provides such a unified modeling framework, including tools for data exploration, model fitting, model criticism, post-hoc analysis, and model comparison.
Kinetic modelling of RDF pyrolysis: Model-fitting and model-free approaches.
Çepelioğullar, Özge; Haykırı-Açma, Hanzade; Yaman, Serdar
2016-02-01
In this study, refuse derived fuel (RDF) was selected as solid fuel and it was pyrolyzed in a thermal analyzer from room temperature to 900°C at heating rates of 5, 10, 20, and 50°C/min in N2 atmosphere. The obtained thermal data was used to calculate the kinetic parameters using Coats-Redfern, Friedman, Flylnn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS) methods. As a result of Coats-Redfern model, decomposition process was assumed to be four independent reactions with different reaction orders. On the other hand, model free methods demonstrated that activation energy trend had similarities for the reaction progresses of 0.1, 0.2-0.7 and 0.8-0.9. The average activation energies were found between 73-161kJ/mol and it is possible to say that FWO and KAS models produced closer results to the average activation energies compared to Friedman model. Experimental studies showed that RDF may be a sustainable and promising feedstock for alternative processes in terms of waste management strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.
Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components
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
Lobbedez, Thierry; Verger, Christian; Ryckelynck, Jean-Philippe; Fabre, Emmanuel; Evans, David
2013-05-01
This study was carried out to examine the association of sub-optimal dialysis initiation of peritoneal dialysis (PD) with all the possible outcomes on PD using survival analysis in the presence of competing risks. This was a retrospective cohort study based on the data of the French Language Peritoneal Dialysis Registry. We analysed 8527 incident patients starting PD between January 2002 and December 2010. The end of the observation period was 01 June 2011. Times from the start of PD to death, transplantation, transfer to haemodialysis (HD) and first peritonitis episode were calculated. The sub-optimal dialysis initiation was defined by a period of <30 days on HD before PD initiation. Among 8527 patients, there were 568 patients who started PD after <30 days on HD. There were 6562 events: 3078 deaths, 2136 transfers to HD, 1348 renal transplantations. When using a Fine and Gray model, sub-optimal dialysis start, early peritonitis and transplant failure were associated with a higher sub-distribution relative hazard of technique failure. There was no association between the sub-optimal dialysis start and the sub-distribution hazard of death or transplantation. In the multivariate analysis using a Fine and Gray regression model, the sub-optimal dialysis start was not associated with a higher sub distribution relative hazard of peritonitis. Sub-optimal dialysis initiation is neither associated with a higher risk of death nor with a lower risk of renal transplantation. Sub-optimal PD patients had a higher risk of transfer to HD.
Furlan, E.; Fischer, W. J.; Ali, B.; Stutz, A. M.; Stanke, T.; Tobin, J. J.; Megeath, S. T.; Osorio, M.; Hartmann, L.; Calvet, N.; Poteet, C. A.; Booker, J.; Manoj, P.; Watson, D. M.; Allen, L.
2016-05-01
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 μm and sample the peak of the protostellar envelope emission at ˜100 μm. 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.
Estimation of retinal vessel caliber using model fitting and random forests
Araújo, Teresa; Mendonça, Ana Maria; Campilho, Aurélio
2017-03-01
Retinal vessel caliber changes are associated with several major diseases, such as diabetes and hypertension. These caliber changes can be evaluated using eye fundus images. However, the clinical assessment is tiresome and prone to errors, motivating the development of automatic methods. An automatic method based on vessel crosssection intensity profile model fitting for the estimation of vessel caliber in retinal images is herein proposed. First, vessels are segmented from the image, vessel centerlines are detected and individual segments are extracted and smoothed. Intensity profiles are extracted perpendicularly to the vessel, and the profile lengths are determined. Then, model fitting is applied to the smoothed profiles. A novel parametric model (DoG-L7) is used, consisting on a Difference-of-Gaussians multiplied by a line which is able to describe profile asymmetry. Finally, the parameters of the best-fit model are used for determining the vessel width through regression using ensembles of bagged regression trees with random sampling of the predictors (random forests). The method is evaluated on the REVIEW public dataset. A precision close to the observers is achieved, outperforming other state-of-the-art methods. The method is robust and reliable for width estimation in images with pathologies and artifacts, with performance independent of the range of diameters.
Irregular GIS Curve Fitting based High Speed Railway Earthquake Influence Range Calculation Model
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Hu Zhaobing
2017-01-01
Full Text Available In this paper, to guarantee that the train can take measures to reduce the damage caused by the earthquake, it propose an irregular GI S curve fitting based high-speed railway earthquake influence range calculation model. Firstly, this model eliminates the abnormal points, calculates feature points and finds demarcation points of the high- speed railway GI S curve to get the processed point collection in Mercator coordinate. Secondly, though usin g the processed point collection, this model applies least square polynomial segmentation fitting method to implement complex high-speed GI S curve fitting. Thirdly, calculate the earthquake influence rang on high-seed railway line, according to the scope of the earthquake equation and the high-speed railway GI S curve fitt ed equation. Finally, the paper selects the Beijing So uth to Dezhou East high-speed railway section which is part of Beijing-Shanghai line as a case study, which proves that the model can calculate the earthquake influence scope on the railway line offering decision support for train operation to ensure safety.
Not Noisy, Just Wrong: The Role of Suboptimal Inference in Behavioral Variability
Beck, Jeffrey M.; Ma, Wei Ji; Pitkow, Xaq; Latham, Peter E.; Pouget, Alexandre
2015-01-01
Behavior varies from trial to trial even when the stimulus is maintained as constant as possible. In many models, this variability is attributed to noise in the brain. Here, we propose that there is another major source of variability: suboptimal inference. Importantly, we argue that in most tasks of interest, and particularly complex ones, suboptimal inference is likely to be the dominant component of behavioral variability. This perspective explains a variety of intriguing observations, including why variability appears to be larger on the sensory than on the motor side, and why our sensors are sometimes surprisingly unreliable. PMID:22500627
Parameter fitting in three-flavor Nambu–Jona-Lasinio model with various regularizations
Energy Technology Data Exchange (ETDEWEB)
Kohyama, H. [Department of Physics, National Taiwan University, Taipei 10617, Taiwan (China); Kimura, D., E-mail: kimurad@ube-k.ac.jp [General Education, Ube National College of Technology, Ube, Yamaguchi 755-8555 (Japan); Inagaki, T. [Information Media Center, Hiroshima University, Higashi-Hiroshima, Hiroshima 739-8521 (Japan); Core of Research for the Energetic Universe, Hiroshima University, Higashi-Hiroshima 739-8526 (Japan)
2016-05-15
We study the three-flavor Nambu–Jona-Lasinio model with various regularization procedures. We perform parameter fitting in each regularization and apply the obtained parameter sets to evaluate various physical quantities, several light meson masses, decay constant and the topological susceptibility. The model parameters are adopted even at very high cutoff scale compare to the hadronic scale to study the asymptotic behavior of the model. It is found that all the regularization methods except for the dimensional one actually lead reliable physical predictions for the kaon decay constant, sigma meson mass and topological susceptibility without restricting the ultra-violet cutoff below the hadronic scale.
Wu, L.; Chow, D. S-L.; Tam, V.; Putcha, L.
2015-01-01
An intranasal gel formulation of scopolamine (INSCOP) was developed for the treatment of Motion Sickness. Bioavailability and pharmacokinetics (PK) were determined per Investigative New Drug (IND) evaluation guidance by the Food and Drug Administration. Earlier, we reported the development of a PK model that can predict the relationship between plasma, saliva and urinary scopolamine (SCOP) concentrations using data collected from an IND clinical trial with INSCOP. This data analysis project is designed to validate the reported best fit PK model for SCOP by comparing observed and model predicted SCOP concentration-time profiles after administration of INSCOP.
Understanding Host-Switching by Ecological Fitting.
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Sabrina B L Araujo
Full Text Available Despite the fact that parasites are highly specialized with respect to their hosts, empirical evidence demonstrates that host switching rather than co-speciation is the dominant factor influencing the diversification of host-parasite associations. Ecological fitting in sloppy fitness space has been proposed as a mechanism allowing ecological specialists to host-switch readily. That proposal is tested herein using an individual-based model of host switching. The model considers a parasite species exposed to multiple host resources. Through time host range expansion can occur readily without the prior evolution of novel genetic capacities. It also produces non-linear variation in the size of the fitness space. The capacity for host colonization is strongly influenced by propagule pressure early in the process and by the size of the fitness space later. The simulations suggest that co-adaptation may be initiated by the temporary loss of less fit phenotypes. Further, parasites can persist for extended periods in sub-optimal hosts, and thus may colonize distantly related hosts by a "stepping-stone" process.
DEFF Research Database (Denmark)
Ding, Tao; Li, Cheng; Huang, Can
2017-01-01
function of the slave model for the master model, which reflects the impacts of each slave model. Second, the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global......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......–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...
Deng, Bai-Chuan; Yun, Yong-Huan; Liang, Yi-Zeng; Cao, Dong-Sheng; Xu, Qing-Song; Yi, Lun-Zhao; Huang, Xin
2015-06-23
Partial least squares (PLS) is one of the most widely used methods for chemical modeling. However, like many other parameter tunable methods, it has strong tendency of over-fitting. Thus, a crucial step in PLS model building is to select the optimal number of latent variables (nLVs). Cross-validation (CV) is the most popular method for PLS model selection because it selects a model from the perspective of prediction ability. However, a clear minimum of prediction errors may not be obtained in CV which makes the model selection difficult. To solve the problem, we proposed a new strategy for PLS model selection which combines the cross-validated coefficient of determination (Qcv(2)) and model stability (S). S is defined as the stability of PLS regression vectors which is obtained using model population analysis (MPA). The results show that, when a clear maximum of Qcv(2) is not obtained, S can provide additional information of over-fitting and it helps in finding the optimal nLVs. Compared with other regression vector based indictors such as the Euclidean 2-norm (B2), the Durbin Watson statistic (DW) and the jaggedness (J), S is more sensitive to over-fitting. The model selected by our method has both good prediction ability and stability. Copyright © 2015 Elsevier B.V. All rights reserved.
Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU
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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.
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Joshua M. Diamond
2016-01-01
Full Text Available The conserved nature of sleep in Drosophila has allowed the fruit fly to emerge in the last decade as a powerful model organism in which to study sleep. Recent sleep studies in Drosophila have focused on the discovery and characterization of hyposomnolent mutants. One common feature of these animals is a change in sleep architecture: sleep bout count tends to be greater, and sleep bout length lower, in hyposomnolent mutants. I propose a mathematical model, produced by least-squares nonlinear regression to fit the form Y = aX∧b, which can explain sleep behavior in the healthy animal as well as previously-reported changes in total sleep and sleep architecture in hyposomnolent mutants. This model, fit to sleep data, yields coefficient of determination R squared, which describes goodness of fit. R squared is lower, as compared to control, in hyposomnolent mutants insomniac and fumin. My findings raise the possibility that low R squared is a feature of all hyposomnolent mutants, not just insomniac and fumin. If this were the case, R squared could emerge as a novel means by which sleep researchers might assess sleep dysfunction.
Fitting the HIV epidemic in Zambia: a two-sex micro-simulation model.
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Pauline M Leclerc
Full Text Available BACKGROUND: In describing and understanding how the HIV epidemic spreads in African countries, previous studies have not taken into account the detailed periods at risk. This study is based on a micro-simulation model (individual-based of the spread of the HIV epidemic in the population of Zambia, where women tend to marry early and where divorces are not frequent. The main target of the model was to fit the HIV seroprevalence profiles by age and sex observed at the Demographic and Health Survey conducted in 2001. METHODS AND FINDINGS: A two-sex micro-simulation model of HIV transmission was developed. Particular attention was paid to precise age-specific estimates of exposure to risk through the modelling of the formation and dissolution of relationships: marriage (stable union, casual partnership, and commercial sex. HIV transmission was exclusively heterosexual for adults or vertical (mother-to-child for children. Three stages of HIV infection were taken into account. All parameters were derived from empirical population-based data. Results show that basic parameters could not explain the dynamics of the HIV epidemic in Zambia. In order to fit the age and sex patterns, several assumptions were made: differential susceptibility of young women to HIV infection, differential susceptibility or larger number of encounters for male clients of commercial sex workers, and higher transmission rate. The model allowed to quantify the role of each type of relationship in HIV transmission, the proportion of infections occurring at each stage of disease progression, and the net reproduction rate of the epidemic (R(0 = 1.95. CONCLUSIONS: The simulation model reproduced the dynamics of the HIV epidemic in Zambia, and fitted the age and sex pattern of HIV seroprevalence in 2001. The same model could be used to measure the effect of changing behaviour in the future.
Measuring Fit of Sequence Data to Phylogenetic Model: Gain of Power Using Marginal Tests
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 (1978) once argued that evolutionary biology was unscientific as its hypotheses were untestable. Here we trace developments in assessing fit from Penny et al. (1982) to the present. We compare the general log-likelihood ratio (the G or G2 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~0.5), but the marginalized tests do. Tests on pair-wise 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 4t 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 analyses may really be far larger than the analytical methods (e.g., bootstrap) report.
Measuring fit of sequence data to phylogenetic model: gain of power using marginal tests.
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.
Fitting additive hazards models for case-cohort studies: a multiple imputation approach.
Jung, Jinhyouk; Harel, Ofer; Kang, Sangwook
2016-07-30
In this paper, we consider fitting semiparametric additive hazards models for case-cohort studies using a multiple imputation approach. In a case-cohort study, main exposure variables are measured only on some selected subjects, but other covariates are often available for the whole cohort. We consider this as a special case of a missing covariate by design. We propose to employ a popular incomplete data method, multiple imputation, for estimation of the regression parameters in additive hazards models. For imputation models, an imputation modeling procedure based on a rejection sampling is developed. A simple imputation modeling that can naturally be applied to a general missing-at-random situation is also considered and compared with the rejection sampling method via extensive simulation studies. In addition, a misspecification aspect in imputation modeling is investigated. The proposed procedures are illustrated using a cancer data example. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
Computational Software for Fitting Seismic Data to Epidemic-Type Aftershock Sequence Models
Chu, A.
2014-12-01
Modern earthquake catalogs are often analyzed using spatial-temporal point process models such as the epidemic-type aftershock sequence (ETAS) models of Ogata (1998). My work introduces software to implement two of ETAS models described in Ogata (1998). To find the Maximum-Likelihood Estimates (MLEs), my software provides estimates of the homogeneous background rate parameter and the temporal and spatial parameters that govern triggering effects by applying the Expectation-Maximization (EM) algorithm introduced in Veen and Schoenberg (2008). Despite other computer programs exist for similar data modeling purpose, using EM-algorithm has the benefits of stability and robustness (Veen and Schoenberg, 2008). Spatial shapes that are very long and narrow cause difficulties in optimization convergence and problems with flat or multi-modal log-likelihood functions encounter similar issues. My program uses a robust method to preset a parameter to overcome the non-convergence computational issue. In addition to model fitting, the software is equipped with useful tools for examining modeling fitting results, for example, visualization of estimated conditional intensity, and estimation of expected number of triggered aftershocks. A simulation generator is also given with flexible spatial shapes that may be defined by the user. This open-source software has a very simple user interface. The user may execute it on a local computer, and the program also has potential to be hosted online. Java language is used for the software's core computing part and an optional interface to the statistical package R is provided.
Grishaev, Alexander; Guo, Liang; Irving, Thomas; Bax, Ad
2010-11-10
A new procedure, AXES, is introduced for fitting small-angle X-ray scattering (SAXS) data to macromolecular structures and ensembles of structures. By using explicit water models to account for the effect of solvent, and by restricting the adjustable fitting parameters to those that dominate experimental uncertainties, including sample/buffer rescaling, detector dark current, and, within a narrow range, hydration layer density, superior fits between experimental high resolution structures and SAXS data are obtained. AXES results are found to be more discriminating than standard Crysol fitting of SAXS data when evaluating poorly or incorrectly modeled protein structures. AXES results for ensembles of structures previously generated for ubiquitin show improved fits over fitting of the individual members of these ensembles, indicating these ensembles capture the dynamic behavior of proteins in solution.
Model-independent partial wave analysis using a massively-parallel fitting framework
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.
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Riionheimo Janne
2003-01-01
Full Text Available We describe a technique for estimating control parameters for a plucked string synthesis model using a genetic algorithm. The model has been intensively used for sound synthesis of various string instruments but the fine tuning of the parameters has been carried out with a semiautomatic method that requires some hand adjustment with human listening. An automated method for extracting the parameters from recorded tones is described in this paper. The calculation of the fitness function utilizes knowledge of the properties of human hearing.
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Bońkowski T.
2017-12-01
Full Text Available This paper is focused on experimental testing and modeling of genuine leather used for a motorcycle personal protective equipment. Simulations of powered two wheelers (PTW accidents are usually performed using human body models (HBM for the injury assessment equipped only with the helmet model. However, the kinematics of the PTW rider during a real accident is disturbed by the stiffness of his suit, which is normally not taken into account during the reconstruction or simulation of the accident scenario. The material model proposed in this paper can be used in numerical simulations of crash scenarios that include the effect of motorcyclist rider garment. The fitting procedure was conducted on 2 sets of samples: 5 uniaxial samples and 5 biaxial samples. The experimental characteristics were used to obtain the set of 25 constitutive material models in terms of Ogden parameters.
Fitting the Fractional Polynomial Model to Non-Gaussian Longitudinal Data
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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.
Blowout Jets: Hinode X-Ray Jets that Don't Fit the Standard Model
Moore, Ronald L.; Cirtain, Jonathan W.; Sterling, Alphonse C.; Falconer, David A.
2010-01-01
Nearly half of all H-alpha macrospicules in polar coronal holes appear to be miniature filament eruptions. This suggests that there is a large class of X-ray jets in which the jet-base magnetic arcade undergoes a blowout eruption as in a CME, instead of remaining static as in most solar X-ray jets, the standard jets that fit the model advocated by Shibata. Along with a cartoon depicting the standard model, we present a cartoon depicting the signatures expected of blowout jets in coronal X-ray images. From Hinode/XRT movies and STEREO/EUVI snapshots in polar coronal holes, we present examples of (1) X-ray jets that fit the standard model, and (2) X-ray jets that do not fit the standard model but do have features appropriate for blowout jets. These features are (1) a flare arcade inside the jet-base arcade in addition to the small flare arcade (bright point) outside that standard jets have, (2) a filament of cool (T is approximately 80,000K) plasma that erupts from the core of the jetbase arcade, and (3) an extra jet strand that should not be made by the reconnection for standard jets but could be made by reconnection between the ambient unipolar open field and the opposite-polarity leg of the filament-carrying flux-rope core field of the erupting jet-base arcade. We therefore infer that these non-standard jets are blowout jets, jets made by miniature versions of the sheared-core-arcade eruptions that make CMEs
Correlated parameter fit of arrhenius model for thermal denaturation of proteins and cells.
Qin, Zhenpeng; Balasubramanian, Saravana Kumar; Wolkers, Willem F; Pearce, John A; Bischof, John C
2014-12-01
Thermal denaturation of proteins is critical to cell injury, food science and other biomaterial processing. For example protein denaturation correlates strongly with cell death by heating, and is increasingly of interest in focal thermal therapies of cancer and other diseases at temperatures which often exceed 50 °C. The Arrhenius model is a simple yet widely used model for both protein denaturation and cell injury. To establish the utility of the Arrhenius model for protein denaturation at 50 °C and above its sensitivities to the kinetic parameters (activation energy E a and frequency factor A) were carefully examined. We propose a simplified correlated parameter fit to the Arrhenius model by treating E a, as an independent fitting parameter and allowing A to follow dependently. The utility of the correlated parameter fit is demonstrated on thermal denaturation of proteins and cells from the literature as a validation, and new experimental measurements in our lab using FTIR spectroscopy to demonstrate broad applicability of this method. Finally, we demonstrate that the end-temperature within which the denaturation is measured is important and changes the kinetics. Specifically, higher E a and A parameters were found at low end-temperature (50 °C) and reduce as end-temperatures increase to 70 °C. This trend is consistent with Arrhenius parameters for cell injury in the literature that are significantly higher for clonogenics (45-50 °C) vs. membrane dye assays (60-70 °C). Future opportunities to monitor cell injury by spectroscopic measurement of protein denaturation are discussed.
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.
Adapted strategic plannig model applied to small business: a case study in the fitness area
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Eduarda Tirelli Hennig
2012-06-01
Full Text Available The strategic planning is an important management tool in the corporate scenario and shall not be restricted to big Companies. However, this kind of planning process in small business may need special adaptations due to their own characteristics. This paper aims to identify and adapt the existent models of strategic planning to the scenario of a small business in the fitness area. Initially, it is accomplished a comparative study among models of different authors to identify theirs phases and activities. Then, it is defined which of these phases and activities should be present in a model that will be utilized in a small business. That model was applied to a Pilates studio; it involves the establishment of an organizational identity, an environmental analysis as well as the definition of strategic goals, strategies and actions to reach them. Finally, benefits to the organization could be identified, as well as hurdles in the implementation of the tool.
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Veres, Peter; Meszaros, Peter [Department of Astronomy and Astrophysics, Department of Physics, and Center for Particle and Gravitational Astrophysics, Pennsylvania State University, 525 Davey Lab, University Park, PA 16802 (United States); Zhang, Bin-Bin, E-mail: veresp@psu.edu [Department of Astronomy and Astrophysics, Pennsylvania State University, 525 Davey Lab, University Park, PA 16802 (United States)
2013-02-10
We consider gamma-ray burst models where the radiation is dominated by a photospheric region providing the MeV Band spectrum, and an external shock region responsible for the GeV radiation via inverse Compton scattering. We parameterize the initial dynamics through an acceleration law {Gamma}{proportional_to}r {sup {mu}}, with {mu} between 1/3 and 1 to represent the range between an extreme magnetically dominated and a baryonically dominated regime, depending also on the magnetic field configuration. We compare these models to several bright Fermi-LAT bursts, and show that both the time-integrated and the time-resolved spectra, where available, can be well described by these models. We discuss the parameters which result from these fits, and discuss the relative merits and shortcomings of the two models.
VizieR Online Data Catalog: GRB prompt emission fitted with the DREAM model (Ahlgren+, 2015)
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).
The backpack run test: a model for a fair and occupationally relevant military fitness test.
Vanderburgh, P M; Flanagan, S
2000-05-01
Our purpose in this investigation was to develop and validate a theoretical model for a backpack run test based on how fast one can run 2 miles while wearing a backpack. Using actual unloaded (no backpack) 2-mile-run test data from 59 male service academy cadets, we calculated the average oxygen cost during the run, the equivalent cost if wearing additional weight, and the corresponding estimated run time with the backpack. The correlations between body weight and loaded (backpack weight = 30 kg) run times (r = 0.55 [p 0.05], respectively) demonstrate that the bias against heavier runners is eliminated with the backpack run. Given that the backpack run test requires only standard-issue equipment, demonstrates clear occupational and health-related fitness relevance, predicts no apparent body-size bias, and measures work- and health-related components of fitness, we recommend that the military services consider the present data when developing or modifying tests of physical fitness.
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Ayfer SAYIN
2016-12-01
Full Text Available In adjustment studies of scales and in terms of cross validity at scale development, confirmatory factor analysis is conducted. Confirmatory factor analysis, multivariate statistics, is estimated via various parameter estimation methods and utilizes several fit indexes for evaluating the model fit. In this study, model fit indexes utilized in confirmatory factor analysis are examined with different parameter estimation methods under different sample sizes. For the purpose of this study, answers of 60, 100, 250, 500 and 1000 students who attended PISA 2012 program were pulled from the answers to two dimensional “thoughts on the importance of mathematics” dimension. Estimations were based on methods of maximum likelihood (ML, unweighted least squares (ULS and generalized least squares (GLS. As a result of the study, it was found that model fit indexes were affected by the conditions, however some fit indexes were affected less than others and vice versa. In order to analyze these, some suggestions were made.
Suboptimal light conditions influence source-sink metabolism during flowering
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Annelies eChristiaens
2016-03-01
Full Text Available Reliance on carbohydrates during flower forcing was investigated in one early and one late flowering cultivar of azalea (Rhododendron simsii hybrids. Carbohydrate accumulation, invertase activity, and expression of a purported sucrose synthase gene (RsSUS was monitored during flower forcing under suboptimal (natural and optimal (supplemental light light conditions, after a cold treatment (7°C + dark to break flower bud dormancy. Post-production sucrose metabolism and flowering quality was also assessed. Glucose and fructose concentrations and invertase activity increased in petals during flowering, while sucrose decreased. In suboptimal light conditions RsSUS expression in leaves increased as compared to optimal light conditions, indicating that plants in suboptimal light conditions have a strong demand for carbohydrates. However, carbohydrates in leaves were markedly lower in suboptimal light conditions compared to optimal light conditions. This resulted in poor flowering of plants in suboptimal light conditions. Post-production flowering relied on the stored leaf carbon, which could be accumulated under optimal light conditions in the greenhouse. These results show that flower opening in azalea relies on carbohydrates imported from leaves and is source-limiting under suboptimal light conditions.
Thompson, James R.; Wehmeyer, Michael L.; Hughes, Carolyn
2010-01-01
A person-environment fit conceptualization of intellectual disability (ID) requires educators to focus on the gap between a student's competencies and the demands of activities and settings in schools. In this article the implications of the person-environment fit conceptual model are considered in regard to instructional benefits, special…
Gebregziabher, Mulugeta; Egede, Leonard; Gilbert, Gregory E; Hunt, Kelly; Nietert, Paul J; Mauldin, Patrick
2012-10-24
With the current focus on personalized medicine, patient/subject level inference is often of key interest in translational research. As a result, random effects models (REM) are becoming popular for patient level inference. However, for very large data sets that are characterized by large sample size, it can be difficult to fit REM using commonly available statistical software such as SAS since they require inordinate amounts of computer time and memory allocations beyond what are available preventing model convergence. For example, in a retrospective cohort study of over 800,000 Veterans with type 2 diabetes with longitudinal data over 5 years, fitting REM via generalized linear mixed modeling using currently available standard procedures in SAS (e.g. PROC GLIMMIX) was very difficult and same problems exist in Stata's gllamm or R's lme packages. Thus, this study proposes and assesses the performance of a meta regression approach and makes comparison with methods based on sampling of the full data. We use both simulated and real data from a national cohort of Veterans with type 2 diabetes (n=890,394) which was created by linking multiple patient and administrative files resulting in a cohort with longitudinal data collected over 5 years. The outcome of interest was mean annual HbA1c measured over a 5 years period. Using this outcome, we compared parameter estimates from the proposed random effects meta regression (REMR) with estimates based on simple random sampling and VISN (Veterans Integrated Service Networks) based stratified sampling of the full data. Our results indicate that REMR provides parameter estimates that are less likely to be biased with tighter confidence intervals when the VISN level estimates are homogenous. When the interest is to fit REM in repeated measures data with very large sample size, REMR can be used as a good alternative. It leads to reasonable inference for both Gaussian and non-Gaussian responses if parameter estimates are
Understanding Systematics in ZZ Ceti Model Fitting to Enable Differential Seismology
Fuchs, J. T.; Dunlap, B. H.; Clemens, J. C.; Meza, J. A.; Dennihy, E.; Koester, D.
2017-03-01
We are conducting a large spectroscopic survey of over 130 Southern ZZ Cetis with the Goodman Spectrograph on the SOAR Telescope. Because it employs a single instrument with high UV throughput, this survey will both improve the signal-to-noise of the sample of SDSS ZZ Cetis and provide a uniform dataset for model comparison. We are paying special attention to systematics in the spectral fitting and quantify three of those systematics here. We show that relative positions in the log g -Teff plane are consistent for these three systematics.
Inverse problem theory methods for data fitting and model parameter estimation
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
Fitting models to correlated data III: A comparison between residual analysis and other methods
Féménias, Jean-Louis
2005-07-01
Applications of the χ2 test, the F test, the Durbin-Watson d test, and the f (or Sign) test, to examples of correlated data treatment, show important drawbacks with the d test and (apparently) with the f test. An analytical approach based on residual analysis suggests an improvement in their use that leads to better results at lowest order; it also points out a distinction between goodness-of-fit tests, as the f test, and goodness-of-modeling tests, as the χ2 and F tests. The residual analysis method is applied to the same examples; it looks faster, simpler, and often more accurate than the classical ones.
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.
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.
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.
Wenseleers, Tom; Helanterä, Heikki; Alves, Denise A; Dueñez-Guzmán, Edgar; Pamilo, Pekka
2013-01-01
The conflicts over sex allocation and male production in insect societies have long served as an important test bed for Hamilton's theory of inclusive fitness, but have for the most part been considered separately. Here, we develop new coevolutionary models to examine the interaction between these two conflicts and demonstrate that sex ratio and colony productivity costs of worker reproduction can lead to vastly different outcomes even in species that show no variation in their relatedness structure. Empirical data on worker-produced males in eight species of Melipona bees support the predictions from a model that takes into account the demographic details of colony growth and reproduction. Overall, these models contribute significantly to explaining behavioural variation that previous theories could not account for.
Zhang, Hui; Lu, Naiji; Feng, Changyong; Thurston, Sally W; Xia, Yinglin; Zhu, Liang; Tu, Xin M
2011-09-10
The generalized linear mixed-effects model (GLMM) is a popular paradigm to extend models for cross-sectional data to a longitudinal setting. When applied to modeling binary responses, different software packages and even different procedures within a package may give quite different results. In this report, we describe the statistical approaches that underlie these different procedures and discuss their strengths and weaknesses when applied to fit correlated binary responses. We then illustrate these considerations by applying these procedures implemented in some popular software packages to simulated and real study data. Our simulation results indicate a lack of reliability for most of the procedures considered, which carries significant implications for applying such popular software packages in practice. Copyright © 2011 John Wiley & Sons, Ltd.
UROX 2.0: an interactive tool for fitting atomic models into electron-microscopy reconstructions.
Siebert, Xavier; Navaza, Jorge
2009-07-01
Electron microscopy of a macromolecular structure can lead to three-dimensional reconstructions with resolutions that are typically in the 30-10 A range and sometimes even beyond 10 A. 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/.
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.
A diffusion process to model generalized von Bertalanffy growth patterns: fitting to real data.
Román-Román, Patricia; Romero, Desirée; Torres-Ruiz, Francisco
2010-03-07
The von Bertalanffy growth curve has been commonly used for modeling animal growth (particularly fish). Both deterministic and stochastic models exist in association with this curve, the latter allowing for the inclusion of fluctuations or disturbances that might exist in the system under consideration which are not always quantifiable or may even be unknown. This curve is mainly used for modeling the length variable whereas a generalized version, including a new parameter b > or = 1, allows for modeling both length and weight for some animal species in both isometric (b = 3) and allometric (b not = 3) situations. In this paper a stochastic model related to the generalized von Bertalanffy growth curve is proposed. This model allows to investigate the time evolution of growth variables associated both with individual behaviors and mean population behavior. Also, with the purpose of fitting the above-mentioned model to real data and so be able to forecast and analyze particular characteristics, we study the maximum likelihood estimation of the parameters of the model. In addition, and regarding the numerical problems posed by solving the likelihood equations, a strategy is developed for obtaining initial solutions for the usual numerical procedures. Such strategy is validated by means of simulated examples. Finally, an application to real data of mean weight of swordfish is presented. 2009 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Matthew R Nassar
2013-04-01
Full Text Available Fitting models to behavior is commonly used to infer the latent computational factors responsible for generating behavior. However, the complexity of many behaviors can handicap the interpretation of such models. Here we provide perspectives on problems that can arise when interpreting parameter fits from models that provide incomplete descriptions of behavior. We illustrate these problems by fitting commonly used and neurophysiologically motivated reinforcement-learning models to simulated behavioral data sets from learning tasks. These model fits can pass a host of standard goodness-of-fit tests and other model-selection diagnostics even when the models do not provide a complete description of the behavioral data. We show that such incomplete models can be misleading by yielding biased estimates of the parameters explicitly included in the models. This problem is particularly pernicious when the neglected factors are unknown and therefore not easily identified by model comparisons and similar methods. An obvious conclusion is that a parsimonious description of behavioral data does not necessarily imply an accurate description of the underlying computations. Moreover, general goodness-of-fit measures are not a strong basis to support claims that a particular model can provide a generalized understanding of the computations that govern behavior. To help overcome these challenges, we advocate the design of tasks that provide direct reports of the computational variables of interest. Such direct reports complement model-fitting approaches by providing a more complete, albeit possibly more task-specific, representation of the factors that drive behavior. Computational models then provide a means to connect such task-specific results to a more general algorithmic understanding of the brain.
A PID Positioning Controller with a Curve Fitting Model Based on RFID Technology
Directory of Open Access Journals (Sweden)
Young-Long Chen
2013-03-01
Full Text Available The global positioning system (GPS is an important research topic to solve outdoor positioning problems, but GPSis unable to locate objects accurately and precisely indoors. Some available systems apply ultrasound or opticaltracking. This paper presents an efficient proportional-integral-derivative (PID controller with curve fitting model formobile robot localization and position estimation which adopts passive radio frequency identification (RFID tags ina space. This scheme is based on a mobile robot carries an RFID reader module which reads the installed low-costpassive tags under the floor in a grid-like pattern. The PID controllers increase the efficiency of captured RFID tagsand the curve fitting model is used to systematically identify the revolutions per minute (RPM of the motor. Wecontrol and monitor the position of the robot from a remote location through a mobile phone via Wi-Fi and Bluetoothnetwork. Experiment results present that the number of captured RFID tags of our proposed scheme outperformsthat of the previous scheme.
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 PID Positioning Controller with a Curve Fitting Model Based on RFID Technology
Directory of Open Access Journals (Sweden)
Young-Long Chen
2013-04-01
Full Text Available The global positioning system (GPS is an important research topic to solve outdoor positioning problems, but GPS is unable to locate objects accurately and precisely indoors. Some available systems apply ultrasound or optical tracking. This paper presents an efficient proportional-integral-derivative (PID controller with curve fitting model for mobile robot localization and position estimation which adopts passive radio frequency identification (RFID tags in a space. This scheme is based on a mobile robot carries an RFID reader module which reads the installed low-cost passive tags under the floor in a grid-like pattern. The PID controllers increase the efficiency of captured RFID tags and the curve fitting model is used to systematically identify the revolutions per minute (RPM of the motor. We control and monitor the position of the robot from a remote location through a mobile phone via Wi-Fi and Bluetooth network. Experiment results present that the number of captured RFID tags of our proposed scheme outperforms that of the previous scheme.
Sih, Bryant L; Negus, Charles H
2016-05-01
The U.S. Army Basic Combat Training (BCT) is the first step in preparing soldier trainees for the physical demands of the military. Unfortunately, a substantial number of trainees fail BCT due to failure on the final Army Physical Fitness Test (also known as the "end of cycle" APFT). Current epidemiological studies have used statistics to identify several risk factors for poor APFT performance, but these studies have had limited utility for guiding regimen design to maximize APFT outcome. This is because such studies focus on intrinsic risks to APFT failure and do not utilize detailed BCT activity data to build models which offer guidance for optimizing the training regimen to improve graduation rates. In this study, a phenomenological run performance model that accounts for physiological changes in fitness and fatigue due to training was applied to recruits undergoing U.S. Army BCT using high resolution (minute-by-minute) activity data. The phenomenological model was better at predicting both the final as well as intermediate APFTs (R(2) range = 0.55-0.59) compared to linear regression models (LRMs) that used the same intrinsic input variables (R(2) range = 0.36-0.50). Unlike a statistical approach, a phenomenological model accounts for physiological changes and, therefore, has the potential to not only identify trainees at risk of failing BCT on novel training regimens, but offer guidance to regimen planners on how to change the regimen for maximizing physical performance. This paper is Part I of a 2-part series on physical training outcome predictions. Reprint & Copyright © 2016 Association of Military Surgeons of the U.S.
Adaptive suboptimal second-order sliding mode control for microgrids
Incremona, Gian Paolo; Cucuzzella, Michele; Ferrara, Antonella
2016-09-01
This paper deals with the design of adaptive suboptimal second-order sliding mode (ASSOSM) control laws for grid-connected microgrids. Due to the presence of the inverter, of unpredicted load changes, of switching among different renewable energy sources, and of electrical parameters variations, the microgrid model is usually affected by uncertain terms which are bounded, but with unknown upper bounds. To theoretically frame the control problem, the class of second-order systems in Brunovsky canonical form, characterised by the presence of matched uncertain terms with unknown bounds, is first considered. Four adaptive strategies are designed, analysed and compared to select the most effective ones to be applied to the microgrid case study. In the first two strategies, the control amplitude is continuously adjusted, so as to arrive at dominating the effect of the uncertainty on the controlled system. When a suitable control amplitude is attained, the origin of the state space of the auxiliary system becomes attractive. In the other two strategies, a suitable blend between two components, one mainly working during the reaching phase, the other being the predominant one in a vicinity of the sliding manifold, is generated, so as to reduce the control amplitude in steady state. The microgrid system in a grid-connected operation mode, controlled via the selected ASSOSM control strategies, exhibits appreciable stability properties, as proved theoretically and shown in simulation.
