UROX 2.0: an interactive tool for fitting atomic models into electron-microscopy reconstructions
Siebert, Xavier; Navaza, Jorge
2009-01-01
Electron microscopy of a macromolecular structure can lead to three-dimensional reconstructions with resolutions that are typically in the 30–10 Å range and sometimes even beyond 10 Å. Fitting atomic models of the individual components of the macromolecular structure (e.g. those obtained by X-ray crystallography or nuclear magnetic resonance) into an electron-microscopy map allows the interpretation of the latter at near-atomic resolution, providing insight into the interactions between the components. Graphical software is presented that was designed for the interactive fitting and refinement of atomic models into electron-microscopy reconstructions. Several characteristics enable it to be applied over a wide range of cases and resolutions. Firstly, calculations are performed in reciprocal space, which results in fast algorithms. This allows the entire reconstruction (or at least a sizeable portion of it) to be used by taking into account the symmetry of the reconstruction both in the calculations and in the graphical display. Secondly, atomic models can be placed graphically in the map while the correlation between the model-based electron density and the electron-microscopy reconstruction is computed and displayed in real time. The positions and orientations of the models are refined by a least-squares minimization. Thirdly, normal-mode calculations can be used to simulate conformational changes between the atomic model of an individual component and its corresponding density within a macromolecular complex determined by electron microscopy. These features are illustrated using three practical cases with different symmetries and resolutions. The software, together with examples and user instructions, is available free of charge at http://mem.ibs.fr/UROX/. PMID:19564685
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. PMID:27444391
NASA Astrophysics Data System (ADS)
Ferreras, Ignacio
2012-08-01
Extracting star formation histories from spectra is a process plagued by numerous degeneracies among the parameters that contribute to the definition of the underlying stellar populations. Traditional approaches to overcome such degeneracies involve carefully defined line strength or spectral fitting procedures. However, all these methods rely on comparisons with population synthesis models. This paper illustrates alternative approaches based on the statistical properties of the information that can be extracted from uniformly selected samples of observed spectra, without any prior reference to modelling. Such methods are more useful with large datasets, such as surveys, where the information from thousands of spectra can be exploited to classify galaxies. An illustrative example is presented on the classification of early-type galaxies with optical spectra from the Sloan Digital Sky Survey.
Fitting PAC spectra with stochastic models: PolyPacFit
NASA Astrophysics Data System (ADS)
Zacate, M. O.; Evenson, W. E.; Newhouse, R.; Collins, G. S.
2010-04-01
PolyPacFit is an advanced fitting program for time-differential perturbed angular correlation (PAC) spectroscopy. It incorporates stochastic models and provides robust options for customization of fits. Notable features of the program include platform independence and support for (1) fits to stochastic models of hyperfine interactions, (2) user-defined constraints among model parameters, (3) fits to multiple spectra simultaneously, and (4) any spin nuclear probe.
ERIC Educational Resources Information Center
Willden, Jeff
2001-01-01
"Bohr's Atomic Model" is a small interactive multimedia program that introduces the viewer to a simplified model of the atom. This interactive simulation lets students build an atom using an atomic construction set. The underlying design methodology for "Bohr's Atomic Model" is model-centered instruction, which means the central model of the…
Fitting and interpreting occupancy models.
Welsh, Alan H; Lindenmayer, David B; Donnelly, Christine F
2013-01-01
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. PMID:23326323
Total force fitness: the military family fitness model.
Bowles, Stephen V; Pollock, Liz Davenport; Moore, Monique; Wadsworth, Shelley MacDermid; Cato, Colanda; Dekle, Judith Ward; Meyer, Sonia Wei; Shriver, Amber; Mueller, Bill; Stephens, Mark; Seidler, Dustin A; Sheldon, Joseph; Picano, James; Finch, Wanda; Morales, Ricardo; Blochberger, Sean; Kleiman, Matthew E; Thompson, Daniel; Bates, Mark J
2015-03-01
The military lifestyle can create formidable challenges for military families. This article describes the Military Family Fitness Model (MFFM), a comprehensive model aimed at enhancing family fitness and resilience across the life span. This model is intended for use by Service members, their families, leaders, and health care providers but also has broader applications for all families. The MFFM has three core components: (1) family demands, (2) resources (including individual resources, family resources, and external resources), and (3) family outcomes (including related metrics). The MFFM proposes that resources from the individual, family, and external areas promote fitness, bolster resilience, and foster well-being for the family. The MFFM highlights each resource level for the purpose of improving family fitness and resilience over time. The MFFM both builds on existing family strengths and encourages the development of new family strengths through resource-acquiring behaviors. The purpose of this article is to (1) expand the military's Total Force Fitness (TFF) intent as it relates to families and (2) offer a family fitness model. This article will summarize relevant evidence, provide supportive theory, describe the model, and proffer metrics that support the dimensions of this model. PMID:25735013
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
Coaches as Fitness Role Models
ERIC Educational Resources Information Center
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…
Sensitivity of Fit Indices to Model Misspecification and Model Types
ERIC Educational Resources Information Center
Fan, Xitao; Sivo, Stephen A.
2007-01-01
The search for cut-off criteria of fit indices for model fit evaluation (e.g., Hu & Bentler, 1999) assumes that these fit indices are sensitive to model misspecification, but not to different types of models. If fit indices were sensitive to different types of models that are misspecified to the same degree, it would be very difficult to establish…
Computer Modeling Of Atomization
NASA Technical Reports Server (NTRS)
Giridharan, M.; Ibrahim, E.; Przekwas, A.; Cheuch, S.; Krishnan, A.; Yang, H.; Lee, J.
1994-01-01
Improved mathematical models based on fundamental principles of conservation of mass, energy, and momentum developed for use in computer simulation of atomization of jets of liquid fuel in rocket engines. Models also used to study atomization in terrestrial applications; prove especially useful in designing improved industrial sprays - humidifier water sprays, chemical process sprays, and sprays of molten metal. Because present improved mathematical models based on first principles, they are minimally dependent on empirical correlations and better able to represent hot-flow conditions that prevail in rocket engines and are too severe to be accessible for detailed experimentation.
Evaluation of Model Fit in Cognitive Diagnosis Models
ERIC Educational Resources Information Center
Hu, Jinxiang; Miller, M. David; Huggins-Manley, Anne Corinne; Chen, Yi-Hsin
2016-01-01
Cognitive diagnosis models (CDMs) estimate student ability profiles using latent attributes. Model fit to the data needs to be ascertained in order to determine whether inferences from CDMs are valid. This study investigated the usefulness of some popular model fit statistics to detect CDM fit including relative fit indices (AIC, BIC, and CAIC),…
Evaluating Model Fit for Growth Curve Models: Integration of Fit Indices from SEM and MLM Frameworks
ERIC Educational Resources Information Center
Wu, Wei; West, Stephen G.; Taylor, Aaron B.
2009-01-01
Evaluating overall model fit for growth curve models involves 3 challenging issues. (a) Three types of longitudinal data with different implications for model fit may be distinguished: balanced on time with complete data, balanced on time with data missing at random, and unbalanced on time. (b) Traditional work on fit from the structural equation…
Are Physical Education Majors Models for Fitness?
ERIC Educational Resources Information Center
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…
Fitting Neuron Models to Spike Trains
Rossant, Cyrille; Goodman, Dan F. M.; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K.; Brette, Romain
2011-01-01
Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input–output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model. PMID:21415925
Pearson, Ralph G.
1981-01-01
The energies of several two- and three-electron atoms, in both ground states and excited states, are calculated by a very simple semiclassical model. The only change from Bohr's original method is to replace definite orbits by probability distribution functions based on classical dynamics. The energies are better than Hartree-Fock values. There is still a need for an exchange-energy correction. Images PMID:16593047
Students' Models of Curve Fitting: A Models and Modeling Perspective
ERIC Educational Resources Information Center
Gupta, Shweta
2010-01-01
The Models and Modeling Perspectives (MMP) has evolved out of research that began 26 years ago. MMP researchers use Model Eliciting Activities (MEAs) to elicit students' mental models. In this study MMP was used as the conceptual framework to investigate the nature of students' models of curve fitting in a problem-solving environment consisting of…
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Hollman, David S; Schaefer, Henry F; Valeev, Edward F
2014-02-14
A local density fitting scheme is considered in which atomic orbital (AO) products are approximated using only auxiliary AOs located on one of the nuclei in that product. The possibility of variational collapse to an unphysical "attractive electron" state that can affect such density fitting [P. Merlot, T. Kjærgaard, T. Helgaker, R. Lindh, F. Aquilante, S. Reine, and T. B. Pedersen, J. Comput. Chem. 34, 1486 (2013)] is alleviated by including atom-wise semidiagonal integrals exactly. Our approach leads to a significant decrease in the computational cost of density fitting for Hartree-Fock theory while still producing results with errors 2-5 times smaller than standard, nonlocal density fitting. Our method allows for large Hartree-Fock and density functional theory computations with exact exchange to be carried out efficiently on large molecules, which we demonstrate by benchmarking our method on 200 of the most widely used prescription drug molecules. Our new fitting scheme leads to smooth and artifact-free potential energy surfaces and the possibility of relatively simple analytic gradients. PMID:24527902
A predictive fitness model for influenza
NASA Astrophysics Data System (ADS)
Łuksza, Marta; Lässig, Michael
2014-03-01
The seasonal human influenza A/H3N2 virus undergoes rapid evolution, which produces significant year-to-year sequence turnover in the population of circulating strains. Adaptive mutations respond to human immune challenge and occur primarily in antigenic epitopes, the antibody-binding domains of the viral surface protein haemagglutinin. Here we develop a fitness model for haemagglutinin that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a strain: adaptive epitope changes and deleterious mutations outside the epitopes. We infer both fitness components for the strains circulating in a given year, using population-genetic data of all previous strains. From fitness and frequency of each strain, we predict the frequency of its descendent strains in the following year. This fitness model maps the adaptive history of influenza A and suggests a principled method for vaccine selection. Our results call for a more comprehensive epidemiology of influenza and other fast-evolving pathogens that integrates antigenic phenotypes with other viral functions coupled by genetic linkage.
Modeling and Fitting Exoplanet Transit Light Curves
NASA Astrophysics Data System (ADS)
Millholland, Sarah; Ruch, G. T.
2013-01-01
We present a numerical model along with an original fitting routine for the analysis of transiting extra-solar planet light curves. Our light curve model is unique in several ways from other available transit models, such as the analytic eclipse formulae of Mandel & Agol (2002) and Giménez (2006), the modified Eclipsing Binary Orbit Program (EBOP) model implemented in Southworth’s JKTEBOP code (Popper & Etzel 1981; Southworth et al. 2004), or the transit model developed as a part of the EXOFAST fitting suite (Eastman et al. in prep.). Our model employs Keplerian orbital dynamics about the system’s center of mass to properly account for stellar wobble and orbital eccentricity, uses a unique analytic solution derived from Kepler’s Second Law to calculate the projected distance between the centers of the star and planet, and calculates the effect of limb darkening using a simple technique that is different from the commonly used eclipse formulae. We have also devised a unique Monte Carlo style optimization routine for fitting the light curve model to observed transits. We demonstrate that, while the effect of stellar wobble on transit light curves is generally small, it becomes significant as the planet to stellar mass ratio increases and the semi-major axes of the orbits decrease. We also illustrate the appreciable effects of orbital ellipticity on the light curve and the necessity of accounting for its impacts for accurate modeling. We show that our simple limb darkening calculations are as accurate as the analytic equations of Mandel & Agol (2002). Although our Monte Carlo fitting algorithm is not as mathematically rigorous as the Markov Chain Monte Carlo based algorithms most often used to determine exoplanetary system parameters, we show that it is straightforward and returns reliable results. Finally, we show that analyses performed with our model and optimization routine compare favorably with exoplanet characterizations published by groups such as the
Degeneracy and discreteness in cosmological model fitting
NASA Astrophysics Data System (ADS)
Teng, Huan-Yu; Huang, Yuan; Zhang, Tong-Jie
2016-03-01
We explore the problems of degeneracy and discreteness in the standard cosmological model (ΛCDM). We use the Observational Hubble Data (OHD) and the type Ia supernovae (SNe Ia) data to study this issue. In order to describe the discreteness in fitting of data, we define a factor G to test the influence from each single data point and analyze the goodness of G. Our results indicate that a higher absolute value of G shows a better capability of distinguishing models, which means the parameters are restricted into smaller confidence intervals with a larger figure of merit evaluation. Consequently, we claim that the factor G is an effective way of model differentiation when using different models to fit the observational data.
Model Fit after Pairwise Maximum Likelihood
Barendse, M. T.; Ligtvoet, R.; Timmerman, M. E.; Oort, F. J.
2016-01-01
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. PMID:27148136
Model Fit after Pairwise Maximum Likelihood.
Barendse, M T; Ligtvoet, R; Timmerman, M E; Oort, F J
2016-01-01
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. PMID:27148136
Model-based estimation of individual fitness
Link, W.A.; Cooch, E.G.; Cam, E.
2002-01-01
Fitness is the currency of natural selection, a measure of the propagation rate of genotypes into future generations. Its various definitions have the common feature that they are functions of survival and fertility rates. At the individual level, the operative level for natural selection, these rates must be understood as latent features, genetically determined propensities existing at birth. This conception of rates requires that individual fitness be defined and estimated by consideration of the individual in a modelled relation to a group of similar individuals; the only alternative is to consider a sample of size one, unless a clone of identical individuals is available. We present hierarchical models describing individual heterogeneity in survival and fertility rates and allowing for associations between these rates at the individual level. We apply these models to an analysis of life histories of Kittiwakes (Rissa tridactyla) observed at several colonies on the Brittany coast of France. We compare Bayesian estimation of the population distribution of individual fitness with estimation based on treating individual life histories in isolation, as samples of size one (e.g. McGraw and Caswell, 1996).
Model-based estimation of individual fitness
Link, W.A.; Cooch, E.G.; Cam, E.
2002-01-01
Fitness is the currency of natural selection, a measure of the propagation rate of genotypes into future generations. Its various definitions have the common feature that they are functions of survival and fertility rates. At the individual level, the operative level for natural selection, these rates must be understood as latent features, genetically determined propensities existing at birth. This conception of rates requires that individual fitness be defined and estimated by consideration of the individual in a modelled relation to a group of similar individuals; the only alternative is to consider a sample of size one, unless a clone of identical individuals is available. We present hierarchical models describing individual heterogeneity in survival and fertility rates and allowing for associations between these rates at the individual level. We apply these models to an analysis of life histories of Kittiwakes (Rissa tridactyla ) observed at several colonies on the Brittany coast of France. We compare Bayesian estimation of the population distribution of individual fitness with estimation based on treating individual life histories in isolation, as samples of size one (e.g. McGraw & Caswell, 1996).
ERIC Educational Resources Information Center
Hayduk, Leslie
2014-01-01
Researchers using factor analysis tend to dismiss the significant ill fit of factor models by presuming that if their factor model is close-to-fitting, it is probably close to being properly causally specified. Close fit may indeed result from a model being close to properly causally specified, but close-fitting factor models can also be seriously…
An Investigation of Goodness of Model Data Fit
ERIC Educational Resources Information Center
Onder, Ismail
2007-01-01
IRT models' advantages can only be realized when the model fits the data set of interest. Therefore, this study aimed to investigate which IRT model will provide the best fit to the data obtained from OZDEBYR OSS 2004 D-II Exam Science Test. In goodness-of-fit analysis, first the model assumptions and then the expected model features were checked.…
An Investigation of Item Fit Statistics for Mixed IRT Models
ERIC Educational Resources Information Center
Chon, Kyong Hee
2009-01-01
The purpose of this study was to investigate procedures for assessing model fit of IRT models for mixed format data. In this study, various IRT model combinations were fitted to data containing both dichotomous and polytomous item responses, and the suitability of the chosen model mixtures was evaluated based on a number of model fit procedures.…
Fitting and Modeling of AXAF Data with the ASC Fitting Application
NASA Astrophysics Data System (ADS)
Doe, S.; Ljungberg, M.; Siemiginowska, A.; Joye, W.
The AXAF mission will provide X-ray data with unprecedented spatial and spectral resolution. Because of the high quality of these data, the AXAF Science Center will provide a new data analysis system--including a new fitting application. Our intent is to enable users to do fitting that is too awkward with, or beyond, the scope of existing astronomical fitting software. Our main goals are: 1) to take advantage of the full capabilities of the AXAF, we intend to provide a more sophisticated modeling capability (i.e., models that are $f(x,y,E,t)$, models to simulate the response of AXAF instruments, and models that enable ``joint-mode'' fitting, i.e., combined spatial-spectral or spectral-temporal fitting); and 2) to provide users with a wide variety of models, optimization methods, and fit statistics. In this paper, we discuss the use of an object-oriented approach in our implementation, the current features of the fitting application, and the features scheduled to be added in the coming year of development. Current features include: an interactive, command-line interface; a modeling language, which allows users to build models from arithmetic combinations of base functions; a suite of optimization and fit statistics; the ability to perform fits to multiple data sets simultaneously; and, an interface with SM and SAOtng to plot or image data, models, and/or residuals from a fit. We currently provide a modeling capability in one or two dimensions, and have recently made an effort to perform spectral fitting in a manner similar to XSPEC. We also allow users to dynamically link the fitting application to their own algorithms. Our goals for the coming year include incorporating the XSPEC model library as a subset of models available in the application, enabling ``joint-mode'' analysis and adding support for new algorithms.
Evaluating Latent Growth Curve Models Using Individual Fit Statistics
ERIC Educational Resources Information Center
Coffman, Donna L.; Millsap, Roger E.
2006-01-01
The usefulness of assessing individual fit in latent growth curve models was examined. The study used simulated data based on an unconditional and a conditional latent growth curve model with a linear component and a small quadratic component and a linear model was fit to the data. Then the overall fit of linear and quadratic models to these data…
Stochastic models for atomic clocks
NASA Technical Reports Server (NTRS)
Barnes, J. A.; Jones, R. H.; Tryon, P. V.; Allan, D. W.
1983-01-01
For the atomic clocks used in the National Bureau of Standards Time Scales, an adequate model is the superposition of white FM, random walk FM, and linear frequency drift for times longer than about one minute. The model was tested on several clocks using maximum likelihood techniques for parameter estimation and the residuals were acceptably random. Conventional diagnostics indicate that additional model elements contribute no significant improvement to the model even at the expense of the added model complexity.
Goodness-of-Fit Assessment of Item Response Theory Models
ERIC Educational Resources Information Center
Maydeu-Olivares, Alberto
2013-01-01
The article provides an overview of goodness-of-fit assessment methods for item response theory (IRT) models. It is now possible to obtain accurate "p"-values of the overall fit of the model if bivariate information statistics are used. Several alternative approaches are described. As the validity of inferences drawn on the fitted model…
ERIC Educational Resources Information Center
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…
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. PMID:27052568
Hyper-Fit: Fitting Linear Models to Multidimensional Data with Multivariate Gaussian Uncertainties
NASA Astrophysics Data System (ADS)
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.
Curve fitting methods for solar radiation data modeling
Karim, Samsul Ariffin Abdul E-mail: balbir@petronas.com.my; Singh, Balbir Singh Mahinder E-mail: balbir@petronas.com.my
2014-10-24
This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R{sup 2}. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods.
Curve fitting methods for solar radiation data modeling
NASA Astrophysics Data System (ADS)
Karim, Samsul Ariffin Abdul; Singh, Balbir Singh Mahinder
2014-10-01
This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R2. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods.
Deviance statistics in model fit and selection in ROC studies
NASA Astrophysics Data System (ADS)
Lei, Tianhu; Bae, K. Ty
2013-03-01
A general non-linear regression model-based Bayesian inference approach is used in our ROC (Receiver Operating Characteristics) study. In the sampling of posterior distribution, two prior models - continuous Gaussian and discrete categorical - are used for the scale parameter. How to judge Goodness-of-Fit (GOF) of each model and how to criticize these two models, Deviance statistics and Deviance information criterion (DIC) are adopted to address these problems. Model fit and model selection focus on the adequacy of models. Judging model adequacy is essentially measuring agreement of model and observations. Deviance statistics and DIC provide overall measures on model fit and selection. In order to investigate model fit at each category of observations, we find that the cumulative, exponential contributions from individual observations to Deviance statistics are good estimates of FPF (false positive fraction) and TPF (true positive fraction) on which the ROC curve is based. This finding further leads to a new measure for model fit, called FPF-TPF distance, which is an Euclidean distance defined on FPF-TPF space. It combines both local and global fitting. Deviance statistics and FPFTPF distance are shown to be consistent and in good agreement. Theoretical derivation and numerical simulations for this new method for model fit and model selection of ROC data analysis are included. Keywords: General non-linear regression model, Bayesian Inference, Markov Chain Monte Carlo (MCMC) method, Goodness-of-Fit (GOF), Model selection, Deviance statistics, Deviance information criterion (DIC), Continuous conjugate prior, Discrete categorical prior. ∗
On the Fitting of Non-Linear, Empirical Functions for the Fitting of Model Crater Ages
NASA Astrophysics Data System (ADS)
Weaver, B. P.; Hilbe, J. M.; Robbins, S. J.; Plesko, C. S.; Riggs, J. D.
2015-05-01
Fitting model crater production functions to observed crater data is considered an "art" by many, and there is no standard in the field for how best to do it. We will discuss mathematical techniques' pros and cons and make recommendations.
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
A comparative study of the results provided by two strategies for fitting data to Latent Trait Theory Models has been performed. The first, called Total-Persons-Items (TPI), is structured in three phases: 1) assessment of item fit, 2) assessment of person fit; and finally, 3) overall fit of data to the models (items and persons). The second strategy, the Total-Items-Persons (TIP), changes the order of the phases: 1) assessment of person fit, 2) assessment of item fit and, 3) overall fit of data to the models. To verify the results of these two strategies, a set of 30 items, designed to measure religious attitude, was administered to a sample of 821 persons. The Latent Trait Theory Models used were the Partial Credit Model and the Rating Scale Model. The results underline an important difference between the two procedures: the TPI maximizes the number of persons with good fit and the TIP maximizes the number of items with good fit. Moreover, a procedure for controlling the sensitivity of fit to sample size is proposed. PMID:12011498
Goodness of Model-Data Fit and Invariant Measurement
ERIC Educational Resources Information Center
Engelhard, George, Jr.; Perkins, Aminah
2013-01-01
In this commentary, Englehard and Perkins remark that Maydeu-Olivares has presented a framework for evaluating the goodness of model-data fit for item response theory (IRT) models and correctly points out that overall goodness-of-fit evaluations of IRT models and data are not generally explored within most applications in educational and…
A Comparison of Item Fit Statistics for Mixed IRT Models
ERIC Educational Resources Information Center
Chon, Kyong Hee; Lee, Won-Chan; Dunbar, Stephen B.
2010-01-01
In this study we examined procedures for assessing model-data fit of item response theory (IRT) models for mixed format data. The model fit indices used in this study include PARSCALE's G[superscript 2], Orlando and Thissen's S-X[superscript 2] and S-G[superscript 2], and Stone's chi[superscript 2*] and G[superscript 2*]. To investigate the…
A Quantum Model of Atoms (the Energy Levels of Atoms).
ERIC Educational Resources Information Center
Rafie, Francois
2001-01-01
Discusses the model for all atoms which was developed on the same basis as Bohr's model for the hydrogen atom. Calculates the radii and the energies of the orbits. Demonstrates how the model obeys the de Broglie's hypothesis that the moving electron exhibits both wave and particle properties. (Author/ASK)
"Electronium": A Quantum Atomic Teaching Model.
ERIC Educational Resources Information Center
Budde, Marion; Niedderer, Hans; Scott, Philip; Leach, John
2002-01-01
Outlines an alternative atomic model to the probability model, the descriptive quantum atomic model Electronium. Discusses the way in which it is intended to support students in learning quantum-mechanical concepts. (Author/MM)
From electron microscopy maps to atomic structures using normal mode-based fitting.
Hinsen, Konrad; Beaumont, Edward; Fournier, Bertrand; Lacapère, Jean-Jacques
2010-01-01
Electron microscopy (EM) has made possible to solve the structure of many proteins. However, the resolution of some of the EM maps is too low for interpretation at the atomic level, which is particularly important to describe function. We describe methods that combine low-resolution EM data with atomic structures for different conformations of the same protein in order to produce atomic models compatible with the EM map.We illustrate these methods with EM data from decavanadate-induced tubular crystals of a pseudo-phosphorylated intermediate of Ca-ATPase and the various atomic structures of other intermediates available in the Protein Data Bank (PDB). Determination of atomic structure permits not only to analyse protein-protein interactions in the crystals, but also to localize residues in the proximity of the crystallizing agent both within Ca-ATPase and between Ca-ATPase molecules. PMID:20665270
Model-Free CUSUM Methods for Person Fit
ERIC Educational Resources Information Center
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…
Sensitivity of Fit Indices to Misspecification in Growth Curve Models
ERIC Educational Resources Information Center
Wu, Wei; West, Stephen G.
2010-01-01
This study investigated the sensitivity of fit indices to model misspecification in within-individual covariance structure, between-individual covariance structure, and marginal mean structure in growth curve models. Five commonly used fit indices were examined, including the likelihood ratio test statistic, root mean square error of…
Modeling of atom-diatom scattering. Technical report
Sindoni, J.M.
1992-05-30
This report entails the work performed on modeling atom-diatom scattering processes utilizing the Impulse Approach (IA). Results of the model, obtained with a computer code, have proven to be in remarkable agreement with laboratory measurements for several atom-diatom scattering systems. Two scattering systems, in particular, that were successfully modeled and compared to measurements were Ar-KBr and Ar-CsF. The IA model provided an explanation for the rapid deactivation evident in the Ar-KBr system. Experimental results in the Ar-CsF experiment that could not be explained by conventional models were also successfully modeled using the IA. Results fit the experimental observations.
NASA Astrophysics Data System (ADS)
Li, Jun; Jiang, Bin; Guo, Hua
2013-11-01
A rigorous, general, and simple method to fit global and permutation invariant potential energy surfaces (PESs) using neural networks (NNs) is discussed. This so-called permutation invariant polynomial neural network (PIP-NN) method imposes permutation symmetry by using in its input a set of symmetry functions based on PIPs. For systems with more than three atoms, it is shown that the number of symmetry functions in the input vector needs to be larger than the number of internal coordinates in order to include both the primary and secondary invariant polynomials. This PIP-NN method is successfully demonstrated in three atom-triatomic reactive systems, resulting in full-dimensional global PESs with average errors on the order of meV. These PESs are used in full-dimensional quantum dynamical calculations.