Edgar, Patricia H
2002-01-01
1. Technological advancements have rapidly increased the need for careful ethical choices to preserve life and environment of the global community. 2. No formula exists to resolve ethical dilemmas, but using an ethical decision making model can help maintain a state of ethical fitness. 3. The Ethical Fitness model relies on the assumption that certain core values are universal. Maintaining ethical fitness is essential to resolve ethical dilemmas. 4. The process of resolving ethical dilemmas consists of analyzing the dilemma using nine checkpoints, four dilemma paradigms, and three resolution principles.
Suboptimal palliative sedation in primary care: an exploration.
Pype, Peter; Teuwen, Inge; Mertens, Fien; Sercu, Marij; De Sutter, An
2017-06-05
Palliative sedation is a therapeutic option to control refractory symptoms in terminal palliative patients. This study aims at describing the occurrence and characteristics of suboptimal palliative sedations in primary care and at exploring the way general practitioners (GPs) experience suboptimal palliative sedation in their practice. We conducted a mixed methods study with a quantitative prospective survey in primary care and qualitative semi-structured interviews with GPs. The research team defined suboptimal palliative sedation as a time interval until deep sleep >1.5 h and/ or >2 awakenings after the start of the unconsciousness. Descriptive statistics were calculated on the quantitative data. Thematic analysis was used to analyse interview transcripts. We registered 63 palliative sedations in 1181 home deaths, 27 forms were completed. Eleven palliative sedations were suboptimal: eight due to the long time span until deep sleep; three due the number of unintended awakenings. GPs' interview analysis revealed two major themes: the shifting perception of failure and the burden of responsibility. Suboptimal palliative sedation occurs frequently in primary palliative care. Efficient communication towards family members is needed to prevent them from having unrealistic expectations and to prevent putting pressure on the GP to hasten the procedure. Sharing the burden of decision-making during the procedure with other health care professionals might diminish the heavy responsibility as perceived by GPs.
Modeling miRNA-mRNA interactions: fitting chemical kinetics equations to microarray data.
Luo, Zijun; Azencott, Robert; Zhao, Yi
2014-02-18
The miRNAs are small non-coding RNAs of roughly 22 nucleotides in length, which can bind with and inhibit protein coding mRNAs through complementary base pairing. By degrading mRNAs and repressing proteins, miRNAs regulate the cell signaling and cell functions. This paper focuses on innovative mathematical techniques to model gene interactions by algorithmic analysis of microarray data. Our goal was to elucidate which mRNAs were actually degraded or had their translation inhibited by miRNAs belonging to a very large pool of potential miRNAs. We proposed two chemical kinetics equations (CKEs) to model the interactions between miRNAs, mRNAs and the associated proteins. In order to reduce computational cost, we used a non linear profile clustering method named minimal net clustering and efficiently condensed the large set of expression profiles observed in our microarray data sets. We determined unknown parameters of the CKE models by minimizing the discrepancy between model prediction and data, using our own fast non linear optimization algorithm. We then retained only the CKE models for which the optimized fit to microarray data is of high quality and validated multiple miRNA-mRNA pairs. The implementation of CKE modeling and minimal net clustering reduces drastically the potential set of miRNA-mRNA pairs, with a high gain for further experimental validations. The minimal net clustering also provides good miRNA candidates that have similar regulatory roles.
Kolmogorov goodness-of-fit test for S -symmetric distributions in climate and weather modeling
Zenkova, Z.; Lanshakova, L.
2016-11-01
Statistical data treatment is an essential part of climate and weather modeling. The Kolmogorov goodness-of-fit test is a widely applicable statistical method to determine the cumulative distribution function of a continuous random variable, e.g., a precipitation level, wind force, etc. In this paper, the authors consider a problem of goodness-of-fit testing involving additional information about S-symmetry of the cumulative distribution function and its influence on the Kolmogorov statistic distributions. A definition of S-symmetry is given; it is a generalized classical definition of distribution symmetry. It is proved that any continuous increasing cumulative distribution function is S-symmetric. A uniform distribution is considered as an example of an S-symmetric distribution. A modification of the Kolmogorov statistic using additional information about the new type of symmetry is proposed. The exact and asymptotic distributions under the null and the alternative hypothesis of the modified statistics are described. The authors also provide an example which proves that the modified test is more powerful than the non-modified one. The new test is used to check the hypothesis of a uniform distribution of the average sum of precipitation.
Model Atmosphere Spectrum Fit to the Soft X-Ray Outburst Spectrum of SS Cyg
Directory of Open Access Journals (Sweden)
V. F. Suleimanov
2015-02-01
Full Text Available The X-ray spectrum of SS Cyg in outburst has a very soft component that can be interpreted as the fast-rotating optically thick boundary layer on the white dwarf surface. This component was carefully investigated by Mauche (2004 using the Chandra LETG spectrum of this object in outburst. The spectrum shows broad ( ≈5 °A spectral features that have been interpreted as a large number of absorption lines on a blackbody continuum with a temperature of ≈250 kK. Because the spectrum resembles the photospheric spectra of super-soft X-ray sources, we tried to fit it with high gravity hot LTE stellar model atmospheres with solar chemical composition, specially computed for this purpose. We obtained a reasonably good fit to the 60–125 °A spectrum with the following parameters: Teff = 190 kK, log g = 6.2, and NH = 8 · 1019 cm−2, although at shorter wavelengths the observed spectrum has a much higher flux. The reasons for this are discussed. The hypothesis of a fast rotating boundary layer is supported by the derived low surface gravity.
Suboptimal Rate Adaptive Resource Allocation for Downlink OFDMA Systems
Directory of Open Access Journals (Sweden)
Sanam Sadr
2009-01-01
Full Text Available This paper aims to study the performance of low complexity adaptive resource allocation in the downlink of OFDMA systems with fixed or variable rate requirements (with fairness consideration. Two suboptimal resource allocation algorithms are proposed using the simplifying assumption of transmit power over the entire bandwidth. The objective of the first algorithm is to maximize the total throughput while maintaining rate proportionality among the users. The proposed suboptimal algorithm prioritizes the user with the highest sensitivity to the subcarrier allocation, and the variance over the subchannel gains is used to define the sensitivity of each user. The second algorithm concerns rate adaptive resource allocation in multiuser systems with fixed rate constraints. We propose a suboptimal joint subchannel and power allocation algorithm which prioritizes the users with the highest required data rates. The main feature of this algorithm is its low complexity while achieving the rate requirements.
FIT ANALYSIS OF INDOSAT DOMPETKU BUSINESS MODEL USING A STRATEGIC DIAGNOSIS APPROACH
Directory of Open Access Journals (Sweden)
Fauzi Ridwansyah
2015-09-01
Full Text Available Mobile payment is an industry's response to global and regional technological-driven, as well as national social-economical driven in less cash society development. The purposes of this study were 1 identifying positioning of PT. Indosat in providing a response to Indonesian mobile payment market, 2 analyzing Indosat’s internal capabilities and business model fit with environment turbulence, and 3 formulating the optimum mobile payment business model development design for Indosat. The method used in this study was a combination of qualitative and quantitative analysis through in-depth interviews with purposive judgment sampling. The analysis tools used in this study were Business Model Canvas (MBC and Ansoff’s Strategic Diagnosis. The interviewees were the representatives of PT. Indosat internal management and mobile payment business value chain stakeholders. Based on BMC mapping which is then analyzed by strategic diagnosis model, a considerable gap (>1 between the current market environment and Indosat strategy of aggressiveness with the expected future of environment turbulence level was obtained. Therefore, changes in the competitive strategy that need to be conducted include 1 developing a new customer segment, 2 shifting the value proposition that leads to the extensification of mobile payment, 3 monetizing effective value proposition, and 4 integrating effective collaboration for harmonizing company’s objective with the government's vision. Keywords: business model canvas, Indosat, mobile payment, less cash society, strategic diagnosis
Statistics of dark matter substructure - I. Model and universal fitting functions
Jiang, Fangzhou; van den Bosch, Frank C.
2016-05-01
We present a new, semi-analytical model describing the evolution of dark matter subhaloes. The model uses merger trees constructed using the method of Parkinson et al. to describe the masses and redshifts of subhaloes at accretion, which are subsequently evolved using a simple model for the orbit-averaged mass-loss rates. The model is extremely fast, treats subhaloes of all orders, accounts for scatter in orbital properties and halo concentrations, uses a simple recipe to convert subhalo mass to maximum circular velocity, and considers subhalo disruption. The model is calibrated to accurately reproduce the average subhalo mass and velocity functions in numerical simulations. We demonstrate that, on average, the mass fraction in subhaloes is tightly correlated with the `dynamical age' of the host halo, defined as the number of halo dynamical times that have elapsed since its formation. Using this relation, we present universal fitting functions for the evolved and unevolved subhalo mass and velocity functions that are valid for a broad range in host halo mass, redshift and Λ cold dark matter cosmology.
Body-Fitted Detonation Shock Dynamics and the Pseudo-Reaction-Zone Energy Release Model
Meyer, Chad; Quirk, James; Short, Mark; Chqiuete, Carlos
2016-11-01
Programmed-burn methods are a class of models used to propagate a detonation wave, without the high resolution cost associated with a direct numerical simulation. They separate the detonation evolution calculation into two components: timing and energy release. The timing component is usually calculated with a Detonation Shock Dynamics model, a surface evolution representation that relates the normal velocity of the surface (Dn) to its local curvature. The energy release component must appropriately capture the degree of energy change associated with chemical reaction while simultaneously remaining synchronized with the timing component. The Pseudo-Reaction-Zone (PRZ) model is a reactive burn like energy release model, converting reactants into products, but with a conversion rate that is a function of the DSD surface Dn field. As such, it requires the DSD calculation produce smooth Dn fields, a challenge in complex geometries. We describe a new body-fitted approach to the Detonation Shock Dynamics calculation which produces the required smooth Dn fields, and a method for calibrating the PRZ model such that the rate of energy release remains as synced as possible with the timing component. We show results for slab, rate-stick and arc geometries.
Comparing Smoothing Techniques for Fitting the Nonlinear Effect of Covariate in Cox Models.
Roshani, Daem; Ghaderi, Ebrahim
2016-02-01
Cox model is a popular model in survival analysis, which assumes linearity of the covariate on the log hazard function, While continuous covariates can affect the hazard through more complicated nonlinear functional forms and therefore, Cox models with continuous covariates are prone to misspecification due to not fitting the correct functional form for continuous covariates. In this study, a smooth nonlinear covariate effect would be approximated by different spline functions. We applied three flexible nonparametric smoothing techniques for nonlinear covariate effect in the Cox models: penalized splines, restricted cubic splines and natural splines. Akaike information criterion (AIC) and degrees of freedom were used to smoothing parameter selection in penalized splines model. The ability of nonparametric methods was evaluated to recover the true functional form of linear, quadratic and nonlinear functions, using different simulated sample sizes. Data analysis was carried out using R 2.11.0 software and significant levels were considered 0.05. Based on AIC, the penalized spline method had consistently lower mean square error compared to others to selection of smoothed parameter. The same result was obtained with real data. Penalized spline smoothing method, with AIC to smoothing parameter selection, was more accurate in evaluate of relation between covariate and log hazard function than other methods.
Suboptimal care in stillbirths - a retrospective audit study.
Saastad, Eli; Vangen, Siri; Frøen, J Frederik
2007-01-01
Stillbirth rates have decreased radically over the last decades. One reason for this is improved perinatal care. The aim of this study was to explore whether sub-optimal factors in stillbirths were more frequent among non-western than western women. Population-based perinatal audit of 356 stillbirths after gestational week 23, in 2 Norwegian counties during 1998-2003 (4.2 per 1,000 deliveries); of these 31% were born to non-western women. By audit, the stillbirths were attributed to optimal or sub-optimal care factors. Multivariate methods were used to analyse the data. Sub-optimal factors were identified in 37% of the deaths. When compared to western women, non-western women had an increased risk of stillbirth (OR: 2.2; 95% CI: 1.3-3.8), and an increased risk of sub-optimal care (OR: 2.4; 95% CI: 1.5-3.9). More often, non-western women received sub-optimal obstetric care (plabour progression. A common failure in antenatal care for both groups was unidentified or inadequate management of intrauterine growth restriction or decreased fetal movements. Non-western women were less prone to attend the program for antenatal care or to take the consequences of recommendations from health professionals. Inadequate communication was documented in 47% of non-western mothers; an interpreter was used in 29% of these cases. Non-western women constituted a risk group for sub-optimal care factors in stillbirths. Possibilities for improvements include a reduction of language barriers, better identification and management of growth restriction for both origin groups, and adequate intervention in complicated vaginal births; with increased vigilance towards non-western women.
A new fit-for-purpose model testing framework: Decision Crash Tests
Tolson, Bryan; Craig, James
2016-04-01
Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building
On the Model-Based Bootstrap with Missing Data: Obtaining a "P"-Value for a Test of Exact Fit
Savalei, Victoria; Yuan, Ke-Hai
2009-01-01
Evaluating the fit of a structural equation model via bootstrap requires a transformation of the data so that the null hypothesis holds exactly in the sample. For complete data, such a transformation was proposed by Beran and Srivastava (1985) for general covariance structure models and applied to structural equation modeling by Bollen and Stine…
Energy Technology Data Exchange (ETDEWEB)
Moore, Kevin L., E-mail: kevinmoore@ucsd.edu [Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California (United States); Schmidt, Rachel [Department of Physics, Fort Hays State University, Hays, Kansas (United States); Moiseenko, Vitali [Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California (United States); Olsen, Lindsey A.; Tan, Jun [Department of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri (United States); Xiao, Ying; Galvin, James [Thomas Jefferson University Hospital, Philadelphia, Pennsylvania (United States); Pugh, Stephanie [NRG Oncology Statistics and Data Management Center, Philadelphia, Pennsylvania (United States); Seider, Michael J. [Akron City Hospital, Akron, Ohio (United States); Dicker, Adam P. [Thomas Jefferson University Hospital, Philadelphia, Pennsylvania (United States); Bosch, Walter; Michalski, Jeff; Mutic, Sasa [Department of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri (United States)
2015-06-01
Purpose: The purpose of this study was to quantify the frequency and clinical severity of quality deficiencies in intensity modulated radiation therapy (IMRT) planning in the Radiation Therapy Oncology Group 0126 protocol. Methods and Materials: A total of 219 IMRT patients from the high-dose arm (79.2 Gy) of RTOG 0126 were analyzed. To quantify plan quality, we used established knowledge-based methods for patient-specific dose-volume histogram (DVH) prediction of organs at risk and a Lyman-Kutcher-Burman (LKB) model for grade ≥2 rectal complications to convert DVHs into normal tissue complication probabilities (NTCPs). The LKB model was validated by fitting dose-response parameters relative to observed toxicities. The 90th percentile (22 of 219) of plans with the lowest excess risk (difference between clinical and model-predicted NTCP) were used to create a model for the presumed best practices in the protocol (pDVH{sub 0126,top10%}). Applying the resultant model to the entire sample enabled comparisons between DVHs that patients could have received to DVHs they actually received. Excess risk quantified the clinical impact of suboptimal planning. Accuracy of pDVH predictions was validated by replanning 30 of 219 patients (13.7%), including equal numbers of presumed “high-quality,” “low-quality,” and randomly sampled plans. NTCP-predicted toxicities were compared to adverse events on protocol. Results: Existing models showed that bladder-sparing variations were less prevalent than rectum quality variations and that increased rectal sparing was not correlated with target metrics (dose received by 98% and 2% of the PTV, respectively). Observed toxicities were consistent with current LKB parameters. Converting DVH and pDVH{sub 0126,top10%} to rectal NTCPs, we observed 94 of 219 patients (42.9%) with ≥5% excess risk, 20 of 219 patients (9.1%) with ≥10% excess risk, and 2 of 219 patients (0.9%) with ≥15% excess risk. Replanning demonstrated the
Pan, Xinyi; Li, Cheng; Ying, Kui; Weng, Dehe; Qin, Wen; Li, Kuncheng
2010-04-01
A model-based proton resonance frequency shift (PRFS) thermometry method was developed to significantly reduce the temperature quantification errors encountered in the conventional phase mapping method and the spatiotemporal limitations of the spectroscopic thermometry method. Spectral data acquired using multi-echo gradient echo (GRE) is fit into a two-component signal model containing temperature information and fat is used as the internal reference. The noniterative extended Prony algorithm is used for the signal fitting and frequency estimate. Monte Carlo simulations demonstrate the advantages of the method for optimal water-fat separation and temperature estimation accuracy. Phantom experiments demonstrate that the model-based method effectively reduces the interscan motion effects and frequency disturbances due to the main field drift. The thermometry result of ex vivo goose liver experiment with high intensity focused ultrasound (HIFU) heating was also presented in the paper to indicate the feasibility of the model-based method in real tissue. Copyright 2010 Elsevier Inc. All rights reserved.
Photothermal model fitting in the complex plane for thermal properties determination in solids.
Zambrano-Arjona, M A; Peñuñuri, F; Acosta, M; Riech, I; Medina-Esquivel, R A; Martínez-Torres, P; Alvarado-Gil, J J
2013-02-01
Thermal properties of solids are obtained by fitting the exact complex photothermal model to the normalized photoacoustic (PA) signal in the front configuration. Simple closed-form expressions for the amplitude and phase are presented in all frequency ranges. In photoacoustic it has been common practice to assume that all the absorptions of radiation take place in the sample. However, in order to obtain the accurate thermal properties it is necessary to consider the PA signal contributions produced at the cell walls. Such contributions were considered in our study. To demonstrate the usefulness of the proposed methodology, commercial stainless steel layers AISI 302 were analyzed. It is shown that using our approach the obtained thermal diffusivity and effusivity were in good agreement with those reported in the literature. Also, a detailed procedure for the calculation of the standard error in the thermal properties is discussed.
A convex programming framework for optimal and bounded suboptimal well field management
DEFF Research Database (Denmark)
Dorini, Gianluca Fabio; Thordarson, Fannar Ørn; Bauer-Gottwein, Peter
2012-01-01
are often convex, hence global optimality can be attained by a wealth of algorithms. Among these, the Interior Point methods are extensively employed for practical applications, as they are capable of efficiently solving large-scale problems. Despite this, management models explicitly embedding both systems...... without simplifications are rare, and they usually involve heuristic techniques. The main limitation with heuristics is that neither optimality nor suboptimality bounds can be guarantee. This paper extends the proof of convexity to mixed management models, enabling the use of Interior Point techniques...... to compute globally optimal management solutions. If convexity is not achieved, it is shown how suboptimal solutions can be computed, and how to bind their deviation from the optimality. Experimental results obtained by testing the methodology in a well field located nearby Copenhagen (DK), show...
Effects of Suboptimal Bidding in Combinatorial Auctions
Schneider, Stefan; Shabalin, Pasha; Bichler, Martin
Though the VCG auction assumes a central place in the mechanism design literature, there are a number of reasons for favoring iterative combinatorial auction designs. Several promising ascending auction formats have been developed throughout the past few years based on primal-dual and subgradient algorithms and linear programming theory. Prices are interpreted as a feasible dual solution and the provisional allocation is interpreted as a feasible primal solution. iBundle( 3) (Parkes and Ungar 2000), dVSV (de Vries et al. 2007) and the Ascending Proxy auction (Ausubel and Milgrom 2002) result in VCG payoffs when the coalitional value function satisfies the buyer submodularity condition and bidders bid straightforward, which is an expost Nash equilibrium in that case. iBEA and CreditDebit auctions (Mishra and Parkes 2007) do not even require the buyer submodularity condition and achieve the same properties for general valuations. In many situations, however, one cannot assume bidders to bid straightforward and it is not clear from the theory how these non-linear personalized price auctions (NLPPAs) perform in this case. Robustness of auctions with respect to different bidding behavior is therefore a critical issue for any application. We have conducted a large number of computational experiments to analyze the performance of NLPPA designs with respect to different bidding strategies and different valuation models. We compare the results of NLPPAs to those of the VCG auction and those of iterative combinatorial auctions with approximate linear prices, such as ALPS (Bichler et al. 2009) and the Combinatorial Clock auction (Porter et al. 2003).
Directory of Open Access Journals (Sweden)
Gurutzeta Guillera-Arroita
Full Text Available In a recent paper, Welsh, Lindenmayer and Donnelly (WLD question the usefulness of models that estimate species occupancy while accounting for detectability. WLD claim that these models are difficult to fit and argue that disregarding detectability can be better than trying to adjust for it. We think that this conclusion and subsequent recommendations are not well founded and may negatively impact the quality of statistical inference in ecology and related management decisions. Here we respond to WLD's claims, evaluating in detail their arguments, using simulations and/or theory to support our points. In particular, WLD argue that both disregarding and accounting for imperfect detection lead to the same estimator performance regardless of sample size when detectability is a function of abundance. We show that this, the key result of their paper, only holds for cases of extreme heterogeneity like the single scenario they considered. Our results illustrate the dangers of disregarding imperfect detection. When ignored, occupancy and detection are confounded: the same naïve occupancy estimates can be obtained for very different true levels of occupancy so the size of the bias is unknowable. Hierarchical occupancy models separate occupancy and detection, and imprecise estimates simply indicate that more data are required for robust inference about the system in question. As for any statistical method, when underlying assumptions of simple hierarchical models are violated, their reliability is reduced. Resorting in those instances where hierarchical occupancy models do no perform well to the naïve occupancy estimator does not provide a satisfactory solution. The aim should instead be to achieve better estimation, by minimizing the effect of these issues during design, data collection and analysis, ensuring that the right amount of data is collected and model assumptions are met, considering model extensions where appropriate.
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.
Silva, Mónica A.; Jonsen, Ian; Russell, Deborah J. F.; Prieto, Rui; Thompson, Dave; Baumgartner, Mark F.
2014-01-01
Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF). The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS) algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs) fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina) tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to “true” GPS locations. Data on 6 fin whales (Balaenoptera physalus) were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM) fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were <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. PMID:24651252
Modeling of physical fitness of young karatyst on the pre basic training
Directory of Open Access Journals (Sweden)
Galimskyi V.A.
2014-05-01
Full Text Available Purpose : to develop a program of physical fitness for the correction of the pre basic training on the basis of model performance. Material: 57 young karate sportsmen of 9-11 years old took part in the research. Results : the level of general and special physical preparedness of young karate 9-11 years old was determined. Classes in the control group occurred in the existing program for yous sports school Muay Thai (Thailand boxing. For the experimental group has developed a program of selective development of general and special physical qualities of model-based training sessions. Special program contains 6 direction: 1. Development of static and dynamic balance; 2. Development of vestibular stability (precision movements after rotation; 3. Development rate movements; 4. The development of the capacity for rapid restructuring movements; 5. Development capabilities to differentiate power and spatial parameters of movement; 6. Development of the ability to perform jumping movements of rotation. Development of special physical qualities continued to work to improve engineering complex shock motions on the place and with movement. Conclusions : the use of selective development of special physical qualities based models of training sessions has a significant performance advantage over the control group.
Global fits of GUT-scale SUSY models with GAMBIT arXiv
Athron, Peter; Bringmann, Torsten; Buckley, Andy; Chrząszcz, Marcin; Conrad, Jan; Cornell, Jonathan M.; Dal, Lars A.; Edsjö, Joakim; Farmer, Ben; Jackson, Paul; Krislock, Abram; Kvellestad, Anders; Mahmoudi, Farvah; \\ Martinez, Gregory D.; Putze, Antje; Raklev, Are; Rogan, Christopher; Ruiz de Austri, Roberto; Saavedra, Aldo; Savage, Christopher; Scott, Pat; Serra, Nicola; Weniger, Christoph; White, Martin
We present the most comprehensive global fits to date of three supersymmetric models motivated by grand unification: the Constrained Minimal Supersymmetric Standard Model (CMSSM), and its Non-Universal Higgs Mass generalisations NUHM1 and NUHM2. We include likelihoods from a number of direct and indirect dark matter searches, a large collection of electroweak precision and flavour observables, direct searches for supersymmetry at LEP and Runs I and II of the LHC, and constraints from Higgs observables. Our analysis improves on existing results not only in terms of the number of included observables, but also in the level of detail with which we treat them, our sampling techniques for scanning the parameter space, and our treatment of nuisance parameters. We show that stau co-annihilation is now ruled out in the CMSSM at more than 95\\% confidence. Stop co-annihilation turns out to be one of the most promising mechanisms for achieving an appropriate relic density of dark matter in all three models, whilst avoid...
Supersymmetric fits after the Higgs discovery and implications for model building.
Ellis, John
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 [Formula: see text] accompanied by jets, and the LHCb and CMS measurements of [Formula: see text]. Results are presented from frequentist analyses of the parameter spaces of the CMSSM and NUHM1. The global [Formula: see text] functions for the supersymmetric models vary slowly over most of the parameter spaces allowed by the Higgs mass and the [Formula: see text] search, with best-fit values that are comparable to the [Formula: see text] for the standard model. The 95 % CL lower limits on the masses of gluinos and squarks allow significant prospects for observing them during the LHC runs at higher energies.
Physician behavioral adaptability: A model to outstrip a "one size fits all" approach.
Carrard, Valérie; Schmid Mast, Marianne
2015-10-01
Based on a literature review, we propose a model of physician behavioral adaptability (PBA) with the goal of inspiring new research. PBA means that the physician adapts his or her behavior according to patients' different preferences. The PBA model shows how physicians infer patients' preferences and adapt their interaction behavior from one patient to the other. We claim that patients will benefit from better outcomes if their physicians show behavioral adaptability rather than a "one size fits all" approach. This literature review is based on a literature search of the PsycINFO(®) and MEDLINE(®) databases. The literature review and first results stemming from the authors' research support the validity and viability of parts of the PBA model. There is evidence suggesting that physicians are able to show behavioral flexibility when interacting with their different patients, that a match between patients' preferences and physician behavior is related to better consultation outcomes, and that physician behavioral adaptability is related to better consultation outcomes. Training of physicians' behavioral flexibility and their ability to infer patients' preferences can facilitate physician behavioral adaptability and positive patient outcomes. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Supersymmetric Fits after the Higgs Discovery and Implications for Model Building
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...
Fitting a Thurstonian IRT model to forced-choice data using Mplus.
Brown, Anna; Maydeu-Olivares, Alberto
2012-12-01
To counter response distortions associated with the use of rating scales (a.k.a. Likert scales), items can be presented in a comparative fashion, so that respondents are asked to rank the items within blocks (forced-choice format). However, classical scoring procedures for these forced-choice designs lead to ipsative data, which presents psychometric challenges that are well described in the literature. Recently, Brown and Maydeu-Olivares (Educational and Psychological Measurement 71: 460-502, 2011a) introduced a model based on Thurstone's law of comparative judgment, which overcomes the problems of ipsative data. Here, we provide a step-by-step tutorial for coding forced-choice responses, specifying a Thurstonian item response theory model that is appropriate for the design used, assessing the model's fit, and scoring individuals on psychological attributes. Estimation and scoring is performed using Mplus, and a very straightforward Excel macro is provided that writes full Mplus input files for any forced-choice design. Armed with these tools, using a forced-choice design is now as easy as using ratings.
Sacral Nerve Stimulation for Constipation: Suboptimal Outcome and Adverse Events
DEFF Research Database (Denmark)
Maeda, Yasuko; Lundby, Lilli; Buntzen, Steen
2010-01-01
Sacral nerve stimulation is an emerging treatment for patients with severe constipation. There has been no substantial report to date on suboptimal outcomes and complications. We report our experience of more than 6 years by focusing on incidents and the management of reportable events....
Optimal and Suboptimal Noises Enhancing Mutual Information in Threshold System
Zhai, Qiqing; Wang, Youguo
2016-05-01
In this paper, we investigate the efficacy of noise enhancing information transmission in a threshold system. At first, in the frame of stochastic resonance (SR), optimal noise (Opt N) is derived to maximize mutual information (MI) of this nonlinear system. When input signal is discrete (binary), the optimal SR noise is found to have a finite distribution. In contrast, when input signal is continuous, the optimal SR noise is a constant one. In addition, suboptimal SR noises are explored as well with optimization methods when the types of noise added into the system are predetermined. We find that for small thresholds, suboptimal noises do not exist. Only when thresholds reach some level, do suboptimal noises come into effect. Meanwhile, we have discussed the impact of tails in noise distribution on SR effect. Finally, this paper extends the single-threshold system to an array of multi-threshold devices and presents the corresponding efficacy of information transmission produced by optimal and suboptimal SR noises. These results may be beneficial to quantization and coding.
Suboptimal Utilisation of Resources in Sub-Saharan African Higher ...
African Journals Online (AJOL)
Suboptimal Utilisation of Resources in Sub-Saharan African Higher Education Institutions: the Case of Teaching Space at Makerere University. ... This means that the institutions need to evaluate their utilization of these resources—to pinpoint their need for the resources and potential for quality assurance. This paper reports ...
When animals misbehave: analogs of human biases and suboptimal choice.
Zentall, Thomas R
2015-03-01
Humans tend to value rewards more if they have had to work hard to obtain them (justification of effort). Similarly they tend to persist in a task even when they would be better off beginning a new one (sunk cost). Humans also often give greater value to objects of good quality than the same objects together with objects of lesser quality (the less is more effect). Commercial gambling (lotteries and slot machines) is another example of suboptimal choice by humans because on average the rewards are less than the investment. In another example of a systematic bias, when humans try to estimate the probability of the occurrence of a low probability event, they often give too much weight to the results of a test, in spite of the fact that the known probability of a false alarm reduces the predictive value of the test (base rate neglect). In each of these examples, we have found that pigeons show a similar tendency to choose suboptimally. When one can show comparable findings of suboptimal choice in animals it suggests that whereas culture may reinforce certain suboptimal behavior, the behavior is likely to result from the overgeneralization of basic behavioral processes or predisposed heuristics that may have been appropriate in natural environments. This article is part of a Special Issue entitled: "Tribute to Tom Zentall." Copyright © 2014 Elsevier B.V. All rights reserved.
Prevalence and predictors of sub-optimal medication adherence ...
African Journals Online (AJOL)
In this study, the levels of adherence, prevalence and the predictors of suboptimal adherence were assessed in a sub-Saharan African setting. Methods: Three hundred and seventy (370) respondents with diagnoses of schizophrenia, bipolar disorder or severe depression were randomly enrolled and interviewed at the ...
Fitting diameter distribution models to data from forest inventories with concentric plot design
Energy Technology Data Exchange (ETDEWEB)
Nanos, N.; Sjöstedt de Luna, S.
2017-11-01
Aim: Several national forest inventories use a complex plot design based on multiple concentric subplots where smaller diameter trees are inventoried when lying in the smaller-radius subplots and ignored otherwise. Data from these plots are truncated with threshold (truncation) diameters varying according to the distance from the plot centre. In this paper we designed a maximum likelihood method to fit the Weibull diameter distribution to data from concentric plots. Material and methods: Our method (M1) was based on multiple truncated probability density functions to build the likelihood. In addition, we used an alternative method (M2) presented recently. We used methods M1 and M2 as well as two other reference methods to estimate the Weibull parameters in 40000 simulated plots. The spatial tree pattern of the simulated plots was generated using four models of spatial point patterns. Two error indices were used to assess the relative performance of M1 and M2 in estimating relevant stand-level variables. In addition, we estimated the Quadratic Mean plot Diameter (QMD) using Expansion Factors (EFs). Main results: Methods M1 and M2 produced comparable estimation errors in random and cluster tree spatial patterns. Method M2 produced biased parameter estimates in plots with inhomogeneous Poisson patterns. Estimation of QMD using EFs produced biased results in plots within inhomogeneous intensity Poisson patterns. Research highlights:We designed a new method to fit the Weibull distribution to forest inventory data from concentric plots that achieves high accuracy and precision in parameter estimates regardless of the within-plot spatial tree pattern.
Experimental model for non-Newtonian fluid viscosity estimation: Fit to mathematical expressions
Directory of Open Access Journals (Sweden)
Guillem Masoliver i Marcos
2017-01-01
Full Text Available The construction process of a viscometer, developed in collaboration with a final project student, is here presented. It is intended to be used by first year's students to know the viscosity as a fluid property, for both Newtonian and non-Newtonian flows. Viscosity determination is crucial for the fluids behaviour knowledge related to their reologic and physical properties. These have great implications in engineering aspects such as friction or lubrication. With the present experimental model device three different fluids are analyzed (water, kétchup and a mixture with cornstarch and water. Tangential stress is measured versus velocity in order to characterize all the fluids in different thermal conditions. A mathematical fit process is proposed to be done in order to adjust the results to expected analytical expressions, obtaining good results for these fittings, with R2 greater than 0.88 in any case.
Semenov, Yuri S; Novozhilov, Artem S
2016-05-01
A two-valued fitness landscape is introduced for the classical Eigen's quasispecies model. This fitness landscape can be considered as a direct generalization of the so-called single- or sharply peaked landscape. A general, non-permutation invariant quasispecies model is studied, and therefore the dimension of the problem is [Formula: see text], where N is the sequence length. It is shown that if the fitness function is equal to [Formula: see text] on a G-orbit A and is equal to w elsewhere, then the mean population fitness can be found as the largest root of an algebraic equation of degree at most [Formula: see text]. Here G is an arbitrary isometry group acting on the metric space of sequences of zeroes and ones of the length N with the Hamming distance. An explicit form of this exact algebraic equation is given in terms of the spherical growth function of the G-orbit A. Motivated by the analysis of the two-valued fitness landscapes, an abstract generalization of Eigen's model is introduced such that the sequences are identified with the points of a finite metric space X together with a group of isometries acting transitively on X. In particular, a simplicial analog of the original quasispecies model is discussed, which can be considered as a mathematical model of the switching of the antigenic variants for some bacteria.
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...14 iv LIST OF FIGURES Figure Page 1 Physical fitness
Use of a loudness model for hearing aid fitting: II. Hearing aids with multi-channel compression.
Moore, B C; Alcántara, J I; Stone, M A; Glasberg, B R
1999-06-01
A model for predicting loudness for people with cochlear hearing loss was applied to the problem of the initial fitting of a multi-channel compression hearing aid. The fitting was based on two constraints: (1) The specific loudness pattern evoked by speech of a moderate level (65 dB SPL) should be reasonably flat (equal loudness per critical band), and the overall loudness should be similar to that evoked in a normal listener by 65-dB speech (about 23 sones for binaural listening); (2) Speech with an overall level of 45 dB SPL should just be audible in all frequency bands from 500 Hz up to about 4 kHz, provided that this does not require compression ratios exceeding about 3. These two constraints were used to determine initial values for the gain, compression ratio and compression threshold in each channel of a multi-channel compression system. This initial fitting was based entirely on audiometric thresholds; it does not require suprathreshold loudness measures. The fitting method was evaluated using an experimental fast-acting four-channel compression system. The initial fitting was followed by an adaptive procedure to 'fine tune' the fitting, and the aids were then used in everyday life. Performance was evaluated by use of questionnaires and by measures of speech intelligibility. Although the fine tuning resulted in modest changes in the fitting parameters for some subjects, on average the frequency response shapes and compression ratios were similar before and after the fine tuning. The fittings led to satisfactory loudness impressions in everyday life and to high speech intelligibility over a wide range of levels. It was concluded that the initial fitting method gives reasonable starting values for the fine tuning.
Yu, Chung-Jong; Kim, Euikwoun; Kim, Jae-Yong
2011-05-01
A general-purpose fitting procedure is presented for X-ray reflectivity data. The Parratt formula was used to fit the low-angle region of the reflectivity data and the resulting electron density profile (continuous base EDP or cbEDP) was then divided into a series of electron density slabs of width 1 angstroms (discrete base EDP or dbEDP), which is then easily incorporated into the Distorted Wave Born Approximation (DWBA). An additional series of density slabs of resolution-limited width are overlapped to the dbEDP, and the density value of the each additional slab is allowed to vary to further fit the data model-independently using DWBA. Because this procedure combines the Parratt formula and the model-independent DWBA fitting, each fitting method can always be employed depending on the type of thin film. Moreover, it provides a way to overcome the difficulties when both fitting methods do not work well for certain types of thin films. Simulations show that this procedure is suitable for nanoscale thin film characterization.
Shih, Cheng-Ting; Wu, Jay
2017-02-01
X ray and γ-ray are widely applied in radiology, radiotherapy, and nuclear medicine. Linear attenuation coefficients and linear energy absorption coefficients are essential for dose calculation and image correction. In this study, a method that entails combining the stoichiometric calibration and parametric physical models was developed to convert computed tomography (CT) images into the linear attenuation coefficients and linear energy absorption coefficients. A calibration scan was performed using standard tissue-equivalent materials to obtain the characteristics of the x-ray energy spectrum. Subsequently, relationships between CT numbers and tissue parameters were established using standard soft tissue and bone tissue data adopted from the literature. The linear attenuation coefficient and linear energy absorption coefficient were calculated using the parametric fit model. The results showed a linear relationship between CT numbers and tissue parameters. The tissue-equivalent materials differed from real human tissues, leading to considerable errors in estimation of mass attenuation coefficients when the photon energy was lower than 50 keV. Mass attenuation coefficients and mass energy transfer coefficients of five tissues were calculated and validated using clinical CT images. The error was less than ± 5% and ± 8%, compared with the values of the International Commission on Radiation Units (ICRU) 46 report. The probability of photon interaction with tissues and physical characteristics of tissues can be accurately evaluated by using the proposed method and applied in various clinical applications. © 2016 American Association of Physicists in Medicine.