Li, Jun; Jiang, Bin; Guo, Hua
2013-11-28
A rigorous, general, and simple method to fit global and permutation invariant potential energy surfaces (PESs) using neural networks (NNs) is discussed. This so-called permutation invariant polynomial neural network (PIP-NN) method imposes permutation symmetry by using in its input a set of symmetry functions based on PIPs. For systems with more than three atoms, it is shown that the number of symmetry functions in the input vector needs to be larger than the number of internal coordinates in order to include both the primary and secondary invariant polynomials. This PIP-NN method is successfully demonstrated in three atom-triatomic reactive systems, resulting in full-dimensional global PESs with average errors on the order of meV. These PESs are used in full-dimensional quantum dynamical calculations.
HDFITS: Porting the FITS data model to HDF5
NASA Astrophysics Data System (ADS)
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.
A liquid drop model for embedded atom method cluster energies
NASA Technical Reports Server (NTRS)
Finley, C. W.; Abel, P. B.; Ferrante, J.
1996-01-01
Minimum energy configurations for homonuclear clusters containing from two to twenty-two atoms of six metals, Ag, Au, Cu, Ni, Pd, and Pt have been calculated using the Embedded Atom Method (EAM). The average energy per atom as a function of cluster size has been fit to a liquid drop model, giving estimates of the surface and curvature energies. The liquid drop model gives a good representation of the relationship between average energy and cluster size. As a test the resulting surface energies are compared to EAM surface energy calculations for various low-index crystal faces with reasonable agreement.
Consequences of Fitting Nonidentified Latent Class Models
ERIC Educational Resources Information Center
Abar, Beau; Loken, Eric
2012-01-01
Latent class models are becoming more popular in behavioral research. When models with a large number of latent classes relative to the number of manifest indicators are estimated, researchers must consider the possibility that the model is not identified. It is not enough to determine that the model has positive degrees of freedom. A well-known…
Fitting Value-Added Models in R
ERIC Educational Resources Information Center
Doran, Harold C.; Lockwood, J. R.
2006-01-01
Value-added models of student achievement have received widespread attention in light of the current test-based accountability movement. These models use longitudinal growth modeling techniques to identify effective schools or teachers based upon the results of changes in student achievement test scores. Given their increasing popularity, this…
Two Strategies for Fitting Real Data to Rasch Polytomous Models.
ERIC Educational Resources Information Center
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…
Evaluating Item Fit for Multidimensional Item Response Models
ERIC Educational Resources Information Center
Zhang, Bo; Stone, Clement A.
2008-01-01
This research examines the utility of the s-x[superscript 2] statistic proposed by Orlando and Thissen (2000) in evaluating item fit for multidimensional item response models. Monte Carlo simulation was conducted to investigate both the Type I error and statistical power of this fit statistic in analyzing two kinds of multidimensional test…
How Good Are Statistical Models at Approximating Complex Fitness Landscapes?
du Plessis, Louis; Leventhal, Gabriel E; Bonhoeffer, Sebastian
2016-09-01
Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations. PMID:27189564
How Good Are Statistical Models at Approximating Complex Fitness Landscapes?
du Plessis, Louis; Leventhal, Gabriel E.; Bonhoeffer, Sebastian
2016-01-01
Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations. PMID:27189564
Fitting population models from field data
Emlen, J.M.; Freeman, D.C.; Kirchhoff, M.D.; Alados, C.L.; Escos, J.; Duda, J.J.
2003-01-01
The application of population and community ecology to solving real-world problems requires population and community dynamics models that reflect the myriad patterns of interaction among organisms and between the biotic and physical environments. Appropriate models are not hard to construct, but the experimental manipulations needed to evaluate their defining coefficients are often both time consuming and costly, and sometimes environmentally destructive, as well. In this paper we present an empirical approach for finding the coefficients of broadly inclusive models without the need for environmental manipulation, demonstrate the approach with both an animal and a plant example, and suggest possible applications. Software has been developed, and is available from the senior author, with a manual describing both field and analytic procedures.
MAPCLUS: A Mathematical Programming Approach to Fitting the ADCLUS Model.
ERIC Educational Resources Information Center
Arabie, Phipps
1980-01-01
A new computing algorithm, MAPCLUS (Mathematical Programming Clustering), for fitting the Shephard-Arabie ADCLUS (Additive Clustering) model is presented. Details and benefits of the algorithm are discussed. (Author/JKS)
A New Tradition To Fit the Model.
ERIC Educational Resources Information Center
Darnell, D. Roe; Rosenthal, Donna McCrohan
2001-01-01
Discusses Cerro Coso Community College in Ridgecrest (California), where 80-85 of all local jobs are with one employer, the China Lake Naval Air Weapons Station (NAWS). States that massive layoffs at NAWS inspired creative ways of rethinking the community college model at Cerro Coso, such as creating the nation's first computer graphics imagery…
Fitting ARMA Time Series by Structural Equation Models.
ERIC Educational Resources Information Center
van Buuren, Stef
1997-01-01
This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)
Relative and Absolute Fit Evaluation in Cognitive Diagnosis Modeling
ERIC Educational Resources Information Center
Chen, Jinsong; de la Torre, Jimmy; Zhang, Zao
2013-01-01
As with any psychometric models, the validity of inferences from cognitive diagnosis models (CDMs) determines the extent to which these models can be useful. For inferences from CDMs to be valid, it is crucial that the fit of the model to the data is ascertained. Based on a simulation study, this study investigated the sensitivity of various fit…
ERIC Educational Resources Information Center
Olsson, Ulf Henning; Troye, Sigurd Villads; Howell, Roy D.
1999-01-01
Used simulation to compare the ability of maximum likelihood (ML) and generalized least-squares (GLS) estimation to provide theoretic fit in models that are parsimonious representations of a true model. The better empirical fit obtained for GLS, compared with ML, was obtained at the cost of lower theoretic fit. (Author/SLD)
Asteroseismic model fitting by comparing ɛnℓ values
NASA Astrophysics Data System (ADS)
Roxburgh, Ian W.
2016-01-01
We present an asteroseismic model fitting algorithm based on comparing model and observed ɛℓ(ν) values defined in terms of frequencies by νnℓ = Δ [ n + ℓ/ 2 + ɛℓ(νnℓ) ] where Δ is an average large separation. We show that if two stellar models have the same interior structure but different outer layers then the difference between their ɛℓ(ν) values, interpolated to the same frequencies, collapses to a function only of frequency, independent of angular degree ℓ. The algorithm tests the goodness fit by comparing the difference in model and observed ɛ values after having subtracted off a best fit ℓ independent function of frequency ℱ(ν), and only requires interpolation in model values and not in observed values so the errors on the observed values are uncorrelated; it is independent of the n values assigned to the radial ordering of the frequencies and does not require the calculation of inner phase shifts of the model. We contrast this to a proposed direct frequency matching technique which minimises the difference between observed and model frequencies after having subtracted off an ℓ independent fit to these differences. We show this technique is flawed in principle, that all models with the same dimensionless structure but any mass and radius have the same quality of fit to an observed data set, and that it can give erroneous best fit models. We illustrate the epsilon matching technique by comparing stellar models and then apply it to data on HD 177153 (aka Perky). On comparing observations with a set of main sequence evolutionary models we find that models which satisfy constraints on the luminosity, radius, Δ, and on ɛ matching, have masses in the range 1.155 ± 0.035 M⊙ and ages in the range 4.486 ± 0.250 × 109 yr. Since the large separation and the radius are surface layer dependent we examine "pure surface layer independent" model fitting where the only constraints on the model fitting are on the luminosity and epsilon
Transit Model Fitting in the Kepler Science Operations Center Pipeline
NASA Astrophysics Data System (ADS)
Li, Jie; Burke, C. J.; Jenkins, J. M.; Quintana, E. V.; Rowe, J. F.; Seader, S. E.; Tenenbaum, P.; Twicken, J. D.
2012-05-01
We describe the algorithm and performance of the transit model fitting of the Kepler Science Operations Center (SOC) Pipeline. Light curves of long cadence targets are subjected to the Transiting Planet Search (TPS) component of the Kepler SOC Pipeline. Those targets for which a Threshold Crossing Event (TCE) is generated in the transit search are subsequently processed in the Data Validation (DV) component. The light curves may span one or more Kepler observing quarters, and data may not be available for any given target in all quarters. Transit model parameters are fitted in DV to transit-like signatures in the light curves of target stars with TCEs. The fitted parameters are used to generate a predicted light curve based on the transit model. The residual flux time series of the target star, with the predicted light curve removed, is fed back to TPS to search for additional TCEs. The iterative process of transit model fitting and transiting planet search continues until no TCE is generated from the residual flux time series or a planet candidate limit is reached. The transit model includes five parameters to be fitted: transit epoch time (i.e. central time of first transit), orbital period, impact parameter, ratio of planet radius to star radius and ratio of semi-major axis to star radius. The initial values of the fit parameters are determined from the TCE values provided by TPS. A limb darkening model is included in the transit model to generate the predicted light curve. The transit model fitting results are used in the diagnostic tests in DV, such as the centroid motion test, eclipsing binary discrimination tests, etc., which helps to validate planet candidates and identify false positive detections. Funding for the Kepler Mission has been provided by the NASA Science Mission Directorate.
Modeling battery life through changes in voltage fit coefficients
NASA Technical Reports Server (NTRS)
Fox, D.; Mcdermott, P.
1983-01-01
A number of 12 ampere-hour cells, nickel cadmium, were cycled under various conditions of temperature and depth of discharge. Using this data, it was confirmed that a five parameter fit equation could be used to model the data within a few millivolts. Both charge and discharge curves can be fit with accuracies in the range of one or two millivolts. The fit coefficients when plotted versus cycles show definite trends and patterns which can be used in an operational sense to predict battery voltage as a function of temperature and depth of discharge.
Atomic Data for X-ray Spectrum Synthesis: Sensitivity Analysis and Consequences for Spectral Fitting
NASA Astrophysics Data System (ADS)
Kallman, Timothy R.
2006-09-01
A great deal of work has been devoted to the accumulation of accurate quantities describing atomic processes for use in analysis of astrophysical spectra. But in many situations of interest the interpretation of a quantity which is observed, such as a line flux, depends on the results of a modeling- or spectrum synthesis code. The results of such a code depends in turn on many atomic rates or cross sections, and the sensitivity of the observable quantity on the various rates and cross sections may be non-linear and if so cannot easily be derived analytically. In such cases the most practical approach to understanding the sensitivity of observables to atomic cross sections is to perform numerical experiments, by calculating models with various rates perturbed by random (but known) factors. In addition, it is useful to compare the results of such experiments with some sample observations, in order to focus attention on the rates which are of the greatest relevance to real observations. I will present some attempts to carry out this program, focussing on two sample datasets taken with the Chandra HETG. I will discuss the sensitivity of synthetic spectra to atomic data affecting ionization balance, temperature, and line opacity or emissivity, and discuss the implications for the ultimate goal of inferring astrophysical parameters. In addition, I will discuss the likely effects on the ionization balance and spectrum synthesis due to the adoption of some recent calculations of dielectronic recombination rate coefficients.
Akaike information criterion to select well-fit resist models
NASA Astrophysics Data System (ADS)
Burbine, Andrew; Fryer, David; Sturtevant, John
2015-03-01
In the field of model design and selection, there is always a risk that a model is over-fit to the data used to train the model. A model is well suited when it describes the physical system and not the stochastic behavior of the particular data collected. K-fold cross validation is a method to check this potential over-fitting to the data by calibrating with k-number of folds in the data, typically between 4 and 10. Model training is a computationally expensive operation, however, and given a wide choice of candidate models, calibrating each one repeatedly becomes prohibitively time consuming. Akaike information criterion (AIC) is an information-theoretic approach to model selection based on the maximized log-likelihood for a given model that only needs a single calibration per model. It is used in this study to demonstrate model ranking and selection among compact resist modelforms that have various numbers and types of terms to describe photoresist behavior. It is shown that there is a good correspondence of AIC to K-fold cross validation in selecting the best modelform, and it is further shown that over-fitting is, in most cases, not indicated. In modelforms with more than 40 fitting parameters, the size of the calibration data set benefits from additional parameters, statistically validating the model complexity.
Twitter classification model: the ABC of two million fitness tweets.
Vickey, Theodore A; Ginis, Kathleen Martin; Dabrowski, Maciej
2013-09-01
The purpose of this project was to design and test data collection and management tools that can be used to study the use of mobile fitness applications and social networking within the context of physical activity. This project was conducted over a 6-month period and involved collecting publically shared Twitter data from five mobile fitness apps (Nike+, RunKeeper, MyFitnessPal, Endomondo, and dailymile). During that time, over 2.8 million tweets were collected, processed, and categorized using an online tweet collection application and a customized JavaScript. Using the grounded theory, a classification model was developed to categorize and understand the types of information being shared by application users. Our data show that by tracking mobile fitness app hashtags, a wealth of information can be gathered to include but not limited to daily use patterns, exercise frequency, location-based workouts, and overall workout sentiment. PMID:24073182
Statistics in asteroseismology: Evaluating confidence in stellar model fits
NASA Astrophysics Data System (ADS)
Johnson, Erik Stewart
We evaluate techniques presently used to match slates of stellar evolution models to asteroseismic observations by using numeric simulations of the model fits with randomly generated numbers. Measuring the quality of the fit between a simulated model and the star by a raw chi2 shows how well a reported model fit to a given star compares to a distribution of random model fits to the same star. The distribution of chi2 between "models" and simulated pulsations exhibits the behavior of a log-normal distribution, which suggests a link between the distribution and an analytic solution. Since the shape of the distribution strongly depends on the peculiar distribution of modes within the simulations, there appears to be no universal analytic quality-of-fit criterion, so evaluating seismic model fits must be done on a case--by--case basis. We also perform numeric simulations to determine the validity of spacings between pulsations by comparing the spacing between the observed modes of a given star to those between 106 sets of random numbers using the Q parameter of the Kolmogorov-Smirnov test. The observed periods in GD 358 and PG 1159--035 outperform these numeric simulations and validate their perceived spacings, while there is little support for spacings in PG 1219+534 or PG 0014+067. The best period spacing in BPM 37098 is marginally significant. The observed frequencies of eta Bootis outstrip random sets with an equal number of modes, but the modes are selectively chosen by the investigators from over 70 detected periodicities. When choosing the random data from sets of 70 values, the observed modes' spacings are reproducible by at least 2% of the random sets. Comparing asteroseismic data to random numbers statistically gauge the prominence of any possible spacing which removes another element of bias from asteroseismic analysis.