Fitting Cox Models with Doubly Censored Data Using Spline-Based Sieve Marginal Likelihood.
Li, Zhiguo; Owzar, Kouros
2016-06-01
In some applications, the failure time of interest is the time from an originating event to a failure event, while both event times are interval censored. We propose fitting Cox proportional hazards models to this type of data using a spline-based sieve maximum marginal likelihood, where the time to the originating event is integrated out in the empirical likelihood function of the failure time of interest. This greatly reduces the complexity of the objective function compared with the fully semiparametric likelihood. The dependence of the time of interest on time to the originating event is induced by including the latter as a covariate in the proportional hazards model for the failure time of interest. The use of splines results in a higher rate of convergence of the estimator of the baseline hazard function compared with the usual nonparametric estimator. The computation of the estimator is facilitated by a multiple imputation approach. Asymptotic theory is established and a simulation study is conducted to assess its finite sample performance. It is also applied to analyzing a real data set on AIDS incubation time.
Directory of Open Access Journals (Sweden)
M. Naeem
2014-08-01
Full Text Available Bayesian Belief Network (BBN is an appealing classification model for learning causal and noncausal dependencies among a set of query variables. It is a challenging task to learning BBN structure from observational data because of pool of large number of candidate network structures. In this study, we have addressed the issue of goodness of data fitting versus model complexity. While doing so, we have proposed discriminant function which is non-parametric, free of implicit assumptions but delivering better classification accuracy in structure learning. The contribution in this study is twofold, first contribution (discriminant function is in BBN structure learning and second contribution is for Decision Stump classifier. While designing the novel discriminant function, we analyzed the underlying relationship between the characteristics of data and accuracy of decision stump classifier. We introduced a meta characteristic measure AMfDS (herein known as Affinity Metric for Decision Stump which is quite useful in prediction of classification accuracy of Decision Stump. AMfDS requires a single scan of the dataset.
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.
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
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.
Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting.
Ross, James C; Kindlmann, Gordon L; Okajima, Yuka; Hatabu, Hiroto; Díaz, Alejandro A; Silverman, Edwin K; Washko, George R; Dy, Jennifer; San José Estépar, Raúl
2013-12-01
Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. The proposed algorithm is effective for lung lobe
Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting
Energy Technology Data Exchange (ETDEWEB)
Ross, James C., E-mail: jross@bwh.harvard.edu [Channing Laboratory, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Surgical Planning Lab, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Laboratory of Mathematics in Imaging, Brigham and Women' s Hospital, Boston, Massachusetts 02126 (United States); Kindlmann, Gordon L. [Computer Science Department and Computation Institute, University of Chicago, Chicago, Illinois 60637 (United States); Okajima, Yuka; Hatabu, Hiroto [Department of Radiology, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Díaz, Alejandro A. [Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 and Department of Pulmonary Diseases, Pontificia Universidad Católica de Chile, Santiago (Chile); Silverman, Edwin K. [Channing Laboratory, Brigham and Women' s Hospital, Boston, Massachusetts 02215 and Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 (United States); Washko, George R. [Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 (United States); Dy, Jennifer [ECE Department, Northeastern University, Boston, Massachusetts 02115 (United States); Estépar, Raúl San José [Department of Radiology, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Surgical Planning Lab, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Laboratory of Mathematics in Imaging, Brigham and Women' s Hospital, Boston, Massachusetts 02126 (United States)
2013-12-15
Purpose: Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. Methods: The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. Results: The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. Conclusions: The
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.
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Farhan Akram
Full Text Available This paper presents a region-based active contour method for the segmentation of intensity inhomogeneous images using an energy functional based on local and global fitted images. A square image fitted model is defined by using both local and global fitted differences. Moreover, local and global signed pressure force functions are introduced in the solution of the energy functional to stabilize the gradient descent flow. In the final gradient descent solution, the local fitted term helps extract regions with intensity inhomogeneity, whereas the global fitted term targets homogeneous regions. A Gaussian kernel is applied to regularize the contour at each step, which not only smoothes it but also avoids the computationally expensive re-initialization. Intensity inhomogeneous images contain undesired smooth intensity variations (bias field that alter the results of intensity-based segmentation methods. The bias field is approximated with a Gaussian distribution and the bias of intensity inhomogeneous regions is corrected by dividing the original image by the approximated bias field. In this paper, a two-phase model is first derived and then extended to a four-phase model to segment brain magnetic resonance (MR images into the desired regions of interest. Experimental results with both synthetic and real brain MR images are used for a quantitative and qualitative comparison with state-of-the-art active contour methods to show the advantages of the proposed segmentation technique in practical terms.
Zheng, Wenjun; Tekpinar, Mustafa
2014-01-01
To circumvent the difficulty of directly solving high-resolution biomolecular structures, low-resolution structural data from Cryo-electron microscopy (EM) and small angle solution X-ray scattering (SAXS) are increasingly used to explore multiple conformational states of biomolecular assemblies. One promising venue to obtain high-resolution structural models from low-resolution data is via data-constrained flexible fitting. To this end, we have developed a new method based on a coarse-grained Cα-only protein representation, and a modified form of the elastic network model (ENM) that allows large-scale conformational changes while maintaining the integrity of local structures including pseudo-bonds and secondary structures. Our method minimizes a pseudo-energy which linearly combines various terms of the modified ENM energy with an EM/SAXS-fitting score and a collision energy that penalizes steric collisions. Unlike some previous flexible fitting efforts using the lowest few normal modes, our method effectively utilizes all normal modes so that both global and local structural changes can be fully modeled with accuracy. This method is also highly efficient in computing time. We have demonstrated our method using adenylate kinase as a test case which undergoes a large open-to-close conformational change. The EM-fitting method is available at a web server (http://enm.lobos.nih.gov), and the SAXS-fitting method is available as a pre-compiled executable upon request. © 2014 Elsevier Inc. All rights reserved.
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Célia Touraine
2017-07-01
Full Text Available The irreversible illness-death model describes the pathway from an initial state to an absorbing state either directly or through an intermediate state. This model is frequently used in medical applications where the intermediate state represents illness and the absorbing state represents death. In many studies, disease onset times are not known exactly. This happens for example if the disease status of a patient can only be assessed at follow-up visits. In this situation the disease onset times are interval-censored. This article presents the SmoothHazard package for R. It implements algorithms for simultaneously fitting regression models to the three transition intensities of an illness-death model where the transition times to the intermediate state may be interval-censored and all the event times can be right-censored. The package parses the individual data structure of the subjects in a data set to find the individual contributions to the likelihood. The three baseline transition intensity functions are modelled by Weibull distributions or alternatively by M -splines in a semi-parametric approach. For a given set of covariates, the estimated transition intensities can be combined into predictions of cumulative event probabilities and life expectancies.
Van Wart, Adam T; Durrant, Jacob; Votapka, Lane; Amaro, Rommie E
2014-02-11
Allostery can occur by way of subtle cooperation among protein residues (e.g., amino acids) even in the absence of large conformational shifts. Dynamical network analysis has been used to model this cooperation, helping to computationally explain how binding to an allosteric site can impact the behavior of a primary site many ångstroms away. Traditionally, computational efforts have focused on the most optimal path of correlated motions leading from the allosteric to the primary active site. We present a program called Weighted Implementation of Suboptimal Paths (WISP) capable of rapidly identifying additional suboptimal pathways that may also play important roles in the transmission of allosteric signals. Aside from providing signal redundancy, suboptimal paths traverse residues that, if disrupted through pharmacological or mutational means, could modulate the allosteric regulation of important drug targets. To demonstrate the utility of our program, we present a case study describing the allostery of HisH-HisF, an amidotransferase from T. maritima thermotiga. WISP and its VMD-based graphical user interface (GUI) can be downloaded from http://nbcr.ucsd.edu/wisp.
Moore, B C; Glasberg, B R; Stone, M A
1999-08-01
A model for predicting loudness for people with cochlear hearing loss is applied to the problem of the initial fitting of multi-channel fast-acting compression hearing aids. The fitting is based entirely on the pure tone audiogram, and does not require measures of loudness growth. One constraint is always applied: the specific loudness pattern evoked by speech of a moderate level (65 dB SPL) should be reasonably flat (equal loudness per critical band), and the overall loudness should be similar to that evoked in a normal listener by 65-dB speech. This is achieved using the 'Cambridge' formula. For hearing aids where the compression threshold in each channel can be set to a very low value, an additional constraint is used: speech with an overall level of 45 dB SPL should be audible over its entire dynamic range in all frequency channels from 500 Hz up to about 4 kHz. For hearing aids where the compression thresholds cannot be set to very low values, a different additional constraint is used: the specific loudness pattern evoked by speech of a high level (85 dB SPL, and with the spectral characteristics of shouted speech) should be reasonably flat, and the overall loudness should be similar to that evoked in a normal listener by 85-dB speech. For both cases, compression ratios are limited to values below 3. For each of these two cases, we show how to derive compression ratios and gains, and for the first case, compression thresholds, for each channel. The derivations apply to systems with any number of channels. A computer program implementing the derivations is described. The program also calculates target insertion gains at the centre frequency of each channel for input levels of 50, 65 and 80 dB SPL, and target gains at the eardrum measured relative to the level at the reference microphone of a probe microphone system.
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Terrapon Nicolas
2012-05-01
Full Text Available Abstract Background Hidden Markov Models (HMMs are a powerful tool for protein domain identification. The Pfam database notably provides a large collection of HMMs which are widely used for the annotation of proteins in new sequenced organisms. In Pfam, each domain family is represented by a curated multiple sequence alignment from which a profile HMM is built. In spite of their high specificity, HMMs may lack sensitivity when searching for domains in divergent organisms. This is particularly the case for species with a biased amino-acid composition, such as P. falciparum, the main causal agent of human malaria. In this context, fitting HMMs to the specificities of the target proteome can help identify additional domains. Results Using P. falciparum as an example, we compare approaches that have been proposed for this problem, and present two alternative methods. Because previous attempts strongly rely on known domain occurrences in the target species or its close relatives, they mainly improve the detection of domains which belong to already identified families. Our methods learn global correction rules that adjust amino-acid distributions associated with the match states of HMMs. These rules are applied to all match states of the whole HMM library, thus enabling the detection of domains from previously absent families. Additionally, we propose a procedure to estimate the proportion of false positives among the newly discovered domains. Starting with the Pfam standard library, we build several new libraries with the different HMM-fitting approaches. These libraries are first used to detect new domain occurrences with low E-values. Second, by applying the Co-Occurrence Domain Discovery (CODD procedure we have recently proposed, the libraries are further used to identify likely occurrences among potential domains with higher E-values. Conclusion We show that the new approaches allow identification of several domain families previously absent in
Visually suboptimal bananas: How ripeness affects consumer expectation and perception.
Symmank, Claudia; Zahn, Susann; Rohm, Harald
2017-10-07
One reason for the significant amount of food that is wasted in developed countries is that consumers often expect visually suboptimal food as being less palatable. Using bananas as example, the objective of this study was to determine how appearance affects consumer overall liking, the rating of sensory attributes, purchase intention, and the intended use of bananas. The ripeness degree (RD) of the samples was adjusted to RD 5 (control) and RD 7 (more ripened, visually suboptimal). After preliminary experiments, a total of 233 participants were asked to judge their satisfaction with the intensity of sensory attributes that referred to flavor, taste, and texture using just-about-right scales. Subjects who received peeled samples were asked after tasting, whereas subjects who received unpeeled bananas judged expectation and, after peeling and tasting, perception. Expected overall liking and purchase intention were significantly lower for RD 7 bananas. Purchase intention was still significantly different between RD 5 and RD 7 after tasting, whereas no difference in overall liking was observed. Significant differences between RD 5 and RD 7 were observed when asking participants for their intended use of the bananas. Concerning the sensory attributes, penalty analysis revealed that only the firmness of the RD 7 bananas was still not just-about-right after tasting. The importance that consumers attribute to the shelf-life of food had a pronounced impact on purchase intention of bananas with different ripeness degree. In the case of suboptimal bananas, the results demonstrate a positive relationship between the sensory perception and overall liking and purchase intention. Convincing consumers that visually suboptimal food is still tasty is of high relevance for recommending different ways of communication. Copyright © 2017 Elsevier Ltd. All rights reserved.
A system analysis of a suboptimal surgical experience
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Richards Michael
2009-01-01
Full Text Available Abstract Background System analyses of incidents that occur in the process of health care delivery are rare. A case study of a series of incidents that one of the authors experienced after routine urologic surgery is presented. We interpret the sequence of events as a case of cascading incidents that resulted in outcomes that were suboptimal, although fortunately not fatal. Methods A system dynamics approach was employed to develop illustrative models (flow diagrams of the dynamics of the patient's interaction with surgery and emergency departments. The flow diagrams were constructed based upon the experience of the patient, chart review, discussion with the involved physicians as well as several physician colleagues, comparison of our diagrams with those developed by the hospital of interest for internal planning purposes, and an iterative process with one of the co-authors who is a system dynamics expert. A dynamic hypothesis was developed using insights gained by building the flow diagrams. Results The incidents originated in design flaws and many small innocuous system changes that have occurred incrementally over time, which by themselves may have no consequence but in conjunction with some system randomness can have serious consequences. In the patient's case, the incidents that occurred in preoperative assessment and surgery originated in communication and procedural failures. System delays, communication failures, and capacity issues contributed largely to the subsequent incidents. Some of these issues were controllable by the physicians and staff of the institution, whereas others were less controllable. To the system's credit, some of the more controllable issues were addressed, but systemic problems like overcrowding are unlikely to be addressed in the near future. Conclusion This is first instance that we are aware of in the literature where a system dynamics approach has been used to analyze a patient safety experience. The
A system analysis of a suboptimal surgical experience.
Lee, Robert C; Cooke, David L; Richards, Michael
2009-01-06
System analyses of incidents that occur in the process of health care delivery are rare. A case study of a series of incidents that one of the authors experienced after routine urologic surgery is presented. We interpret the sequence of events as a case of cascading incidents that resulted in outcomes that were suboptimal, although fortunately not fatal. A system dynamics approach was employed to develop illustrative models (flow diagrams) of the dynamics of the patient's interaction with surgery and emergency departments. The flow diagrams were constructed based upon the experience of the patient, chart review, discussion with the involved physicians as well as several physician colleagues, comparison of our diagrams with those developed by the hospital of interest for internal planning purposes, and an iterative process with one of the co-authors who is a system dynamics expert. A dynamic hypothesis was developed using insights gained by building the flow diagrams. The incidents originated in design flaws and many small innocuous system changes that have occurred incrementally over time, which by themselves may have no consequence but in conjunction with some system randomness can have serious consequences. In the patient's case, the incidents that occurred in preoperative assessment and surgery originated in communication and procedural failures. System delays, communication failures, and capacity issues contributed largely to the subsequent incidents. Some of these issues were controllable by the physicians and staff of the institution, whereas others were less controllable. To the system's credit, some of the more controllable issues were addressed, but systemic problems like overcrowding are unlikely to be addressed in the near future. This is first instance that we are aware of in the literature where a system dynamics approach has been used to analyze a patient safety experience. The qualitative system dynamics analysis was useful in understanding the
Nättilä, J.; Miller, M. C.; Steiner, A. W.; Kajava, J. J. E.; Suleimanov, V. F.; Poutanen, J.
2017-12-01
Observations of thermonuclear X-ray bursts from accreting neutron stars (NSs) in low-mass X-ray binary systems can be used to constrain NS masses and radii. Most previous work of this type has set these constraints using Planck function fits as a proxy: the models and the data are both fit with diluted blackbody functions to yield normalizations and temperatures that are then compared with each other. For the first time, we here fit atmosphere models of X-ray bursting NSs directly to the observed spectra. We present a hierarchical Bayesian fitting framework that uses current X-ray bursting NS atmosphere models with realistic opacities and relativistic exact Compton scattering kernels as a model for the surface emission. We test our approach against synthetic data and find that for data that are well described by our model, we can obtain robust radius, mass, distance, and composition measurements. We then apply our technique to Rossi X-ray Timing Explorer observations of five hard-state X-ray bursts from 4U 1702-429. Our joint fit to all five bursts shows that the theoretical atmosphere models describe the data well, but there are still some unmodeled features in the spectrum corresponding to a relative error of 1-5% of the energy flux. After marginalizing over this intrinsic scatter, we find that at 68% credibility, the circumferential radius of the NS in 4U 1702-429 is R = 12.4±0.4 km, the gravitational mass is M = 1.9±0.3 M⊙, the distance is 5.1 < D/ kpc < 6.2, and the hydrogen mass fraction is X < 0.09.
Hansen, Mark; Cai, Li; Monroe, Scott; Li, Zhen
2014-01-01
It is a well-known problem in testing the fit of models to multinomial data that the full underlying contingency table will inevitably be sparse for tests of reasonable length and for realistic sample sizes. Under such conditions, full-information test statistics such as Pearson's X[superscript 2]?? and the likelihood ratio statistic…
Score, pseudo-score and residual diagnostics for goodness-of-fit of spatial point process models
DEFF Research Database (Denmark)
Baddeley, Adrian; Rubak, Ege H.; Møller, Jesper
theoretical support to the established practice of using functional summary statistics such as Ripley’s K-function, when testing for complete spatial randomness; and they provide new tools such as the compensator of the K-function for testing other fitted models. The results also support localisation methods...
A Person-Centered Approach to P-E Fit Questions Using a Multiple-Trait Model.
De Fruyt, Filip
2002-01-01
Employed college students (n=401) completed the Self-Directed Search and NEO Personality Inventory-Revised. Person-environment fit across Holland's six personality types predicted job satisfaction and skill development. Five-Factor Model traits significantly predicted intrinsic career outcomes. Use of the five-factor, person-centered approach to…
Guiffrida, Douglas A.
2005-01-01
The author presents a critical review of counselor education literature that has focused on student acquisition of theoretical orientations in order to identify the potential of these practices to facilitate critical self-reflection and theoretical fit among students. Two reflective, awareness-based pedagogical models--radical constructivism (E.…
Worthington, Thomas A.; Zhang, T.; Logue, Daniel R.; Mittelstet, Aaron R.; Brewer, Shannon K.
2016-01-01
Truncated distributions of pelagophilic fishes have been observed across the Great Plains of North America, with water use and landscape fragmentation implicated as contributing factors. Developing conservation strategies for these species is hindered by the existence of multiple competing flow regime hypotheses related to species persistence. Our primary study objective was to compare the predicted distributions of one pelagophil, the Arkansas River Shiner Notropis girardi, constructed using different flow regime metrics. Further, we investigated different approaches for improving temporal transferability of the species distribution model (SDM). We compared four hypotheses: mean annual flow (a baseline), the 75th percentile of daily flow, the number of zero-flow days, and the number of days above 55th percentile flows, to examine the relative importance of flows during the spawning period. Building on an earlier SDM, we added covariates that quantified wells in each catchment, point source discharges, and non-native species presence to a structured variable framework. We assessed the effects on model transferability and fit by reducing multicollinearity using Spearman’s rank correlations, variance inflation factors, and principal component analysis, as well as altering the regularization coefficient (β) within MaxEnt. The 75th percentile of daily flow was the most important flow metric related to structuring the species distribution. The number of wells and point source discharges were also highly ranked. At the default level of β, model transferability was improved using all methods to reduce collinearity; however, at higher levels of β, the correlation method performed best. Using β = 5 provided the best model transferability, while retaining the majority of variables that contributed 95% to the model. This study provides a workflow for improving model transferability and also presents water-management options that may be considered to improve the
Madsen, Jonas S; Lin, Yu-Cheng; Squyres, Georgia R; Price-Whelan, Alexa; de Santiago Torio, Ana; Song, Angela; Cornell, William C; Sørensen, Søren J; Xavier, Joao B; Dietrich, Lars E P
2015-12-01
As biofilms grow, resident cells inevitably face the challenge of resource limitation. In the opportunistic pathogen Pseudomonas aeruginosa PA14, electron acceptor availability affects matrix production and, as a result, biofilm morphogenesis. The secreted matrix polysaccharide Pel is required for pellicle formation and for colony wrinkling, two activities that promote access to O2. We examined the exploitability and evolvability of Pel production at the air-liquid interface (during pellicle formation) and on solid surfaces (during colony formation). Although Pel contributes to the developmental response to electron acceptor limitation in both biofilm formation regimes, we found variation in the exploitability of its production and necessity for competitive fitness between the two systems. The wild type showed a competitive advantage against a non-Pel-producing mutant in pellicles but no advantage in colonies. Adaptation to the pellicle environment selected for mutants with a competitive advantage against the wild type in pellicles but also caused a severe disadvantage in colonies, even in wrinkled colony centers. Evolution in the colony center produced divergent phenotypes, while adaptation to the colony edge produced mutants with clear competitive advantages against the wild type in this O2-replete niche. In general, the structurally heterogeneous colony environment promoted more diversification than the more homogeneous pellicle. These results suggest that the role of Pel in community structure formation in response to electron acceptor limitation is unique to specific biofilm models and that the facultative control of Pel production is required for PA14 to maintain optimum benefit in different types of communities. Copyright © 2015, American Society for Microbiology. All Rights Reserved.
DEFF Research Database (Denmark)
de Vries, Stefan P. W.; Gupta, Srishti; Baig, Abiyad
2017-01-01
and the environment. Here, we report a detailed analysis of C. jejuni fitness across models reflecting stages in its life cycle. Transposon (Tn) gene-inactivation libraries were generated in three C. jejuni strains and the impact on fitness during chicken colonisation, survival in houseflies and under nutrient...... to growth. We report novel C. jejuni factors essential throughout its life cycle. Importantly, we identified genes that fulfil important roles across multiple conditions. Our comprehensive screens showed which flagella elements are essential for growth and which are vital to the interaction with host......-rich and -poor conditions at 4 degrees C and infection of human gut epithelial cells was assessed by Tn-insertion site sequencing (Tn-seq). A total of 331 homologous gene clusters were essential for fitness during in vitro growth in three C. jejuni strains, revealing that a large part of its genome is dedicated...
Minor fitness costs in an experimental model of horizontal gene transfer in bacteria.
Knöppel, Anna; Lind, Peter A; Lustig, Ulrika; Näsvall, Joakim; Andersson, Dan I
2014-05-01
Genes introduced by horizontal gene transfer (HGT) from other species constitute a significant portion of many bacterial genomes, and the evolutionary dynamics of HGTs are important for understanding the spread of antibiotic resistance and the emergence of new pathogenic strains of bacteria. The fitness effects of the transferred genes largely determine the fixation rates and the amount of neutral diversity of newly acquired genes in bacterial populations. Comparative analysis of bacterial genomes provides insight into what genes are commonly transferred, but direct experimental tests of the fitness constraints on HGT are scarce. Here, we address this paucity of experimental studies by introducing 98 random DNA fragments varying in size from 0.45 to 5 kb from Bacteroides, Proteus, and human intestinal phage into a defined position in the Salmonella chromosome and measuring the effects on fitness. Using highly sensitive competition assays, we found that eight inserts were deleterious with selection coefficients (s) ranging from ≈ -0.007 to -0.02 and 90 did not have significant fitness effects. When inducing transcription from a PBAD promoter located at one end of the insert, 16 transfers were deleterious and 82 were not significantly different from the control. In conclusion, a major fraction of the inserts had minor effects on fitness implying that extra DNA transferred by HGT, even though it does not confer an immediate selective advantage, could be maintained at selection-transfer balance and serve as raw material for the evolution of novel beneficial functions.
Recruit Fitness as a Predictor of Police Academy Graduation.
Shusko, M; Benedetti, L; Korre, M; Eshleman, E J; Farioli, A; Christophi, C A; Kales, S N
2017-10-01
Suboptimal recruit fitness may be a risk factor for poor performance, injury, illness, and lost time during police academy training. To assess the probability of successful completion and graduation from a police academy as a function of recruits' baseline fitness levels at the time of academy entry. Retrospective study where all available records from recruit training courses held (2006-2012) at all Massachusetts municipal police academies were reviewed and analysed. Entry fitness levels were quantified from the following measures, as recorded at the start of each training class: body composition, push-ups, sit-ups, sit-and-reach, and 1.5-mile run-time. The primary outcome of interest was the odds of not successfully graduating from an academy. We used generalized linear mixed models in order to fit logistic regression models with random intercepts for assessing the probability of not graduating, based on entry-level fitness. The primary analyses were restricted to recruits with complete entry-level fitness data. The fitness measures most strongly associated with academy failure were lesser number of push-ups completed (odds ratio [OR] = 5.2, 95% confidence interval [CI] 2.3-11.7, for 20 versus 41-60 push-ups) and slower run times (OR = 3.8, 95% CI 1.8-7.8, [1.5 mile run time of ≥15'20″] versus [12'33″ to 10'37″]). Baseline pushups and 1.5-mile run-time showed the best ability to predict successful academy graduation, especially when considered together. Future research should include prospective validation of entry-level fitness as a predictor of subsequent police academy success.
Jbabdi, Saad; Sotiropoulos, Stamatios N; Savio, Alexander M; Graña, Manuel; Behrens, Timothy EJ
2012-01-01
In this article, we highlight an issue that arises when using multiple b-values in a model-based analysis of diffusion MR data for tractography. The non-mono-exponential decay, commonly observed in experimental data, is shown to induce over-fitting in the distribution of fibre orientations when not considered in the model. Extra fibre orientations perpendicular to the main orientation arise to compensate for the slower apparent signal decay at higher b-values. We propose a simple extension to the ball and stick model based on a continuous Gamma distribution of diffusivities, which significantly improves the fitting and reduces the over-fitting. Using in-vivo experimental data, we show that this model outperforms a simpler, noise floor model, especially at the interfaces between brain tissues, suggesting that partial volume effects are a major cause of the observed non-mono-exponential decay. This model may be helpful for future data acquisition strategies that may attempt to combine multiple shells to improve estimates of fibre orientations in white matter and near the cortex. PMID:22334356
van Hout, MSE; Schmand, B; Wekking, EM; Hageman, G; Deelman, BG
Suboptimal performance during neuropsychological testing can seriously complicate assessment in behavioral neurotoxicology. We present data on the prevalence of suboptimal performance in a group of Dutch patients with suspected chronic toxic encephalopathy (CTE) after long-term occupational exposure
van Hout, Moniek S. E.; Schmand, Ben; Wekking, Ellie M.; Hageman, Gerard; Deelman, Betto G.
2003-01-01
Suboptimal performance during neuropsychological testing can seriously complicate assessment in behavioral neurotoxicology. We present data on the prevalence of suboptimal performance in a group of Dutch patients with suspected chronic toxic encephalopathy (CTE) after long-term occupational exposure
Linking the Fits, Fitting the Links: Connecting Different Types of PO Fit to Attitudinal Outcomes
Leung, Aegean; Chaturvedi, Sankalp
2011-01-01
In this paper we explore the linkages among various types of person-organization (PO) fit and their effects on employee attitudinal outcomes. We propose and test a conceptual model which links various types of fits--objective fit, perceived fit and subjective fit--in a hierarchical order of cognitive information processing and relate them to…
Joseph, Agnel P; Swapna, Lakshmipuram S; Rakesh, Ramachandran; Srinivasan, Narayanaswamy
2016-09-01
Protein-protein interface residues, especially those at the core of the interface, exhibit higher conservation than residues in solvent exposed regions. Here, we explore the ability of this differential conservation to evaluate fittings of atomic models in low-resolution cryo-EM maps and select models from the ensemble of solutions that are often proposed by different model fitting techniques. As a prelude, using a non-redundant and high-resolution structural dataset involving 125 permanent and 95 transient complexes, we confirm that core interface residues are conserved significantly better than nearby non-interface residues and this result is used in the cryo-EM map analysis. From the analysis of inter-component interfaces in a set of fitted models associated with low-resolution cryo-EM maps of ribosomes, chaperones and proteasomes we note that a few poorly conserved residues occur at interfaces. Interestingly a few conserved residues are not in the interface, though they are close to the interface. These observations raise the potential requirement of refitting the models in the cryo-EM maps. We show that sampling an ensemble of models and selection of models with high residue conservation at the interface and in good agreement with the density helps in improving the accuracy of the fit. This study indicates that evolutionary information can serve as an additional input to improve and validate fitting of atomic models in cryo-EM density maps. Copyright © 2016 Elsevier Inc. All rights reserved.
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.
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.
Debnath, Dipak; Sarathi Pal, Partha; Chakrabarti, Sandip Kumar; Mondal, Santanu; Jana, Arghajit; Chatterjee, Debjit; Molla, Aslam Ali
2016-07-01
There are many theoretical and phenomenological models in the literature which explain physics of accretion around black holes (BHs). Some of these models assume ad hoc components to explain different timing and spectral aspects of black hole candidates (BHCs) which no necessarily follow from physical equations. Chakrabarti and his collaborators, on the other hand claim in the last two decades that the spectral and timing properties of BHCs must not be treated separately since variation of these properties happens due to variation of two component (Keplerian and sub-Keplerian) accretion flow rates, and the Compton cloud parameters only. Recently after the inclusion of Two-component advective flow (TCAF) model in to HEASARC's spectral analysis software package XSPEC as an additive local model, we found that TCAF is quite capable to describe the underlying accretion flow dynamics around BHs with spectral fitted physical parameters. Properties of different spectral states and their transitions during an outburst of a transient BHC are more clear. A strong correlation between spectral and timing properties could also be seen in Accretion Rate Ratio Intensity Diagram (ARRID), where transitions between different spectral states are prominent. One can also predict frequency of the dominating quasi-periodic oscillation (QPO) from TCAF model fitted shock parameters and even predict the most probable mass range of an unknown BHC from TCAF fits. This gives us a confidence that the description of accretion process is more clear than ever before.
Salvo, Deborah; Reis, Rodrigo S; Hino, Adriano A F; Hallal, Pedro C; Pratt, Michael
2015-03-01
There is little understanding about which sets of environmental features could simultaneously predict intensity-specific leisure-time physical activity (LTPA) among Brazilians. The objectives were to identify the environmental correlates for intensity-specific LTPA, and to build the best-fit linear models to predict intensity-specific LTPA among adults of Curitiba, Brazil. Cross sectional study in Curitiba, Brazil (2009, n = 1461). The International Physical Activity Questionnaire and Abbreviated Neighborhood Environment Assessment Scale were used. Ninety-two perceived environment variables were categorized in 10 domains. LTPA was classified as walking for leisure (LWLK), moderate-intensity leisure-time PA (MLPA), vigorous-intensity leisure-time PA (VLPA), and moderate-to-vigorous intensity leisure-time PA (MVLPA). Best fitting linear predictive models were built. Forty environmental variables were correlated to at least 1 LTPA outcome. The variability explained by the 4 best-fit models ranged from 17% (MLPA) to 46% (MVLPA). All models contained recreation areas and aesthetics variables; none included residential density predictors. At least 1 neighborhood satisfaction variable was present in each of the intensity-specific models, but not for overall MVLPA. This study demonstrates the simultaneous effect of sets of perceived environmental features on intensity-specific LTPA among Brazilian adults. The differences found compared with high-income countries suggest caution in generalizing results across settings.
Directory of Open Access Journals (Sweden)
Abílio G.T. Ferreira
2015-03-01
Full Text Available The objective of this study was to evaluate four mathematical models with regards to their fit to lactation curves of Holstein cows from herds raised in the southwestern region of the state of Parana, Brazil. Initially, 42,281 milk production records from 2005 to 2011 were obtained from "Associação Paranaense de Criadores de Bovinos da Raça Holandesa (APCBRH". Data lacking dates of drying and total milk production at 305 days of lactation were excluded, resulting in a remaining 15,142 records corresponding to 2,441 Holstein cows. Data were sorted according to the parity order (ranging from one to six, and within each parity order the animals were divided into quartiles (Q25%, Q50%, Q75% and Q100% corresponding to 305-day lactation yield. Within each parity order, for each quartile, four mathematical models were adjusted, two of which were predominantly empirical (Brody and Wood whereas the other two presented more mechanistic characteristics (models Dijkstra and Pollott. The quality of fit was evaluated by the corrected Akaike information criterion. The Wood model showed the best fit in almost all evaluated situations and, therefore, may be considered as the most suitable model to describe, at least empirically, the lactation curves of Holstein cows raised in Southwestern Parana.
Gray Matter Correlates of Fluid, Crystallized, and Spatial Intelligence: Testing the P-FIT Model
Colom, Roberto; Haier, Richard J.; Head, Kevin; Alvarez-Linera, Juan; Quiroga, Maria Angeles; Shih, Pei Chun; Jung, Rex E.
2009-01-01
The parieto-frontal integration theory (P-FIT) nominates several areas distributed throughout the brain as relevant for intelligence. This theory was derived from previously published studies using a variety of both imaging methods and tests of cognitive ability. Here we test this theory in a new sample of young healthy adults (N = 100) using a…
van der Niet, Anneke G.; Hartman, Esther; Smith, Joanne; Visscher, Chris
Objectives: The relationship between physical fitness and academic achievement in children has received much attention, however, whether executive functioning plays a mediating role in this relationship is unclear. The aim of this study therefore was to investigate the relationships between physical
Rybizki, Jan; Just, Andreas; Rix, Hans-Walter
2017-09-01
Elemental abundances of stars are the result of the complex enrichment history of their galaxy. Interpretation of observed abundances requires flexible modeling tools to explore and quantify the information about Galactic chemical evolution (GCE) stored in such data. Here we present Chempy, a newly developed code for GCE modeling, representing a parametrized open one-zone model within a Bayesian framework. A Chempy model is specified by a set of five to ten parameters that describe the effective galaxy evolution along with the stellar and star-formation physics: for example, the star-formation history (SFH), the feedback efficiency, the stellar initial mass function (IMF), and the incidence of supernova of type Ia (SN Ia). Unlike established approaches, Chempy can sample the posterior probability distribution in the full model parameter space and test data-model matches for different nucleosynthetic yield sets. It is essentially a chemical evolution fitting tool. We straightforwardly extend Chempy to a multi-zone scheme. As an illustrative application, we show that interesting parameter constraints result from only the ages and elemental abundances of the Sun, Arcturus, and the present-day interstellar medium (ISM). For the first time, we use such information to infer the IMF parameter via GCE modeling, where we properly marginalize over nuisance parameters and account for different yield sets. We find that 11.6+ 2.1-1.6% of the IMF explodes as core-collapse supernova (CC-SN), compatible with Salpeter (1955, ApJ, 121, 161). We also constrain the incidence of SN Ia per 103M⊙ to 0.5-1.4. At the same time, this Chempy application shows persistent discrepancies between predicted and observed abundances for some elements, irrespective of the chosen yield set. These cannot be remedied by any variations of Chempy's parameters and could be an indication of missing nucleosynthetic channels. Chempy could be a powerful tool to confront predictions from stellar
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
Yu, Jonas C. P.; Wee, H. M.; Yang, P. C.; Wu, Simon
2016-06-01
One of the supply chain risks for hi-tech products is the result of rapid technological innovation; it results in a significant decline in the selling price and demand after the initial launch period. Hi-tech products include computers and communication consumer's products. From a practical standpoint, a more realistic replenishment policy is needed to consider the impact of risks; especially when some portions of shortages are lost. In this paper, suboptimal and optimal order policies with partial backordering are developed for a buyer when the component cost, the selling price, and the demand rate decline at a continuous rate. Two mathematical models are derived and discussed: one model has the suboptimal solution with the fixed replenishment interval and a simpler computational process; the other one has the optimal solution with the varying replenishment interval and a more complicated computational process. The second model results in more profit. Numerical examples are provided to illustrate the two replenishment models. Sensitivity analysis is carried out to investigate the relationship between the parameters and the net profit.
Wen, Mingjian; Brommer, Peter; Elliott, Ryan S; Sethna, James P; Tadmor, Ellad B
2016-01-01
Fitted interatomic potentials are widely used in atomistic simulations thanks to their ability to compute the energy and forces on atoms quickly. However, the simulation results crucially depend on the quality of the potential being used. Force matching is a method aimed at constructing reliable and transferable interatomic potentials by matching the forces computed by the potential as closely as possible, with those obtained from first principles calculations. The potfit program is an implementation of the force-matching method that optimizes the potential parameters using a global minimization algorithm followed by a local minimization polish. We extended potfit in two ways. First, we adapted the code to be compliant with the KIM Application Programming Interface (API) standard (part of the Knowledgebase of Interatomic Models Project). This makes it possible to use potfit to fit many KIM potential models, not just those prebuilt into the potfit code. Second, we incorporated the geodesic Levenberg--Marquardt...
Johnson, T. J.; Harding, A. K.; Venter, C.
2012-01-01
Pulsed gamma rays have been detected with the Fermi Large Area Telescope (LAT) from more than 20 millisecond pulsars (MSPs), some of which were discovered in radio observations of bright, unassociated LAT sources. We have fit the radio and gamma-ray light curves of 19 LAT-detected MSPs in the context of geometric, outermagnetospheric emission models assuming the retarded vacuum dipole magnetic field using a Markov chain Monte Carlo maximum likelihood technique. We find that, in many cases, the models are able to reproduce the observed light curves well and provide constraints on the viewing geometries that are in agreement with those from radio polarization measurements. Additionally, for some MSPs we constrain the altitudes of both the gamma-ray and radio emission regions. The best-fit magnetic inclination angles are found to cover a broader range than those of non-recycled gamma-ray pulsars.
White, J Wilson; Nickols, Kerry J; Malone, Daniel; Carr, Mark H; Starr, Richard M; Cordoleani, Flora; Baskett, Marissa L; Hastings, Alan; Botsford, Louis W
2016-12-01
Integral projection models (IPMs) have a number of advantages over matrix-model approaches for analyzing size-structured population dynamics, because the latter require parameter estimates for each age or stage transition. However, IPMs still require appropriate data. Typically they are parameterized using individual-scale relationships between body size and demographic rates, but these are not always available. We present an alternative approach for estimating demographic parameters from time series of size-structured survey data using a Bayesian state-space IPM (SSIPM). By fitting an IPM in a state-space framework, we estimate unknown parameters and explicitly account for process and measurement error in a dataset to estimate the underlying process model dynamics. We tested our method by fitting SSIPMs to simulated data; the model fit the simulated size distributions well and estimated unknown demographic parameters accurately. We then illustrated our method using nine years of annual surveys of the density and size distribution of two fish species (blue rockfish, Sebastes mystinus, and gopher rockfish, S. carnatus) at seven kelp forest sites in California. The SSIPM produced reasonable fits to the data, and estimated fishing rates for both species that were higher than our Bayesian prior estimates based on coast-wide stock assessment estimates of harvest. That improvement reinforces the value of being able to estimate demographic parameters from local-scale monitoring data. We highlight a number of key decision points in SSIPM development (e.g., open vs. closed demography, number of particles in the state-space filter) so that users can apply the method to their own datasets. © 2016 by the Ecological Society of America.
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.
National Research Council Canada - National Science Library
Pan, Xinyi; Li, Cheng; Li, Kuncheng; Ying, Kui; Weng, Dehe; Qin, Wen
2010-01-01
.... The noniterative extended Prony algorithm is used for the signal fitting and frequency estimate. Monte Carlo simulations demonstrate the advantages of the method for optimal water-fat separation and temperature estimation accuracy...
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
Maydeu-Olivares, Alberto; Montano, Rosa
2013-01-01
We investigate the performance of three statistics, R [subscript 1], R [subscript 2] (Glas in "Psychometrika" 53:525-546, 1988), and M [subscript 2] (Maydeu-Olivares & Joe in "J. Am. Stat. Assoc." 100:1009-1020, 2005, "Psychometrika" 71:713-732, 2006) to assess the overall fit of a one-parameter logistic model…
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
China suboptimal health cohort study: rationale, design and baseline characteristics.
Wang, Youxin; Ge, Siqi; Yan, Yuxiang; Wang, Anxin; Zhao, Zhongyao; Yu, Xinwei; Qiu, Jing; Alzain, Mohamed Ali; Wang, Hao; Fang, Honghong; Gao, Qing; Song, Manshu; Zhang, Jie; Zhou, Yong; Wang, Wei
2016-10-13
Suboptimal health status (SHS) is a physical state between health and disease, characterized by the perception of health complaints, general weakness, chronic fatigue and low energy levels. SHS is proposed by the ancient concept of traditional Chinese medicine (TCM) from the perspective of preservative, predictive and personalized (precision) medicine. We previously created the suboptimal health status questionnaire 25 (SHSQ-25), a novel instrument to measure SHS, validated in various populations. SHSQ-25 thus affords a window of opportunity for early detection and intervention, contributing to the reduction of chronic disease burdens. To investigate the causative effect of SHS in non-communicable chronic diseases (NCD), we initiated the China suboptimal health cohort study (COACS), a longitudinal study starting from 2013. Phase I of the study involved a cross-sectional survey aimed at identifying the risk/protective factors associated with SHS; and Phase II: a longitudinal yearly follow-up study investigating how SHS contributes to the incidence and pattern of NCD. (1) Cross-sectional survey: in total, 4313 participants (53.8 % women) aged from 18 to 65 years were included in the cohort. The prevalence of SHS was 9.0 % using SHS score of 35 as threshold. Women showed a significantly higher prevalence of SHS (10.6 % in the female vs. 7.2 % in the male, P differed significantly between subjects of SHS (SHS score ≥35) and those of ideal health (SHS score difference in prevalence of SHS might partly explain the gender difference of incidence of certain chronic diseases. The COACS will enable a thorough characterization of SHS and establish a cohort that will be used for longitudinal analyses of the interaction between the genetic, lifestyle and environmental factors that contribute to the onset and etiology of targeted chronic diseases. The study together with the designed prospective cohort provides a chance to characterize and evaluate the effect of SHS
Falahati Marvast, Fatemeh; Arabalibeik, Hossein; Alipour, Fatemeh; Sheikhtaheri, Abbas; Nouri, Leila; Soozande, Mehdi; Yarmahmoodi, Masood
2016-01-01
Keratoconus is a progressive non-inflammatory disease of the cornea. Rigid gas permeable contact lenses (RGPs) are prescribed when the disease progresses. Contact lens fitting and assessment is very difficult in these patients and is a concern of ophthalmologists and optometrists. In this study, a hierarchical fuzzy system is used to capture the expertise of experienced ophthalmologists during the lens evaluation phase of prescription. The system is fine-tuned using genetic algorithms. Sensitivity, specificity and accuracy of the final system are 88.9%, 94.4% and 92.6% respectively.
Fusco, Roberta; Sansone, Mario; Petrillo, Antonella
2017-04-01
The objective of this study is to propose a modified VARiable PROjection (VARPRO) algorithm specifically tailored for fitting the intravoxel incoherent motion (IVIM) model to diffusion-weighted magnetic resonance imaging (DW-MRI) data from locally advanced rectal cancer (LARC). The proposed algorithm is compared with classical non-linear least squares (NLLS) analysis using the Levenberg-Marquardt (LM) algorithm and with two recently proposed algorithms for 'segmented' analysis. These latter two comprise two consecutive steps: first, a subset of parameters is estimated using a portion of data; second, the remaining parameters are estimated using the whole data and the previous estimates. The comparison between the algorithms was based on the [Formula: see text] goodness-of-fit measure: performance analysis was carried out on real data obtained by DW-MRI on 40 LARC patients. The performance of the proposed algorithm was higher than that of LM in 64 % of cases; 'segmented' methods were poorer than our algorithm in 100 % of cases. The proposed modified VARPRO algorithm can lead to better fit of the IVIM model to LARC DW-MRI data compared to other techniques.
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].
Feature-preserving surface mesh smoothing via suboptimal Delaunay triangulation.
Gao, Zhanheng; Yu, Zeyun; Holst, Michael
2013-01-01
A method of triangular surface mesh smoothing is presented to improve angle quality by extending the original optimal Delaunay triangulation (ODT) to surface meshes. The mesh quality is improved by solving a quadratic optimization problem that minimizes the approximated interpolation error between a parabolic function and its piecewise linear interpolation defined on the mesh. A suboptimal problem is derived to guarantee a unique, analytic solution that is significantly faster with little loss in accuracy as compared to the optimal one. In addition to the quality-improving capability, the proposed method has been adapted to remove noise while faithfully preserving sharp features such as edges and corners of a mesh. Numerous experiments are included to demonstrate the performance of the method.
Brodie, E.; King, E.; Molins, S.; Karaoz, U.; Steefel, C. I.; Banfield, J. F.; Beller, H. R.; Anantharaman, K.; Ligocki, T. J.; Trebotich, D.
2015-12-01
Pore-scale processes mediated by microorganisms underlie a range of critical ecosystem services, regulating carbon stability, nutrient flux, and the purification of water. Advances in cultivation-independent approaches now provide us with the ability to reconstruct thousands of genomes from microbial populations from which functional roles may be assigned. With this capability to reveal microbial metabolic potential, the next step is to put these microbes back where they belong to interact with their natural environment, i.e. the pore scale. At this scale, microorganisms communicate, cooperate and compete across their fitness landscapes with communities emerging that feedback on the physical and chemical properties of their environment, ultimately altering the fitness landscape and selecting for new microbial communities with new properties and so on. We have developed a trait-based model of microbial activity that simulates coupled functional guilds that are parameterized with unique combinations of traits that govern fitness under dynamic conditions. Using a reactive transport framework, we simulate the thermodynamics of coupled electron donor-acceptor reactions to predict energy available for cellular maintenance, respiration, biomass development, and enzyme production. From metagenomics, we directly estimate some trait values related to growth and identify the linkage of key traits associated with respiration and fermentation, macromolecule depolymerizing enzymes, and other key functions such as nitrogen fixation. Our simulations were carried out to explore abiotic controls on community emergence such as seasonally fluctuating water table regimes across floodplain organic matter hotspots. Simulations and metagenomic/metatranscriptomic observations highlighted the many dependencies connecting the relative fitness of functional guilds and the importance of chemolithoautotrophic lifestyles. Using an X-Ray microCT-derived soil microaggregate physical model combined
Risk of Suboptimal Iodine Intake in Pregnant Norwegian Women
Directory of Open Access Journals (Sweden)
Helle Margrete Meltzer
2013-02-01
Full Text Available Pregnant women and infants are exceptionally vulnerable to iodine deficiency. The aims of the present study were to estimate iodine intake, to investigate sources of iodine, to identify predictors of low or suboptimal iodine intake (defined as intakes below 100 μg/day and 150 μg/day in a large population of pregnant Norwegian women and to evaluate iodine status in a sub-population. Iodine intake was calculated based on a validated Food Frequency Questionnaire in the Norwegian Mother and Child Cohort. The median iodine intake was 141 μg/day from food and 166 μg/day from food and supplements. Use of iodine-containing supplements was reported by 31.6%. The main source of iodine from food was dairy products, contributing 67% and 43% in non-supplement and iodine-supplement users, respectively. Of 61,904 women, 16.1% had iodine intake below 100 μg/day, 42.0% had iodine intake below 150 μg/day and only 21.7% reached the WHO/UNICEF/ICCIDD recommendation of 250 μg/day. Dietary behaviors associated with increased risk of low and suboptimal iodine intake were: no use of iodine-containing supplements and low intake of milk/yogurt, seafood and eggs. The median urinary iodine concentration measured in 119 participants (69 μg/L confirmed insufficient iodine intake. Public health strategies are needed to improve and secure the iodine status of pregnant women in Norway.
Directory of Open Access Journals (Sweden)
Rebecca Lee Smith
Full Text Available Hansen's disease (leprosy elimination has proven difficult in several countries, including Brazil, and there is a need for a mathematical model that can predict control program efficacy. This study applied the Approximate Bayesian Computation algorithm to fit 6 different proposed models to each of the 5 regions of Brazil, then fitted hierarchical models based on the best-fit regional models to the entire country. The best model proposed for most regions was a simple model. Posterior checks found that the model results were more similar to the observed incidence after fitting than before, and that parameters varied slightly by region. Current control programs were predicted to require additional measures to eliminate Hansen's Disease as a public health problem in Brazil.
DEFF Research Database (Denmark)
Bennike, Søren
Samfundet forandrer sig og ligeså gør danskernes idrætsmønstre. Fodbold Fitness, der er afhandlingens omdrejningspunkt, kan iagttages som en reaktion på disse forandringer. Afhandlingen ser nærmere på Fodbold Fitness og implementeringen af dette, der ingenlunde er nogen let opgave. Bennike bidrager...
Yu, Tai-Kuei; Yu, Tai-Yi
2010-01-01
Understanding learners' behaviour, perceptions and influence in terms of learner performance is crucial to predict the use of electronic learning systems. By integrating the task-technology fit (TTF) model and the theory of planned behaviour (TPB), this paper investigates the online learning utilisation of Taiwanese students. This paper provides a…
3D Product Development for Loose-Fitting Garments Based on Parametric Human Models
Krzywinski, S.; Siegmund, J.
2017-10-01
Researchers and commercial suppliers worldwide pursue the objective of achieving a more transparent garment construction process that is computationally linked to a virtual body, in order to save development costs over the long term. The current aim is not to transfer the complete pattern making step to a 3D design environment but to work out basic constructions in 3D that provide excellent fit due to their accurate construction and morphological pattern grading (automatic change of sizes in 3D) in respect of sizes and body types. After a computer-aided derivation of 2D pattern parts, these can be made available to the industry as a basis on which to create more fashionable variations.
DEFF Research Database (Denmark)
Madsen, Jonas Stenløkke; Lin, Yu Cheng; Squyres, Georgia R.
2015-01-01
response to electron acceptor limitation in both biofilm formation regimes, we found variation in the exploitability of its production and necessity for competitive fitness between the two systems. The wild type showed a competitive advantage against a non-Pel-producing mutant in pellicles but no advantage...... in colonies. Adaptation to the pellicle environment selected for mutants with a competitive advantage against the wild type in pellicles but also caused a severe disadvantage in colonies, even in wrinkled colony centers. Evolution in the colony center produced divergent phenotypes, while adaptation...... to the colony edge produced mutants with clear competitive advantages against the wild type in this O2-replete niche. In general, the structurally heterogeneous colony environment promoted more diversification than the more homogeneous pellicle. These results suggest that the role of Pel in community structure...
The electroweak fit of the standard model after the discovery of a new boson at the LHC
Energy Technology Data Exchange (ETDEWEB)
Baak, M.; Hoecker, A.; Schott, M. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Goebel, M.; Kennedy, D.; Moenig, K. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany); Haller, J.; Kogler, R. [Hamburg Univ. (Germany). Inst. fuer Experimentalphysik; Stelzer, J. [Michigan State Univ., East Lansing, MI (United States). Dept. of Physics and Astronomy; Collaboration: The Gfitter Group
2012-09-15
In view of the discovery of a new boson by the ATLAS and CMS Collaborations at the LHC, we present an update of the global Standard Model (SM) fit to electroweak precision data. Assuming the new particle to be the SM Higgs boson, all fundamental parameters of the SM are known allowing, for the first time, to overconstrain the SM at the electroweak scale and assert its validity. Including the effects of radiative corrections and the experimental and theoretical uncertainties, the global fit exhibits a p-value of 0.07. The mass measurements by ATLAS and CMS agree within 1.3{sigma} with the indirect determination M{sub H}=94{sup +25}{sub -22} GeV. Within the SM the W boson mass and the effective weak mixing angle can be accurately predicted to be M{sub W}=80.359{+-}0.011 GeV and sin{sup 2}{theta}{sup l}{sub eff}=0.23150{+-}0.00010 from the global fit. These results are compatible with, and exceed in precision, the direct measurements. For the indirect determination of the top quark mass we find m{sub t}=175.8{sup +2.7}{sub -2.4} GeV, in agreement with the kinematic and cross-section based measurements.
Commisso, Maria S; Martínez-Reina, Javier; Mayo, Juana; Domínguez, Jaime
2013-02-01
The main objectives of this work are: (a) to introduce an algorithm for adjusting the quasi-linear viscoelastic model to fit a material using a stress relaxation test and (b) to validate a protocol for performing such tests in temporomandibular joint discs. This algorithm is intended for fitting the Prony series coefficients and the hyperelastic constants of the quasi-linear viscoelastic model by considering that the relaxation test is performed with an initial ramp loading at a certain rate. This algorithm was validated before being applied to achieve the second objective. Generally, the complete three-dimensional formulation of the quasi-linear viscoelastic model is very complex. Therefore, it is necessary to design an experimental test to ensure a simple stress state, such as uniaxial compression to facilitate obtaining the viscoelastic properties. This work provides some recommendations about the experimental setup, which are important to follow, as an inadequate setup could produce a stress state far from uniaxial, thus, distorting the material constants determined from the experiment. The test considered is a stress relaxation test using unconfined compression performed in cylindrical specimens extracted from temporomandibular joint discs. To validate the experimental protocol, the test was numerically simulated using finite-element modelling. The disc was arbitrarily assigned a set of quasi-linear viscoelastic constants (c1) in the finite-element model. Another set of constants (c2) was obtained by fitting the results of the simulated test with the proposed algorithm. The deviation of constants c2 from constants c1 measures how far the stresses are from the uniaxial state. The effects of the following features of the experimental setup on this deviation have been analysed: (a) the friction coefficient between the compression plates and the specimen (which should be as low as possible); (b) the portion of the specimen glued to the compression plates (smaller
2017-08-01
No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 h per response, including the time for reviewing ...instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information...Universal kinetic rate model selector (URMS) Kinetic modeling Kinetic data set fitting Surface-enhanced Raman spectroscopy (SERS) Biosensor Degree of
The Cinderella effect: searching for the best fit between mouse models and human diseases.
Sundberg, John P; Roopenian, Derry C; Liu, Edison T; Schofield, Paul N
2013-11-01
A recent publication questions the suitability of mice as a model for the human inflammatory response and has fueled the continuing debate about the suitability of mice as models for human disease. We discuss recent advances in disease modeling using mice, and the genetic factors that need to be considered when trying to recapitulate aspects of human disease. Failure to appreciate the important differences between human and mouse biology and genetics underlying attempts to generate faithful models frequently leads to poor outcomes. Closely coordinated human and model organism studies are essential to provide traction for translational research.
... on staying active , playing sports , and special fitness gear . Focus on fun. Pick activities you enjoy so ... 27, 2015 Page last updated June 22, 2015 top About this site Mission Statement Privacy Policy For ...
Tarrés, J; Fina, M; Piedrafita, J
2010-09-01
The aim of this study was to compare the goodness of fit of the threshold models with homoscedasticity or heteroscedasticity and the grouped data model for the analysis of calving ease in beef cattle by using a parametric bootstrap procedure. Field data included 8,205 records of the Bruna dels Pirineus beef cattle breed in the Pyrenean mountain areas of Catalonia (Spain). The actual distribution was 81.81% of calvings without assistance, 11.02% slightly assisted by the farmer, 5.12% strongly assisted by the farmer, 0.89% assisted by the veterinarian, and 1.16% cesarean, but these percentages were very different in the different herds. This can be explained partially by the different subjective way of scoring of each farmer. Primiparous cows had a greater (P data were analyzed using 3 different models: the threshold models with homoscedasticity or heteroscedasticity and the grouped data model. The bootstrap comparison among models suggested that the threshold models, even allowing for heteroscedasticity, did not fit the herd effects well. In contrast, fitting deficiencies were not observed for the grouped data model in any factor. The variance of direct effect of the calf was estimated using the 3 models, and the heritability estimate ranged from 0.165 for the grouped data model to 0.185 for the hereroscedastic threshold model. This heritability was moderate, but it would justify the inclusion of direct effects of the calf on calving ease in the breeding objective. Overall, results highlighted the flexibility of the grouped data model for the analysis of discrete traits, like calving ease of beef calves.
The inert doublet model in the light of Fermi-LAT gamma-ray data: a global fit analysis
Energy Technology Data Exchange (ETDEWEB)
Eiteneuer, Benedikt; Heisig, Jan [RWTH Aachen University, Institute for Theoretical Particle Physics and Cosmology, Aachen (Germany); Goudelis, Andreas [UMR 7589 CNRS and UPMC, Laboratoire de Physique Theorique et Hautes Energies (LPTHE), Paris (France)
2017-09-15
We perform a global fit within the inert doublet model taking into account experimental observables from colliders, direct and indirect dark matter searches and theoretical constraints. In particular, we consider recent results from searches for dark matter annihilation-induced gamma-rays in dwarf spheroidal galaxies and relax the assumption that the inert doublet model should account for the entire dark matter in the Universe. We, moreover, study in how far the model is compatible with a possible dark matter explanation of the so-called Galactic center excess. We find two distinct parameter space regions that are consistent with existing constraints and can simultaneously explain the excess: One with dark matter masses near the Higgs resonance and one around 72 GeV where dark matter annihilates predominantly into pairs of virtual electroweak gauge bosons via the four-vertex arising from the inert doublet's kinetic term. We briefly discuss future prospects to probe these scenarios. (orig.)
Energy expenditures & physical activity in rats with chronic suboptimal nutrition
Directory of Open Access Journals (Sweden)
Lifshitz Fima
2006-01-01
Full Text Available Abstract Background Sub-optimally nourished rats show reduced growth, biochemical and physiological changes. However, no one has assessed metabolic rate adaptations in rats subjected to chronic suboptimal nutrition (CSN. In this study energy expenditure (EE; kcal/100 g body weight and physical activity (PA; oscillations in weight/min/kg body weight were assessed in rats subjected to three levels of CSN. Results Body weight gain was diminished (76.7 ± 12.0 and 61.6 ± 11.0 g in rats fed 70 and 60% of the ad-libitum fed controls which gained more weight (148.5 ± 32.3 g. The rats fed 80% gained weight similarly to controls (136.3 ± 10.5 g. Percent Fat-free body mass was reduced (143.8 ± 8.7 and 142.0 ± 7.6 g in rats fed 70 and 60% of ad-libitum, but not in those fed 80% (200.8 ± 17.5 g as compared with controls (201.6 ± 33.4 g. Body fat (g decreased in rats fed 80% (19.7 ± 5.3, 70% (15.3 ± 3.5 and 60% (9.6 ± 2.7 of ad-libitum in comparison to controls (26.0 ± 6.7. EE and PA were also altered by CSN. The control rats increased their EE and PA during the dark periods by 1.4 ± 0.8 and 1.7 ± 1.1 respectively, as compared with light the period; whereas CSN rats fed 80 and 70% of ad-libitum energy intake had reduced EE and PA during the dark periods as compared with the light period EE(7.5 ± 1.4 and 7.8 ± 0.6 vs. 9.0 ± 1.2 and 9.7 ± 0.8; p Conclusion CSN rats adapt to mild energy restriction by reducing body fat, EE and PA mainly during the dark period while growth proceeds and lean body mass is preserved. At higher levels of energy restrictions there is decreased growth, body fat and lean mass. Moreover EE and PA are also reduced during both light and dark periods.
Growing Fit: Georgia's model for engaging early care environments in preventing childhood obesity.
McDavid, Kelsey; Piedrahita, Catalina; Hashima, Patricia; Vall, Emily Anne; Kay, Christi; O'Connor, Jean
2016-01-01
In the United States, one in three children is overweight or obese by their fifth birthday. In Georgia, 35 percent of children are overweight or obese. Contrary to popular belief, children who are overweight or obese are likely to be the same weight status as adults, making early childhood an essential time to address weight status. An estimated 380,000 Georgia children attend early care and education environments, such as licensed child care centers, Head Start, and pre-kindergarten programs, which provide an opportunity to reach large numbers of children, including those at risk for obesity and overweight. To address this opportunity, the Georgia Department of Public Health, Georgia Shape - the Governor's Initiative to prevent childhood obesity, and HealthMPowers, Inc., created the Growing Fit training and toolkit to assist early childhood educators in creating policy, systems, and environmental changes that support good nutrition and physical activity. This report, the first related to this project, describes the training and its dissemination between January and December 2015. A total of 103 early childcare educators from 39 early childcare education centers (22 individual childcare systems) from 19 counties in Georgia were trained. Fifteen systems completed a pre and post-test assessment of their system, demonstrating slight improvements. Training for an additional 125 early childcare education centers is planned for 2016. Lessons learned from the first year of the training include the need for more robust assessment of adoption and implementation of policy, systems, and environmental changes in trained centers.
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...
The PX-EM algorithm for fast stable fitting of Henderson's mixed model
Foulley, Jean-Louis; Van Dyk, David A
2000-01-01
This paper presents procedures for implementing the PX-EM algorithm of Liu, Rubin and Wu to compute REML estimates of variance covariance components in Henderson's linear mixed models. The class of models considered encompasses several correlated random factors having the same vector length e.g., as in random regression models for longitudinal data analysis and in sire-maternal grandsire models for genetic evaluation. Numerical examples are presented to illustrate the procedures. Much better results in terms of convergence characteristics (number of iterations and time required for convergence) are obtained for PX-EM relative to the basic EM algorithm in the random regression. PMID:14736399
The PX-EM algorithm for fast stable fitting of Henderson's mixed model
Directory of Open Access Journals (Sweden)
Van Dyk David A
2000-03-01
Full Text Available Abstract This paper presents procedures for implementing the PX-EM algorithm of Liu, Rubin and Wu to compute REML estimates of variance covariance components in Henderson's linear mixed models. The class of models considered encompasses several correlated random factors having the same vector length e.g., as in random regression models for longitudinal data analysis and in sire-maternal grandsire models for genetic evaluation. Numerical examples are presented to illustrate the procedures. Much better results in terms of convergence characteristics (number of iterations and time required for convergence are obtained for PX-EM relative to the basic EM algorithm in the random regression.
Aguilera, Luis U; Zimmer, Christoph; Kummer, Ursula
2017-02-20
Mathematical models are used to gain an integrative understanding of biochemical processes and networks. Commonly the models are based on deterministic ordinary differential equations. When molecular counts are low, stochastic formalisms like Monte Carlo simulations are more appropriate and well established. However, compared to the wealth of computational methods used to fit and analyze deterministic models, there is only little available to quantify the exactness of the fit of stochastic models compared to experimental data or to analyze different aspects of the modeling results. Here, we developed a method to fit stochastic simulations to experimental high-throughput data, meaning data that exhibits distributions. The method uses a comparison of the probability density functions that are computed based on Monte Carlo simulations and the experimental data. Multiple parameter values are iteratively evaluated using optimization routines. The method improves its performance by selecting parameters values after comparing the similitude between the deterministic stability of the system and the modes in the experimental data distribution. As a case study we fitted a model of the IRF7 gene expression circuit to time-course experimental data obtained by flow cytometry. IRF7 shows bimodal dynamics upon IFN stimulation. This dynamics occurs due to the switching between active and basal states of the IRF7 promoter. However, the exact molecular mechanisms responsible for the bimodality of IRF7 is not fully understood. Our results allow us to conclude that the activation of the IRF7 promoter by the combination of IRF7 and ISGF3 is sufficient to explain the observed bimodal dynamics.
Physiologically based pharmacokinetic (PBPK) modelling tools: how to fit with our needs?
Bouzom, François; Ball, Kathryn; Perdaems, Nathalie; Walther, Bernard
2012-03-01
In 2005, a survey compared a number of commercial PBPK software available at the time, mainly focusing on 'ready to use' modelling tools. Since then, these tools and software have been further developed and improved to allow modellers to perform WB-PBPK modelling including ADME processes at a high level of sophistication. This review presents a comparison of the features, values and limitations of both the 'ready to use' software and of the traditional user customizable software that are frequently used for the building and use of PBPK models, as well as the challenges associated with the various modelling approaches regarding their current and future use. PBPK models continue to be used more and more frequently during the drug development process since they represent a quantitative, physiologically realistic platform with which to simulate and predict the impact of various potential scenarios on the pharmacokinetics and pharmacodynamics of drugs. The 'ready to use' PBPK software has been a major factor in the increasing use of PBPK modelling in the pharmaceutical industry, opening up the PBPK approach to a broader range of users. The challenge is now to educate and to train scientists and modellers to ensure their appropriate understanding of the assumptions and the limitations linked both to the physiological framework of the 'virtual body' and to the scaling methodology from in vitro to in vivo (IVIVE). Copyright © 2012 John Wiley & Sons, Ltd.
de Vries, S O; Fidler, Vaclav; Kuipers, Wietze D; Hunink, Maria G M
1998-01-01
The purpose of this study was to develop a model that predicts the outcome of supervised exercise for intermittent claudication. The authors present an example of the use of autoregressive logistic regression for modeling observed longitudinal data. Data were collected from 329 participants in a
Fitting macroevolutionary models to phylogenies: an example using vertebrate body sizes
Mooers, Arne Ø.; Schluter, Dolph
1998-01-01
How do traits change through time and with speciation? We present a simple and generally applicable method for comparing various models of the macroevolution of traits within a maximum likelihood framework. We illustrate four such models: 1) variance among species accumulates in direct proportion to
Fast and exact Newton and Bidirectional fitting of Active Appearance Models
Kossaifi, Jean; Tzimiropoulos, Georgios; Pantic, Maja
Active Appearance Models (AAMs) are generative models of shape and appearance that have proven very attractive for their ability to handle wide changes in illumination, pose and occlusion when trained in the wild, while not requiring large training dataset like regression-based or deep learning
Fu, W.; Gu, L.; Hoffman, F. M.
2013-12-01
The photosynthesis model of Farquhar, von Caemmerer & Berry (1980) is an important tool for predicting the response of plants to climate change. So far, the critical parameters required by the model have been obtained from the leaf-level measurements of gas exchange, namely the net assimilation of CO2 against intercellular CO2 concentration (A-Ci) curves, made at saturating light conditions. With such measurements, most points are likely in the Rubisco-limited state for which the model is structurally overparameterized (the model is also overparameterized in the TPU-limited state). In order to reliably estimate photosynthetic parameters, there must be sufficient number of points in the RuBP regeneration-limited state, which has no structural over-parameterization. To improve the accuracy of A-Ci data analysis, we investigate the potential of using multiple A-Ci curves at subsaturating light intensities to generate some important parameter estimates more accurately. Using subsaturating light intensities allow more RuBp regeneration-limited points to be obtained. In this study, simulated examples are used to demonstrate how this method can eliminate the errors of conventional A-Ci curve fitting methods. Some fitted parameters like the photocompensation point and day respiration impose a significant limitation on modeling leaf CO2 exchange. The multiple A-Ci curves fitting can also improve over the so-called Laisk (1977) method, which was shown by some recent publication to produce incorrect estimates of photocompensation point and day respiration. We also test the approach with actual measurements, along with suggested measurement conditions to constrain measured A-Ci points to maximize the occurrence of RuBP regeneration-limited photosynthesis. Finally, we use our measured gas exchange datasets to quantify the magnitude of resistance of chloroplast and cell wall-plasmalemma and explore the effect of variable mesophyll conductance. The variable mesophyll conductance
Treatment of KPC-producing Enterobacteriaceae: suboptimal efficacy of polymyxins.
de Oliveira, M S; de Assis, D B; Freire, M P; Boas do Prado, G V; Machado, A S; Abdala, E; Pierrotti, L C; Mangini, C; Campos, L; Caiaffa Filho, H H; Levin, A S
2015-02-01
Treatment of Klebsiella pneumoniae carbapenemase-producing Enterobacteriaceae infections (KPC-EI) remains a challenge. Combined therapy has been proposed as the best choice, but there are no clear data showing which combination therapy is superior. Our aim was to evaluate the effectiveness of antimicrobial regimens for treating KPC-EI. This was a retrospective cohort study of KPC-EI nosocomial infections (based on CDC criteria) between October 2009 and June 2013 at three tertiary Brazilian hospitals. The primary outcomes were the 30-day mortality for all infections and the 30-day mortality for patients with bacteraemia. Risk factors for mortality were evaluated by comparing clinical variables of survivors and nonsurvivors. In this study, 118 patients were included, of whom 78 had bacteraemia. Catheter-related bloodstream infections were the most frequent (43%), followed by urinary tract infections (n = 27, 23%). Monotherapy was used in 57 patients and combined treatment in 61 patients. The most common therapeutic combination was polymyxin plus carbapenem 20 (33%). Multivariate analysis for all infections (n = 118) and for bacteremic infections (n = 78) revealed that renal failure at the end of treatment, use of polymyxin and older age were prognostic factors for mortality. In conclusion, polymyxins showed suboptimal efficacy and combination therapy was not superior to monotherapy. Copyright © 2014 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.
Robust Adaptive LCMV Beamformer Based On An Iterative Suboptimal Solution
Directory of Open Access Journals (Sweden)
Xiansheng Guo
2015-06-01
Full Text Available The main drawback of closed-form solution of linearly constrained minimum variance (CF-LCMV beamformer is the dilemma of acquiring long observation time for stable covariance matrix estimates and short observation time to track dynamic behavior of targets, leading to poor performance including low signal-noise-ratio (SNR, low jammer-to-noise ratios (JNRs and small number of snapshots. Additionally, CF-LCMV suffers from heavy computational burden which mainly comes from two matrix inverse operations for computing the optimal weight vector. In this paper, we derive a low-complexity Robust Adaptive LCMV beamformer based on an Iterative Suboptimal solution (RAIS-LCMV using conjugate gradient (CG optimization method. The merit of our proposed method is threefold. Firstly, RAIS-LCMV beamformer can reduce the complexity of CF-LCMV remarkably. Secondly, RAIS-LCMV beamformer can adjust output adaptively based on measurement and its convergence speed is comparable. Finally, RAIS-LCMV algorithm has robust performance against low SNR, JNRs, and small number of snapshots. Simulation results demonstrate the superiority of our proposed algorithms.
Predictors of Suboptimal Follow-up in Pediatric Cancer Survivors.
May, Leana; Schwartz, David D; Frugé, Ernest; Laufman, Larry; Holm, Suzanne; Kamdar, Kala; Harris, Lynnette; Brackett, Julienne; Unal, Sule; Tanyildiz, Gulsah; Bryant, Rosalind; Suzawa, Hilary; Dreyer, Zoann; Okcu, M Fatih
2017-04-01
Attendance to follow-up care after completion of cancer treatment is an understudied area. We examined demographic, clinical, and socioeconomic predictors of follow-up by pediatric cancer patients at a large center in 442 newly diagnosed patients using multivariable logistic regression analyses. Patients who did not return to clinic for at least 1000 days were considered lost to follow-up. Two hundred forty-two (54.8%) patients were lost. In multivariable analyses, the following variables were independent predictors of being lost to follow-up: treatment with surgery alone (odds ratio [OR]=6.7; 95% confidence interval [CI], 3.1-14.9), older age at diagnosis (reference, 0 to 4; ages, 5 to 9: OR=1.8, 95% CI, 1.1-3; ages, 10 to 14: OR=3.3; CI, 1.8-6.1; and ages, 15 and above: OR=4.8; CI, 2.1-11.7), lack of history of stem cell transplantation (OR=2, 95% CI, 1.04-3.7) and lack of insurance (OR=3.4; CI, 1.2-9.2). Hispanic patients had the best follow-up rates (53.7%) compared to whites and blacks (P=0.03). Attendance to long-term follow-up care is suboptimal in childhood cancer survivors. Predictors that were associated with nonattendance can be used to design targeted interventions to improve follow-up care for survivors of pediatric cancer.
Talbot, Clifford B; Lagarto, João; Warren, Sean; Neil, Mark A A; French, Paul M W; Dunsby, Chris
2015-09-01
A correction is proposed to the Delta function convolution method (DFCM) for fitting a multiexponential decay model to time-resolved fluorescence decay data using a monoexponential reference fluorophore. A theoretical analysis of the discretised DFCM multiexponential decay function shows the presence an extra exponential decay term with the same lifetime as the reference fluorophore that we denote as the residual reference component. This extra decay component arises as a result of the discretised convolution of one of the two terms in the modified model function required by the DFCM. The effect of the residual reference component becomes more pronounced when the fluorescence lifetime of the reference is longer than all of the individual components of the specimen under inspection and when the temporal sampling interval is not negligible compared to the quantity (τR (-1) - τ(-1))(-1), where τR and τ are the fluorescence lifetimes of the reference and the specimen respectively. It is shown that the unwanted residual reference component results in systematic errors when fitting simulated data and that these errors are not present when the proposed correction is applied. The correction is also verified using real data obtained from experiment.
One size does not fit all: Adapting mark-recapture and occupancy models for state uncertainty
Kendall, W.L.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.
2009-01-01
Multistate capture?recapture models continue to be employed with greater frequency to test hypotheses about metapopulation dynamics and life history, and more recently disease dynamics. In recent years efforts have begun to adjust these models for cases where there is uncertainty about an animal?s state upon capture. These efforts can be categorized into models that permit misclassification between two states to occur in either direction or one direction, where state is certain for a subset of individuals or is always uncertain, and where estimation is based on one sampling occasion per period of interest or multiple sampling occasions per period. State uncertainty also arises in modeling patch occupancy dynamics. I consider several case studies involving bird and marine mammal studies that illustrate how misclassified states can arise, and outline model structures for properly utilizing the data that are produced. In each case misclassification occurs in only one direction (thus there is a subset of individuals or patches where state is known with certainty), and there are multiple sampling occasions per period of interest. For the cases involving capture?recapture data I allude to a general model structure that could include each example as a special case. However, this collection of cases also illustrates how difficult it is to develop a model structure that can be directly useful for answering every ecological question of interest and account for every type of data from the field.
Giardino, Pier Paolo; Masina, Isabella; Raidal, Martti; Strumia, Alessandro
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, invisible Higgs decay 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 $M_h = 125.0 \\pm 1.8$ GeV.