Eigen model with general fitness functions and degradation rates
NASA Astrophysics Data System (ADS)
Hu, Chin-Kun; Saakian, David B.
2006-03-01
We present an exact solution of Eigen's quasispecies model with a general degradation rate and fitness functions, including a square root decrease of fitness with increasing Hamming distance from the wild type. The found behavior of the model with a degradation rate is analogous to a viral quasi-species under attack by the immune system of the host. Our exact solutions also revise the known results of neutral networks in quasispecies theory. To explain the existence of mutants with large Hamming distances from the wild type, we propose three different modifications of the Eigen model: mutation landscape, multiple adjacent mutations, and frequency-dependent fitness in which the steady state solution shows a multi-center behavior.
Evolution in random fitness landscapes: the infinite sites model
NASA Astrophysics Data System (ADS)
Park, Su-Chan; Krug, Joachim
2008-04-01
We consider the evolution of an asexually reproducing population in an uncorrelated random fitness landscape in the limit of infinite genome size, which implies that each mutation generates a new fitness value drawn from a probability distribution g(w). This is the finite population version of Kingman's house of cards model (Kingman 1978 J. Appl. Probab. 15 1). In contrast to Kingman's work, the focus here is on unbounded distributions g(w) which lead to an indefinite growth of the population fitness. The model is solved analytically in the limit of infinite population size N \\to \\infty and simulated numerically for finite N. When the genome-wide mutation probability U is small, the long-time behavior of the model reduces to a point process of fixation events, which is referred to as a diluted record process (DRP). The DRP is similar to the standard record process except that a new record candidate (a number that exceeds all previous entries in the sequence) is accepted only with a certain probability that depends on the values of the current record and the candidate. We develop a systematic analytic approximation scheme for the DRP. At finite U the fitness frequency distribution of the population decomposes into a stationary part due to mutations and a traveling wave component due to selection, which is shown to imply a reduction of the mean fitness by a factor of 1-U compared to the U \\to 0 limit.
Time-domain fitting of battery electrochemical impedance models
NASA Astrophysics Data System (ADS)
Alavi, S. M. M.; Birkl, C. R.; Howey, D. A.
2015-08-01
Electrochemical impedance spectroscopy (EIS) is an effective technique for diagnosing the behaviour of electrochemical devices such as batteries and fuel cells, usually by fitting data to an equivalent circuit model (ECM). The common approach in the laboratory is to measure the impedance spectrum of a cell in the frequency domain using a single sine sweep signal, then fit the ECM parameters in the frequency domain. This paper focuses instead on estimation of the ECM parameters directly from time-domain data. This may be advantageous for parameter estimation in practical applications such as automotive systems including battery-powered vehicles, where the data may be heavily corrupted by noise. The proposed methodology is based on the simplified refined instrumental variable for continuous-time fractional systems method ('srivcf'), provided by the Crone toolbox [1,2], combined with gradient-based optimisation to estimate the order of the fractional term in the ECM. The approach was tested first on synthetic data and then on real data measured from a 26650 lithium-ion iron phosphate cell with low-cost equipment. The resulting Nyquist plots from the time-domain fitted models match the impedance spectrum closely (much more accurately than when a Randles model is assumed), and the fitted parameters as separately determined through a laboratory potentiostat with frequency domain fitting match to within 13%.
Prill, Dragica; Juhas, Pavol; Billinge, Simon J. L.; Schmidt, Martin U.
2016-01-01
In this study, a method towards the solution and refinement of organic crystal structures by fitting to the atomic pair distribution function (PDF) is developed. Approximate lattice parameters and molecular geometry must be given as input. The molecule is generally treated as a rigid body. The positions and orientations of the molecules inside the unit cell are optimized starting from random values. The PDF is obtained from carefully measured X-ray powder diffraction data. The method resembles `real-space' methods for structure solution from powder data, but works with PDF data instead of the diffraction pattern itself. As such it may bemore » used in situations where the organic compounds are not long-range-ordered, are poorly crystalline, or nanocrystalline. The procedure was applied to solve and refine the crystal structures of quinacridone (β phase), naphthalene and allopurinol. In the case of allopurinol it was even possible to successfully solve and refine the structure in P1 with four independent molecules. As an example of a flexible molecule, the crystal structure of paracetamol was refined using restraints for bond lengths, bond angles and selected torsion angles. In all cases, the resulting structures are in excellent agreement with structures from single-crystal data.« less
Prill, Dragica; Juhás, Pavol; Billinge, Simon J L; Schmidt, Martin U
2016-01-01
A method towards the solution and refinement of organic crystal structures by fitting to the atomic pair distribution function (PDF) is developed. Approximate lattice parameters and molecular geometry must be given as input. The molecule is generally treated as a rigid body. The positions and orientations of the molecules inside the unit cell are optimized starting from random values. The PDF is obtained from carefully measured X-ray powder diffraction data. The method resembles `real-space' methods for structure solution from powder data, but works with PDF data instead of the diffraction pattern itself. As such it may be used in situations where the organic compounds are not long-range-ordered, are poorly crystalline, or nanocrystalline. The procedure was applied to solve and refine the crystal structures of quinacridone (β phase), naphthalene and allopurinol. In the case of allopurinol it was even possible to successfully solve and refine the structure in P1 with four independent molecules. As an example of a flexible molecule, the crystal structure of paracetamol was refined using restraints for bond lengths, bond angles and selected torsion angles. In all cases, the resulting structures are in excellent agreement with structures from single-crystal data. PMID:26697868
Prill, Dragica; Juhas, Pavol; Billinge, Simon J. L.; Schmidt, Martin U.
2016-01-01
In this study, a method towards the solution and refinement of organic crystal structures by fitting to the atomic pair distribution function (PDF) is developed. Approximate lattice parameters and molecular geometry must be given as input. The molecule is generally treated as a rigid body. The positions and orientations of the molecules inside the unit cell are optimized starting from random values. The PDF is obtained from carefully measured X-ray powder diffraction data. The method resembles `real-space' methods for structure solution from powder data, but works with PDF data instead of the diffraction pattern itself. As such it may be used in situations where the organic compounds are not long-range-ordered, are poorly crystalline, or nanocrystalline. The procedure was applied to solve and refine the crystal structures of quinacridone (β phase), naphthalene and allopurinol. In the case of allopurinol it was even possible to successfully solve and refine the structure in P1 with four independent molecules. As an example of a flexible molecule, the crystal structure of paracetamol was refined using restraints for bond lengths, bond angles and selected torsion angles. In all cases, the resulting structures are in excellent agreement with structures from single-crystal data.
On the accuracy and fitting of transversely isotropic material models.
Feng, Yuan; Okamoto, Ruth J; Genin, Guy M; Bayly, Philip V
2016-08-01
Fiber reinforced structures are central to the form and function of biological tissues. Hyperelastic, transversely isotropic material models are used widely in the modeling and simulation of such tissues. Many of the most widely used models involve strain energy functions that include one or both pseudo-invariants (I4 or I5) to incorporate energy stored in the fibers. In a previous study we showed that both of these invariants must be included in the strain energy function if the material model is to reduce correctly to the well-known framework of transversely isotropic linear elasticity in the limit of small deformations. Even with such a model, fitting of parameters is a challenge. Here, by evaluating the relative roles of I4 and I5 in the responses to simple loadings, we identify loading scenarios in which previous models accounting for only one of these invariants can be expected to provide accurate estimation of material response, and identify mechanical tests that have special utility for fitting of transversely isotropic constitutive models. Results provide guidance for fitting of transversely isotropic constitutive models and for interpretation of the predictions of these models. PMID:27136091
The Gold Medal Fitness Program: A Model for Teacher Change
ERIC Educational Resources Information Center
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 Teaching and…
The conical fit approach to modeling ionospheric total electron content
NASA Technical Reports Server (NTRS)
Sparks, L.; Komjathy, A.; Mannucci, A. J.
2002-01-01
The Global Positioning System (GPS) can be used to measure the integrated electron density along raypaths between satellites and receivers. Such measurements may, in turn, be used to construct regional and global maps of the ionospheric total electron content (TEC). Maps are generated by fitting measurements to an assumed ionospheric model.
Fuzzy Partition Models for Fitting a Set of Partitions.
ERIC Educational Resources Information Center
Gordon, A. D.; Vichi, M.
2001-01-01
Describes methods for fitting a fuzzy consensus partition to a set of partitions of the same set of objects. Describes and illustrates three models defining median partitions and compares these methods to an alternative approach to obtaining a consensus fuzzy partition. Discusses interesting differences in the results. (SLD)
Multidimensional Rasch Model Information-Based Fit Index Accuracy
ERIC Educational Resources Information Center
Harrell-Williams, Leigh M.; Wolfe, Edward W.
2013-01-01
Most research on confirmatory factor analysis using information-based fit indices (Akaike information criterion [AIC], Bayesian information criteria [BIC], bias-corrected AIC [AICc], and consistent AIC [CAIC]) has used a structural equation modeling framework. Minimal research has been done concerning application of these indices to item response…
Statistical assessment of model fit for synthetic aperture radar data
NASA Astrophysics Data System (ADS)
DeVore, Michael D.; O'Sullivan, Joseph A.
2001-08-01
Parametric approaches to problems of inference from observed data often rely on assumed probabilistic models for the data which may be based on knowledge of the physics of the data acquisition. Given a rich enough collection of sample data, the validity of those assumed models can be assessed in a statistical hypothesis testing framework using any of a number of goodness-of-fit tests developed over the last hundred years for this purpose. Such assessments can be used both to compare alternate models for observed data and to help determine the conditions under which a given model breaks down. We apply three such methods, the (chi) 2 test of Karl Pearson, Kolmogorov's goodness-of-fit test, and the D'Agostino-Pearson test for normality, to quantify how well the data fit various models for synthetic aperture radar (SAR) images. The results of these tests are used to compare a conditionally Gaussian model for complex-valued SAR pixel values, a conditionally log-normal model for SAR pixel magnitudes, and a conditionally normal model for SAR pixel quarter-power values. Sample data for these tests are drawn from the publicly released MSTAR dataset.
Nagaoka's atomic model and hyperfine interactions.
Inamura, Takashi T
2016-01-01
The prevailing view of Nagaoka's "Saturnian" atom is so misleading that today many people have an erroneous picture of Nagaoka's vision. They believe it to be a system involving a 'giant core' with electrons circulating just outside. Actually, though, in view of the Coulomb potential related to the atomic nucleus, Nagaoka's model is exactly the same as Rutherford's. This is true of the Bohr atom, too. To give proper credit, Nagaoka should be remembered together with Rutherford and Bohr in the history of the atomic model. It is also pointed out that Nagaoka was a pioneer of understanding hyperfine interactions in order to study nuclear structure. PMID:27063182
The Hydrogen Atom: The Rutherford Model
NASA Astrophysics Data System (ADS)
Tilton, Homer Benjamin
1996-06-01
Early this century Ernest Rutherford established the nuclear model of the hydrogen atom, presently taught as representing the best visual model after modification by Niels Bohr and Arnold Sommerfeld. It replaced the so-called "plum pudding" model of J. J. Thomson which held sway previously. While the Rutherford model represented a large step forward in our understanding of the hydrogen atom, questions remained, and still do.
The Completeness Criterion in Atomic Modeling
NASA Astrophysics Data System (ADS)
Liedahl, Duane A.
2000-10-01
I discuss two variations on the completeness theme in atomic modeling; missing lines as they affect the performance of spectral synthesis codes, and missing configurations as they affect the theoretical emissivities of bright lines, with emphasis on the latter. It is shown that the detrimental effects of working with incomplete atomic models can overshadow those brought about by working with less-than-perfect atomic rates. Atomic models can be brought up to an acceptable level of completeness in a fairly straightforward manner, and on a reasonably short timescale, whereas the long-term goal of comprehensive accuracy is unlikely to be reached on the timescale of the current generation of X-ray observatories. A near-term, albeit imperfect, solution is to hybridize atomic models used to synthesize spectra. A hybrid atomic model is one for which a large-scale atomic model, in which completeness is achieved at the expense of accuracy, is augmented with more accurate atomic quantities as they become available.
Assessing the fit of site-occupancy models
MacKenzie, D.I.; Bailey, L.L.
2004-01-01
Few species are likely to be so evident that they will always be detected at a site when present. Recently a model has been developed that enables estimation of the proportion of area occupied, when the target species is not detected with certainty. Here we apply this modeling approach to data collected on terrestrial salamanders in the Plethodon glutinosus complex in the Great Smoky Mountains National Park, USA, and wish to address the question 'how accurately does the fitted model represent the data?' The goodness-of-fit of the model needs to be assessed in order to make accurate inferences. This article presents a method where a simple Pearson chi-square statistic is calculated and a parametric bootstrap procedure is used to determine whether the observed statistic is unusually large. We found evidence that the most global model considered provides a poor fit to the data, hence estimated an overdispersion factor to adjust model selection procedures and inflate standard errors. Two hypothetical datasets with known assumption violations are also analyzed, illustrating that the method may be used to guide researchers to making appropriate inferences. The results of a simulation study are presented to provide a broader view of the methods properties.
LITpro: a model fitting software for optical interferometry
NASA Astrophysics Data System (ADS)
Tallon-Bosc, I.; Tallon, M.; Thiébaut, E.; Béchet, C.; Mella, G.; Lafrasse, S.; Chesneau, O.; Domiciano de Souza, A.; Duvert, G.; Mourard, D.; Petrov, R.; Vannier, M.
2008-07-01
LITpro is a software for fitting models on data obtained from various stellar optical interferometers, like the VLTI. As a baseline, for modeling the object, it provides a set of elementary geometrical and center-to-limb darkening functions, all combinable together. But it is also designed to make very easy the implementation of more specific models with their own parameters, to be able to use models closer to astrophysical considerations. So LITpro only requires the modeling functions to compute the Fourier transform of the object at given spatial frequencies, and wavelengths and time if needed. From this, LITpro computes all the necessary quantities as needed (e.g. visibilities, spectral energy distribution, partial derivatives of the model, map of the object model). The fitting engine, especially designed for this kind of optimization, is based on a modified Levenberg-Marquardt algorithm and has been successfully tested on real data in a prototype version. It includes a Trust Region Method, minimizing a heterogeneous non-linear and non-convex criterion and allows the user to set boundaries on free parameters. From a robust local minimization algorithm and a starting points strategy, a global optimization solution is effectively achieved. Tools have been developped to help users to find the global minimum. LITpro is also designed for performing fitting on heterogeneous data. It will be shown, on an example, how it fits simultaneously interferometric data and spectral energy distribution, with some benefits on the reliability of the solution and a better estimation of errors and correlations on the parameters. That is indeed necessary since present interferometric data are generally multi-wavelengths.
Methodology for fitting and updating predictive accident models with trend.
Connors, Richard D; Maher, Mike; Wood, Alan; Mountain, Linda; Ropkins, Karl
2013-07-01
Reliable predictive accident models (PAMs) (also referred to as Safety Performance Functions (SPFs)) have a variety of important uses in traffic safety research and practice. They are used to help identify sites in need of remedial treatment, in the design of transport schemes to assess safety implications, and to estimate the effectiveness of remedial treatments. The PAMs currently in use in the UK are now quite old; the data used in their development was gathered up to 30 years ago. Many changes have occurred over that period in road and vehicle design, in road safety campaigns and legislation, and the national accident rate has fallen substantially. It seems unlikely that these ageing models can be relied upon to provide accurate and reliable predictions of accident frequencies on the roads today. This paper addresses a number of methodological issues that arise in seeking practical and efficient ways to update PAMs, whether by re-calibration or by re-fitting. Models for accidents on rural single carriageway roads have been chosen to illustrate these issues, including the choice of distributional assumption for overdispersion, the choice of goodness of fit measures, questions of independence between observations in different years, and between links on the same scheme, the estimation of trends in the models, the uncertainty of predictions, as well as considerations about the most efficient and convenient ways to fit the required models. PMID:23612560
Atomic modeling of the plasma EUV sources
NASA Astrophysics Data System (ADS)
Sasaki, Akira; Sunahara, Atsushi; Furukawa, Hiroyuki; Nishihara, Katsunobu; Nishikawa, Takeshi; Koike, Fumihiro; Tanuma, Hajime
2009-09-01
We present the development of population kinetics models for tin plasmas that can be employed to design an EUV source for microlithography. The atomic kinetic code is constrained for the requirement that the model must be able to calculate spectral emissivity and opacity that can be used in radiation hydrodynamic simulations. Methods to develop compact and reliable atomic model with an appropriate set of atomic states are discussed. Specifically, after investigation of model dependencies and comparison experiment, we improve the effect of configuration interaction and the treatment of satellite lines. Using the present atomic model we discuss the temperature and density dependencies of the emissivity, as well as conditions necessary to obtain high efficiency EUV power at λ = 13.5 nm.
Model fitting and inference under Latent Equilibrium Processes
Bhattacharya, Sourabh; Gelfand, Alan E.; Holsinger, Kent E.
2008-01-01
This paper presents a methodology for model fitting and inference in the context of Bayesian models of the type f(Y | X, θ)f(X | θ)f(θ), where Y is the (set of) observed data, θ is a set of model parameters and X is an unobserved (latent) stationary stochastic process induced by the first order transition model f(X(t+1) | X(t), θ), where X(t) denotes the state of the process at time (or generation) t. The crucial feature of the above type of model is that, given θ, the transition model f(X(t+1) | X(t), θ) is known but the distribution of the stochastic process in equilibrium, that is f(X | θ), is, except in very special cases, intractable, hence unknown. A further point to note is that the data Y has been assumed to be observed when the underlying process is in equilibrium. In other words, the data is not collected dynamically over time. We refer to such specification as a latent equilibrium process (LEP) model. It is motivated by problems in population genetics (though other applications are discussed), where it is of interest to learn about parameters such as mutation and migration rates and population sizes, given a sample of allele frequencies at one or more loci. In such problems it is natural to assume that the distribution of the observed allele frequencies depends on the true (unobserved) population allele frequencies, whereas the distribution of the true allele frequencies is only indirectly specified through a transition model. As a hierarchical specification, it is natural to fit the LEP within a Bayesian framework. Fitting such models is usually done via Markov chain Monte Carlo (MCMC). However, we demonstrate that, in the case of LEP models, implementation of MCMC is far from straightforward. The main contribution of this paper is to provide a methodology to implement MCMC for LEP models. We demonstrate our approach in population genetics problems with both simulated and real data sets. The resultant model fitting is computationally intensive
Atmospheric Turbulence Modeling for Aerospace Vehicles: Fractional Order Fit
NASA Technical Reports Server (NTRS)
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.
ERIC Educational Resources Information Center
Thissen, David
2013-01-01
In this commentary, David Thissen states that "Goodness-of-fit assessment for IRT models is maturing; it has come a long way from zero." Thissen then references prior works on "goodness of fit" in the index of Lord and Novick's (1968) classic text; Yen (1984); Drasgow, Levine, Tsien, Williams, and Mead (1995); Chen and…
Blanquart, François; Bataillon, Thomas
2016-01-01
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. PMID:27052568
Chapman, Michael S.; Trzynka, Andrew; Chapman, Brynmor K.
2013-01-01
When refining the fit of component atomic structures into electron microscopic reconstructions, use of a resolution-dependent atomic density function makes it possible to jointly optimize the atomic model and imaging parameters of the microscope. Atomic density is calculated by one-dimensional Fourier transform of atomic form factors convoluted with a microscope envelope correction and a low-pass filter, allowing refinement of imaging parameters such as resolution, by optimizing the agreement of calculated and experimental maps. A similar approach allows refinement of atomic displacement parameters, providing indications of molecular flexibility even at low resolution. A modest improvement in atomic coordinates is possible following optimization of these additional parameters. Methods have been implemented in a Python program that can be used in stand-alone mode for rigid-group refinement, or embedded in other optimizers for flexible refinement with stereochemical restraints. The approach is demonstrated with refinements of virus and chaperonin structures at resolutions of 9 through 4.5 Å, representing regimes where rigid-group and fully flexible parameterizations are appropriate. Through comparisons to known crystal structures, flexible fitting by RSRef is shown to be an improvement relative to other methods and to generate models with all-atom rms accuracies of 1.5–2.5 Å at resolutions of 4.5–6 Å. PMID:23376441
Chapman, Michael S; Trzynka, Andrew; Chapman, Brynmor K
2013-04-01
When refining the fit of component atomic structures into electron microscopic reconstructions, use of a resolution-dependent atomic density function makes it possible to jointly optimize the atomic model and imaging parameters of the microscope. Atomic density is calculated by one-dimensional Fourier transform of atomic form factors convoluted with a microscope envelope correction and a low-pass filter, allowing refinement of imaging parameters such as resolution, by optimizing the agreement of calculated and experimental maps. A similar approach allows refinement of atomic displacement parameters, providing indications of molecular flexibility even at low resolution. A modest improvement in atomic coordinates is possible following optimization of these additional parameters. Methods have been implemented in a Python program that can be used in stand-alone mode for rigid-group refinement, or embedded in other optimizers for flexible refinement with stereochemical restraints. The approach is demonstrated with refinements of virus and chaperonin structures at resolutions of 9 through 4.5 Å, representing regimes where rigid-group and fully flexible parameterizations are appropriate. Through comparisons to known crystal structures, flexible fitting by RSRef is shown to be an improvement relative to other methods and to generate models with all-atom rms accuracies of 1.5-2.5 Å at resolutions of 4.5-6 Å. PMID:23376441
Bayesian Data-Model Fit Assessment for Structural Equation Modeling
ERIC Educational Resources Information Center
Levy, Roy
2011-01-01
Bayesian approaches to modeling are receiving an increasing amount of attention in the areas of model construction and estimation in factor analysis, structural equation modeling (SEM), and related latent variable models. However, model diagnostics and model criticism remain relatively understudied aspects of Bayesian SEM. This article describes…
Goodness-of-fit diagnostics for Bayesian hierarchical models.
Yuan, Ying; Johnson, Valen E
2012-03-01
This article proposes methodology for assessing goodness of fit in Bayesian hierarchical models. The methodology is based on comparing values of pivotal discrepancy measures (PDMs), computed using parameter values drawn from the posterior distribution, to known reference distributions. Because the resulting diagnostics can be calculated from standard output of Markov chain Monte Carlo algorithms, their computational costs are minimal. Several simulation studies are provided, each of which suggests that diagnostics based on PDMs have higher statistical power than comparable posterior-predictive diagnostic checks in detecting model departures. The proposed methodology is illustrated in a clinical application; an application to discrete data is described in supplementary material. PMID:22050079
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. PMID:25680684
Testing goodness of fit of parametric models for censored data.
Nysen, Ruth; Aerts, Marc; Faes, Christel
2012-09-20
We propose and study a goodness-of-fit test for left-censored, right-censored, and interval-censored data assuming random censorship. Main motivation comes from dietary exposure assessment in chemical risk assessment, where the determination of an appropriate distribution for concentration data is of major importance. We base the new goodness-of-fit test procedure proposed in this paper on the order selection test. As part of the testing procedure, we extend the null model to a series of nested alternative models for censored data. Then, we use a modified AIC model selection to select the best model to describe the data. If a model with one or more extra parameters is selected, then we reject the null hypothesis. As an alternative to the use of the asymptotic null distribution of the test statistic, we define a bootstrap-based procedure. We illustrate the applicability of the test procedure on data of cadmium concentrations and on data from the Signal Tandmobiel study and demonstrate its performance characteristics through simulation studies. PMID:22714389
ERIC Educational Resources Information Center
Tay, Louis; Ali, Usama S.; Drasgow, Fritz; Williams, Bruce
2011-01-01
This study investigated the relative model-data fit of an ideal point item response theory (IRT) model (the generalized graded unfolding model [GGUM]) and dominance IRT models (e.g., the two-parameter logistic model [2PLM] and Samejima's graded response model [GRM]) to simulated dichotomous and polytomous data generated from each of these models.…
Rapid world modeling: Fitting range data to geometric primitives
Feddema, J.; Little, C.
1996-12-31
For the past seven years, Sandia National Laboratories has been active in the development of robotic systems to help remediate DOE`s waste sites and decommissioned facilities. Some of these facilities have high levels of radioactivity which prevent manual clean-up. Tele-operated and autonomous robotic systems have been envisioned as the only suitable means of removing the radioactive elements. World modeling is defined as the process of creating a numerical geometric model of a real world environment or workspace. This model is often used in robotics to plan robot motions which perform a task while avoiding obstacles. In many applications where the world model does not exist ahead of time, structured lighting, laser range finders, and even acoustical sensors have been used to create three dimensional maps of the environment. These maps consist of thousands of range points which are difficult to handle and interpret. This paper presents a least squares technique for fitting range data to planar and quadric surfaces, including cylinders and ellipsoids. Once fit to these primitive surfaces, the amount of data associated with a surface is greatly reduced up to three orders of magnitude, thus allowing for more rapid handling and analysis of world data.
Issues in Evaluating Model Fit With Missing Data
ERIC Educational Resources Information Center
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),…
Ion-Atom and Atom-Atom Collisional Processes and Modeling of Stellar Atmospheres
NASA Astrophysics Data System (ADS)
Mihajlov, A. A.; Ignjatovic, Lj. M.; Sreckovic, V. A.; Dimitrijevic, M. S.; Dimitrijevic, M. S.