Directory of Open Access Journals (Sweden)
Jeffrey L Peters
Full Text Available Inferring aspects of the population histories of species using coalescent analyses of non-coding nuclear DNA has grown in popularity. These inferences, such as divergence, gene flow, and changes in population size, assume that genetic data reflect simple population histories and neutral evolutionary processes. However, violating model assumptions can result in a poor fit between empirical data and the models. We sampled 22 nuclear intron sequences from at least 19 different chromosomes (a genomic transect to test for deviations from selective neutrality in the gadwall (Anas strepera, a Holarctic duck. Nucleotide diversity among these loci varied by nearly two orders of magnitude (from 0.0004 to 0.029, and this heterogeneity could not be explained by differences in substitution rates alone. Using two different coalescent methods to infer models of population history and then simulating neutral genetic diversity under these models, we found that the observed among-locus heterogeneity in nucleotide diversity was significantly higher than expected for these simple models. Defining more complex models of population history demonstrated that a pre-divergence bottleneck was also unlikely to explain this heterogeneity. However, both selection and interspecific hybridization could account for the heterogeneity observed among loci. Regardless of the cause of the deviation, our results illustrate that violating key assumptions of coalescent models can mislead inferences of population history.
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).
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
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......PEM fuel cell are dealt with in detail.The model solves the convective and diffusive transport of thegaseous phase in the fuel cell and allows prediction of theconcentration of the species present. A special feature of themodel is a method that allows detailed modelling and predictionof electrode kinetics...... dependency on the gas concentration andactivation overpotential can thereby be addressed. The proposedmodel makes it possible to predict the effect of geometrical andmaterial properties on the fuel cell?s performance. It is shownhow the ionic conductivity and porosity of the catalyst layeraffects...
Checking model-data weather hazard occurrence fit in the context of climate change
Tolosana Delgado, Raimon; Ortego Martínez, María Isabel; Egozcue Rubí, Juan José; Sánchez-Arcilla Conejo, Agustín
2011-01-01
In climate change impact studies it is common to run a given response model (from ecosystem changes to wavestorm or landslide occurrence) nested into one of the available long-term Global or Regional Circulation Models (GCM, RCM) reproducing the climate for the XX century or predicting it for the XXI. In this way, it is expected to capture the average behaviour of the studied system to a changing climate forcing: in other words, with such response forecasts, one does not actual...
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.
Fitting a Turbulent Cloud Model to CO Observations of Starless Bok Globules
Hegmann, M.; Hengel, C.; Röllig, M.; Kegel, W. H.
We present observations of five starless Bok globules in transitions of 12CO (J=2-1 and {J=3-2}), 13CO (J=2-1), and C18O (J=2-1) which have been obtained at the Heinrich-Hertz-Telescope. For an analysis of the data we use the model of Kegel et al. (see e.g. Piehler & Kegel 1995, A&A 297, 841; Hegmann & Kegel 2000, A&A 359, 405) which describes an isothermal sphere stabilized by turbulent and thermal pressure. This approach deals with the full NLTE radiative transfer problem and accounts for a turbulent velocity field with finite correlation length. By a comparison of observed and calculated line profiles we are able not only to determine the kinetic temperature, hydrogen density and CO coloumn density of the globules, but also to study the properties of the turbulent velocity field, i.e. the variance of its one-point-distribution and its correlation length. We consider our model to be an alternative tool for the evaluation of molecular lines emitted by molecular clouds. The model assumptions are certainly closer to reality than the assumptions behind the standard evaluation models, as for example the LVG model. Our current study shows that that the results obtained from our model can differ significantly from those obtained from a LVG analysis.
Fitting identity in the reasoned action framework: A meta-analysis and model comparison.
Paquin, Ryan S; Keating, David M
2017-01-01
Several competing models have been put forth regarding the role of identity in the reasoned action framework. The standard model proposes that identity is a background variable. Under a typical augmented model, identity is treated as an additional direct predictor of intention and behavior. Alternatively, it has been proposed that identity measures are inadvertent indicators of an underlying intention factor (e.g., a manifest-intention model). In order to test these competing hypotheses, we used data from 73 independent studies (total N = 23,917) to conduct a series of meta-analytic structural equation models. We also tested for moderation effects based on whether there was a match between identity constructs and the target behaviors examined (e.g., if the study examined a "smoker identity" and "smoking behavior," there would be a match; if the study examined a "health conscious identity" and "smoking behavior," there would not be a match). Average effects among primary reasoned action variables were all substantial, rs = .37-.69. Results gave evidence for the manifest-intention model over the other explanations, and a moderation effect by identity-behavior matching.
Fitting three-level meta-analytic models in R: A step-by-step tutorial
Directory of Open Access Journals (Sweden)
Assink, Mark
2016-10-01
Full Text Available Applying a multilevel approach to meta-analysis is a strong method for dealing with dependency of effect sizes. However, this method is relatively unknown among researchers and, to date, has not been widely used in meta-analytic research. Therefore, the purpose of this tutorial was to show how a three-level random effects model can be applied to meta-analytic models in R using the rma.mv function of the metafor package. This application is illustrated by taking the reader through a step-by-step guide to the multilevel analyses comprising the steps of (1 organizing a data file; (2 setting up the R environment; (3 calculating an overall effect; (4 examining heterogeneity of within-study variance and between-study variance; (5 performing categorical and continuous moderator analyses; and (6 examining a multiple moderator model. By example, the authors demonstrate how the multilevel approach can be applied to meta-analytically examining the association between mental health disorders of juveniles and juvenile offender recidivism. In our opinion, the rma.mv function of the metafor package provides an easy and flexible way of applying a multi-level structure to meta-analytic models in R. Further, the multilevel meta-analytic models can be easily extended so that the potential moderating influence of variables can be examined.
Do telemonitoring projects of heart failure fit the Chronic Care Model?
Willemse, Evi; Adriaenssens, Jef; Dilles, Tinne; Remmen, Roy
2014-07-01
This study describes the characteristics of extramural and transmural telemonitoring projects on chronic heart failure in Belgium. It describes to what extent these telemonitoring projects coincide with the Chronic Care Model of Wagner. The Chronic Care Model describes essential components for high-quality health care. Telemonitoring can be used to optimise home care for chronic heart failure. It provides a potential prospective to change the current care organisation. This qualitative study describes seven non-invasive home-care telemonitoring projects in patients with heart failure in Belgium. A qualitative design, including interviews and literature review, was used to describe the correspondence of these home-care telemonitoring projects with the dimensions of the Chronic Care Model. The projects were situated in primary and secondary health care. Their primary goal was to reduce the number of readmissions for chronic heart failure. None of these projects succeeded in a final implementation of telemonitoring in home care after the pilot phase. Not all the projects were initiated to accomplish all of the dimensions of the Chronic Care Model. A central role for the patient was sparse. Limited financial resources hampered continuation after the pilot phase. Cooperation and coordination in telemonitoring appears to be major barriers but are, within primary care as well as between the lines of care, important links in follow-up. This discrepancy can be prohibitive for deployment of good chronic care. Chronic Care Model is recommended as basis for future.
Directory of Open Access Journals (Sweden)
James M McCaw
2011-04-01
Full Text Available We present a method to measure the relative transmissibility ("transmission fitness" of one strain of a pathogen compared to another. The model is applied to data from "competitive mixtures" experiments in which animals are co-infected with a mixture of two strains. We observe the mixture in each animal over time and over multiple generations of transmission. We use data from influenza experiments in ferrets to demonstrate the approach. Assessment of the relative transmissibility between two strains of influenza is important in at least three contexts: 1 Within the human population antigenically novel strains of influenza arise and compete for susceptible hosts. 2 During a pandemic event, a novel sub-type of influenza competes with the existing seasonal strain(s. The unfolding epidemiological dynamics are dependent upon both the population's susceptibility profile and the inherent transmissibility of the novel strain compared to the existing strain(s. 3 Neuraminidase inhibitors (NAIs, while providing significant potential to reduce transmission of influenza, exert selective pressure on the virus and so promote the emergence of drug-resistant strains. Any adverse outcome due to selection and subsequent spread of an NAI-resistant strain is exquisitely dependent upon the transmission fitness of that strain. Measurement of the transmission fitness of two competing strains of influenza is thus of critical importance in determining the likely time-course and epidemiology of an influenza outbreak, or the potential impact of an intervention measure such as NAI distribution. The mathematical framework introduced here also provides an estimate for the size of the transmitted inoculum. We demonstrate the framework's behaviour using data from ferret transmission studies, and through simulation suggest how to optimise experimental design for assessment of transmissibility. The method introduced here for assessment of mixed transmission events has
Effect of tectonic setting on the fit and performance of a long-range earthquake forecasting model
Directory of Open Access Journals (Sweden)
David Alan Rhoades
2012-02-01
Full Text Available The Every Earthquake a Precursor According to Scale (EEPAS long-range earthquake forecasting model has been shown to be informative in several seismically active regions, including New Zealand, California and Japan. In previous applications of the model, the tectonic setting of earthquakes has been ignored. Here we distinguish crustal, plate interface, and slab earthquakes and apply the model to earthquakes with magnitude M≥4 in the Japan region from 1926 onwards. The target magnitude range is M≥ 6; the fitting period is 1966-1995; and the testing period is 1996-2005. In forecasting major slab earthquakes, it is optimal to use only slab and interface events as precursors. In forecasting major interface events, it is optimal to use only interface events as precursors. In forecasting major crustal events, it is optimal to use only crustal events as precursors. For the smoothed-seismicity component of the EEPAS model, it is optimal to use slab and interface events for earthquakes in the slab, interface events only for earthquakes on the interface, and crustal and interface events for crustal earthquakes. The optimal model parameters indicate that the precursor areas for slab earthquakes are relatively small compared to those for earthquakes in other tectonic categories, and that the precursor times and precursory earthquake magnitudes for crustal earthquakes are relatively large. The optimal models fit the learning data sets better than the raw EEPAS model, with an average information gain per earthquake of about 0.4. The average information gain is similar in the testing period, although it is higher for crustal earthquakes and lower for slab and interface earthquakes than in the learning period. These results show that earthquake interactions are stronger between earthquakes of similar tectonic types and that distinguishing tectonic types improves forecasts by enhancing the depth resolution where tectonic categories of earthquakes are
A CONTRASTIVE ANALYSIS OF THE FACTORIAL STRUCTURE OF THE PCL-R: WHICH MODEL FITS BEST THE DATA?
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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
Group Practices and Partnerships: A traditional model that Fits Many Situations.
Pickering, Stephen R
2015-01-01
The traditional group practice model can take many forms, including general practitioners, specialists, and combinations, as well as solo practitioners sharing space and staff, partnerships, and other legal entities. These practices may share some or all staff functions, including contracting for some functions. The essential characteristic is that those treating patients also have full control over and often direct management of the business aspects of the practice. The most important requirements for success in this model may be a common philosophy of patient care and mutual trust regarding business matters.
VizieR Online Data Catalog: PSF models fits maps (Karabal+, 2017)
Karabal, E.; Duc, P.-A.; Kuntschner, H.; Chanial, P.; Cuillandre, J.-C.; Gwyn, S.
2017-02-01
This dataset includes the PSF models that were used to deconvolve the images and correct them from scattered light. The library includes PSFs corresponding to different full width at half maximum (FWHM) in g and r bands. They were built from stacked individual images obtained with the dithering pattern of the MATLAS large programme. Bright stars located close to the center of the stacked images were used for the modeling. The PSFs were normalized to 1, i.e. the pixel with maximum value in the image is set to 1. (2 data files).
Speeding-up the Fitting of the Model Defining the Ribs-bounded Contour
Directory of Open Access Journals (Sweden)
Bilinskas Mykolas J.
2017-05-01
Full Text Available The method for analysing transversal plane images from computer tomography scans is considered in the paper. This method allows not only approximating ribs-bounded contour but also evaluating patient rotation around the vertical axis during a scan. In this method, a mathematical model describing the ribs-bounded contour was created and the problem of approximation has been solved by finding the optimal parameters of the mathematical model using least-squares-type objective function. The local search has been per-formed using local descent by quasi-Newton methods. The benefits of analytical derivatives of the function are disclosed in the paper.
Meaning-making and the matrix model: does one size really fit all?
Neimeyer, Robert A
2005-09-01
Despite the multifocal complexity of the matrix model (C.R. Snyder & T.R. Elliott, this issue, pp. 1033-1054), its close correspondence with the theoretical dialectics and philosophy of clinical constructivism auger well for its capacity to articulate with existing approaches to graduate education in psychology. In this article points of contact are documented between the two approaches, and a caveat is included about the limits of the matrix model in ensuring greater relevance of clinical training to the settings in which contemporary professionals will work. (c) 2005 Wiley Periodicals, Inc.
Understanding the Listening Process: Rethinking the "One Size Fits All" Model
Wolvin, Andrew
2013-01-01
Robert Bostrom's seminal contributions to listening theory and research represent an impressive legacy and provide listening scholars with important perspectives on the complexities of listening cognition and behavior. Bostrom's work provides a solid foundation on which to build models that more realistically explain how listeners function…
Fitting Social Network Models Using Varying Truncation Stochastic Approximation MCMC Algorithm
Jin, Ick Hoon
2013-10-01
The exponential random graph model (ERGM) plays a major role in social network analysis. However, parameter estimation for the ERGM is a hard problem due to the intractability of its normalizing constant and the model degeneracy. The existing algorithms, such as Monte Carlo maximum likelihood estimation (MCMLE) and stochastic approximation, often fail for this problem in the presence of model degeneracy. In this article, we introduce the varying truncation stochastic approximation Markov chain Monte Carlo (SAMCMC) algorithm to tackle this problem. The varying truncation mechanism enables the algorithm to choose an appropriate starting point and an appropriate gain factor sequence, and thus to produce a reasonable parameter estimate for the ERGM even in the presence of model degeneracy. The numerical results indicate that the varying truncation SAMCMC algorithm can significantly outperform the MCMLE and stochastic approximation algorithms: for degenerate ERGMs, MCMLE and stochastic approximation often fail to produce any reasonable parameter estimates, while SAMCMC can do; for nondegenerate ERGMs, SAMCMC can work as well as or better than MCMLE and stochastic approximation. The data and source codes used for this article are available online as supplementary materials. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.
Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?
Ghassib, Hisham B.
2010-01-01
The basic premise of this paper is the fact that science has become a major industry: the knowledge industry. The paper throws some light on the reasons for the transformation of science from a limited, constrained and marginal craft into a major industry. It, then, presents a productivist industrial model of knowledge production, which shows its…
van Baalen, Sophie Jacobine; Leemans, Alexander; Dik, Pieter; Lilien, Marc R.; ten Haken, Bernard; Froeling, Martijn
Purpose To evaluate if a three-component model correctly describes the diffusion signal in the kidney and whether it can provide complementary anatomical or physiological information about the underlying tissue. Materials and Methods Ten healthy volunteers were examined at 3T, with T2-weighted
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 all...
Do telemonitoring projects of heart failure fit the Chronic Care Model?
Directory of Open Access Journals (Sweden)
Evi Willemse
2014-07-01
Full Text Available This study describes the characteristics of extramural and transmural telemonitoring projects on chronic heart failure in Belgium. It describes to what extent these telemonitoring projects coincide with the Chronic Care Model of Wagner. Background: The Chronic Care Model describes essential components for high-quality health care. Telemonitoring can be used to optimise home care for chronic heart failure. It provides a potential prospective to change the current care organisation. Methods: This qualitative study describes seven non-invasive home-care telemonitoring projects in patients with heart failure in Belgium. A qualitative design, including interviews and literature review, was used to describe the correspondence of these home-care telemonitoring projects with the dimensions of the Chronic Care Model. Results: The projects were situated in primary and secondary health care. Their primary goal was to reduce the number of readmissions for chronic heart failure. None of these projects succeeded in a final implementation of telemonitoring in home care after the pilot phase. Not all the projects were initiated to accomplish all of the dimensions of the Chronic Care Model. A central role for the patient was sparse. Conclusion: Limited financial resources hampered continuation after the pilot phase. Cooperation and coordination in telemonitoring appears to be major barriers but are, within primary care as well as between the lines of care, important links in follow-up. This discrepancy can be prohibitive for deployment of good chronic care. Chronic Care Model is recommended as basis for future.
Do telemonitoring projects of heart failure fit the Chronic Care Model?
Directory of Open Access Journals (Sweden)
Evi Willemse
2014-07-01
Full Text Available This study describes the characteristics of extramural and transmural telemonitoring projects on chronic heart failure in Belgium. It describes to what extent these telemonitoring projects coincide with the Chronic Care Model of Wagner.Background: The Chronic Care Model describes essential components for high-quality health care. Telemonitoring can be used to optimise home care for chronic heart failure. It provides a potential prospective to change the current care organisation.Methods: This qualitative study describes seven non-invasive home-care telemonitoring projects in patients with heart failure in Belgium. A qualitative design, including interviews and literature review, was used to describe the correspondence of these home-care telemonitoring projects with the dimensions of the Chronic Care Model.Results: The projects were situated in primary and secondary health care. Their primary goal was to reduce the number of readmissions for chronic heart failure. None of these projects succeeded in a final implementation of telemonitoring in home care after the pilot phase. Not all the projects were initiated to accomplish all of the dimensions of the Chronic Care Model. A central role for the patient was sparse.Conclusion: Limited financial resources hampered continuation after the pilot phase. Cooperation and coordination in telemonitoring appears to be major barriers but are, within primary care as well as between the lines of care, important links in follow-up. This discrepancy can be prohibitive for deployment of good chronic care. Chronic Care Model is recommended as basis for future.
Knight, Gwenan M.; Colijn, Caroline; Shrestha, Sourya; Fofana, Mariam; Cobelens, Frank; White, Richard G.; Dowdy, David W.; Cohen, Ted
2015-01-01
Background. Drug resistance poses a serious challenge for the control of tuberculosis in many settings. It is well established that the expected future trend in resistance depends on the reproductive fitness of drug-resistant Mycobacterium tuberculosis. However, the variability in fitness between strains with different resistance-conferring mutations has been largely ignored when making these predictions. Methods. We developed a novel approach for incorporating the variable fitness costs of drug resistance-conferring mutations and for tracking this distribution of fitness costs over time within a transmission model. We used this approach to describe the effects of realistic fitness cost distributions on the future prevalence of drug-resistant tuberculosis. Results. The shape of the distribution of fitness costs was a strong predictor of the long-term prevalence of resistance. While, as expected, lower average fitness costs of drug resistance–conferring mutations were associated with more severe epidemics of drug-resistant tuberculosis, fitness distributions with greater variance also led to higher levels of drug resistance. For example, compared to simulations in which the fitness cost of resistance was fixed, introducing a realistic amount of variance resulted in a 40% increase in prevalence of drug-resistant tuberculosis after 20 years. Conclusions. The differences in the fitness costs associated with drug resistance–conferring mutations are a key determinant of the future burden of drug-resistant tuberculosis. Future studies that can better establish the range of fitness costs associated with drug resistance–conferring mutations will improve projections and thus facilitate better public health planning efforts. PMID:26409276
Determinants of suboptimal breast-feeding practices in Pakistan.
Hazir, Tabish; Akram, Dure-Samin; Nisar, Yasir Bin; Kazmi, Narjis; Agho, Kingsley E; Abbasi, Saleem; Khan, Amira M; Dibley, Michael J
2013-04-01
Exclusive breast-feeding is estimated to reduce infant mortality in low-income countries by up to 13 %. The aim of the present study was to determine the risk factors associated with suboptimal breast-feeding practices in Pakistan. A cross-sectional study using data extracted from the multistage cluster sample survey of the Pakistan Demographic and Health Survey 2006-2007. A nationally representative sample of households. Last-born alive children aged 0-23 months (total weighted sample size 3103). The prevalences of timely initiation of breast-feeding, bottle-feeding in children aged 0-23 months, exclusive breast-feeding and predominant breast-feeding in infants aged 0-5 months were 27·3 %, 32·1 %, 37·1 % and 18·7 %, respectively. Multivariate analysis indicated that working mothers (OR = 1·48, 95 % CI 1·16, 1·87; P = 0·001) and mothers who delivered by Caesarean section (OR = 1·95, 95 % CI 1·30, 2·90; P = 0·001) had significantly higher odds for no timely initiation of breast-feeding. Mothers from North West Frontier Province were significantly less likely (OR = 0·37, 95 % CI 0·23, 0·59; P feed their babies exclusively. Mothers delivered by traditional birth attendants had significantly higher odds to predominantly breast-feed their babies (OR = 1·96, 95 % CI 1·18, 3·24; P = 0·009). The odds of being bottle-fed was significantly higher in infants whose mothers had four or more antenatal clinic visits (OR = 1·93, 95 % CI 1·46, 2·55; P feeding practices. To gain the full benefits of breast-feeding for child health and nutrition, there is an urgent need to develop interventions to improve the rates of exclusive breast-feeding.
Ploeg, van der A.; Carvalho, S.M.P.; Heuvelink, E.
2009-01-01
Energy efficiency of greenhouse cut chrysanthemum (Chrysanthemum morifolium Ramat.) may be increased by breeding. In addition to breeding for cultivars with a shorter reaction time at suboptimal temperatures, an alternative approach would be to develop cultivars that are heavier at suboptimal
Directory of Open Access Journals (Sweden)
Xiaohong Chen
2017-05-01
Full Text Available The upper tail of a flood frequency distribution is always specifically concerned with flood control. However, different model selection criteria often give different optimal distributions when the focus is on the upper tail of distribution. With emphasis on the upper-tail behavior, five distribution selection criteria including two hypothesis tests and three information-based criteria are evaluated in selecting the best fitted distribution from eight widely used distributions by using datasets from Thames River, Wabash River, Beijiang River and Huai River. The performance of the five selection criteria is verified by using a composite criterion with focus on upper tail events. This paper demonstrated an approach for optimally selecting suitable flood frequency distributions. Results illustrate that (1 there are different selections of frequency distributions in the four rivers by using hypothesis tests and information-based criteria approaches. Hypothesis tests are more likely to choose complex, parametric models, and information-based criteria prefer to choose simple, effective models. Different selection criteria have no particular tendency toward the tail of the distribution; (2 The information-based criteria perform better than hypothesis tests in most cases when the focus is on the goodness of predictions of the extreme upper tail events. The distributions selected by information-based criteria are more likely to be close to true values than the distributions selected by hypothesis test methods in the upper tail of the frequency curve; (3 The proposed composite criterion not only can select the optimal distribution, but also can evaluate the error of estimated value, which often plays an important role in the risk assessment and engineering design. In order to decide on a particular distribution to fit the high flow, it would be better to use the composite criterion.
Marconi, M.; Molinaro, R.; Ripepi, V.; Cioni, M.-R. L.; Clementini, G.; Moretti, M. I.; Ragosta, F.; de Grijs, R.; Groenewegen, M. A. T.; Ivanov, V. D.
2017-04-01
We present the results of the χ2 minimization model fitting technique applied to optical and near-infrared photometric and radial velocity data for a sample of nine fundamental and three first overtone classical Cepheids in the Small Magellanic Cloud (SMC). The near-infrared photometry (JK filters) was obtained by the European Southern Observatory (ESO) public survey 'VISTA near-infrared Y, J, Ks survey of the Magellanic Clouds system' (VMC). For each pulsator, isoperiodic model sequences have been computed by adopting a non-linear convective hydrodynamical code in order to reproduce the multifilter light and (when available) radial velocity curve amplitudes and morphological details. The inferred individual distances provide an intrinsic mean value for the SMC distance modulus of 19.01 mag and a standard deviation of 0.08 mag, in agreement with the literature. Moreover, the intrinsic masses and luminosities of the best-fitting model show that all these pulsators are brighter than the canonical evolutionary mass-luminosity relation (MLR), suggesting a significant efficiency of core overshooting and/or mass-loss. Assuming that the inferred deviation from the canonical MLR is only due to mass-loss, we derive the expected distribution of percentage mass-loss as a function of both the pulsation period and the canonical stellar mass. Finally, a good agreement is found between the predicted mean radii and current period-radius (PR) relations in the SMC available in the literature. The results of this investigation support the predictive capabilities of the adopted theoretical scenario and pave the way for the application to other extensive data bases at various chemical compositions, including the VMC Large Magellanic Cloud pulsators and Galactic Cepheids with Gaia parallaxes.
A Monte Carlo-adjusted goodness-of-fit test for parametric models describing spatial point patterns
Dao, Ngocanh
2014-04-03
Assessing the goodness-of-fit (GOF) for intricate parametric spatial point process models is important for many application fields. When the probability density of the statistic of the GOF test is intractable, a commonly used procedure is the Monte Carlo GOF test. Additionally, if the data comprise a single dataset, a popular version of the test plugs a parameter estimate in the hypothesized parametric model to generate data for theMonte Carlo GOF test. In this case, the test is invalid because the resulting empirical level does not reach the nominal level. In this article, we propose a method consisting of nested Monte Carlo simulations which has the following advantages: the bias of the resulting empirical level of the test is eliminated, hence the empirical levels can always reach the nominal level, and information about inhomogeneity of the data can be provided.We theoretically justify our testing procedure using Taylor expansions and demonstrate that it is correctly sized through various simulation studies. In our first data application, we discover, in agreement with Illian et al., that Phlebocarya filifolia plants near Perth, Australia, can follow a homogeneous Poisson clustered process that provides insight into the propagation mechanism of these plants. In our second data application, we find, in contrast to Diggle, that a pairwise interaction model provides a good fit to the micro-anatomy data of amacrine cells designed for analyzing the developmental growth of immature retina cells in rabbits. This article has supplementary material online. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.
Directory of Open Access Journals (Sweden)
Tirza Z Tamin
2015-04-01
Full Text Available Aim: to design a model and assess the effectiveness of endurance exercise to increase physical fitness in intelectual disability (ID patients with obesity. Methods: a randomized-controlled clinical trial was performed in ID patients with obesity aged 10-30 years old from all Special School in DKI Jakarta, which were randomly allocated into 3 groups and then given 3 different type of exercises: lower extremity muscles endurance exercise for 20 RM followed by cardiorespiratory endurance exercise for 24-25 minutes (type I, lower extremity muscles endurance exercises for 10 RM followed by cardiorespiratory endurance exercises for 26-27 minutes (type II, and threw a tennis ball with 10 m distance for 10 minutes as control (type III. These program was performed 3 times a week for 4 months. Assesment of the exercise effectiveness was done by measuring maximum load that can be lifted and six-minutes walking test on rectangular track which was converted with the VO2 max prediction formula. Analysis was perfomed with Kruskal Wallis test. Results: two hundred and twelve (212 subjects were included in the study, randomly allocated into three types (I, II, and III of exercises groups. The type II of endurance exercise model was proved to be more effective in increasing lower extremity muscles endurance level compared to type I and III for ID patients with obesity (p<0.05. Meanwhile, type I of endurance exercise model was proved to be more effective in increasing cardiorespiratory endurance level compared to type II and III for ID patients with obesity (p<0.05. Conclusion: lower extremity muscles endurance exercise followed by a cardiorespiratory endurance exercise can be used to increase physical fitness in ID patients with obesity. Key words: intelectual disability patient, obesity, lower extremity muscles and cardiorespiratory endurance exercise, lower extremity muscles endurance level, cardiorespiratory endurance level.
Exact Solution of Mutator Model with Linear Fitness and Finite Genome Length
Saakian, David B.
2017-08-01
We considered the infinite population version of the mutator phenomenon in evolutionary dynamics, looking at the uni-directional mutations in the mutator-specific genes and linear selection. We solved exactly the model for the finite genome length case, looking at the quasispecies version of the phenomenon. We calculated the mutator probability both in the statics and dynamics. The exact solution is important for us because the mutator probability depends on the genome length in a highly non-trivial way.
Taking Error Into Account When Fitting Models Using Approximate Bayesian Computation.
van der Vaart, Elske; Prangle, Dennis; Sibly, Richard M
2017-11-25
Stochastic computer simulations are often the only practical way of answering questions relating to ecological management. However, due to their complexity, such models are difficult to calibrate and evaluate. Approximate Bayesian Computation (ABC) offers an increasingly popular approach to this problem, widely applied across a variety of fields. However, ensuring the accuracy of ABC's estimates has been difficult. Here, we obtain more accurate estimates by incorporating estimation of error into the ABC protocol. We show how this can be done where the data consist of repeated measures of the same quantity and errors may be assumed to be normally distributed and independent. We then derive the correct acceptance probabilities for a probabilistic ABC algorithm, and update the 'coverage test' with which accuracy is assessed. We apply this method - which we call 'error-calibrated ABC' - to a toy example and a realistic 14-parameter simulation model of earthworms that is used in environmental risk assessment. A comparison with exact methods and the diagnostic 'coverage test' show that our approach improves estimation of parameter values and their credible intervals for both models. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Fitting Proportional Odds Model to Case-Control data with Incorporating Hardy-Weinberg Equilibrium.
Zhang, Wei; Zhang, Zehui; Li, Xinmin; Li, Qizhai
2015-11-26
Genetic association studies have been proved to be an efficient tool to reveal the aetiology of many human complex diseases and traits. When the phenotype is binary, the logistic regression model is commonly employed to evaluate the association strength of the genetic variants predispose to human diseases because the maximum likelihood estimator of the odds ratio based on case-control data is equivalent to that from the same model by taking the data as being arisen prospectively. This equivalence does not hold for the proportional odds model and using it to analyze the case-control data directly often results in a substantial bias. Through putting a parameter of the minor allele frequency in the modified likelihood function under the condition that the Hardy-Weinberg equilibrium law holds within controls, a consistent estimator is obtained. On the basis of it, we construct a score test statistic to test whether the genetic variant is associated with the diseases. Simulation studies show that the proposed estimator has smaller mean squared error than the existing methods when the genetic effect size is away from zero and the proposed test statistic has a good control of type I error rate and is more powerful than the existing procedures. Application to 45 single nucleotide polymorphisms located in the region of TRAF1-C5 genes for the association with four-level anticyclic citrullinated protein antibody from Genetic Analysis Workshop 16 further demonstrates its performance.
Lepping, R. P.; Wu, C.-C.; Berdichevsky, D. B.; Szabo, A.
2015-01-01
We fitted the parameters of magnetic clouds (MCs) as identified in the Wind spacecraft data from early 2010 to the end of 2012 using the model of Lepping, Jones, and Burlaga (J. Geophys. Res. 95, 1195, 1990). The interval contains 48 MCs and 39 magnetic cloud-like (MCL) events. This work is a continuation of MC model fittings of the earlier Wind sets, including those in a recent publication, which covers 2007 to 2009. This period (2010 - 2012) mainly covers the maximum portion of Solar Cycle 24. Between the previous and current interval, we document 5.7 years of MCs observations. For this interval, the occurrence frequency of MCs markedly increased in the last third of the time. In addition, over approximately the last six years, the MC type (i.e. the profile of the magnetic-field direction within an MC, such as North-to-South, South-to-North, all South) dramatically evolved to mainly North-to-South types when compared to earlier years. Furthermore, this evolution of MC type is consistent with global solar magnetic-field changes predicted by Bothmer and Rust (Coronal Mass Ejections, 139, 1997). Model fit parameters for the MCs are listed for 2010 - 2012. For the 5.7 year interval, the observed MCs are found to be slower, weaker in estimated axial magnetic-field intensity, and shorter in duration than those of the earlier 12.3 years, yielding much lower axial magnetic-field fluxes. For about the first half of this 5.7 year period, i.e. up to the end of 2009, there were very few associated MC-driven shock waves (distinctly fewer than the long-term average of about 50 % of MCs). But since 2010, such driven shocks have increased markedly, reflecting similar statistics as the long-term averages. We estimate that 56 % of the total observed MCs have upstream shocks when the full interval of 1995 - 2012 is considered. However, only 28 % of the total number of MCLs have driven shocks over the same period. Some interplanetary shocks during the 2010 - 2012 interval are seen
Fitness club
2013-01-01
Nordic Walking Classes Come join the Nordic walking classes and outings offered by the CERN Fitness Club starting September 2013. Our licensed instructor Christine offers classes for people who’ve never tried Nordic Walking and who would like to learn the technique, and outings for people who have completed the classes and enjoy going out as a group. Course 1: Tuesdays 12:30 - 13:30 24 September, 1 October, 8 October, 15 October Course 2: Tuesdays 12:30 - 13:30 5 November, 12 November, 19 November, 26 November Outings will take place on Thursdays (12:30 to 13:30) from 12 September 2013. We meet at the CERN Club Barracks car park (close to Entrance A) 10 minutes before departure. Prices: 50 CHF for 4 classes, including the 10 CHF Club membership. Payments made directly to instructor. Renting Poles: Poles can be rented from Christine at 5 CHF / hour. Subscription: Please subscribe at: http://cern.ch/club-fitness Looking forward to seeing you among us! Fitness Club FitnessClub@c...
Fitness Club
2012-01-01
The CERN Fitness Club is pleased to announce its new early morning class which will be taking place on: Tuesdays from 24th April 07:30 to 08:15 216 (Pump Hall, close to entrance C) – Facilities include changing rooms and showers. The Classes: The early morning classes will focus on workouts which will help you build not only strength and stamina, but will also improve your balance, and coordination. Our qualified instructor Germana will accompany you throughout the workout to ensure you stay motivated so you achieve the best results. Sign up and discover the best way to start your working day full of energy! How to subscribe? We invite you along to a FREE trial session, if you enjoy the activity, please sign up via our website: https://espace.cern.ch/club-fitness/Activities/SUBSCRIBE.aspx. * * * * * * * * Saturday 28th April Get in shape for the summer at our fitness workshop and zumba dance party: Fitness workshop with Germana 13:00 to 14:30 - 216 (Pump Hall) Price...
Fitness Club
2012-01-01
Get in Shape for Summer with the CERN Fitness Club Saturday 23 June 2012 from 14:30 to 16.30 (doors open at 14.00) Germana’s Fitness Workshop. Build strength and stamina, sculpt and tone your body and get your heart pumping with Germana’s workout mixture of Cardio Attack, Power Pump, Power Step, Cardio Combat and Cross-Training. Where: 216 (Pump room – equipped with changing rooms and showers). What to wear: comfortable clothes and indoor sports shoes + bring a drink! How much: 15 chf Sign up here: https://espace.cern.ch/club-fitness/Lists/Test_Subscription/NewForm.aspx? Join the Party and dance yourself into shape at Marco + Marials Zumba Masterclass. Saturday 30 June 2012 from 15:00 to 16:30 Marco + Mariel’s Zumba Masterclass Where: 216 (Pump room – equipped with changing rooms and showers). What to wear: comfortable clothes and indoor sports shoes + bring a drink! How much: 25 chf Sign up here: https://espace.cern.ch/club-fitness/Lists/Zumba%20...
Fitness Club
2010-01-01
Nordic Walking Please note that the subscriptions for the general fitness classes from July to December are open: Subscriptions general fitness classes Jul-Dec 2010 Sign-up to the Fitness Club mailing list here Nordic Walking: Sign-up to the Nordic Walking mailing list here Beginners Nordic walking lessons Monday Lunchtimes (rdv 12:20 for 12:30 departure) 13.09/20.09/27.09/04.10 11.10/18.10/08.11/15.11 22.11/29.11/06.12/20.12 Nordic walking lessons Tuesday evenings (rdv 17:50 for 18:00 departure) 07.09/14.09/21.09/28.09 05.10/12.10/19.10/26.10 Intermediate/Advanced Nordic walking outings (follow the nordic walking lessons before signing up for the outings) every Thursday from 16.09 - 16.12, excluding 28.10 and 09.12 Subscriptions and info: fitness.club@cern.ch
Gilkey, Roderick; Kilts, Clint
2007-11-01
Recent neuroscientific research shows that the health of your brain isn't, as experts once thought, just the product of childhood experiences and genetics; it reflects your adult choices and experiences as well. Professors Gilkey and Kilts of Emory University's medical and business schools explain how you can strengthen your brain's anatomy, neural networks, and cognitive abilities, and prevent functions such as memory from deteriorating as you age. The brain's alertness is the result of what the authors call cognitive fitness -a state of optimized ability to reason, remember, learn, plan, and adapt. Certain attitudes, lifestyle choices, and exercises enhance cognitive fitness. Mental workouts are the key. Brain-imaging studies indicate that acquiring expertise in areas as diverse as playing a cello, juggling, speaking a foreign language, and driving a taxicab expands your neural systems and makes them more communicative. In other words, you can alter the physical makeup of your brain by learning new skills. The more cognitively fit you are, the better equipped you are to make decisions, solve problems, and deal with stress and change. Cognitive fitness will help you be more open to new ideas and alternative perspectives. It will give you the capacity to change your behavior and realize your goals. You can delay senescence for years and even enjoy a second career. Drawing from the rapidly expanding body of neuroscience research as well as from well-established research in psychology and other mental health fields, the authors have identified four steps you can take to become cognitively fit: understand how experience makes the brain grow, work hard at play, search for patterns, and seek novelty and innovation. Together these steps capture some of the key opportunities for maintaining an engaged, creative brain.