2015-09-01
We report the results obtained in our previous works on the influence of two groups of collisional processes (ion--atom and atom--atom) on the optical and kinetic properties of weakly ionised plasma. The first group includes radiative processes of the photodissociation/association type and radiative charge exchange, the second one -- chemi-ionisation/recombination processes. The effect of the radiative processed is assessed by comparing their intensities with those of the known competing processed in application to the solar photosphere and to the photospheres of DB white dwarfs. The studied chemi-ionisation/recombination processes are considered from the viewpoint of their influence on the populations of the excited states of the hydrogen atom (the Sun and an M-type red dwarf with an effective temperature of 3800~K) and helium atom (DB white dwarfs). The effect of these processes on the populations of the excited states of the hydrogen atom has been studied using the PHOENIX code, which generates the model of the considered atmosphere. The reported results demonstrate the unquestionable influence of the considered radiative and chemi- ionisation/recombination processes on the optical properties and on the kinetics of the weakly ionised layers in stellar atmospheres. It can be expected that the reported results will be a sufficient reason for including these processes in the models of stellar atmospheres.
Tight Binding Models in Cold Atoms Physics
NASA Astrophysics Data System (ADS)
Zakrzewski, J.
2007-05-01
Cold atomic gases placed in optical lattice potentials offer a unique tool to study simple tight binding models. Both the standard cases known from the condensed matter theory as well as novel situations may be addressed. Cold atoms setting allows for a precise control of parameters of the systems discussed, stimulating new questions and problems. The attempts to treat disorder in a controlled fashion are addressed in detail.
Effect of the Number of Variables on Measures of Fit in Structural Equation Modeling.
ERIC Educational Resources Information Center
Kenny, David A.; McCoach, D. Betsy
2003-01-01
Used three approaches to understand the effect of the number of variables in the model on model fit in structural equation modeling through computer simulation. Developed a simple formula for the theoretical value of the comparative fit index. (SLD)
HIBAYES: Global 21-cm Bayesian Monte-Carlo Model Fitting
NASA Astrophysics Data System (ADS)
Zwart, Jonathan T. L.; Price, Daniel; Bernardi, Gianni
2016-06-01
HIBAYES implements fully-Bayesian extraction of the sky-averaged (global) 21-cm signal from the Cosmic Dawn and Epoch of Reionization in the presence of foreground emission. User-defined likelihood and prior functions are called by the sampler PyMultiNest (ascl:1606.005) in order to jointly explore the full (signal plus foreground) posterior probability distribution and evaluate the Bayesian evidence for a given model. Implemented models, for simulation and fitting, include gaussians (HI signal) and polynomials (foregrounds). Some simple plotting and analysis tools are supplied. The code can be extended to other models (physical or empirical), to incorporate data from other experiments, or to use alternative Monte-Carlo sampling engines as required.
An NCME Instructional Module on Item-Fit Statistics for Item Response Theory Models
ERIC Educational Resources Information Center
Ames, Allison J.; Penfield, Randall D.
2015-01-01
Drawing valid inferences from item response theory (IRT) models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. This instructional module provides an overview of methods used for evaluating the fit of IRT models. Upon completing…
Empirical fitness models for hepatitis C virus immunogen design
NASA Astrophysics Data System (ADS)
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.
Assessing Model Data Fit of Unidimensional Item Response Theory Models in Simulated Data
ERIC Educational Resources Information Center
Kose, Ibrahim Alper
2014-01-01
The purpose of this paper is to give an example of how to assess the model-data fit of unidimensional IRT models in simulated data. Also, the present research aims to explain the importance of fit and the consequences of misfit by using simulated data sets. Responses of 1000 examinees to a dichotomously scoring 20 item test were simulated with 25…
ERIC Educational Resources Information Center
Raykov, Tenko; Lee, Chun-Lung; Marcoulides, George A.; Chang, Chi
2013-01-01
The relationship between saturated path-analysis models and their fit to data is revisited. It is demonstrated that a saturated model need not fit perfectly or even well a given data set when fit to the raw data is examined, a criterion currently frequently overlooked by researchers utilizing path analysis modeling techniques. The potential of…
Left Ventricle Segmentation Using Model Fitting and Active Surfaces
Tay, Peter C.; Li, Bing; Garson, Chris D.; Acton, Scott T.; Hossack, John A.
2010-01-01
A method to perform 4D (3D over time) segmentation of the left ventricle of a mouse heart using a set of B mode cine slices acquired in vivo from a series of short axis scans is described. We incorporate previously suggested methods such as temporal propagation, the gradient vector flow active surface, superquadric models, etc. into our proposed 4D segmentation of the left ventricle. The contributions of this paper are incorporation of a novel despeckling method and the use of locally fitted superellipsoid models to provide a better initialization for the active surface segmentation algorithm. Average distances of the improved surface segmentation to a manually segmented surface throughout the entire cardiac cycle and cross-sectional contours are provided to demonstrate the improvements produced by the proposed 4D segmentation. PMID:20300558
Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS
Bolker, Benjamin M.; Gardner, Beth; Maunder, Mark; Berg, Casper W.; Brooks, Mollie; Comita, Liza; Crone, Elizabeth; Cubaynes, Sarah; Davies, Trevor; de Valpine, Perry; Ford, Jessica; Gimenez, Olivier; Kéry, Marc; Kim, Eun Jung; Lennert-Cody, Cleridy; Magunsson, Arni; Martell, Steve; Nash, John; Nielson, Anders; Regentz, Jim; Skaug, Hans; Zipkin, Elise
2013-01-01
1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. 2. R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. 3. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. 4. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data.
The FIT Model - Fuel-cycle Integration and Tradeoffs
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.
Robust Fitting of a Weibull Model with Optional Censoring
Yang, Jingjing; Scott, David W.
2013-01-01
The Weibull family is widely used to model failure data, or lifetime data, although the classical two-parameter Weibull distribution is limited to positive data and monotone failure rate. The parameters of the Weibull model are commonly obtained by maximum likelihood estimation; however, it is well-known that this estimator is not robust when dealing with contaminated data. A new robust procedure is introduced to fit a Weibull model by using L2 distance, i.e. integrated square distance, of the Weibull probability density function. The Weibull model is augmented with a weight parameter to robustly deal with contaminated data. Results comparing a maximum likelihood estimator with an L2 estimator are given in this article, based on both simulated and real data sets. It is shown that this new L2 parametric estimation method is more robust and does a better job than maximum likelihood in the newly proposed Weibull model when data are contaminated. The same preference for L2 distance criterion and the new Weibull model also happens for right-censored data with contamination. PMID:23888090
Fitting of Parametric Building Models to Oblique Aerial Images
NASA Astrophysics Data System (ADS)
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
Using R^2 to compare least-squares fit models: When it must fail
Technology Transfer Automated Retrieval System (TEKTRAN)
R^2 can be used correctly to select from among competing least-squares fit models when the data are fitted in common form and with common weighting. However, then R^2 comparisons become equivalent to comparisons of the estimated fit variance s^2 in unweighted fitting, or of the reduced chi-square in...
A Newtonian Model of the Hydrogen Atom
NASA Astrophysics Data System (ADS)
Espinosa, James; Woodyard, James
2010-03-01
Classical physics was deemed useless in atomic physics in the early 1900's by the vast majority of the physics community. There were multiple problems that were believed to be insoluble, such as blackbody radiation and the photoelectric and Compton effects. Another outstanding problem had been the explanation of atomic spectra. By the 1920's, a very powerful theory called quantum mechanics was created which explained all atomic experiments. Nevertheless, a few physicists, most notably Albert Einstein, rejected this theory on the grounds that it did not give a complete description of the microscopic world. Another more radical view held by Walter Ritz is that Newtonian physics is applicable to all of atomic physics. Over the last couple of years, we have presented classical explanations of many of the ``insoluble'' problems given by textbooks. We will present a model of the hydrogen atom that stays within the framework of Newton. Using only the assumption that the stable building blocks of matter are the electron, positron, and neutrino, we will deduce the following results from our model: orbital stability, line spectra, and scattering cross sections for electrons and protons. We will also qualitatively demonstrate how to explain the lifetime of excited states.
Simulations of Statistical Model Fits to RHIC Data
NASA Astrophysics Data System (ADS)
Llope, W. J.
2013-04-01
The application of statistical model fits to experimentally measured particle multiplicity ratios allows inferences of the average values of temperatures, T, baryochemical potentials, μB, and other quantities at chemical freeze-out. The location of the boundary between the hadronic and partonic regions in the (μB,T) phase diagram, and the possible existence of a critical point, remains largely speculative. The search for a critical point using the moments of the particle multiplicity distributions in tightly centrality constrained event samples makes the tacit assumption that the variances in the (μB,T) values in these samples is sufficiently small to tightly localize the events in the phase diagram. This and other aspects were explored in simulations by coupling the UrQMD transport model to the statistical model code Thermus. The phase diagram trajectories of individual events versus the time in fm/c was calculated versus the centrality and beam energy. The variances of the (μB,T) values at freeze-out, even in narrow centrality bins, are seen to be relatively large. This suggests that a new way to constrain the events on the phase diagram may lead to more sensitive searches for the possible critical point.
A Comprehensive X-Ray Absorption Model for Atomic Oxygen
NASA Technical Reports Server (NTRS)
Gorczyca, T. W.; Bautista, M. A.; Hasoglu, M. F.; Garcia, J.; Gatuzz, E.; Kaastra, J. S.; Kallman, T. R.; Manson, S. T.; Mendoza, C.; Raassen, A. J. J.; de Vries, C. P.; Zatsarinny, O.
2013-01-01
An analytical formula is developed to accurately represent the photoabsorption cross section of atomic Oxygen for all energies of interest in X-ray spectral modeling. In the vicinity of the K edge, a Rydberg series expression is used to fit R-matrix results, including important orbital relaxation effects, that accurately predict the absorption oscillator strengths below threshold and merge consistently and continuously to the above-threshold cross section. Further, minor adjustments are made to the threshold energies in order to reliably align the atomic Rydberg resonances after consideration of both experimental and observed line positions. At energies far below or above the K-edge region, the formulation is based on both outer- and inner-shell direct photoionization, including significant shake-up and shake-off processes that result in photoionization-excitation and double-photoionization contributions to the total cross section. The ultimate purpose for developing a definitive model for oxygen absorption is to resolve standing discrepancies between the astronomically observed and laboratory-measured line positions, and between the inferred atomic and molecular oxygen abundances in the interstellar medium from XSTAR and SPEX spectral models.
Melbourne, Andrew; Toussaint, Nicolas; Owen, David; Simpson, Ivor; Anthopoulos, Thanasis; De Vita, Enrico; Atkinson, David; Ourselin, Sebastien
2016-07-01
Multi-modal, multi-parametric Magnetic Resonance (MR) Imaging is becoming an increasingly sophisticated tool for neuroimaging. The relationships between parameters estimated from different individual MR modalities have the potential to transform our understanding of brain function, structure, development and disease. This article describes a new software package for such multi-contrast Magnetic Resonance Imaging that provides a unified model-fitting framework. We describe model-fitting functionality for Arterial Spin Labeled MRI, T1 Relaxometry, T2 relaxometry and Diffusion Weighted imaging, providing command line documentation to generate the figures in the manuscript. Software and data (using the nifti file format) used in this article are simultaneously provided for download. We also present some extended applications of the joint model fitting framework applied to diffusion weighted imaging and T2 relaxometry, in order to both improve parameter estimation in these models and generate new parameters that link different MR modalities. NiftyFit is intended as a clear and open-source educational release so that the user may adapt and develop their own functionality as they require. PMID:26972806
Atomic Data Applications for Supernova Modeling
NASA Astrophysics Data System (ADS)
Fontes, Christopher J.
2013-06-01
The modeling of supernovae (SNe) incorporates a variety of disciplines, including hydrodynamics, radiation transport, nuclear physics and atomic physics. These efforts require numerical simulation of the final stages of a star's life, the supernova explosion phase, and the radiation that is subsequently emitted by the supernova remnant, which can occur over a time span of tens of thousands of years. While there are several different types of SNe, they all emit radiation in some form. The measurement and interpretation of these spectra provide important information about the structure of the exploding star and the supernova engine. In this talk, the role of atomic data is highlighted as iit pertains to the modeling of supernova spectra. Recent applications [1,2] involve the Los Alamos OPLIB opacity database, which has been used to provide atomic opacities for modeling supernova plasmas under local thermodynamic equilibrium (LTE) conditions. Ongoing work includes the application of atomic data generated by the Los Alamos suite of atomic physics codes under more complicated, non-LTE conditions [3]. As a specific, recent example, a portion of the x-ray spectrum produced by Tycho's supernova remnant (SN 1572) will be discussed [4]. [1] C.L. Fryer et al, Astrophys. J. 707, 193 (2009). [2] C.L. Fryer et al, Astrophys. J. 725, 296 (2009). [3] C.J. Fontes et al, Conference Proceedings for ICPEAC XXVII, J. of Phys: Conf. Series 388, 012022 (2012). [4] K.A. Eriksen et al, Presentation at the 2012 AAS Meeting (Austin, TX). (This work was performed under the auspices of the U.S. Department of Energy by Los Alamos National Laboratory under Contract No. DE-AC52-06NA25396.)
ERIC Educational Resources Information Center
Zhang, Wei
2008-01-01
A major issue in the utilization of covariance structure analysis is model fit evaluation. Recent years have witnessed increasing interest in various test statistics and so-called fit indexes, most of which are actually based on or closely related to F[subscript 0], a measure of model fit in the population. This study aims to provide a systematic…
Performance of the Generalized S-X[squared] Item Fit Index for the Graded Response Model
ERIC Educational Resources Information Center
Kang, Taehoon; Chen, Troy T.