Moshagen, Morten
2012-01-01
The size of a model has been shown to critically affect the goodness of approximation of the model fit statistic "T" to the asymptotic chi-square distribution in finite samples. It is not clear, however, whether this "model size effect" is a function of the number of manifest variables, the number of free parameters, or both. It is demonstrated by…
Baele, Guy; Van de Peer, Yves; Vansteelandt, Stijn
2011-05-27
Accurate modelling of substitution processes in protein-coding sequences is often hampered by the computational burdens associated with full codon models. Lately, codon partition models have been proposed as a viable alternative, mimicking the substitution behaviour of codon models at a low computational cost. Such codon partition models however impose independent evolution of the different codon positions, which is overly restrictive from a biological point of view. Given that empirical research has provided indications of context-dependent substitution patterns at four-fold degenerate sites, we take those indications into account in this paper. We present so-called context-dependent codon partition models to assess previous empirical claims that the evolution of four-fold degenerate sites is strongly dependent on the composition of its two flanking bases. To this end, we have estimated and compared various existing independent models, codon models, codon partition models and context-dependent codon partition models for the atpB and rbcL genes of the chloroplast genome, which are frequently used in plant systematics. Such context-dependent codon partition models employ a full dependency scheme for four-fold degenerate sites, whilst maintaining the independence assumption for the first and second codon positions. We show that, both in the atpB and rbcL alignments of a collection of land plants, these context-dependent codon partition models significantly improve model fit over existing codon partition models. Using Bayes factors based on thermodynamic integration, we show that in both datasets the same context-dependent codon partition model yields the largest increase in model fit compared to an independent evolutionary model. Context-dependent codon partition models hence perform closer to codon models, which remain the best performing models at a drastically increased computational cost, compared to codon partition models, but remain computationally interesting
STATISTICAL EVALUATION OF FITTING ACCURACY OF GLOBAL AND LOCAL DIGITAL ELEVATION MODELS IN IRAN
Directory of Open Access Journals (Sweden)
F. Alidoost
2013-09-01
Full Text Available Digital Elevation Models (DEMs are one of the most important data for various applications such as hydrological studies, topography mapping and ortho image generation. There are well-known DEMs of the whole world that represent the terrain's surface at variable resolution and they are also freely available for 99% of the globe. However, it is necessary to assess the quality of the global DEMs for the regional scale applications.These models are evaluated by differencing with other reference DEMs or ground control points (GCPs in order to estimate the quality and accuracy parameters over different land cover types. In this paper, a comparison of ASTER GDEM ver2, SRTM DEM with more than 800 reference GCPs and also with a local elevation model over the area of Iran is presented. This study investigates DEM’s characteristics such as systematic error (bias, vertical accuracy and outliers for DEMs using both the usual (Mean error, Root Mean Square Error, Standard Deviation and the robust (Median, Normalized Median Absolute Deviation, Sample Quantiles descriptors. Also, the visual assessment tools are used to illustrate the quality of DEMs, such as normalized histograms and Q-Q plots. The results of the study confirmed that there is a negative elevation bias of approximately 5 meters of GDEM ver2. The measured RMSE and NMAD for elevation differences of GDEM-GCPs are 7.1 m and 3.2 m, respectively, while these values for SRTM and GCPs are 9.0 m and 4.4 m. On the other hand, in comparison with the local DEM, GDEM ver2 exhibits the RMSE of about 6.7 m, a little higher than the RMSE of SRTM (5.1 m.The results of height difference classification and other statistical analysis of GDEM ver2-local DEM and SRTM-local DEM reveal that SRTM is slightly more accurate than GDEM ver2. Accordingly, SRTM has no noticeable bias and shift from Local DEM and they have more consistency to each other, while GDEM ver2 has always a negative bias.
Lee, Tsair-Fwu; Lin, Wei-Chun; Wang, Hung-Yu; Lin, Shu-Yuan; Wu, Li-Fu; Guo, Shih-Sian; Huang, Hsiang-Jui; Ting, Hui-Min; Chao, Pei-Ju
2015-01-01
To develop the logistic and the probit models to analyse electromyographic (EMG) equivalent uniform voltage- (EUV-) response for the tenderness of tennis elbow. In total, 78 hands from 39 subjects were enrolled. In this study, surface EMG (sEMG) signal is obtained by an innovative device with electrodes over forearm region. The analytical endpoint was defined as Visual Analog Score (VAS) 3+ tenderness of tennis elbow. The logistic and the probit diseased probability (DP) models were established for the VAS score and EMG absolute voltage-time histograms (AVTH). TV50 is the threshold equivalent uniform voltage predicting a 50% risk of disease. Twenty-one out of 78 samples (27%) developed VAS 3+ tenderness of tennis elbow reported by the subject and confirmed by the physician. The fitted DP parameters were TV50 = 153.0 mV (CI: 136.3-169.7 mV), γ 50 = 0.84 (CI: 0.78-0.90) and TV50 = 155.6 mV (CI: 138.9-172.4 mV), m = 0.54 (CI: 0.49-0.59) for logistic and probit models, respectively. When the EUV ≥ 153 mV, the DP of the patient is greater than 50% and vice versa. The logistic and the probit models are valuable tools to predict the DP of VAS 3+ tenderness of tennis elbow.
Lin, Wei-Chun; Lin, Shu-Yuan; Wu, Li-Fu; Guo, Shih-Sian; Huang, Hsiang-Jui; Chao, Pei-Ju
2015-01-01
To develop the logistic and the probit models to analyse electromyographic (EMG) equivalent uniform voltage- (EUV-) response for the tenderness of tennis elbow. In total, 78 hands from 39 subjects were enrolled. In this study, surface EMG (sEMG) signal is obtained by an innovative device with electrodes over forearm region. The analytical endpoint was defined as Visual Analog Score (VAS) 3+ tenderness of tennis elbow. The logistic and the probit diseased probability (DP) models were established for the VAS score and EMG absolute voltage-time histograms (AVTH). TV50 is the threshold equivalent uniform voltage predicting a 50% risk of disease. Twenty-one out of 78 samples (27%) developed VAS 3+ tenderness of tennis elbow reported by the subject and confirmed by the physician. The fitted DP parameters were TV50 = 153.0 mV (CI: 136.3–169.7 mV), γ 50 = 0.84 (CI: 0.78–0.90) and TV50 = 155.6 mV (CI: 138.9–172.4 mV), m = 0.54 (CI: 0.49–0.59) for logistic and probit models, respectively. When the EUV ≥ 153 mV, the DP of the patient is greater than 50% and vice versa. The logistic and the probit models are valuable tools to predict the DP of VAS 3+ tenderness of tennis elbow. PMID:26380281
Directory of Open Access Journals (Sweden)
Tsair-Fwu Lee
2015-01-01
Full Text Available To develop the logistic and the probit models to analyse electromyographic (EMG equivalent uniform voltage- (EUV- response for the tenderness of tennis elbow. In total, 78 hands from 39 subjects were enrolled. In this study, surface EMG (sEMG signal is obtained by an innovative device with electrodes over forearm region. The analytical endpoint was defined as Visual Analog Score (VAS 3+ tenderness of tennis elbow. The logistic and the probit diseased probability (DP models were established for the VAS score and EMG absolute voltage-time histograms (AVTH. TV50 is the threshold equivalent uniform voltage predicting a 50% risk of disease. Twenty-one out of 78 samples (27% developed VAS 3+ tenderness of tennis elbow reported by the subject and confirmed by the physician. The fitted DP parameters were TV50 = 153.0 mV (CI: 136.3–169.7 mV, γ50 = 0.84 (CI: 0.78–0.90 and TV50 = 155.6 mV (CI: 138.9–172.4 mV, m = 0.54 (CI: 0.49–0.59 for logistic and probit models, respectively. When the EUV ≥ 153 mV, the DP of the patient is greater than 50% and vice versa. The logistic and the probit models are valuable tools to predict the DP of VAS 3+ tenderness of tennis elbow.
Use of a loudness model for hearing aid fitting. V. On-line gain control in a digital hearing aid.
Launer, Stefan; Moore, Brian C J
2003-07-01
Many researchers have proposed that hearing aids should process sounds so as to restore loudness perception to 'normal'. We describe how a model for predicting loudness for people with cochlear hearing loss can be implemented in a digital hearing aid so as to calculate the frequency-dependent gains that would be required to achieve that goal. It is assumed that the input signal is processed using brief segments or 'frames'. For each frame, the spectrum is calculated, usually via a fast Fourier transform (FFT). From the spectrum, an excitation pattern is calculated for a normal car and for the impaired ear of the patient. The loudness model is then used to calculate the gain required at the centre frequency of each channel in the aid, so as to match the specific loudness in the normal and impaired ears. The whole process is repeated for each successive frame, with overlap of frames and with smoothing of the gain changes across frames. We describe both an 'exact' model, which prescribes a 'curvilinear' compression characteristic at each frequency, and an approximation using 'straight' compression, which is computationally less intensive. Limitations of the present approach are described, and the approach is compared with more traditional approaches using multichannel compression, and with previous approaches using loudness models for fitting hearing aids.
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.
Volkmann, Niels
2012-02-01
A complete understanding of complex dynamic cellular processes such as cell migration or cell adhesion requires the integration of atomic level structural information into the larger cellular context. While direct atomic-level information at the cellular level remains inaccessible, electron microscopy, electron tomography and their associated computational image processing approaches have now matured to a point where sub-cellular structures can be imaged in three dimensions at the nanometer scale. Atomic-resolution information obtained by other means can be combined with this data to obtain three-dimensional models of large macromolecular assemblies in their cellular context. This article summarizes some recent advances in this field. Copyright © 2011 Elsevier Ltd. All rights reserved.
Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.
Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L
2017-02-01
Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.
The conceptual basis of mathematics in cardiology IV: statistics and model fitting.
Bates, Jason H T; Sobel, Burton E
2003-06-01
This is the fourth in a series of four articles developed for the readers of Coronary Artery Disease. Without language ideas cannot be articulated. What may not be so immediately obvious is that they cannot be formulated either. One of the essential languages of cardiology is mathematics. Unfortunately, medical education does not emphasize, and in fact, often neglects empowering physicians to think mathematically. Reference to statistics, conditional probability, multicompartmental modeling, algebra, calculus and transforms is common but often without provision of genuine conceptual understanding. At the University of Vermont College of Medicine, Professor Bates developed a course designed to address these deficiencies. The course covered mathematical principles pertinent to clinical cardiovascular and pulmonary medicine and research. It focused on fundamental concepts to facilitate formulation and grasp of ideas. This series of four articles was developed to make the material available for a wider audience. The articles will be published sequentially in Coronary Artery Disease. Beginning with fundamental axioms and basic algebraic manipulations they address algebra, function and graph theory, real and complex numbers, calculus and differential equations, mathematical modeling, linear system theory and integral transforms and statistical theory. The principles and concepts they address provide the foundation needed for in-depth study of any of these topics. Perhaps of even more importance, they should empower cardiologists and cardiovascular researchers to utilize the language of mathematics in assessing the phenomena of immediate pertinence to diagnosis, pathophysiology and therapeutics. The presentations are interposed with queries (by Coronary Artery Disease abbreviated as CAD) simulating the nature of interactions that occurred during the course itself. Each article concludes with one or more examples illustrating application of the concepts covered to
Modeling the fitness consequences of a cyanophage-encoded photosynthesis gene.
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Jason G Bragg
Full Text Available BACKGROUND: Phages infecting marine picocyanobacteria often carry a psbA gene, which encodes a homolog to the photosynthetic reaction center protein, D1. Host encoded D1 decays during phage infection in the light. Phage encoded D1 may help to maintain photosynthesis during the lytic cycle, which in turn could bolster the production of deoxynucleoside triphosphates (dNTPs for phage genome replication. METHODOLOGY/PRINCIPAL FINDINGS: To explore the consequences to a phage of encoding and expressing psbA, we derive a simple model of infection for a cyanophage/host pair--cyanophage P-SSP7 and Prochlorococcus MED4--for which pertinent laboratory data are available. We first use the model to describe phage genome replication and the kinetics of psbA expression by host and phage. We then examine the contribution of phage psbA expression to phage genome replication under constant low irradiance (25 microE m(-2 s(-1. We predict that while phage psbA expression could lead to an increase in the number of phage genomes produced during a lytic cycle of between 2.5 and 4.5% (depending on parameter values, this advantage can be nearly negated by the cost of psbA in elongating the phage genome. Under higher irradiance conditions that promote D1 degradation, however, phage psbA confers a greater advantage to phage genome replication. CONCLUSIONS/SIGNIFICANCE: These analyses illustrate how psbA may benefit phage in the dynamic ocean surface mixed layer.
Nevin, John A; Craig, Andrew R; Cunningham, Paul J; Podlesnik, Christopher A; Shahan, Timothy A; Sweeney, Mary M
2017-08-01
We review quantitative accounts of behavioral momentum theory (BMT), its application to clinical treatment, and its extension to post-intervention relapse of target behavior. We suggest that its extension can account for relapse using reinstatement and renewal models, but that its application to resurgence is flawed both conceptually and in its failure to account for recent data. We propose that the enhanced persistence of target behavior engendered by alternative reinforcers is limited to their concurrent availability within a distinctive stimulus context. However, a failure to find effects of stimulus-correlated reinforcer rates in a Pavlovian-to-Instrumental Transfer (PIT) paradigm challenges even a straightforward Pavlovian account of alternative reinforcer effects. BMT has been valuable in understanding basic research findings and in guiding clinical applications and accounting for their data, but alternatives are needed that can account more effectively for resurgence while encompassing basic data on resistance to change as well as other forms of relapse. Copyright © 2017 Elsevier B.V. All rights reserved.
Factors associated with suboptimal adherence to antiretroviral therapy in Asia
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Awachana Jiamsakul
2014-05-01
Full Text Available Introduction: Adherence to antiretroviral therapy (ART plays an important role in treatment outcomes. It is crucial to identify factors influencing adherence in order to optimize treatment responses. The aim of this study was to assess the rates of, and factors associated with, suboptimal adherence (SubAdh in the first 24 months of ART in an Asian HIV cohort. Methods: As part of a prospective resistance monitoring study, the TREAT Asia Studies to Evaluate Resistance Monitoring Study (TASER-M collected patients’ adherence based on the World Health Organization-validated Adherence Visual Analogue Scale. SubAdh was defined in two ways: (i 14 days. Time was divided into four intervals: 0–6, 6–12, 12–18 and 18–24 months. Factors associated with SubAdh were analysed using generalized estimating equations. Results: Out of 1316 patients, 32% ever reported 2 assessments per patient per year had an odds ratio (OR=0.7 (95% confidence interval (CI (0.55 to 0.90, p=0.006, compared to sites with ≤2 assessments per patient per year. Compared to heterosexual exposure, SubAdh was higher in injecting drug users (IDUs (OR=1.92, 95% CI (1.23 to 3.00, p=0.004 and lower in homosexual exposure (OR=0.52, 95% CI (0.38 to 0.71, p<0.001. Patients taking a nucleoside transcriptase inhibitor and protease inhibitor (NRTI+PI combination were less likely to report adherence <100% (OR=0.36, 95% CI (0.20 to 0.67, p=0.001 compared to patients taking an NRTI and non-nucleoside transcriptase inhibitor (NRTI+NNRTI combination. SubAdh decreased with increasing time on ART (all p<0.001. Similar associations were found with adherence <95% as the outcome. Conclusions: We found that SubAdh, defined as either <100% and <95%, was associated with mode of HIV exposure, ART regimen, time on ART and frequency of adherence measurement. The more frequently sites assessed patients, the lower the SubAdh, possibly reflecting site resourcing for patient counselling. Although social
Over-the-counter suboptimal dispensing of antibiotics in Uganda
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Mukonzo JK
2013-08-01
: In Uganda, at least four in every ten individuals that visit a health-care facility are treated with an antibiotic. Antibiotics are largely given as over-the-counter drugs at community pharmacies. The number of antibiotic prescribed daily doses/1,000 antibiotic clients does not significantly differ between categories of health-care facilities except at community pharmacies, where lower doses are dispensed compared to other health-care facilities. Keywords: antibiotic, over-the-counter dispensing, suboptimal dosing, Uganda
Factors associated with suboptimal adherence to antiretroviral therapy in Asia
Jiamsakul, Awachana; Kumarasamy, Nagalingeswaran; Ditangco, Rossana; Li, Patrick CK; Phanuphak, Praphan; Sirisanthana, Thira; Sungkanuparph, Somnuek; Kantipong, Pacharee; Lee, Christopher KC; Mustafa, Mahiran; Merati, Tuti; Kamarulzaman, Adeeba; Singtoroj, Thida; Law, Matthew
2014-01-01
Introduction Adherence to antiretroviral therapy (ART) plays an important role in treatment outcomes. It is crucial to identify factors influencing adherence in order to optimize treatment responses. The aim of this study was to assess the rates of, and factors associated with, suboptimal adherence (SubAdh) in the first 24 months of ART in an Asian HIV cohort. Methods As part of a prospective resistance monitoring study, the TREAT Asia Studies to Evaluate Resistance Monitoring Study (TASER-M) collected patients’ adherence based on the World Health Organization-validated Adherence Visual Analogue Scale. SubAdh was defined in two ways: (i) 14 days. Time was divided into four intervals: 0–6, 6–12, 12–18 and 18–24 months. Factors associated with SubAdh were analysed using generalized estimating equations. Results Out of 1316 patients, 32% ever reported 2 assessments per patient per year had an odds ratio (OR)=0.7 (95% confidence interval (CI) (0.55 to 0.90), p=0.006), compared to sites with ≤2 assessments per patient per year. Compared to heterosexual exposure, SubAdh was higher in injecting drug users (IDUs) (OR=1.92, 95% CI (1.23 to 3.00), p=0.004) and lower in homosexual exposure (OR=0.52, 95% CI (0.38 to 0.71), p<0.001). Patients taking a nucleoside transcriptase inhibitor and protease inhibitor (NRTI+PI) combination were less likely to report adherence <100% (OR=0.36, 95% CI (0.20 to 0.67), p=0.001) compared to patients taking an NRTI and non-nucleoside transcriptase inhibitor (NRTI+NNRTI) combination. SubAdh decreased with increasing time on ART (all p<0.001). Similar associations were found with adherence <95% as the outcome. Conclusions We found that SubAdh, defined as either <100% and <95%, was associated with mode of HIV exposure, ART regimen, time on ART and frequency of adherence measurement. The more frequently sites assessed patients, the lower the SubAdh, possibly reflecting site resourcing for patient counselling. Although social
Pereira, Sara; Katzmarzyk, Peter T; Gomes, Thayse Natacha; Souza, Michele; Chaves, Raquel N; Santos, Fernanda K Dos; Santos, Daniel; Hedeker, Donald; Maia, José A R
2017-06-01
Somatotype is a complex trait influenced by different genetic and environmental factors as well as by other covariates whose effects are still unclear. To (1) estimate siblings' resemblance in their general somatotype; (2) identify sib-pair (brother-brother (BB), sister-sister (SS), brother-sister (BS)) similarities in individual somatotype components; (3) examine the degree to which between and within variances differ among sib-ships; and (4) investigate the effects of physical activity (PA) and family socioeconomic status (SES) on these relationships. The sample comprises 1058 Portuguese siblings (538 females) aged 9-20 years. Somatotype was calculated using the Health-Carter method, while PA and SES information was obtained by questionnaire. Multi-level modelling was done in SuperMix software. Older subjects showed the lowest values for endomorphy and mesomorphy, but the highest values for ectomorphy; and more physically active subjects showed the highest values for mesomorphy. In general, the familiality of somatotype was moderate (ρ = 0.35). Same-sex siblings had the strongest resemblance (endomorphy: ρSS > ρBB > ρBS; mesomorphy: ρBB = ρSS > ρBS; ectomorphy: ρBB > ρSS > ρBS). For the ectomorphy and mesomorphy components, BS pairs showed the highest between sib-ship variance, but the lowest within sib-ship variance; while for endomorphy BS showed the lowest between and within sib-ship variances. These results highlight the significant familial effects on somatotype and the complexity of the role of familial resemblance in explaining variance in somatotypes.
Fitness Club
2012-01-01
Nordic Walking Classes Sessions of four classes of one hour each are held on Tuesdays. RDV barracks parking at Entrance A, 10 minutes before class time. Session 1 = 11.09 / 18.09 / 25.09 / 02.10, 18:15 - 19:15 Session 2 = 25.09 / 02.10 / 09.10 / 16.10, 12:30 - 13:30 Session 3 = 23.10 / 30.10 / 06.11 / 13.11, 12:30 - 13:30 Session 4 = 20.11 / 27.11 / 04.12 / 11.12, 12:30 - 13:30 Prices 40 CHF per session + 10 CHF club membership 5 CHF/hour pole rental Check out our schedule and enroll at http://cern.ch/club-fitness Hope to see you among us! fitness.club@cern.ch In spring 2012 there was a long-awaited progress in CERN Fitness club. We have officially opened a Powerlifting @ CERN, and the number of members of the new section has been increasing since then reaching 70+ people in less than 4 months. Powerlifting is a strength sport, which is simple as 1-2-3 and efficient. The "1-2-3" are the three basic lifts (bench press...
Directory of Open Access Journals (Sweden)
Erida Gjini
2016-03-01
Full Text Available The efficacy of vaccines is typically estimated prior to implementation, on the basis of randomized controlled trials. This does not preclude, however, subsequent assessment post-licensure, while mass-immunization and nonlinear transmission feedbacks are in place. In this paper we show how cross-sectional prevalence data post-vaccination can be interpreted in terms of pathogen transmission processes and vaccine parameters, using a dynamic epidemiological model. We advocate the use of such frameworks for model-based vaccine evaluation in the field, fitting trajectories of cross-sectional prevalence of pathogen strains before and after intervention. Using SI and SIS models, we illustrate how prevalence ratios in vaccinated and non-vaccinated hosts depend on true vaccine efficacy, the absolute and relative strength of competition between target and non-target strains, the time post follow-up, and transmission intensity. We argue that a mechanistic approach should be added to vaccine efficacy estimation against multi-type pathogens, because it naturally accounts for inter-strain competition and indirect effects, leading to a robust measure of individual protection per contact. Our study calls for systematic attention to epidemiological feedbacks when interpreting population level impact. At a broader level, our parameter estimation procedure provides a promising proof of principle for a generalizable framework to infer vaccine efficacy post-licensure.
Tsamandouras, Nikolaos; Rostami-Hodjegan, Amin; Aarons, Leon
2015-01-01
Pharmacokinetic models range from being entirely exploratory and empirical, to semi-mechanistic and ultimately complex physiologically based pharmacokinetic (PBPK) models. This choice is conditional on the modelling purpose as well as the amount and quality of the available data. The main advantage of PBPK models is that they can be used to extrapolate outside the studied population and experimental conditions. The trade-off for this advantage is a complex system of differential equations with a considerable number of model parameters. When these parameters cannot be informed from in vitro or in silico experiments they are usually optimized with respect to observed clinical data. Parameter estimation in complex models is a challenging task associated with many methodological issues which are discussed here with specific recommendations. Concepts such as structural and practical identifiability are described with regards to PBPK modelling and the value of experimental design and sensitivity analyses is sketched out. Parameter estimation approaches are discussed, while we also highlight the importance of not neglecting the covariance structure between model parameters and the uncertainty and population variability that is associated with them. Finally the possibility of using model order reduction techniques and minimal semi-mechanistic models that retain the physiological-mechanistic nature only in the parts of the model which are relevant to the desired modelling purpose is emphasized. Careful attention to all the above issues allows us to integrate successfully information from in vitro or in silico experiments together with information deriving from observed clinical data and develop mechanistically sound models with clinical relevance. © 2013 The British Pharmacological Society.
Liu, Zhenqiu; Beach, Jessica A; Agadjanian, Hasmik; Jia, Dongyu; Aspuria, Paul-Joseph; Karlan, Beth Y; Orsulic, Sandra
2015-12-01
Suboptimal cytoreductive surgery in advanced epithelial ovarian cancer (EOC) is associated with poor survival but it is unknown if poor outcome is due to the intrinsic biology of unresectable tumors or insufficient surgical effort resulting in residual tumor-sustaining clones. Our objective was to identify the potential molecular pathway(s) and cell type(s) that may be responsible for suboptimal surgical resection. By comparing gene expression in optimally and suboptimally cytoreduced patients, we identified a gene network associated with suboptimal cytoreduction and explored the biological processes and cell types associated with this gene network. We show that primary tumors from suboptimally cytoreduced patients express molecular signatures that are typically present in a distinct molecular subtype of EOC characterized by increased stromal activation and lymphovascular invasion. Similar molecular pathways are present in EOC metastases, suggesting that primary tumors in suboptimally cytoreduced patients are biologically similar to metastatic tumors. We demonstrate that the suboptimal cytoreduction network genes are enriched in reactive tumor stroma cells rather than malignant tumor cells. Our data suggest that the success of cytoreductive surgery is dictated by tumor biology, such as extensive stromal reaction and increased invasiveness, which may hinder surgical resection and ultimately lead to poor survival. Copyright © 2015. Published by Elsevier Inc.
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Morton Daniel J
2012-06-01
Full Text Available Abstract Background Haemophilus influenzae requires heme for aerobic growth and possesses multiple mechanisms to obtain this essential nutrient. Methods An insertional mutation in tonB was constructed and the impact of the mutation on virulence and fitness in a chinchilla model of otitis media was determined. The tonB insertion mutant strain was significantly impacted in both virulence and fitness as compared to the wildtype strain in this model. Conclusions The tonB gene of H. influenzae is required for the establishment and maintenance of middle ear infection in this chinchilla model of bacterial disease.
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 H...... 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.......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...
Reike, Dennis; Schwarz, Wolf
2016-01-01
The time required to determine the larger of 2 digits decreases with their numerical distance, and, for a given distance, increases with their magnitude (Moyer & Landauer, 1967). One detailed quantitative framework to account for these effects is provided by random walk models. These chronometric models describe how number-related noisy…
Suboptimal care and maternal mortality among foreign-born women in Sweden
DEFF Research Database (Denmark)
Esscher, Annika; Binder-Finnema, Pauline; Bødker, Birgit
2014-01-01
BACKGROUND: Several European countries report differences in risk of maternal mortality between immigrants from low- and middle-income countries and host country women. The present study identified suboptimal factors related to care-seeking, accessibility, and quality of care for maternal deaths...... language and suboptimal interpreter system or usage. Inadequate care occurred more often among the foreign-born (p = 0.04), whereas delays in consultation/referral and miscommunication between health care providers where equally common between the two groups. CONCLUSIONS: Suboptimal care factors, major...
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Colebunders Robert
2011-02-01
Full Text Available Abstract Background Antiretroviral therapy (ART partially corrects immune dysfunction associated with HIV infection. The levels of T-cell immune activation and exhaustion after long-term, suppressive ART and their correlation with CD4 T-cell count reconstitution among ART-treated patients in African cohorts have not been extensively evaluated. Methods T-cell activation (CD38+HLA-DR+ and immune exhaustion (PD-1+ were measured in a prospective cohort of patients initiated on ART; 128 patient samples were evaluated and subcategorized by CD4 reconstitution after long-term suppressive treatment: Suboptimal [median CD4 count increase 129 (-43-199 cells/μl], N = 34 ], optimal [282 (200-415 cells/μl, N = 64] and super-optimal [528 (416-878 cells/μl, N = 30]. Results Both CD4+ and CD8 T-cell activation was significantly higher among suboptimal CD4 T-cell responders compared to super-optimal responders. In a multivariate model, CD4+CD38+HLADR+ T-cells were associated with suboptimal CD4 reconstitution [AOR, 5.7 (95% CI, 1.4-23, P = 0.014]. T-cell exhaustion (CD4+PD1+ and CD8+PD1+ was higher among suboptimal relative to optimal (P P = 0.022]. Conclusion T-cell activation and exhaustion persist among HIV-infected patients despite long-term, sustained HIV-RNA viral suppression. These immune abnormalities were associated with suboptimal CD4 reconstitution and their regulation may modify immune recovery among suboptimal responders to ART.
Fitness club
2013-01-01
Nordic Walking Classes New session of 4 classes of 1 hour each will be held on Tuesdays in May 2013. Meet at the CERN barracks parking at Entrance A, 10 minutes before class time. Dates and time: 07.05, 14.05, 21.05 and 28.05, fom 12 h 30 to 13 h 30 Prices: 40 CHF per session + 10 CHF club membership – 5 CHF / hour pole rental Check out our schedule and enroll at http://cern.ch/club-fitness Hope to see you among us!
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Shidrokh Goudarzi
2015-01-01
Full Text Available The vertical handover mechanism is an essential issue in the heterogeneous wireless environments where selection of an efficient network that provides seamless connectivity involves complex scenarios. This study uses two modules that utilize the particle swarm optimization (PSO algorithm to predict and make an intelligent vertical handover decision. In this paper, we predict the received signal strength indicator parameter using the curve fitting based particle swarm optimization (CF-PSO and the RBF neural networks. The results of the proposed methodology compare the predictive capabilities in terms of coefficient determination (R2 and mean square error (MSE based on the validation dataset. The results show that the effect of the model based on the CF-PSO is better than that of the model based on the RBF neural network in predicting the received signal strength indicator situation. In addition, we present a novel network selection algorithm to select the best candidate access point among the various access technologies based on the PSO. Simulation results indicate that using CF-PSO algorithm can decrease the number of unnecessary handovers and prevent the “Ping-Pong” effect. Moreover, it is demonstrated that the multiobjective particle swarm optimization based method finds an optimal network selection in a heterogeneous wireless environment.
Chu, A.
2016-12-01
Modern earthquake catalogs are often analyzed using spatial-temporal point process models such as the epidemic-type aftershock sequence (ETAS) models of Ogata (1998). My work implements three of the homogeneous ETAS models described in Ogata (1998). With a model's log-likelihood function, my software finds the Maximum-Likelihood Estimates (MLEs) of the model's parameters to estimate the homogeneous background rate and the temporal and spatial parameters that govern triggering effects. EM-algorithm is employed for its advantages of stability and robustness (Veen and Schoenberg, 2008). My work also presents comparisons among the three models in robustness, convergence speed, and implementations from theory to computing practice. Up-to-date regional seismic data of seismic active areas such as Southern California and Japan are used to demonstrate the comparisons. Data analysis has been done using computer languages Java and R. Java has the advantages of being strong-typed and easiness of controlling memory resources, while R has the advantages of having numerous available functions in statistical computing. Comparisons are also made between the two programming languages in convergence and stability, computational speed, and easiness of implementation. Issues that may affect convergence such as spatial shapes are discussed.
Veinot, Tiffany C; Senteio, Charles R; Hanauer, David; Lowery, Julie C
2017-09-02
To describe a new, comprehensive process model of clinical information interaction in primary care (Clinical Information Interaction Model, or CIIM) based on a systematic synthesis of published research. We used the "best fit" framework synthesis approach. Searches were performed in PubMed, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Library and Information Science Abstracts, Library, Information Science and Technology Abstracts, and Engineering Village. Two authors reviewed articles according to inclusion and exclusion criteria. Data abstraction and content analysis of 443 published papers were used to create a model in which every element was supported by empirical research. The CIIM documents how primary care clinicians interact with information as they make point-of-care clinical decisions. The model highlights 3 major process components: (1) context, (2) activity (usual and contingent), and (3) influence. Usual activities include information processing, source-user interaction, information evaluation, selection of information, information use, clinical reasoning, and clinical decisions. Clinician characteristics, patient behaviors, and other professionals influence the process. The CIIM depicts the complete process of information interaction, enabling a grasp of relationships previously difficult to discern. The CIIM suggests potentially helpful functionality for clinical decision support systems (CDSSs) to support primary care, including a greater focus on information processing and use. The CIIM also documents the role of influence in clinical information interaction; influencers may affect the success of CDSS implementations. The CIIM offers a new framework for achieving CDSS workflow integration and new directions for CDSS design that can support the work of diverse primary care clinicians.
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James Tsai
2017-06-01
In conclusion, among adult ever users of marijuana, current tobacco use is high and strongly associated with suboptimal SRH; regular marijuana smoking with or without current tobacco use is significantly associated with suboptimal SRH.
Espinosa, José R; Sanz, Verónica; Trott, Michael
2012-01-01
We perform a global fit to Higgs signal-strength data in the context of light stops in Natural SUSY. In this case, the Wilson coefficients of the higher dimensional operators mediating g g -> h and h -> \\gamma \\gamma, given by c_g, c_\\gamma, are related by c_g = 3 (1 + 3 \\alpha_s/(2 \\pi)) c_\\gamma/8. We examine this predictive scenario in detail, combining Higgs signal-strength constraints with recent precision measurements of m_W, b-> s \\gamma constraints and direct collider bounds on weak scale SUSY, finding regions of parameter space that are consistent with all of these constraints. However it is challenging for the allowed parameter space to reproduce the observed Higgs mass value with sub-TeV stops. We discuss some of the direct stop discovery prospects and show how global Higgs fits can be used to exclude light stop parameter space difficult to probe by direct collider searches. We determine the current status of such indirect exclusions and estimate their reach by the end of the 8 TeV LHC run.
Dawis, Rene V.; Gati, Itamar; Hesketh, Beryl; Prediger, Dale J.; Rounds, James; McKenna, Molly C.; Hubert, Lawrence; Day, Susan X.; Tracey, Terence J. G.; Darcy, Maria; Kovalski, Theresa M.
2000-01-01
Includes "P-E [Person-Environment] Fit as Paradigm" (Dawis); "Pitfalls of Congruence Research" (Gati); "The Next Millennium of 'Fit' Research" (Hesketh); "Holland's Hexagon Is Alive and Well--Though Somewhat out of Shape" (Prediger); "Tinsley on Holland: A Misshapen Argument" (Rounds, McKenna,…
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
State-space models (SSM) are often used for analyzing complex ecological processes that are not observed directly, such as marine animal movement. When outliers are present in the measurements, special care is needed in the analysis to obtain reliable location and process estimates. Here we...
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Lemieux Sébastien
2006-08-01
Full Text Available Abstract Background The identification of differentially expressed genes (DEGs from Affymetrix GeneChips arrays is currently done by first computing expression levels from the low-level probe intensities, then deriving significance by comparing these expression levels between conditions. The proposed PL-LM (Probe-Level Linear Model method implements a linear model applied on the probe-level data to directly estimate the treatment effect. A finite mixture of Gaussian components is then used to identify DEGs using the coefficients estimated by the linear model. This approach can readily be applied to experimental design with or without replication. Results On a wholly defined dataset, the PL-LM method was able to identify 75% of the differentially expressed genes within 10% of false positives. This accuracy was achieved both using the three replicates per conditions available in the dataset and using only one replicate per condition. Conclusion The method achieves, on this dataset, a higher accuracy than the best set of tools identified by the authors of the dataset, and does so using only one replicate per condition.
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 ρ1 ; (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. A
Alston, D. W.
1981-01-01
The considered research had the objective to design a statistical model that could perform an error analysis of curve fits of wind tunnel test data using analysis of variance and regression analysis techniques. Four related subproblems were defined, and by solving each of these a solution to the general research problem was obtained. The capabilities of the evolved true statistical model are considered. The least squares fit is used to determine the nature of the force, moment, and pressure data. The order of the curve fit is increased in order to delete the quadratic effect in the residuals. The analysis of variance is used to determine the magnitude and effect of the error factor associated with the experimental data.
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Eric eBoyd
2012-06-01
Full Text Available The extent to which geochemical variation constrains the distribution of phototrophic metabolisms was modeled based on 439 observations in geothermal springs in Yellowstone National Park (YNP, Wyoming. Generalized additive models (GAMs were developed to predict the distribution of photosynthesis as a function of spring temperature, pH, and total sulfide. GAMs comprised of temperature explained 42.7% of the variation in the distribution of phototrophic metabolisms whereas GAMs comprised of sulfide and pH explained 20.7% and 11.7% of the variation, respectively. These results suggest that of the measured variables, temperature is the primary constraint on the distribution of phototrophic metabolism in YNP. GAMs comprised of multiple variables explained a larger percentage of the variation in the distribution of phototrophic metabolism, indicating additive interactions among variables. A GAM that combined temperature and sulfide explained the greatest variation in the dataset (54.8% while minimizing the introduction of degrees of freedom. In an effort to verify the extent to which phototroph distribution reflects constraints on activity, we examined the influence of sulfide and temperature on dissolved inorganic carbon (DIC uptake rates under both light and dark conditions. Light-driven DIC uptake decreased systematically with increasing concentrations of sulfide in acidic, algal-dominated systems, but was unaffected in alkaline, bacterial-dominated systems. In both alkaline and acidic systems, light-driven DIC uptake was suppressed in cultures incubated at temperatures 10°C greater than their in situ temperature. Collectively, these results suggest that the habitat range of phototrophs in YNP springs, specifically that of cyanobacteria and algae, largely results from constraints imposed by temperature and sulfide on the activity and fitness of these populations, a finding that is consistent with the predictions from GAMs.
Lewandowski, Damian; Dubińska-Magiera, Magda; Posyniak, Ewelina; Rupik, Weronika; Daczewska, Małgorzata
2017-07-01
In the grass snake (Natrix natrix), the newly developed somites form vesicles that are located on both sides of the neural tube. The walls of the vesicles are composed of tightly connected epithelial cells surrounding the cavity (the somitocoel). Also, in the newly formed somites, the Pax3 protein can be observed in the somite wall cells. Subsequently, the somite splits into three compartments: the sclerotome, dermomyotome (with the dorsomedial [DM] and the ventrolateral [VL] lips) and the myotome. At this stage, the Pax3 protein is detected in both the DM and VL lips of the dermomyotome and in the mononucleated cells of the myotome, whereas the Pax7 protein is observed in the medial part of the dermomyotome and in some of the mononucleated cells of the myotome. The mononucleated cells then become elongated and form myotubes. As myogenesis proceeds, the myotome is filled with multinucleated myotubes accompanied by mononucleated, Pax7-positive cells (satellite cells) that are involved in muscle growth. The Pax3-positive progenitor muscle cells are no longer observed. Moreover, we have observed unique features in the differentiation of the muscles in these snakes. Specifically, our studies have revealed the presence of two classes of muscles in the myotomes. The first class is characterised by fast muscle fibres, with myofibrils equally distributed throughout the sarcoplasm. In the second class, composed of slow muscle fibres, the sarcoplasm is filled with lipid droplets. We assume that their storage could play a crucial role during hibernation in the adult snakes. We suggest that the model of myotomal myogenesis in reptiles, birds and mammals shows the same morphological and molecular character. We therefore believe that the grass snake, in spite of the unique features of its myogenesis, fits into the amniotes-specific model of trunk muscle development.
Rumi, Alejandra; Gregoric, Diego E Gutiérrez; Roche, M Andrea
2007-06-01
The genus Drepanotrema includes six species in Argentina. The life cycle in natural systems of Drepanotrema depressissimum, and D. lucidum has been little studied, except for some casual observations. The aim of this study is to analyze main population trends (age structures, recruitment periods, life span and curves of individual growth) in Paiva pond, Argentina. We explored growth model fitting and comparison methodologies between species and environments in Paiva pond and Isla Martin Garcia (IMG), to determine interspecific patterns. Theoretical curves of von Bertalanffy's model for each population were contrasted with samplings using the chi2 test. Expected sizes were transformed into a percentage of maximum size and cohorts started from zero time, which allowed them to be independent of the real or estimated starting date and a comparison was possible. A similar time scale was used, because the k values proved to be sensitive to time scale. Maximum size reached by D. lucidum was 6.9 mm and by D. depressissimum 9.38 mm. Growth rates (k) fluctuated from 1.302 to 1.368 in the first and 1.339 to 1.509 in the second species. No statistically significant differences were found in growth curves among species inhabiting the Paiva pond and in the different IMG water bodies independent of the beginning of each cohort and maximum size. In general, no winter cohorts were observed, except in one population of D. kermatoides (IMG). Comparing circannual and biannual growth rhythms most of the species reached 60 % of their development during their first year, and 85 % or more during their second year.
Motor planning under temporal uncertainty is suboptimal when the gain function is asymmetric.
Ota, Keiji; Shinya, Masahiro; Kudo, Kazutoshi
2015-01-01
For optimal action planning, the gain/loss associated with actions and the variability in motor output should both be considered. A number of studies make conflicting claims about the optimality of human action planning but cannot be reconciled due to their use of different movements and gain/loss functions. The disagreement is possibly because of differences in the experimental design and differences in the energetic cost of participant motor effort. We used a coincident timing task, which requires decision making with constant energetic cost, to test the optimality of participant's timing strategies under four configurations of the gain function. We compared participant strategies to an optimal timing strategy calculated from a Bayesian model that maximizes the expected gain. We found suboptimal timing strategies under two configurations of the gain function characterized by asymmetry, in which higher gain is associated with higher risk of zero gain. Participants showed a risk-seeking strategy by responding closer than optimal to the time of onset/offset of zero gain. Meanwhile, there was good agreement of the model with actual performance under two configurations of the gain function characterized by symmetry. Our findings show that human ability to make decisions that must reflect uncertainty in one's own motor output has limits that depend on the configuration of the gain function.
Motor planning under temporal uncertainty is suboptimal when the gain function is asymmetric
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Keiji eOta
2015-07-01
Full Text Available For optimal action planning, the gain/loss associated with actions and the variability in motor output should both be considered. A number of studies make conflicting claims about the optimality of human action planning but cannot be reconciled due to their use of different movements and gain/loss functions. The disagreement is possibly because of differences in the experimental design and differences in the energetic cost of participant motor effort. We used a coincident timing task, which requires decision making with constant energetic cost, to test the optimality of participant’s timing strategies under four configurations of the gain function. We compared participant strategies to an optimal timing strategy calculated from a Bayesian model that maximizes the expected gain. We found suboptimal timing strategies under two configurations of the gain function characterized by asymmetry, in which higher gain is associated with higher risk of zero gain. Participants showed a risk-seeking strategy by responding closer than optimal to the time of onset/offset of zero gain. Meanwhile, there was good agreement of the model with actual performance under two configurations of the gain function characterized by symmetry. Our findings show that human ability to make decisions that must reflect uncertainty in one’s own motor output has limits that depend on the configuration of the gain function.
Tang, Chuanning; Lew, Scott; He, Dacheng
2016-04-01
In vitro protein stability studies are commonly conducted via thermal or chemical denaturation/renaturation of protein. Conventional data analyses on the protein unfolding/(re)folding require well-defined pre- and post-transition baselines to evaluate Gibbs free-energy change associated with the protein unfolding/(re)folding. This evaluation becomes problematic when there is insufficient data for determining the pre- or post-transition baselines. In this study, fitting on such partial data obtained in protein chemical denaturation is established by introducing second-order differential (SOD) analysis to overcome the limitations that the conventional fitting method has. By reducing numbers of the baseline-related fitting parameters, the SOD analysis can successfully fit incomplete chemical denaturation data sets with high agreement to the conventional evaluation on the equivalent completed data, where the conventional fitting fails in analyzing them. This SOD fitting for the abbreviated isothermal chemical denaturation further fulfills data analysis methods on the insufficient data sets conducted in the two prevalent protein stability studies. © 2016 The Protein Society.
Tang, Chuanning; Lew, Scott
2016-01-01
Abstract In vitro protein stability studies are commonly conducted via thermal or chemical denaturation/renaturation of protein. Conventional data analyses on the protein unfolding/(re)folding require well‐defined pre‐ and post‐transition baselines to evaluate Gibbs free‐energy change associated with the protein unfolding/(re)folding. This evaluation becomes problematic when there is insufficient data for determining the pre‐ or post‐transition baselines. In this study, fitting on such partial data obtained in protein chemical denaturation is established by introducing second‐order differential (SOD) analysis to overcome the limitations that the conventional fitting method has. By reducing numbers of the baseline‐related fitting parameters, the SOD analysis can successfully fit incomplete chemical denaturation data sets with high agreement to the conventional evaluation on the equivalent completed data, where the conventional fitting fails in analyzing them. This SOD fitting for the abbreviated isothermal chemical denaturation further fulfills data analysis methods on the insufficient data sets conducted in the two prevalent protein stability studies. PMID:26757366
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Nele Goeyvaerts
2015-12-01
Full Text Available Dynamic transmission models are essential to design and evaluate control strategies for airborne infections. Our objective was to develop a dynamic transmission model for seasonal influenza allowing to evaluate the impact of vaccinating specific age groups on the incidence of infection, disease and mortality. Projections based on such models heavily rely on assumed ‘input’ parameter values. In previous seasonal influenza models, these parameter values were commonly chosen ad hoc, ignoring between-season variability and without formal model validation or sensitivity analyses. We propose to directly estimate the parameters by fitting the model to age-specific influenza-like illness (ILI incidence data over multiple influenza seasons. We used a weighted least squares (WLS criterion to assess model fit and applied our method to Belgian ILI data over six influenza seasons. After exploring parameter importance using symbolic regression, we evaluated a set of candidate models of differing complexity according to the number of season-specific parameters. The transmission parameters (average R0, seasonal amplitude and timing of the seasonal peak, waning rates and the scale factor used for WLS optimization, influenced the fit to the observed ILI incidence the most. Our results demonstrate the importance of between-season variability in influenza transmission and our estimates are in line with the classification of influenza seasons according to intensity and vaccine matching.
Black, Ryan A.; Butler, Stephen F.
2012-01-01
Although Rasch models have been shown to be a sound methodological approach to develop and validate measures of psychological constructs for more than 50 years, they remain underutilized in psychology and other social sciences. Until recently, one reason for this underutilization was the lack of syntactically simple procedures to fit Rasch and…
Lichtenberg, James W.; Hummel, Thomas J.
This investigation tested the hypothesis that the probabilistic structure underlying psychotherapy interviews is Markovian. The "goodness of fit" of a first-order Markov chain model to actual therapy interviews was assessed using a x squared test of homogeneity, and by generating by Monte Carlo methods empirical sampling distributions of…
Middelkamp, P.J.C.; Rooijen, M. van; Wolfhagen, P.; Steenbergen, B.
2017-01-01
The transtheoretical model of behavior change (TTM) is often used to understand changes in health-related behavior, like exercise. Exercise behavior in fitness clubs is an understudied topic, but preliminary studies showed low frequencies and large numbers of drop-out. An initial 12-week
Lightning: SED Fitting Package
Eufrasio, Rafael T.
2017-11-01
Lightning is a spectral energy distribution (SED) fitting procedure that quickly and reliably recovers star formation history (SFH) and extinction parameters. The SFH is modeled as discrete steps in time. The code consists of a fully vectorized inversion algorithm to determine SFH step intensities and combines this with a grid-based approach to determine three extinction parameters.
Behrendt, J. C.; Finn, C. A.; Blankenship, D. D.
2006-12-01
Aeromagnetic and marine magnetic surveys over the volcanically active West Antarctic rift system, constrained by seismic reflection profiles over the Ross Sea continual shelf, and radar ice sounding surveys over the West Antarctic Ice Sheet (WAIS) allowed calculation of models fit to very high-amplitude anomalies. We present several examples: exposed 2700-m high, subaerial erupted volcano Mt Melbourne; the 750-m high source of anomaly D (Hamilton submarine volcano) in the Ross sea; and the 600-m high edifice of Mt. CASERTZ beneath the WAIS. The character of these anomalies and their sources varies greatly, and is inferred to be the result of subaerial, submarine and subglacial emplacement respectively. Mt. Melbourne erupted through the WAIS at a time when it was grounded over the Ross Sea continental shelf. Highly magnetic volcanic flows inferred to have high remanent (normal) magnetization in the present field direction produce the 600-nT positive anomaly. The flows protected the edifice above the ice from erosion. Negligible amounts of probably subglacially erupted, apparently non-magnetic hyaloclastite exist in association with Mt. Melbourne. Mt. CASERTZ is nonmagnetic and the edifice is interpreted as consisting of a transient mound of unconsolidated hyaloclastite injected into the WAIS. However Mt. CASERTZ, about 8-km diameter, overlies a 200-m high, 40-km wide highly magnetic residual edifice modeled as the top of the source (an active subglacial volcano) of a 400-nT high positive anomaly. Any former edifices comprising hyaloclastite, pillow breccia or other volcanic debris injected into the moving WAIS apparently have been removed. About 400 other high- amplitude anomalies associated with low relief (80 percent less than 200 m) edifices at the base of the ice (the tops of the sources of these steep gradient anomalies) beneath the WAIS defined by radar ice sounding have been interpreted as having former hyaloclastite edifices, which were removed by the moving
Suboptimal asthma care for immigrant children: results of an audit study
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Klazinga Niek S
2008-01-01
Full Text Available Abstract Background Little is known on the scope and nature of ethnic inequalities in suboptimal asthma care for children. This study aimed to assess (1 ethnic differences in suboptimal asthma care for children with an asthma exacerbation who consulted a physician, and (2 ethnic differences in the nature of suboptimal care. Methods All children aged 6–16 years who during a period of six months consulted the paediatric department of the Academic Medical Centre-University of Amsterdam or one of the six regional primary care centres with an asthma exacerbation were included. Clinical guidelines were systematically converted to review criteria following the strategy as proposed by the Agency for Health Care Policy and Research. Based upon these review criteria and their experience experts of two multidisciplinary panels retrospectively assessed the quality of care and its (possible failure to prevent the occurrence of asthma exacerbation. Results Only a small number of children (n = 35 were included in the analysis as a result of which the ethnic differences in suboptimal care were not significant. However, the results do indicate immigrant children, in particular 'other non-Western' children (n = 11, more frequently to receive suboptimal care related to the asthma exacerbation when compared to ethnic Dutch children. Furthermore, we found the nature of suboptimal care to differ with under-prescribing in the 'other non-Western' group (n = 11, lack of information exchange between physicians in the Surinamese/Antillean group (n = 12 and lack of education, and counselling of patients and parents in the ethnic Dutch (n = 12 as the most relevant factor. Conclusion Ethnic inequalities in the scope and nature of suboptimal asthma care for children in the Netherlands seem to exist. For the non-western immigrant groups the results indicate the importance of the prescription behaviour of the medical doctor, as well as the supervision by one health care
Directory of Open Access Journals (Sweden)
Di Pierro F
2012-07-01
Full Text Available Francesco Di Pierro,1 Nicola Villanova,2 Federica Agostini,2 Rebecca Marzocchi,2 Valentina Soverini,2 Giulio Marchesini21Scientific Department, Velleja Research, Milano, 2Diseases of Metabolism, S Orsola Malpighi Hospital, Bologna, ItalyBackground: Suboptimal glycemic control is a common situation in diabetes, regardless of the wide range of drugs available to reach glycemic targets. Basic research in diabetes is endeavoring to identify new actives working as insulin savers, use of which could delay the introduction of injectable insulin or reduce the insulin dose needed. Commonly available as a nutraceutical, berberine is a potential candidate.Methods and results: Because its low oral bioavailability can be overcome by P-glycoprotein inhibitors like herbal polyphenols, we have tested the nutraceutical combination of Berberis aristata extract and Silybum marianum extract (Berberol® in type 2 diabetes in terms of its additive effect when combined with a conventional oral regimen for patients with suboptimal glycemic control. After 90 days of treatment, the nutraceutical association had a positive effect on glycemic and lipid parameters, significantly reducing glycosylated hemoglobin, basal insulin, homeostatic model assessment of insulin resistance, total and low-density lipoprotein cholesterol, and triglycerides. A relevant effect was also observed in terms of liver function by measuring aspartate transaminase and alanine transaminase. The product had a good safety profile, with distinctive gastrointestinal side effects likely due to its acarbose-like action.Conclusion: Although further studies should be carried out to confirm our data, Berberol could be considered a good candidate as an adjunctive treatment option in diabetes, especially in patients with suboptimal glycemic control.Keywords: berberine, silymarin, glycosylated hemoglobin, diabetes
One size does not fit all: a diagnostic post-occupancy evaluation model for an emergency department.
Guinther, Lindsey; Carll-White, Allison; Real, Kevin
2014-01-01
This study presents a detailed account of processes and multiple methodologies used in conducting a diagnostic post-occupancy evaluation (POE) in an urban hospital emergency department. Healthcare design POE research findings can lead to improved work environments for healthcare providers and higher levels of staff, patient, and visitor satisfaction. This evaluation was conducted in two separate phases over 12 months, with data analysis occurring after each phase. Phase 1 involved 200 hours of observation, physical measurements, and occupancy counts. Phase 2 included surveys (n = 315) of staff, visitors, and patients. In addition, eight distinct staff focus groups (e.g., Nursing, Housekeeping, Physician, etc.) were conducted. To illustrate the process, one healthcare design-related issue, privacy and confidentiality, was assessed in light of the linear design model with a central core. Phase 1 observation results indicated that most confidential conversations were contained within the linear core. However, Phase 2 focus groups revealed that many staff members had concerns regarding the level of privacy and confidentiality due to the core's open design. The use of multiple methods provided greater information and a more comprehensive picture of the emergency department environment and design. This study presents a comprehensive framework for diagnostic post-occupancy evaluation in healthcare design. The findings indicate that a systematic, multi-methodological approach developed around a conceptual framework can lead to higher quality evaluations. Diagnostic POEs should be grounded in extant literature and customized based on the setting, the client's guiding principles, and the design team's objectives. In diagnostic POEs, one size does not fit all. Case study, design process, interdisciplinary, post-occupancy, privacy and confidentiality.
Is a 'one size fits all' taphonomic model appropriate for the Mazon Creek Lagerstätte?
Clements, Thomas; Purnell, Mark; Gabbott, Sarah
2017-04-01
The Late Carboniferous Mazon Creek Lagerstätte (Illinois, USA) is a world renowned fossil deposit with a huge diversity of preserved flora and fauna. It is widely considered to represent the most complete Late Carboniferous river delta ecosystem because researchers have identified that the deposit preserves organisms from multiple habitats including coastal swamps, brackish lagoons and oceanic environments. Often these fossils have exquisite soft tissue preservation yielding far more information that the 'normal' skeletal fossil record, while some soft bodied animals, such as the notorious Tully Monster (Tullimonstrum gregarium), are only known from this locality. However, constraining a 'one-size fits all' taphonomic model for the Mazon Creek is difficult because of our poor understanding of sideritic concretionary formation or preservation (i.e. the presence of large numbers of unfossiliferous concretions), the large geographical area, the influences of fresh, brackish and saline waters during burial and the subsequent complicated diagenetic processes. To determine the preservational pathways of Mazon Creek fossils, we have compiled data of the mode of preservation of morphological characters for all major groups of fossil organisms found in this Lagerstätte. This data can be used to test for variance in mode of preservation between taxa and also between specific tissue types. Furthermore, experimental decay data is used to constrain the impact of decay prior to fossilisation. Our analysis indicates that there are variations in preservation potential of specific characters shared by taxa. Modes of preservation, however, seem to be consistent across the majority of taxa dependant on locality. This quantitative approach is being utilised as part of a larger ongoing investigation which combines taphonomy with geochemical analysis of siderite concretions from across the vast geographical area of the Mazon Creek. Together this approach will allow us to elucidate the
Yan, Yu-Xiang; Liu, You-Qin; Li, Man; Hu, Pei-Feng; Guo, Ai-Min; Yang, Xing-Hua; Qiu, Jing-Jun; Yang, Shan-Shan; Shen, Jian; Zhang, Li-Ping; Wang, Wei
2009-01-01
Suboptimal health status (SHS) is characterized by ambiguous health complaints, general weakness, and lack of vitality, and has become a new public health challenge in China. It is believed to be a subclinical, reversible stage of chronic disease. Studies of intervention and prognosis for SHS are expected to become increasingly important. Consequently, a reliable and valid instrument to assess SHS is essential. We developed and evaluated a questionnaire for measuring SHS in urban Chinese. Focus group discussions and a literature review provided the basis for the development of the questionnaire. Questionnaire validity and reliability were evaluated in a small pilot study and in a larger cross-sectional study of 3000 individuals. Analyses included tests for reliability and internal consistency, exploratory and confirmatory factor analysis, and tests for discriminative ability and convergent validity. The final questionnaire included 25 items on SHS (SHSQ-25), and encompassed 5 subscales: fatigue, the cardiovascular system, the digestive tract, the immune system, and mental status. Overall, 2799 of 3000 participants completed the questionnaire (93.3%). Test-retest reliability coefficients of individual items ranged from 0.89 to 0.98. Item-subscale correlations ranged from 0.51 to 0.72, and Cronbach's alpha was 0.70 or higher for all subscales. Factor analysis established 5 distinct domains, as conceptualized in our model. One-way ANOVA showed statistically significant differences in scale scores between 3 occupation groups; these included total scores and subscores (Purban Chinese.
Herring, Bradley
2010-04-01
Many preventive healthcare procedures are widely recognized as cost-effective but have relatively low utilization rates in the US. Because preventive care is a present-period investment with a future-period expected financial return, enrollee turnover among private insurers lowers the expected return of this investment. In this paper, I present a simple theoretical model to illustrate the suboptimal provision of preventive healthcare that results from insurers 'free riding' off of the provision from others. I also provide an empirical test of this hypothesis using data from the Community Tracking Study's Household Survey. I use lagged market-level measures of employment-induced insurer turnover to identify variation in insurers' expectations and test for the effect of turnover on several different measures of medical utilization. As expected, I find that turnover has a significantly negative effect on the utilization of preventive services and has no effect on the utilization of acute services used as a control. Copyright (c) 2009 John Wiley & Sons, Ltd.
Unar-Munguía, Mishel; Meza, Rafael; Colchero, M Arantxa; Torres-Mejía, Gabriela; de Cosío, Teresita Gonzalez
2017-10-05
Exclusive breastfeeding and longer breastfeeding reduce women's breast cancer risk but Mexico has one of the lowest breastfeeding rates worldwide. We estimated the lifetime economic and disease burden of breast cancer in Mexico if 95% of parous women breastfeed each child exclusively for 6 months and continue breastfeeding for over a year. We used a static microsimulation model with a cost-of-illness approach to simulate a cohort of Mexican women. We estimated breast cancer incidence, premature mortality, disability-adjusted life years (DALYs), medical costs, and income losses due to breast cancer and extrapolated the results to 1.116 million Mexican women of age 15 in 2012. Costs were expressed in 2015 US dollars and discounted at a 3% annual rate. We estimated that 2,186 premature deaths (95% CI 2,123-2,248), 9,936 breast cancer cases (95% CI 9,651-10,220), 45,109 DALYs (95% CI 43,000-47,217), and $245 million USD (95% CI 234-256) in medical costs and income losses owing to breast cancer could be saved over a cohort's lifetime. Medical costs account for 80% of the economic burden; income losses and opportunity costs for caregivers account for 15 and 5%, respectively. In Mexico, the burden of breast cancer due to suboptimal breastfeeding in women is high in terms of morbidity, premature mortality, and the economic costs for the health sector and society.
Bai, Yu; Katahira, Kentaro; Ohira, Hideki
2014-01-01
Humans are capable of correcting their actions based on actions performed in the past, and this ability enables them to adapt to a changing environment. The computational field of reinforcement learning (RL) has provided a powerful explanation for understanding such processes. Recently, the dual learning system, modeled as a hybrid model that incorporates value update based on reward-prediction error and learning rate modulation based on the surprise signal, has gained attention as a model for explaining various neural signals. However, the functional significance of the hybrid model has not been established. In the present study, we used computer simulation in a reversal learning task to address functional significance in a probabilistic reversal learning task. The hybrid model was found to perform better than the standard RL model in a large parameter setting. These results suggest that the hybrid model is more robust against the mistuning of parameters compared with the standard RL model when decision-makers continue to learn stimulus-reward contingencies, which can create abrupt changes. The parameter fitting results also indicated that the hybrid model fit better than the standard RL model for more than 50% of the participants, which suggests that the hybrid model has more explanatory power for the behavioral data than the standard RL model.
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Yu eBai
2014-08-01
Full Text Available Humans are capable of correcting their actions based on actions performed in the past, and this ability enables them to adapt to a changing environment. The computational field of reinforcement learning (RL has provided a powerful explanation for understanding such processes. Recently, the dual learning system, modeled as a hybrid model that incorporates value update based on reward-prediction error and learning rate modulation based on the surprise signal, has gained attention as a model for explaining various neural signals. However, the functional significance of the hybrid model has not been established. In the present study, we used computer simulation in a reversal learning task to address functional significance. The hybrid model was found to perform better than the standard RL model in a large parameter setting. These results suggest that the hybrid model is more robust against mistuning of parameters compared to the standard RL model when decision makers continue to learn stimulus-reward contingencies, which make an abrupt changes. The parameter fitting results also indicated that the hybrid model fit better than the standard RL model for more than 50% of the participants, which suggests that the hybrid model has more explanatory power for the behavioral data than the standard RL model.
Boyd, Eric S; Fecteau, Kristopher M; Havig, Jeff R; Shock, Everett L; Peters, John W
2012-01-01
The extent to which geochemical variation shapes the distribution of phototrophic metabolisms was modeled based on 439 observations in geothermal springs in Yellowstone National Park (YNP), Wyoming. Generalized additive models (GAMs) were developed to predict the distribution of phototrophic metabolism as a function of spring temperature, pH, and total sulfide. GAMs comprised of temperature explained 38.8% of the variation in the distribution of phototrophic metabolism, whereas GAMs comprised of sulfide and pH explained 19.6 and 11.2% of the variation, respectively. These results suggest that of the measured variables, temperature is the primary constraint on the distribution of phototrophs in YNP. GAMs comprised of multiple variables explained a larger percentage of the variation in the distribution of phototrophic metabolism, indicating additive interactions among variables. A GAM that combined temperature and sulfide explained the greatest variation in the dataset (53.4%) while minimizing the introduction of degrees of freedom. In an effort to verify the extent to which phototroph distribution reflects constraints on activity, we examined the influence of sulfide and temperature on dissolved inorganic carbon (DIC) uptake rates under both light and dark conditions. Light-driven DIC uptake decreased systematically with increasing concentrations of sulfide in acidic, algal-dominated systems, but was unaffected in alkaline, cyanobacterial-dominated systems. In both alkaline and acidic systems, light-driven DIC uptake was suppressed in cultures incubated at temperatures 10°C greater than their in situ temperature. Collectively, these quantitative results indicate that apart from light availability, the habitat range of phototrophs in YNP springs is defined largely by constraints imposed firstly by temperature and secondly by sulfide on the activity of these populations that inhabit the edges of the habitat range. These findings are consistent with the predictions
Suboptimal maternal and paternal mental health are associated with child bullying perpetration.
Shetgiri, Rashmi; Lin, Hua; Flores, Glenn
2015-06-01
This study examines associations between maternal and paternal mental health and child bullying perpetration among school-age children, and whether having one or both parents with suboptimal mental health is associated with bullying. The 2007 National Survey of Children's Health, a nationally-representative, random-digit-dial survey, was analyzed, using a parent-reported bullying measure. Suboptimal mental health was defined as fair/poor (vs. good/very good/excellent) parental self-reported mental and emotional health. Of the 61,613 parents surveyed, more than half were parents of boys and were white, 20% were Latino, 15% African American, and 7% other race/ethnicity. Suboptimal maternal (OR 1.4; 95% CI 1.1-1.8) and paternal (OR 1.5; 95% CI 1.1-2.2) mental health are associated with bullying. Compared with children with no parents with suboptimal mental health, children with only one or both parents with suboptimal mental health have higher bullying odds. Addressing the mental health of both parents may prove beneficial in preventing bullying.
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Jurjen van der Schans
Full Text Available Attention-Deficit/Hyperactivity Disorder (ADHD is a common psychiatric disorder in children and adolescents. Immediate-release methylphenidate (IR-MPH is the medical treatment of first choice. The necessity to use several IR-MPH tablets per day and associated potential social stigma at school often leads to reduced compliance, sub-optimal treatment, and therefore economic loss. Replacement of IR-MPH with a single-dose extended release (ER-MPH formulation may improve drug response and economic efficiency.To evaluate the cost-effectiveness from a societal perspective of a switch from IR-MPH to ER-MPH in patients who are sub-optimally treated.A daily Markov-cycle model covering a time-span of 10 years was developed including four different health states: (1 optimal response, (2 sub-optimal response, (3 discontinued treatment, and (4 natural remission. ER-MPH options included methylphenidate osmotic release oral system (MPH-OROS and Equasym XL/Medikinet CR. Both direct costs and indirect costs were included in the analysis, and effects were expressed as quality-adjusted life years (QALYs. Univariate, multivariate as well as probabilistic sensitivity analysis were conducted and the main outcomes were incremental cost-effectiveness ratios.Switching sub-optimally treated patients from IR-MPH to MPH-OROS or Equasym XL/Medikinet CR led to per-patient cost-savings of €4200 and €5400, respectively, over a 10-year treatment span. Sensitivity analysis with plausible variations of input parameters resulted in cost-savings in the vast majority of estimations.This study lends economic support to switching patients with ADHD with suboptimal response to short-acting IR-MPH to long-acting ER-MPH regimens.
van der Schans, Jurjen; Kotsopoulos, Nikos; Hoekstra, Pieter J; Hak, Eelko; Postma, Maarten J
2015-01-01
Attention-Deficit/Hyperactivity Disorder (ADHD) is a common psychiatric disorder in children and adolescents. Immediate-release methylphenidate (IR-MPH) is the medical treatment of first choice. The necessity to use several IR-MPH tablets per day and associated potential social stigma at school often leads to reduced compliance, sub-optimal treatment, and therefore economic loss. Replacement of IR-MPH with a single-dose extended release (ER-MPH) formulation may improve drug response and economic efficiency. To evaluate the cost-effectiveness from a societal perspective of a switch from IR-MPH to ER-MPH in patients who are sub-optimally treated. A daily Markov-cycle model covering a time-span of 10 years was developed including four different health states: (1) optimal response, (2) sub-optimal response, (3) discontinued treatment, and (4) natural remission. ER-MPH options included methylphenidate osmotic release oral system (MPH-OROS) and Equasym XL/Medikinet CR. Both direct costs and indirect costs were included in the analysis, and effects were expressed as quality-adjusted life years (QALYs). Univariate, multivariate as well as probabilistic sensitivity analysis were conducted and the main outcomes were incremental cost-effectiveness ratios. Switching sub-optimally treated patients from IR-MPH to MPH-OROS or Equasym XL/Medikinet CR led to per-patient cost-savings of €4200 and €5400, respectively, over a 10-year treatment span. Sensitivity analysis with plausible variations of input parameters resulted in cost-savings in the vast majority of estimations. This study lends economic support to switching patients with ADHD with suboptimal response to short-acting IR-MPH to long-acting ER-MPH regimens.
Directory of Open Access Journals (Sweden)
Giada Mattiuzzo
Full Text Available BACKGROUND: Porcine endogenous retrovirus (PERV poses a potential risk of zoonotic infection in xenotransplantation. Preclinical transplantation trials using non-human primates (NHP as recipients of porcine xenografts present the opportunity to assess the zoonosis risk in vivo. However, PERV poorly infects NHP cells for unclear reasons and therefore NHP may represent a suboptimal animal model to assess the risk of PERV zoonoses. We investigated the mechanism responsible for the low efficiency of PERV-A infection in NHP cells. PRINCIPAL FINDINGS: Two steps, cell entry and exit, were inefficient for the replication of high-titer, human-tropic A/C recombinant PERV. A restriction factor, tetherin, is likely to be responsible for the block to matured virion release, supported by the correlation between the levels of inhibition and tetherin expression. In rhesus macaque, cynomolgus macaque and baboon the main receptor for PERV entry, PERV-A receptor 1 (PAR-1, was found to be genetically deficient: PAR-1 genes in these species encode serine at amino acid 109 in place of the leucine in human PAR-1. This genetic defect inevitably impacts in vivo sensitivity to PERV infection of these species. In contrast, African green monkey (AGM PAR-1 is functional, but PERV infection is still poor. Although the mechanism is unclear, tunicamycin treatment, which removes N-glycosylated sugar chains, increases PERV infection, suggesting a possible role for the glycosylation of the receptors. CONCLUSIONS: Since cynomolgus macaque and baboon, species often used in pig-to-NHP xenotransplantation experiments, have a defective PAR-1, they hardly represent an ideal animal model to assess the risk of PERV transmission in xenotransplantation. Alternatively, NHP species, like AGM, whose both PARs are functional may represent a better model than baboon and cynomolgus macaque for PERV zoonosis in vivo studies.
de Villiers, Marelize; Kriticos, Darren J; Veldtman, Ruan
2017-01-01
The European wasp, Vespula germanica (Fabricius) (Hymenoptera: Vespidae), is of Palaearctic origin, being native to Europe, northern Africa and Asia, and introduced into North America, Chile, Argentina, Iceland, Ascension Island, South Africa, Australia and New Zealand. Due to its polyphagous nature and scavenging behaviour, V. germanica threatens agriculture and silviculture, and negatively affects biodiversity, while its aggressive nature and venomous sting pose a health risk to humans. In areas with warmer winters and longer summers, queens and workers can survive the winter months, leading to the build-up of large nests during the following season; thereby increasing the risk posed by this species. To prevent or prepare for such unwanted impacts it is important to know where the wasp may be able to establish, either through natural spread or through introduction as a result of human transport. Distribution data from Argentina and Australia, and seasonal phenology data from Argentina were used to determine the potential distribution of V. germanica using CLIMEX modelling. In contrast to previous models, the influence of irrigation on its distribution was also investigated. Under a natural rainfall scenario, the model showed similarities to previous models. When irrigation is applied, dry stress is alleviated, leading to larger areas modelled climatically suitable compared with previous models, which provided a better fit with the actual distribution of the species. The main areas at risk of invasion by V. germanica include western USA, Mexico, small areas in Central America and in the north-western region of South America, eastern Brazil, western Russia, north-western China, Japan, the Mediterranean coastal regions of North Africa, and parts of southern and eastern Africa.
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Marelize de Villiers
Full Text Available The European wasp, Vespula germanica (Fabricius (Hymenoptera: Vespidae, is of Palaearctic origin, being native to Europe, northern Africa and Asia, and introduced into North America, Chile, Argentina, Iceland, Ascension Island, South Africa, Australia and New Zealand. Due to its polyphagous nature and scavenging behaviour, V. germanica threatens agriculture and silviculture, and negatively affects biodiversity, while its aggressive nature and venomous sting pose a health risk to humans. In areas with warmer winters and longer summers, queens and workers can survive the winter months, leading to the build-up of large nests during the following season; thereby increasing the risk posed by this species. To prevent or prepare for such unwanted impacts it is important to know where the wasp may be able to establish, either through natural spread or through introduction as a result of human transport. Distribution data from Argentina and Australia, and seasonal phenology data from Argentina were used to determine the potential distribution of V. germanica using CLIMEX modelling. In contrast to previous models, the influence of irrigation on its distribution was also investigated. Under a natural rainfall scenario, the model showed similarities to previous models. When irrigation is applied, dry stress is alleviated, leading to larger areas modelled climatically suitable compared with previous models, which provided a better fit with the actual distribution of the species. The main areas at risk of invasion by V. germanica include western USA, Mexico, small areas in Central America and in the north-western region of South America, eastern Brazil, western Russia, north-western China, Japan, the Mediterranean coastal regions of North Africa, and parts of southern and eastern Africa.
Tipton, Elizabeth; Pustejovsky, James E.
2015-01-01
Randomized experiments are commonly used to evaluate the effectiveness of educational interventions. The goal of the present investigation is to develop small-sample corrections for multiple contrast hypothesis tests (i.e., F-tests) such as the omnibus test of meta-regression fit or a test for equality of three or more levels of a categorical…
Frequency and predictors of suboptimal glycemic control in an African diabetic population
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Kibirige D
2017-02-01
Full Text Available Davis Kibirige,1 George Patrick Akabwai,2 Leaticia Kampiire,3 Daniel Ssekikubo Kiggundu,4 William Lumu5 1Department of Medicine/Diabetic and Hypertension Clinics, Our Lady of Consolota Hospital, Kisubi, 2Baylor College of Medicine, Children’s Foundation, 3Infectious Diseases Research Collaboration, Kampala, 4Nephrology Unit, Mulago National Referral and Teaching Hospital, Kampala, 5Department of Medicine and Diabetes/Endocrine Unit, Mengo Hospital, Mengo, Uganda Background: Persistent suboptimal glycemic control is invariably associated with onset and progression of acute and chronic diabetic complications in diabetic patients. In Uganda, studies documenting the magnitude and predictors of suboptimal glycemic control in adult ambulatory diabetic patients are limited. This study aimed at determining the frequency and predictors of suboptimal glycemic control in adult diabetic patients attending three urban outpatient diabetic clinics in Uganda. Methods: In this hospital-based cross-sectional study, eligible ambulatory adult diabetic patients attending outpatient diabetic clinics of three urban hospitals were consecutively enrolled over 11 months. Suboptimal glycemic control was defined as glycated hemoglobin (HbA1c level ≥7%. Multivariable analysis was applied to determine the predictors. Results: The mean age of the study participants was 52.2±14.4 years, and the majority of them were females (283, 66.9%. The median (interquartile range HbA1c level was 9% (6.8%–12.4%. Suboptimal glycemic control was noted in 311 study participants, accounting for 73.52% of the participants. HbA1c levels of 7%–8%, 8.1%–9.9%, and ≥10% were noted in 56 (13.24%, 76 (17.97%, and 179 (42.32% study participants, respectively. The documented predictors of suboptimal glycemic control were metformin monotherapy (odds ratio: 0.36, 95% confidence interval: 0.21–0.63, p<0.005 and insulin therapy (odds ratio: 2.41, 95% confidence interval: 1.41–4.12, p=0
Growing random networks with fitness
Ergun, G.; Rodgers, GJ
2001-01-01
Three models of growing random networks with fitness dependent growth rates are analysed using the rate equations for the distribution of their connectivities. In the first model (A), a network is built by connecting incoming nodes to nodes of connectivity $k$ and random additive fitness $\\eta$, with rate $(k-1)+ \\eta $. For $\\eta >0$ we find the connectivity distribution is power law with exponent $\\gamma=+2$. In the second model (B), the network is built by connecting nodes to nodes of conn...