2011-01-01
The utility of Orlando and Thissen's ("2000", "2003") S-X[squared] fit index was extended to the model-fit analysis of the graded response model (GRM). The performance of a modified S-X[squared] in assessing item-fit of the GRM was investigated in light of empirical Type I error rates and power with a simulation study having various conditions…
Model-independent fit to Planck and BICEP2 data
NASA Astrophysics Data System (ADS)
Barranco, Laura; Boubekeur, Lotfi; Mena, Olga
2014-09-01
Inflation is the leading theory to describe elegantly the initial conditions that led to structure formation in our Universe. In this paper, we present a novel phenomenological fit to the Planck, WMAP polarization (WP) and the BICEP2 data sets using an alternative parametrization. Instead of starting from inflationary potentials and computing the inflationary observables, we use a phenomenological parametrization due to Mukhanov, describing inflation by an effective equation of state, in terms of the number of e-folds and two phenomenological parameters α and β. Within such a parametrization, which captures the different inflationary models in a model-independent way, the values of the scalar spectral index ns, its running and the tensor-to-scalar ratio r are predicted, given a set of parameters (α ,β). We perform a Markov Chain Monte Carlo analysis of these parameters, and we show that the combined analysis of Planck and WP data favors the Starobinsky and Higgs inflation scenarios. Assuming that the BICEP2 signal is not entirely due to foregrounds, the addition of this last data set prefers instead the ϕ2 chaotic models. The constraint we get from Planck and WP data alone on the derived tensor-to-scalar ratio is r <0.18 at 95% C.L., value which is consistent with the one quoted from the BICEP2 Collaboration analysis, r =0.16-0.05+0-06, after foreground subtraction. This is not necessarily at odds with the 2σ tension found between Planck and BICEP2 measurements when analyzing data in terms of the usual ns and r parameters, given that the parametrization used here, for the preferred value ns≃0.96, allows only for a restricted parameter space in the usual (ns,r) plane.
Optical analogs of model atoms in fields
Milonni, P.W.
1991-05-02
The equivalence of the paraxial wave equation to a time-dependent Schroedinger equation is exploited to construct optical analogs of model atoms in monochromatic fields. The approximation of geometrical optics provides the analog of the corresponding classical mechanics. Optical analogs of Rabi oscillations, photoionization, stabilization, and the Kramers-Henneberger transformation are discussed. One possibility for experimental realization of such optical analogs is proposed. These analogs may be useful for studies of quantum chaos'' when the ray trajectories are chaotic. 9 refs.
A quantitative confidence signal detection model: 1. Fitting psychometric functions.
Yi, Yongwoo; Merfeld, Daniel M
2016-04-01
Perceptual thresholds are commonly assayed in the laboratory and clinic. When precision and accuracy are required, thresholds are quantified by fitting a psychometric function to forced-choice data. The primary shortcoming of this approach is that it typically requires 100 trials or more to yield accurate (i.e., small bias) and precise (i.e., small variance) psychometric parameter estimates. We show that confidence probability judgments combined with a model of confidence can yield psychometric parameter estimates that are markedly more precise and/or markedly more efficient than conventional methods. Specifically, both human data and simulations show that including confidence probability judgments for just 20 trials can yield psychometric parameter estimates that match the precision of those obtained from 100 trials using conventional analyses. Such an efficiency advantage would be especially beneficial for tasks (e.g., taste, smell, and vestibular assays) that require more than a few seconds for each trial, but this potential benefit could accrue for many other tasks. PMID:26763777
A Green's function quantum average atom model
Starrett, Charles Edward
2015-05-21
A quantum average atom model is reformulated using Green's functions. This allows integrals along the real energy axis to be deformed into the complex plane. The advantage being that sharp features such as resonances and bound states are broadened by a Lorentzian with a half-width chosen for numerical convenience. An implementation of this method therefore avoids numerically challenging resonance tracking and the search for weakly bound states, without changing the physical content or results of the model. A straightforward implementation results in up to a factor of 5 speed-up relative to an optimized orbital based code.
Atom-Role-Based Access Control Model
NASA Astrophysics Data System (ADS)
Cai, Weihong; Huang, Richeng; Hou, Xiaoli; Wei, Gang; Xiao, Shui; Chen, Yindong
Role-based access control (RBAC) model has been widely recognized as an efficient access control model and becomes a hot research topic of information security at present. However, in the large-scale enterprise application environments, the traditional RBAC model based on the role hierarchy has the following deficiencies: Firstly, it is unable to reflect the role relationships in complicated cases effectively, which does not accord with practical applications. Secondly, the senior role unconditionally inherits all permissions of the junior role, thus if a user is under the supervisor role, he may accumulate all permissions, and this easily causes the abuse of permission and violates the least privilege principle, which is one of the main security principles. To deal with these problems, we, after analyzing permission types and role relationships, proposed the concept of atom role and built an atom-role-based access control model, called ATRBAC, by dividing the permission set of each regular role based on inheritance path relationships. Through the application-specific analysis, this model can well meet the access control requirements.
An Application of M[subscript 2] Statistic to Evaluate the Fit of Cognitive Diagnostic Models
ERIC Educational Resources Information Center
Liu, Yanlou; Tian, Wei; Xin, Tao
2016-01-01
The fit of cognitive diagnostic models (CDMs) to response data needs to be evaluated, since CDMs might yield misleading results when they do not fit the data well. Limited-information statistic M[subscript 2] and the associated root mean square error of approximation (RMSEA[subscript 2]) in item factor analysis were extended to evaluate the fit of…
Comparing the Fit of Item Response Theory and Factor Analysis Models
ERIC Educational Resources Information Center
Maydeu-Olivares, Alberto; Cai, Li; Hernandez, Adolfo
2011-01-01
Linear factor analysis (FA) models can be reliably tested using test statistics based on residual covariances. We show that the same statistics can be used to reliably test the fit of item response theory (IRT) models for ordinal data (under some conditions). Hence, the fit of an FA model and of an IRT model to the same data set can now be…
Convergence, Admissibility, and Fit of Alternative Confirmatory Factor Analysis Models for MTMM Data
ERIC Educational Resources Information Center
Lance, Charles E.; Fan, Yi
2016-01-01
We compared six different analytic models for multitrait-multimethod (MTMM) data in terms of convergence, admissibility, and model fit to 258 samples of previously reported data. Two well-known models, the correlated trait-correlated method (CTCM) and the correlated trait-correlated uniqueness (CTCU) models, were fit for reference purposes in…
ERIC Educational Resources Information Center
Finch, W. Holmes; Finch, Maria E. Hernandez
2016-01-01
Researchers and data analysts are sometimes faced with the problem of very small samples, where the number of variables approaches or exceeds the overall sample size; i.e. high dimensional data. In such cases, standard statistical models such as regression or analysis of variance cannot be used, either because the resulting parameter estimates…
NASA Technical Reports Server (NTRS)
Sokalski, W. A.; Shibata, M.; Ornstein, R. L.; Rein, R.
1992-01-01
The quality of several atomic charge models based on different definitions has been analyzed using cumulative atomic multipole moments (CAMM). This formalism can generate higher atomic moments starting from any atomic charges, while preserving the corresponding molecular moments. The atomic charge contribution to the higher molecular moments, as well as to the electrostatic potentials, has been examined for CO and HCN molecules at several different levels of theory. The results clearly show that the electrostatic potential obtained from CAMM expansion is convergent up to R-5 term for all atomic charge models used. This illustrates that higher atomic moments can be used to supplement any atomic charge model to obtain more accurate description of electrostatic properties.
A comprehensive X-ray absorption model for atomic oxygen
Gorczyca, T. W.; Bautista, M. A.; Mendoza, C.; Hasoglu, M. F.; García, J.; Gatuzz, E.; Kaastra, J. S.; Raassen, A. J. J.; De Vries, C. P.; Kallman, T. R.; Manson, S. T.; Zatsarinny, O.
2013-12-10
An analytical formula is developed to accurately represent the photoabsorption cross section of O I for all energies of interest in X-ray spectral modeling. In the vicinity of the K edge, a Rydberg series expression is used to fit R-matrix results, including important orbital relaxation effects, that accurately predict the absorption oscillator strengths below threshold and merge consistently and continuously to the above-threshold cross section. Further, minor adjustments are made to the threshold energies in order to reliably align the atomic Rydberg resonances after consideration of both experimental and observed line positions. At energies far below or above the K-edge region, the formulation is based on both outer- and inner-shell direct photoionization, including significant shake-up and shake-off processes that result in photoionization-excitation and double-photoionization contributions to the total cross section. The ultimate purpose for developing a definitive model for oxygen absorption is to resolve standing discrepancies between the astronomically observed and laboratory-measured line positions, and between the inferred atomic and molecular oxygen abundances in the interstellar medium from XSTAR and SPEX spectral models.
Making It Visual: Creating a Model of the Atom
ERIC Educational Resources Information Center
Pringle, Rose M.
2004-01-01
This article describes a lesson in which students construct Bohr's planetary model of the atom. Niels Bohr's atomic model provides a framework for discussing with middle and high school students the historical development of our understanding of the structure of the atom. The model constructed in this activity will enable students to visualize the…
Derevyanko, Georgy; Grudinin, Sergei
2014-08-01
HermiteFit, a novel algorithm for fitting a protein structure into a low-resolution electron-density map, is presented. The algorithm accelerates the rotation of the Fourier image of the electron density by using three-dimensional orthogonal Hermite functions. As part of the new method, an algorithm for the rotation of the density in the Hermite basis and an algorithm for the conversion of the expansion coefficients into the Fourier basis are presented. HermiteFit was implemented using the cross-correlation or the Laplacian-filtered cross-correlation as the fitting criterion. It is demonstrated that in the Hermite basis the Laplacian filter has a particularly simple form. To assess the quality of density encoding in the Hermite basis, an analytical way of computing the crystallographic R factor is presented. Finally, the algorithm is validated using two examples and its efficiency is compared with two widely used fitting methods, ADP_EM and colores from the Situs package. HermiteFit will be made available at http://nano-d.inrialpes.fr/software/HermiteFit or upon request from the authors. PMID:25084327
Computer Model Of Fragmentation Of Atomic Nuclei
NASA Technical Reports Server (NTRS)
Wilson, John W.; Townsend, Lawrence W.; Tripathi, Ram K.; Norbury, John W.; KHAN FERDOUS; Badavi, Francis F.
1995-01-01
High Charge and Energy Semiempirical Nuclear Fragmentation Model (HZEFRG1) computer program developed to be computationally efficient, user-friendly, physics-based program for generating data bases on fragmentation of atomic nuclei. Data bases generated used in calculations pertaining to such radiation-transport applications as shielding against radiation in outer space, radiation dosimetry in outer space, cancer therapy in laboratories with beams of heavy ions, and simulation studies for designing detectors for experiments in nuclear physics. Provides cross sections for production of individual elements and isotopes in breakups of high-energy heavy ions by combined nuclear and Coulomb fields of interacting nuclei. Written in ANSI FORTRAN 77.
YUP.SCX: Coaxing Atomic Models into Medium Resolution Electron Density Maps
Tan, Robert K.-Z.; Devkota, Batsal; Harvey, Stephen C.
2008-01-01
The structures of large macromolecular complexes in different functional states can be determined by cryo-electron microscopy, which yields electron density maps of low to intermediate resolutions. The maps can be combined with high-resolution atomic structures of components of the complex, to produce a model for the complex that is more accurate than the formal resolution of the map. To this end, methods have been developed to dock atomic models into density maps rigidly or flexibly, and to refine a docked model so as to optimize the fit of the atomic model into the map. We have developed a new refinement method called YUP.SCX. The electron density map is converted into a component of the potential energy function to which terms for stereochemical restraints and volume exclusion are added. The potential energy function is then minimized (using simulated annealing) to yield a stereochemically-restrained atomic structure that fits into the electron density map optimally. We used this procedure to construct an atomic model of the 70S ribosome in the pre-accommodation state. Although some atoms are displaced by as much as 33 Å, they divide themselves into nearly rigid fragments along natural boundaries with smooth transitions between the fragments. PMID:18572416
The Search for "Optimal" Cutoff Properties: Fit Index Criteria in Structural Equation Modeling
ERIC Educational Resources Information Center
Sivo, Stephen A.; Xitao, Fan; Witta, E. Lea; Willse, John T.
2006-01-01
This study is a partial replication of L. Hu and P. M. Bentler's (1999) fit criteria work. The purpose of this study was twofold: (a) to determine whether cut-off values vary according to which model is the true population model for a dataset and (b) to identify which of 13 fit indexes behave optimally by retaining all of the correct models while…
ERIC Educational Resources Information Center
Dyehouse, Melissa A.
2009-01-01
This study compared the model-data fit of a parametric item response theory (PIRT) model to a nonparametric item response theory (NIRT) model to determine the best-fitting model for use with ordinal-level alternate assessment ratings. The PIRT Generalized Graded Unfolding Model (GGUM) was compared to the NIRT Mokken model. Chi-square statistics…
Multiplex networks with intrinsic fitness: Modeling the merit-fame interplay via latent layers
NASA Astrophysics Data System (ADS)
Fotouhi, Babak; Momeni, Naghmeh
2015-11-01
We consider the problem of growing multiplex networks with intrinsic fitness and inter-layer coupling. The model comprises two layers; one that incorporates fitness and another in which attachments are preferential. In the first layer, attachment probabilities are proportional to fitness values, and in the second layer, proportional to the sum of degrees in both layers. We provide analytical closed-form solutions for the joint distributions of fitness and degrees. We also derive closed-form expressions for the expected value of the degree as a function of fitness. The model alleviates two shortcomings that are present in the current models of growing multiplex networks: homogeneity of connections, and homogeneity of fitness. In this paper, we posit and analyze a growth model that is heterogeneous in both senses.