Focht, Dorota; Croll, Tristan I; Pedersen, Bjorn P; Nissen, Poul
2017-01-01
The plasma membrane H(+)-ATPase is a proton pump of the P-type ATPase family and essential in plants and fungi. It extrudes protons to regulate pH and maintains a strong proton-motive force that energizes e.g., secondary uptake of nutrients. The only crystal structure of a H(+)-ATPase (AHA2 from Arabidopsis thaliana) was reported in 2007. Here, we present an improved atomic model of AHA2, obtained by a combination of model rebuilding through interactive molecular dynamics flexible fitting (iMDFF) and structural refinement based on the original data, but using up-to-date refinement methods. More detailed map features prompted local corrections of the transmembrane domain, in particular rearrangement of transmembrane helices 7 and 8, and the cytoplasmic N- and P-domains, and the new model shows improved overall quality and reliability scores. The AHA2 structure shows similarity to the Ca(2+)-ATPase E1 state, and provides a valuable starting point model for structural and functional analysis of proton transport mechanism of P-type H(+)-ATPases. Specifically, Asp684 protonation associated with phosphorylation and occlusion of the E1P state may result from hydrogen bond interaction with Asn106. A subsequent deprotonation associated with extracellular release in the E2P state may result from an internal salt bridge formation to an Arg655 residue, which in the present E1 state is stabilized in a solvated pocket. A release mechanism based on an in-built counter-cation was also later proposed for Zn(2+)-ATPase, for which structures have been determined in Zn(2+) released E2P-like states with the salt bridge interaction formed.
Middelkamp, P.J.C.; van Rooijen, M.; Wolfhagen, P.; Steenbergen, B.
2017-01-01
The transtheoretical model of behavior change (TTM) is often used to understand changes in health-related behavior, like exercise. Exercise behavior in fitness clubs is an understudied topic, but preliminary studies showed low frequencies and large numbers of drop-out. An initial 12-week self-efficacy intervention reported significant effects on exercise behavior. The objective of this follow up study is testing effects on exercise behavior over 52 weeks and the long-term relationships of all...
The DisVis and PowerFit Web Servers: Explorative and Integrative Modeling of Biomolecular Complexes.
van Zundert, G C P; Trellet, M; Schaarschmidt, J; Kurkcuoglu, Z; David, M; Verlato, M; Rosato, A; Bonvin, A M J J
2017-02-03
Structure determination of complex molecular machines requires a combination of an increasing number of experimental methods with highly specialized software geared toward each data source to properly handle the gathered data. Recently, we introduced the two software packages PowerFit and DisVis. These combine high-resolution structures of atomic subunits with density maps from cryo-electron microscopy or distance restraints, typically acquired by chemical cross-linking coupled with mass spectrometry, respectively. Here, we report on recent advances in both GPGPU-accelerated software packages: PowerFit is a tool for rigid body fitting of atomic structures in cryo-electron density maps and has been updated to also output reliability indicators for the success of fitting, through the use of the Fisher z-transformation and associated confidence intervals; DisVis aims at quantifying the information content of distance restraints and identifying false-positive restraints. We extended its analysis capabilities to include an analysis of putative interface residues and to output an average shape representing the putative location of the ligand. To facilitate their use by a broad community, they have been implemented as web portals harvesting both local CPU resources and GPGPU-accelerated EGI grid resources. They offer user-friendly interfaces, while minimizing computational requirements, and provide a first interactive view of the results. The portals can be accessed freely after registration via http://milou.science.uu.nl/services/DISVIS and http://milou.science.uu.nl/services/POWERFIT. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Shidrokh Goudarzi; Wan Haslina Hassan; Mohammad Hossein Anisi; Seyed Ahmad Soleymani; Parvaneh Shabanzadeh
2015-01-01
The vertical handover mechanism is an essential issue in the heterogeneous wireless environments where selection of an efficient network that provides seamless connectivity involves complex scenarios. This study uses two modules that utilize the particle swarm optimization (PSO) algorithm to predict and make an intelligent vertical handover decision. In this paper, we predict the received signal strength indicator parameter using the curve fitting based particle swarm optimization (CF-PSO) an...
Permadi, Ginanjar Setyo; Adi, Kusworo; Gernowo, Rahmad
2018-02-01
RSA algorithm give security in the process of the sending of messages or data by using 2 key, namely private key and public key .In this research to ensure and assess directly systems are made have meet goals or desire using a comprehensive evaluation methods HOT-Fit system .The purpose of this research is to build a information system sending mail by applying methods of security RSA algorithm and to evaluate in uses the method HOT-Fit to produce a system corresponding in the faculty physics. Security RSA algorithm located at the difficulty of factoring number of large coiled factors prima, the results of the prime factors has to be done to obtain private key. HOT-Fit has three aspects assessment, in the aspect of technology judging from the system status, the quality of system and quality of service. In the aspect of human judging from the use of systems and satisfaction users while in the aspect of organization judging from the structure and environment. The results of give a tracking system sending message based on the evaluation acquired.
Milani, G.; Milani, F.
A GUI software (GURU) for experimental data fitting of rheometer curves in Natural Rubber (NR) vulcanized with sulphur at different curing temperatures is presented. Experimental data are automatically loaded in GURU from an Excel spreadsheet coming from the output of the experimental machine (moving die rheometer). To fit the experimental data, the general reaction scheme proposed by Han and co-workers for NR vulcanized with sulphur is considered. From the simplified kinetic scheme adopted, a closed form solution can be found for the crosslink density, with the only limitation that the induction period is excluded from computations. Three kinetic constants must be determined in such a way to minimize the absolute error between normalized experimental data and numerical prediction. Usually, this result is achieved by means of standard least-squares data fitting. On the contrary, GURU works interactively by means of a Graphical User Interface (GUI) to minimize the error and allows an interactive calibration of the kinetic constants by means of sliders. A simple mouse click on the sliders allows the assignment of a value for each kinetic constant and a visual comparison between numerical and experimental curves. Users will thus find optimal values of the constants by means of a classic trial and error strategy. An experimental case of technical relevance is shown as benchmark.
Schultz, L D; Chasco, B E; Whitlock, S L; Meeuwig, M H; Schreck, C B
2017-04-01
This study used existing western brook lamprey Lampetra richardsoni age information to fit three different growth models (i.e. von Bertalanffy, Gompertz and logistic) with and without error in age estimates. Among these growth models, there was greater support for the logistic and Gompertz models than the von Bertalanffy model, regardless of ageing error assumptions. The von Bertalanffy model, however, appeared to fit the data well enough to permit survival estimates; using length-based estimators, annual survival varied between 0·64 (95% credibility interval: 0·44-0·79) and 0·81 (0·79-0·83) depending on ageing and growth process error structure. These estimates are applicable to conservation and management of L. richardsoni and other western lampreys (e.g. Pacific lamprey Entosphenus tridentatus) and can potentially be used in the development of life-cycle models for these species. These results also suggest that estimators derived from von Bertalanffy growth models should be interpreted with caution if there is high uncertainty in age estimates. © 2016 The Fisheries Society of the British Isles.
Suboptimal herd performance amplifies the spread of infectious disease in the cattle industry.
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M Carolyn Gates
Full Text Available Farms that purchase replacement breeding cattle are at increased risk of introducing many economically important diseases. The objectives of this analysis were to determine whether the total number of replacement breeding cattle purchased by individual farms could be reduced by improving herd performance and to quantify the effects of such reductions on the industry-level transmission dynamics of infectious cattle diseases. Detailed information on the performance and contact patterns of British cattle herds was extracted from the national cattle movement database as a case example. Approximately 69% of beef herds and 59% of dairy herds with an average of at least 20 recorded calvings per year purchased at least one replacement breeding animal. Results from zero-inflated negative binomial regression models revealed that herds with high average ages at first calving, prolonged calving intervals, abnormally high or low culling rates, and high calf mortality rates were generally more likely to be open herds and to purchase greater numbers of replacement breeding cattle. If all herds achieved the same level of performance as the top 20% of herds, the total number of replacement beef and dairy cattle purchased could be reduced by an estimated 34% and 51%, respectively. Although these purchases accounted for only 13% of between-herd contacts in the industry trade network, they were found to have a disproportionately strong influence on disease transmission dynamics. These findings suggest that targeting extension services at herds with suboptimal performance may be an effective strategy for controlling endemic cattle diseases while simultaneously improving industry productivity.
Are theoretical perspectives useful to explain nurses' tolerance of suboptimal care?
Price, Lesley; Duffy, Kathleen; McCallum, Jacqueline; Ness, Valerie
2015-10-01
This paper explores two theoretical perspectives that may help nurse managers understand why staff tolerate suboptimal standards of care. Standards of care have been questioned in relation to adverse events and errors for some years in health care across the western world. More recently, the focus has shifted to inadequate nursing standards with regard to care and compassion, and a culture of tolerance by staff to these inadequate standards. The theories of conformity and cognitive dissonance are analysed to investigate their potential for helping nurse managers to understand why staff tolerate suboptimal standards of care. The literature suggests that nurses appear to adopt behaviours consistent with the theory of conformity and that they may accept suboptimal care to reduce their cognitive dissonance. Nurses may conform to be accepted by the team. This may be confounded by nurses rationalising their care to reduce the cognitive dissonance they feel. The investigation into the Mid Staffordshire National Health Service called for a change in culture towards transparency, candidness and openness. Providing insights as to why some nursing staff tolerate suboptimal care may provide a springboard to allow nurse managers to consider the complexities surrounding this required transformation. © 2014 John Wiley & Sons Ltd.
Influence of sub-optimal temperature on tomato growth and yield : a review
Ploeg, van der A.; Heuvelink, E.
2005-01-01
The effects of temperature on growth, development and yield of tomato (Lycopersicon esculentum) are reviewed with special emphasis on cultivar differences. The focus is on sub-optimal temperatures, above the level where chilling injury occurs. Temperature has a large effect on all aspects of
Suboptimal decision making by children with ADHD in the face of risk
DEFF Research Database (Denmark)
Sørensen, Lin; Sonuga-Barke, Edmund; Eichele, Heike
2017-01-01
Objective: Suboptimal decision making in the face of risk (DMR) in children with attention-deficit hyperactivity disorder (ADHD) may be mediated by deficits in a number of different neuropsychological processes. We investigated DMR in children with ADHD using the Cambridge Gambling Task (CGT...
High Current CD4+ T Cell Count Predicts Suboptimal Adherence to Antiretroviral Therapy
Pasternak, Alexander O.; de Bruin, Marijn; Bakker, Margreet; Berkhout, Ben; Prins, Jan M.
2015-01-01
High levels of adherence to antiretroviral therapy (ART) are necessary for achieving and maintaining optimal virological suppression, as suboptimal adherence leads to therapy failure and disease progression. It is well known that adherence to ART predicts therapy response, but it is unclear whether
Indicators of suboptimal performance embedded in the Wechsler Memory Scale : Fourth Edition (WMS-IV)
Bouman, Z.; Hendriks, M.P.H.; Schmand, B.A.; Kessels, R.P.C.; Aldenkamp, A.P.
2016-01-01
INTRODUCTION: Recognition and visual working memory tasks from the Wechsler Memory Scale-Fourth Edition (WMS-IV) have previously been documented as useful indicators for suboptimal performance. The present study examined the clinical utility of the Dutch version of the WMS-IV (WMS-IV-NL) for the
High current CD4+ T cell count predicts suboptimal adherence to antiretroviral therapy
Pasternak, A.O.; de Bruin, M.; Bakker, M.; Berkhout, B.; Prins, J.M.
2015-01-01
High levels of adherence to antiretroviral therapy (ART) are necessary for achieving and maintaining optimal virological suppression, as suboptimal adherence leads to therapy failure and disease progression. It is well known that adherence to ART predicts therapy response, but it is unclear whether
State Space Formulas for a Solution of the Suboptimal Nehari Problem on the Unit Disc
Curtain, Ruth F.; Opmeer, Mark R.
We give state space formulas for a ("central") solution of the suboptimal Nehari problem for functions defined on the unit disc and taking values in the space of bounded operators in separable Hilbert spaces. Instead of assuming exponential stability, we assume a weaker stability concept (the
Sub-optimal birth weight in newborns of a high socioeconomic status population
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Conceição Aparecida de Mattos Segre
2008-09-01
Full Text Available Objective: To compare sub-optimal birth weight (2,500 to 2,999 g term newborns to appropriate for gestational age (birth weight ≥ 3,000 g term newborns, regarding maternal data and newborn morbidity and mortality. Methods: Single term newborns, appropriate for gestational age from a high socioeconomic population (n = 1,242 with birth weight ranging from 2,500 to 2,999 g (Group I were compared to 4,907 newborns with birth weight ≥ than 3,000 g (Group II. Maternal and newborn characteristics were compared between the groups. The Mann-Whitney test, χ2 test and multivariate analysis were used. The significance level adopted was p < 0.05. Rresults: The frequency of sub-optimal birth weight newborns in the population studied was 20.2%. There was a significant association between sub-optimal birth weight and maternal weight before pregnancy and body mass index, maternal weight gain, height, smoking habit and hypertension. Newborns’ 1-minute Apgar score, neonatal hypoglycemia, jaundice, transient tachypnea, congenital pneumonia and hospital stay were significantly different between the groups (p < 0.05. A significant relationship could not be established with the 5-minute Apgar score and pulmonary hypertension in both groups. Neonatal mortality did not differ between the groups. Cconclusions: Socioeconomic status was not a risk factor for sub-optimal birth weight in the studied population. Genetic and environmental factors were associated to sub-optimal weight and neonatal diseases. According to these data, this group of newborns should receive special attention from the health team.
HistFactory: A tool for creating statistical models for use with RooFit and RooStats
Cranmer, Kyle; Moneta, Lorenzo; Shibata, Akira; Verkerke, Wouter
2012-01-01
The HistFactory is a tool to build parametrized probability density functions (pdfs) in the RooFit/RooStats framework based based on simple ROOT histograms organized in an XML file. The pdf has a restricted form, but it is sufficiently flexible to describe many analyses based on template histograms. The tool takes a modular approach to build complex pdfs from more primative conceptual building blocks. The resulting PDF is stored in a RooWorkspace which can be saved to and read from a ROOT file. This document describes the defaults and interface in HistFactory 5.32.
DEFF Research Database (Denmark)
Stein, Wilfred D; Litman, Thomas
2006-01-01
by the body's immune system, or by random apoptosis or senescence. (iv) Recurrence suppressor mechanisms exist. (v) When such genes are disabled by random mutations, the dormant metastatic cell is activated, and will develop to a cancer recurrence. The model was also fitted to data on the survival......We successfully modeled the recurrence of tumors in breast cancer patients, assuming that: (i) A breast cancer patient is likely to have some circulating metastatic cells, even after initial surgery. (ii) These metastatic cells are dormant. (iii) The dormant cells are subject to attrition...
Fit for purpose: Australia's National Fitness Campaign.
Collins, Julie A; Lekkas, Peter
2011-12-19
During a time of war, the federal government passed the National Fitness Act 1941 to improve the fitness of the youth of Australia and better prepare them for roles in the armed services and industry. Implementation of the National Fitness Act made federal funds available at a local level through state-based national fitness councils, which coordinated promotional campaigns, programs, education and infrastructure for physical fitness, with volunteers undertaking most of the work. Specifically focused on children and youth, national fitness councils supported the provision of children's playgrounds, youth clubs and school camping programs, as well as the development of physical education in schools and its teaching and research in universities. By the time the Act was repealed in 1994, fitness had become associated with leisure and recreation rather than being seen as equipping people for everyday life and work. The emergence of the Australian National Preventive Health Agency Act 2010 offers the opportunity to reflect on synergies with its historic precedent.
Directory of Open Access Journals (Sweden)
Wakhid Slamet Ciptono
2011-02-01
Full Text Available This study purposively is to conduct an empirical analysis of the structural relations among critical factors of quality management practices (QMPs, world-class company practice (WCC, operational excellence practice (OE, and company performance (company non-financial performance or CNFP and company financial performance or CFP in the oil and gas companies operating in Indonesia. The current study additionally examines the relationships between QMPs and CFP through WCC, OE, and CNFP (as partial mediators simultaneously. The study uses data from a survey of 140 strategic business units (SBUs within 49 oil and gas contractor companies in Indonesia. The findings suggest that all six QMPs have positive and significant indirect relationships on CFP through WCC and CNFP. Only four of six QMPs have positive and significant indirect relationships on CFP through OE and CNFP. Hence, WCC, OE, and CNFP play as partial mediators between QMPs and CFP. CNFP has a significant influence on CFP. A major implication of this study is that oil and gas managers need to recognize the structural relations model fit by developing all of the research constructs simultaneously associated with a comprehensive TQM practice. Furthermore, the findings will assist oil and gas companies by improving CNFP, which is very critical to TQM, thereby contributing to a better achievement of CFP. The current study uses the Deming’s principles, Hayes and Wheelwright dimensions of world-class company practice, Chevron Texaco’s operational excellence practice, and the dimensions of company financial and non-financial performances. The paper also provides an insight into the sustainability of TQM implementation model and their effect on company financial performance in oil and gas companies in Indonesia.
Moore, B C
2000-06-01
Many researchers have proposed that multi-channel compression hearing aids should process sounds so as to restore loudness perception to 'normal'. However, procedures for achieving this have generally been based on measurements or calculations using narrowband stimuli, and these procedures may not be accurate for broadband sounds such as speech. Here, a model for predicting loudness for people with cochlear hearing loss is used to calculate the frequency- and level-dependent gains that would be required to restore loudness perception to 'normal' for speech-like signals. The calculations are based entirely on the pure tone audiogram, and do not require measures of loudness growth. The model was applied to several different hypothetical hearing losses, varying in slope and severity. In each case, the model was used to calculate the insertion gains (IGs) that would be required as a function of frequency so that speech-shaped noise with a level of 65 dB SPL would evoke a specific loudness pattern matching that for a normal ear. A similar procedure was applied using speech-shaped noise with a level of 85 dB SPL (with the spectral characteristics of shouted speech). The results were used to derive functions relating the required IG to hearing loss for each audiometric frequency and each speech-shaped noise level. These functions were used in turn to derive compression ratios and gains for each channel of a multi-channel compression system. The derivations apply to systems with any number of channels. The outcome is a method than can be used for the initial fitting of multichannel compression hearing aids, so as to restore loudness perception to near 'normal' for broadband speech-like signals.
Toribo, S.G.; Gray, B.R.; Liang, S.
2011-01-01
The N-mixture model proposed by Royle in 2004 may be used to approximate the abundance and detection probability of animal species in a given region. In 2006, Royle and Dorazio discussed the advantages of using a Bayesian approach in modelling animal abundance and occurrence using a hierarchical N-mixture model. N-mixture models assume replication on sampling sites, an assumption that may be violated when the site is not closed to changes in abundance during the survey period or when nominal replicates are defined spatially. In this paper, we studied the robustness of a Bayesian approach to fitting the N-mixture model for pseudo-replicated count data. Our simulation results showed that the Bayesian estimates for abundance and detection probability are slightly biased when the actual detection probability is small and are sensitive to the presence of extra variability within local sites.
Directory of Open Access Journals (Sweden)
Eun-Hye Hong
Full Text Available Several anti-influenza drugs that reduce disease manifestation exist, and although these drugs provide clinical benefits in infected patients, their efficacy is limited by the emergence of drug-resistant influenza viruses. In the current study, we assessed the therapeutic strategy of enhancing the antiviral efficacy of an existing neuraminidase inhibitor, oseltamivir, by coadministering with the leaf extract from Hedera helix L, commonly known as ivy. Ivy extract has anti-inflammatory, antibacterial, antifungal, and antihelminthic properties. In the present study, we investigated its potential antiviral properties against influenza A/PR/8 (PR8 virus in a mouse model with suboptimal oseltamivir that mimics a poor clinical response to antiviral drug treatment. Suboptimal oseltamivir resulted in insufficient protection against PR8 infection. Oral administration of ivy extract with suboptimal oseltamivir increased the antiviral activity of oseltamivir. Ivy extract and its compounds, particularly hedrasaponin F, significantly reduced the cytopathic effect in PR8-infected A549 cells in the presence of oseltamivir. Compared with oseltamivir treatment alone, coadministration of the fraction of ivy extract that contained the highest proportion of hedrasaponin F with oseltamivir decreased pulmonary inflammation in PR8-infected mice. Inflammatory cytokines and chemokines, including tumor necrosis factor-alpha and chemokine (C-C motif ligand 2, were reduced by treatment with oseltamivir and the fraction of ivy extract. Analysis of inflammatory cell infiltration in the bronchial alveolar of PR8-infected mice revealed that CD11b+Ly6G+ and CD11b+Ly6Cint cells were recruited after virus infection; coadministration of the ivy extract fraction with oseltamivir reduced infiltration of these inflammatory cells. In a model of suboptimal oseltamivir treatment, coadministration of ivy extract fraction that includes hedrasaponin F increased protection against PR8
Hong, Eun-Hye; Song, Jae-Hyoung; Shim, Aeri; Lee, Bo-Ra; Kwon, Bo-Eun; Song, Hyuk-Hwan; Kim, Yeon-Jeong; Chang, Sun-Young; Jeong, Hyeon Gun; Kim, Jong Geal; Seo, Sang-Uk; Kim, HyunPyo; Kwon, YongSoo; Ko, Hyun-Jeong
2015-01-01
Several anti-influenza drugs that reduce disease manifestation exist, and although these drugs provide clinical benefits in infected patients, their efficacy is limited by the emergence of drug-resistant influenza viruses. In the current study, we assessed the therapeutic strategy of enhancing the antiviral efficacy of an existing neuraminidase inhibitor, oseltamivir, by coadministering with the leaf extract from Hedera helix L, commonly known as ivy. Ivy extract has anti-inflammatory, antibacterial, antifungal, and antihelminthic properties. In the present study, we investigated its potential antiviral properties against influenza A/PR/8 (PR8) virus in a mouse model with suboptimal oseltamivir that mimics a poor clinical response to antiviral drug treatment. Suboptimal oseltamivir resulted in insufficient protection against PR8 infection. Oral administration of ivy extract with suboptimal oseltamivir increased the antiviral activity of oseltamivir. Ivy extract and its compounds, particularly hedrasaponin F, significantly reduced the cytopathic effect in PR8-infected A549 cells in the presence of oseltamivir. Compared with oseltamivir treatment alone, coadministration of the fraction of ivy extract that contained the highest proportion of hedrasaponin F with oseltamivir decreased pulmonary inflammation in PR8-infected mice. Inflammatory cytokines and chemokines, including tumor necrosis factor-alpha and chemokine (C-C motif) ligand 2, were reduced by treatment with oseltamivir and the fraction of ivy extract. Analysis of inflammatory cell infiltration in the bronchial alveolar of PR8-infected mice revealed that CD11b+Ly6G+ and CD11b+Ly6Cint cells were recruited after virus infection; coadministration of the ivy extract fraction with oseltamivir reduced infiltration of these inflammatory cells. In a model of suboptimal oseltamivir treatment, coadministration of ivy extract fraction that includes hedrasaponin F increased protection against PR8 infection that could be
Anan, Mohammad Tarek M.; Al-Saadi, Mohannad H.
2015-01-01
Objective The aim of this study was to compare the fit accuracies of metal partial removable dental prosthesis (PRDP) frameworks fabricated by the traditional technique (TT) or the light-curing modeling material technique (LCMT). Materials and methods A metal model of a Kennedy class III modification 1 mandibular dental arch with two edentulous spaces of different spans, short and long, was used for the study. Thirty identical working casts were used to produce 15 PRDP frameworks each by TT and by LCMT. Every framework was transferred to a metal master cast to measure the gap between the metal base of the framework and the crest of the alveolar ridge of the cast. Gaps were measured at three points on each side by a USB digital intraoral camera at ×16.5 magnification. Images were transferred to a graphics editing program. A single examiner performed all measurements. The two-tailed t-test was performed at the 5% significance level. Results The mean gap value was significantly smaller in the LCMT group compared to the TT group. The mean value of the short edentulous span was significantly smaller than that of the long edentulous span in the LCMT group, whereas the opposite result was obtained in the TT group. Conclusion Within the limitations of this study, it can be concluded that the fit of the LCMT-fabricated frameworks was better than the fit of the TT-fabricated frameworks. The framework fit can differ according to the span of the edentate ridge and the fabrication technique for the metal framework. PMID:26236129
Energy Technology Data Exchange (ETDEWEB)
Abdeldayem, H.M.; Ruiz, P.; Delmon, B. [Unite de Catalyse et Chimie des Materiaux Divises, Universite Catholique de Louvain, Louvain-La-Neuve (Belgium); Thyrion, F.C. [Unite des Procedes Faculte des Sciences Appliquees, Universite Catholique de Louvain, Louvain-La-Neuve (Belgium)
1998-12-31
A new kinetic model for a more accurate and detailed fitting of the experimental data is proposed. The model is based on the remote control mechanism (RCM). The RCM assumes that some oxides (called `donors`) are able to activate molecular oxygen transforming it to very active mobile species (spillover oxygen (O{sub OS})). O{sub OS} migrates onto the surface of the other oxide (called `acceptor`) where it creates and/or regenerates the active sites during the reaction. The model contains tow terms, one considering the creation of selective sites and the other the catalytic reaction at each site. The model has been tested in the selective oxidation of propene into acrolein (T=380, 400, 420 C; oxygen and propene partial pressures between 38 and 152 Torr). Catalysts were prepared as pure MoO{sub 3} (acceptor) and their mechanical mixtures with {alpha}-Sb{sub 2}O{sub 4} (donor) in different proportions. The presence of {alpha}-Sb{sub 2}O{sub 4} changes the reaction order, the activation energy of the reaction and the number of active sites of MoO{sub 3} produced by oxygen spillover. These changes are consistent with a modification in the degree of irrigation of the surface by oxygen spillover. The fitting of the model to experimental results shows that the number of sites created by O{sub SO} increases with the amount of {alpha}-Sb{sub 2}O{sub 4}. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Mavroidis, P; Price, A; Kostich, M; Green, R; Das, S; Marks, L; Chera, B [University North Carolina, Chapel Hill, NC (United States); Amdur, R; Mendenhall, W [University of Florida, Gainesville, FL (United States); Sheets, N [University of North Carolina, Raleigh, NC (United States)
2016-06-15
Purpose: To estimate the radiobiological parameters of four popular NTCP models that describe the dose-response relations of salivary glands to the severity of patient reported dry mouth 6 months post chemo-radiotherapy. To identify the glands, which best correlate with the manifestation of those clinical endpoints. Finally, to evaluate the goodness-of-fit of the NTCP models. Methods: Forty-three patients were treated on a prospective multiinstitutional phase II study for oropharyngeal squamous cell carcinoma. All the patients received 60 Gy IMRT and they reported symptoms using the novel patient reported outcome version of the CTCAE. We derived the individual patient dosimetric data of the parotid and submandibular glands (SMG) as separate structures as well as combinations. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS), Logit and Relative Logit (RL) NTCP models were used to fit the patients data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC) and the Odds Ratio methods. Results: The AUC values were highest for the contralateral parotid for Grade ≥ 2 (0.762 for the LKB, RS, Logit and 0.753 for the RL). For the salivary glands the AUC values were: 0.725 for the LKB, RS, Logit and 0.721 for the RL. For the contralateral SMG the AUC values were: 0.721 for LKB, 0.714 for Logit and 0.712 for RS and RL. The Odds Ratio for the contralateral parotid was 5.8 (1.3–25.5) for all the four NTCP models for the radiobiological dose threshold of 21Gy. Conclusion: It was shown that all the examined NTCP models could fit the clinical data well with very similar accuracy. The contralateral parotid gland appears to correlated best with the clinical endpoints of severe/very severe dry mouth. An EQD2Gy dose of 21Gy appears to be a safe threshold to be used as a constraint in treatment planning.
Drijfhout, E.; Oeveren, J.C. van; Jansen, R.C.
1991-01-01
A non-destructive method has been developed to select common bean (Phaseolus vulgaris L.) plants whose growth is less effected at a suboptimal temperature. Shoot weight was determined at a suboptimal (14°C) and optimal temperature (20°C), 38 days after sowing and accessions identified with a
Directory of Open Access Journals (Sweden)
Lumu W
2017-02-01
Full Text Available William Lumu,1 Leaticia Kampiire,2 George Patrick Akabwai,3 Daniel Ssekikubo Kiggundu,4 Davis Kibirige5 1Department of Medicine and Diabetes/Endocrine Unit, Mengo Hospital, 2Infectious Disease Research Collaboration, 3Baylor College of Medicine Children’s Foundation, 4Nephrology Unit, Mulago National Referral and Teaching Hospital, 5Department of Medicine, Uganda Martyrs Hospital Lubaga, Kampala, Uganda Background: Hypertension is one of the recognized risk factors of cardiovascular diseases in adult diabetic patients. High prevalence of suboptimal blood pressure (BP control has been well documented in the majority of studies assessing BP control in diabetic patients in sub-Saharan Africa. In Uganda, there is a dearth of similar studies. This study evaluated the prevalence and correlates of suboptimal BP control in an adult diabetic population in Uganda.Patients and methods: This was a cross-sectional study that enrolled 425 eligible ambulatory adult diabetic patients attending three urban diabetic outpatient clinics over 11 months. Data about their sociodemographic characteristics and clinical history were collected using pre-tested questionnaires. Suboptimal BP control was defined according to the 2015 American Diabetes Association standards of diabetes care guideline as BP levels ≥140/90 mmHg.Results: The mean age of the study participants was 52.2±14.4 years, with the majority being females (283, 66.9%. Suboptimal BP control was documented in 192 (45.3% study participants and was independently associated with the study site (private hospitals; odds ratio 2.01, 95% confidence interval 1.18–3.43, P=0.01 and use of statin therapy (odds ratio 0.5, 95% confidence interval 0.26–0.96, P=0.037.Conclusion: Suboptimal BP control was highly prevalent in this study population. Strategies to improve optimal BP control, especially in the private hospitals, and the use of statin therapy should be encouraged in adult diabetic patients
Directory of Open Access Journals (Sweden)
Brenna M.
2014-03-01
Full Text Available A completely microscopic beyond mean-field approach has been elaborated to overcome some intrinsic limitations of self-consistent mean-field schemes applied to nuclear systems, such as the incapability to produce some properties of single-particle states (e.g. spectroscopic factors, as well as of collective states (e.g. their damping width and their gamma decay to the ground state or to low lying states. Since commonly used effective interactions are fitted at the mean-field level, one should aim at refitting them including the desired beyond mean-field contributions in the refitting procedure. If zero-range interactions are used, divergences arise. We present some steps towards the refitting of Skyrme interactions, for its application in finite nuclei.
Zhao, Z G; Rong, E H; Li, S C; Zhang, L J; Zhang, Z W; Guo, Y Q; Ma, R Y
2016-08-01
Monitoring of oriental fruit moths (Grapholita molesta Busck) is a prerequisite for its control. This study introduced a digital image-processing method and logistic model for the control of oriental fruit moths. First, five triangular sex pheromone traps were installed separately within each area of 667 m2 in a peach orchard to monitor oriental fruit moths consecutively for 3 years. Next, full view images of oriental fruit moths were collected via a digital camera and then subjected to graying, separation and morphological analysis for automatic counting using MATLAB software. Afterwards, the results of automatic counting were used for fitting a logistic model to forecast the control threshold and key control period. There was a high consistency between automatic counting and manual counting (0.99, P < 0.05). According to the logistic model, oriental fruit moths had four occurrence peaks during a year, with a time-lag of 15-18 days between adult occurrence peak and the larval damage peak. Additionally, the key control period was from 28 June to 3 July each year, when the wormy fruit rate reached up to 5% and the trapping volume was approximately 10.2 per day per trap. Additionally, the key control period for the overwintering generation was 25 April. This study provides an automatic counting method and fitted logistic model with a great potential for application to the control of oriental fruit moths.
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....
Decision making on fitness landscapes
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.
Descision Making on Fitness Landscapes
Arthur, Rudy
2016-01-01
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.
Chen, Si-Guang; Stradins, Paul; Gregg, Brian A
2005-07-21
An in-depth study of n-type doping in a crystalline perylene diimide organic semiconductor (PPEEB) reveals that electrostatic attractions between the dopant electron and its conjugate dopant cation cause the free carrier density to be much lower than the doping density. Measurements of the dark currents as a function of field, doping density, electrode spacing, and temperature are reported along with preliminary Hall-effect measurements. The activation energy of the current, E(aJ), decreases with increasing field and with increasing dopant density, n(d). It is the measured change in E(aJ) with n(d) that accounts primarily for the variations between PPEEB films; the two adjustable parameters employed to fit the current-voltage data proved to be almost constants, independent of n(d) and temperature. The free electron density and the electron mobility are nonlinearly coupled through their shared dependences on both field and temperature. The data are fit to a modified Poole-Frenkel-like model that is shown to be valid for three important electronic processes in organic (excitonic) semiconductors: excitonic effects, doping, and transport. At room temperature, the electron mobility in PPEEB films is estimated to be 0.3 cm(2)/Vs; the fitted value of the mobility for an ideal PPEEB crystal is 3.4 +/- 2.7 cm(2)/Vs. The modified Poole-Frenkel factor that describes the field dependence of the current is 2 +/- 1 x 10(-4) eV (cm/V)(1/2). The analytical model is surprisingly accurate for a system that would require a coupled set of nonlinear tensor equations to describe it precisely. Being based on general electrostatic considerations, our model can form the requisite foundation for treatments of more complex systems. Some analogies to adventitiously doped materials such as pi-conjugated polymers are proposed.
Peptide Suboptimal Conformation Sampling for the Prediction of Protein-Peptide Interactions.
Lamiable, Alexis; Thévenet, Pierre; Eustache, Stephanie; Saladin, Adrien; Moroy, Gautier; Tuffery, Pierre
2017-01-01
The blind identification of candidate patches of interaction on the protein surface is a difficult task that can hardly be accomplished without a heuristic or the use of simplified representations to speed up the search. The PEP-SiteFinder protocol performs a systematic blind search on the protein surface using a rigid docking procedure applied to a limited set of peptide suboptimal conformations expected to approximate satisfactorily the conformation of the peptide in interaction. All steps rely on a coarse-grained representation of the protein and the peptide. While simple, such a protocol can help to infer useful information, assuming a critical analysis of the results. Moreover, such a protocol can be extended to a semi-flexible protocol where the suboptimal conformations are directly folded in the vicinity of the receptor.
Suboptimal investments and M&A deals in emerging capital markets
Directory of Open Access Journals (Sweden)
Cherkasova Victoria
2016-01-01
Full Text Available This paper focuses on the efficiency of target-company investment decisions before and after Merger & Acquisition deals. We study whether M&A deals help to solve the problem of suboptimal investment after the acquisition. Using a sample of 145 target companies from BRICS countries that were acquired during the period 2004-2014, we outline those that had over- or underinvested before the deal and show that more than half the companies managed to optimize the investment level after the deal. We determine the key factors that improve the inefficiency of investment decisions and demonstrate that the industry and country have an impact on the degree of suboptimal investment.
DEFF Research Database (Denmark)
Jensen, Jens-Ole
2003-01-01
Artiklen redegør for udbredelsen af fitness blandt unge og diskuterer, hvor det er blevet så populært at dyrke fitness.......Artiklen redegør for udbredelsen af fitness blandt unge og diskuterer, hvor det er blevet så populært at dyrke fitness....
Erickson, Tim
2008-01-01
We often look for a best-fit function to a set of data. This article describes how a "pretty good" fit might be better than a "best" fit when it comes to promoting conceptual understanding of functions. In a pretty good fit, students design the function themselves rather than choosing it from a menu; they use appropriate variable names; and they…
Rakesh, Ramachandran; Srinivasan, Narayanaswamy
2016-01-01
Cryo-Electron Microscopy (cryo-EM) has become an important technique to obtain structural insights into large macromolecular assemblies. However the resolution of the density maps do not allow for its interpretation at atomic level. Hence they are combined with high resolution structures along with information from other experimental or bioinformatics techniques to obtain pseudo-atomic models. Here, we describe the use of evolutionary conservation of residues as obtained from protein structures and alignments of homologous proteins to detect errors in the fitting of atomic structures as well as improve accuracy of the protein-protein interfacial regions in the cryo-EM density maps.
One size does not fit all - understanding the front-end and back-ens of business model innovation
DEFF Research Database (Denmark)
Günzel, Franziska; Holm, Anna B.
2013-01-01
Business model innovation is becoming a central research topic in management. However, a lack of a common understanding of the nature of the business model leads to disregarding its multifaceted structure when analyzing the business model innovation process. This article proposes a more detailed...... understanding of the business model innovation process by drawing on existing knowledge from new product development literature and examining the front-end and the back-end of business model innovation of three leading Danish newspapers. We studied how changes introduced during the development of digital news...... production and delivery have affected key components of these business models, namely value creation, proposition, delivery and capture in the period 2002–2011. Our findings suggest the need to distinguish between front-end and back-end business model innovation processes, and to recognize the importance...
Selb, Juliette; Ogden, Tyler M.; Dubb, Jay; Fang, Qianqian; Boas, David A.
2014-01-01
Abstract. Near-infrared spectroscopy (NIRS) estimations of the adult brain baseline optical properties based on a homogeneous model of the head are known to introduce significant contamination from extracerebral layers. More complex models have been proposed and occasionally applied to in vivo data, but their performances have never been characterized on realistic head structures. Here we implement a flexible fitting routine of time-domain NIRS data using graphics processing unit based Monte Carlo simulations. We compare the results for two different geometries: a two-layer slab with variable thickness of the first layer and a template atlas head registered to the subject’s head surface. We characterize the performance of the Monte Carlo approaches for fitting the optical properties from simulated time-resolved data of the adult head. We show that both geometries provide better results than the commonly used homogeneous model, and we quantify the improvement in terms of accuracy, linearity, and cross-talk from extracerebral layers. PMID:24407503