Refinement of atomic models in high resolution EM reconstructions using Flex-EM and local assessment
Joseph, Agnel Praveen; Malhotra, Sony; Burnley, Tom; Wood, Chris; Clare, Daniel K.; Winn, Martyn; Topf, Maya
2016-01-01
As the resolutions of Three Dimensional Electron Microscopic reconstructions of biological macromolecules are being improved, there is a need for better fitting and refinement methods at high resolutions and robust approaches for model assessment. Flex-EM/MODELLER has been used for flexible fitting of atomic models in intermediate-to-low resolution density maps of different biological systems. Here, we demonstrate the suitability of the method to successfully refine structures at higher resolutions (2.5–4.5 Å) using both simulated and experimental data, including a newly processed map of Apo-GroEL. A hierarchical refinement protocol was adopted where the rigid body definitions are relaxed and atom displacement steps are reduced progressively at successive stages of refinement. For the assessment of local fit, we used the SMOC (segment-based Manders’ overlap coefficient) score, while the model quality was checked using the Qmean score. Comparison of SMOC profiles at different stages of refinement helped in detecting regions that are poorly fitted. We also show how initial model errors can have significant impact on the goodness-of-fit. Finally, we discuss the implementation of Flex-EM in the CCP-EM software suite. PMID:26988127
Joseph, Agnel Praveen; Malhotra, Sony; Burnley, Tom; Wood, Chris; Clare, Daniel K; Winn, Martyn; Topf, Maya
2016-05-01
As the resolutions of Three Dimensional Electron Microscopic reconstructions of biological macromolecules are being improved, there is a need for better fitting and refinement methods at high resolutions and robust approaches for model assessment. Flex-EM/MODELLER has been used for flexible fitting of atomic models in intermediate-to-low resolution density maps of different biological systems. Here, we demonstrate the suitability of the method to successfully refine structures at higher resolutions (2.5-4.5Å) using both simulated and experimental data, including a newly processed map of Apo-GroEL. A hierarchical refinement protocol was adopted where the rigid body definitions are relaxed and atom displacement steps are reduced progressively at successive stages of refinement. For the assessment of local fit, we used the SMOC (segment-based Manders' overlap coefficient) score, while the model quality was checked using the Qmean score. Comparison of SMOC profiles at different stages of refinement helped in detecting regions that are poorly fitted. We also show how initial model errors can have significant impact on the goodness-of-fit. Finally, we discuss the implementation of Flex-EM in the CCP-EM software suite. PMID:26988127
Model Fitting for Predicted Precipitation in Darwin: Some Issues with Model Choice
ERIC Educational Resources Information Center
Farmer, Jim
2010-01-01
In Volume 23(2) of the "Australian Senior Mathematics Journal," Boncek and Harden present an exercise in fitting a Markov chain model to rainfall data for Darwin Airport (Boncek & Harden, 2009). Days are subdivided into those with precipitation and precipitation-free days. The author abbreviates these labels to wet days and dry days. It is…
Atomic Models for Motional Stark Effects Diagnostics
Gu, M F; Holcomb, C; Jayakuma, J; Allen, S; Pablant, N A; Burrell, K
2007-07-26
We present detailed atomic physics models for motional Stark effects (MSE) diagnostic on magnetic fusion devices. Excitation and ionization cross sections of the hydrogen or deuterium beam traveling in a magnetic field in collisions with electrons, ions, and neutral gas are calculated in the first Born approximation. The density matrices and polarization states of individual Stark-Zeeman components of the Balmer {alpha} line are obtained for both beam into plasma and beam into gas models. A detailed comparison of the model calculations and the MSE polarimetry and spectral intensity measurements obtained at the DIII-D tokamak is carried out. Although our beam into gas models provide a qualitative explanation for the larger {pi}/{sigma} intensity ratios and represent significant improvements over the statistical population models, empirical adjustment factors ranging from 1.0-2.0 must still be applied to individual line intensities to bring the calculations into full agreement with the observations. Nevertheless, we demonstrate that beam into gas measurements can be used successfully as calibration procedures for measuring the magnetic pitch angle through {pi}/{sigma} intensity ratios. The analyses of the filter-scan polarization spectra from the DIII-D MSE polarimetry system indicate unknown channel and time dependent light contaminations in the beam into gas measurements. Such contaminations may be the main reason for the failure of beam into gas calibration on MSE polarimetry systems.
Fitting the Rasch Model to Account for Variation in Item Discrimination
ERIC Educational Resources Information Center
Weitzman, R. A.
2009-01-01
Building on the Kelley and Gulliksen versions of classical test theory, this article shows that a logistic model having only a single item parameter can account for varying item discrimination, as well as difficulty, by using item-test correlations to adjust incorrect-correct (0-1) item responses prior to an initial model fit. The fit occurs…
Why Should We Assess the Goodness-of-Fit of IRT Models?
ERIC Educational Resources Information Center
Maydeu-Olivares, Alberto
2013-01-01
In this rejoinder, Maydeu-Olivares states that, in item response theory (IRT) measurement applications, the application of goodness-of-fit (GOF) methods informs researchers of the discrepancy between the model and the data being fitted (the room for improvement). By routinely reporting the GOF of IRT models, together with the substantive results…
ERIC Educational Resources Information Center
Bauer, Daniel J.; Sterba, Sonya K.
2011-01-01
Previous research has compared methods of estimation for fitting multilevel models to binary data, but there are reasons to believe that the results will not always generalize to the ordinal case. This article thus evaluates (a) whether and when fitting multilevel linear models to ordinal outcome data is justified and (b) which estimator to employ…
Residuals and the Residual-Based Statistic for Testing Goodness of Fit of Structural Equation Models
ERIC Educational Resources Information Center
Foldnes, Njal; Foss, Tron; Olsson, Ulf Henning
2012-01-01
The residuals obtained from fitting a structural equation model are crucial ingredients in obtaining chi-square goodness-of-fit statistics for the model. The authors present a didactic discussion of the residuals, obtaining a geometrical interpretation by recognizing the residuals as the result of oblique projections. This sheds light on the…
Performance of the Generalized S-X[Superscript 2] Item Fit Index for Polytomous IRT Models
ERIC Educational Resources Information Center
Kang, Taehoon; Chen, Troy T.
2008-01-01
Orlando and Thissen's S-X[superscript 2] item fit index has performed better than traditional item fit statistics such as Yen' s Q[subscript 1] and McKinley and Mill' s G[superscript 2] for dichotomous item response theory (IRT) models. This study extends the utility of S-X[superscript 2] to polytomous IRT models, including the generalized partial…
TRANSIT MODEL FITTING IN THE KEPLER SCIENCE OPERATIONS CENTER PIPELINE: NEW FEATURES AND PERFORMANCE
NASA Astrophysics Data System (ADS)
Li, Jie; Burke, C. J.; Jenkins, J. M.; Quintana, E. V.; Rowe, J. F.; Seader, S. E.; Tenenbaum, P.; Twicken, J. D.
2013-10-01
We describe new transit model fitting features and performance of the latest release (9.1, July 2013) of the Kepler Science Operations Center (SOC) Pipeline. The targets for which a Threshold Crossing Event (TCE) is generated in the Transiting Planet Search (TPS) component of the pipeline are subsequently processed in the Data Validation (DV) component. Transit model parameters are fitted in DV to transit-like signatures in the light curves of the targets with TCEs. The transit model fitting results are used in diagnostic tests in DV, which help to validate planet candidates and identify false positive detections. The standard transit model includes five fit parameters: transit epoch time (i.e. central time of first transit), orbital period, impact parameter, ratio of planet radius to star radius and ratio of semi-major axis to star radius. Light curves for many targets do not contain enough information to uniquely determine the impact parameter, which results in poor convergence performance of the fitter. In the latest release of the Kepler SOC pipeline, a reduced parameter fit is included in DV: the impact parameter is set to a fixed value and the four remaining parameters are fitted. The standard transit model fit is implemented after a series of reduced parameter fits in which the impact parameter is varied between 0 and 1. Initial values for the standard transit model fit parameters are determined by the reduced parameter fit with the minimum chi-square metric. With reduced parameter fits, the robustness of the transit model fit is improved significantly. Diagnostic plots of the chi-square metrics and reduced parameter fit results illustrate how the fitted parameters vary as a function of impact parameter. Essentially, a family of transiting planet characteristics is determined in DV for each Pipeline TCE. Transit model fitting performance of release 9.1 of the Kepler SOC pipeline is demonstrated with the results of the processing of 16 quarters of flight data
Operation of the computer model for microenvironment atomic oxygen exposure
NASA Technical Reports Server (NTRS)
Bourassa, R. J.; Gillis, J. R.; Gruenbaum, P. E.
1995-01-01
A computer model for microenvironment atomic oxygen exposure has been developed to extend atomic oxygen modeling capability to include shadowing and reflections. The model uses average exposure conditions established by the direct exposure model and extends the application of these conditions to treat surfaces of arbitrary shape and orientation.
NASA Astrophysics Data System (ADS)
Mead, A. J.; Peacock, J. A.; Heymans, C.; Joudaki, S.; Heavens, A. F.
2015-12-01
We present an optimized variant of the halo model, designed to produce accurate matter power spectra well into the non-linear regime for a wide range of cosmological models. To do this, we introduce physically motivated free parameters into the halo-model formalism and fit these to data from high-resolution N-body simulations. For a variety of Λ cold dark matter (ΛCDM) and wCDM models, the halo-model power is accurate to ≃ 5 per cent for k ≤ 10h Mpc-1 and z ≤ 2. An advantage of our new halo model is that it can be adapted to account for the effects of baryonic feedback on the power spectrum. We demonstrate this by fitting the halo model to power spectra from the OWLS (OverWhelmingly Large Simulations) hydrodynamical simulation suite via parameters that govern halo internal structure. We are able to fit all feedback models investigated at the 5 per cent level using only two free parameters, and we place limits on the range of these halo parameters for feedback models investigated by the OWLS simulations. Accurate predictions to high k are vital for weak-lensing surveys, and these halo parameters could be considered nuisance parameters to marginalize over in future analyses to mitigate uncertainty regarding the details of feedback. Finally, we investigate how lensing observables predicted by our model compare to those from simulations and from HALOFIT for a range of k-cuts and feedback models and quantify the angular scales at which these effects become important. Code to calculate power spectra from the model presented in this paper can be found at https://github.com/alexander-mead/hmcode.
Assessing Fit of Cognitive Diagnostic Models: A Case Study
ERIC Educational Resources Information Center
Sinharay, Sandip; Almond, Russell G.
2007-01-01
A cognitive diagnostic model uses information from educational experts to describe the relationships between item performances and posited proficiencies. When the cognitive relationships can be described using a fully Bayesian model, Bayesian model checking procedures become available. Checking models tied to cognitive theory of the domains…
Atomic Oscillator Strengths for Stellar Atmosphere Modeling
NASA Astrophysics Data System (ADS)
Ruffoni, Matthew; Pickering, Juliet C.
2015-08-01
In order to correctly model stellar atmospheres, fundamental atomic data must be available to describe atomic lines observed in their spectra. Accurate, laboratory-measured oscillator strengths (f-values) for Fe peak elements in neutral or low-ionisation states are particularly important for determining chemical abundances.However, advances in astronomical spectroscopy in recent decades have outpaced those in laboratory astrophysics, with the latter frequently being overlooked at the planning stages of new projects. As a result, numerous big-budget astronomy projects have been, and continue to be hindered by a lack of suitable, accurately-measured reference data to permit the analysis of expensive astronomical spectra; a problem only likely to worsen in the coming decades as spectrographs at new facilities increasingly move to infrared wavelengths.At Imperial College London - and in collaboration with NIST, Wisconsin University and Lund University - we have been working with the astronomy community in an effort to provide new accurately-measured f-values for a range of projects. In particular, we have been working closely with the Gaia-ESO (GES) and SDSS-III/APOGEE surveys, both of which have discovered that many lines that would make ideal candidates for inclusion in their analyses have poorly defined f-values, or are simply absent from the database. Using high-resolution Fourier transform spectroscopy (R ~ 2,000,000) to provide atomic branching fractions, and combining these with level lifetimes measured with laser induced fluorescence, we have provided new laboratory-measured f-values for a range of Fe-peak elements, most recently including Fe I, Fe II, and V I. For strong, unblended lines, uncertainties are as low as ±0.02 dex.In this presentation, I will describe how experimental f-values are obtained in the laboratory and present our recent work for GES and APOGEE. In particular, I will also discuss the strengths and limitations of current laboratory
Project Physics Text 5, Models of the Atom.
ERIC Educational Resources Information Center
Harvard Univ., Cambridge, MA. Harvard Project Physics.
Basic atomic theories are presented in this fifth unit of the Project Physics text for use by senior high students. Chemical basis of atomic models in the early years of the 18th Century is discussed n connection with Dalton's theory, atomic properties, and periodic tables. The discovery of electrons is described by using cathode rays, Millikan's…
Moment-Based Probability Modeling and Extreme Response Estimation, The FITS Routine Version 1.2
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.
Mac, Amy; Rhodes, Gillian; Webster, Michael A.
2015-01-01
Recently, we proposed that the aftereffects of adapting to facial age are consistent with a renormalization of the perceived age (e.g., so that after adapting to a younger or older age, all ages appear slightly older or younger, respectively). This conclusion has been challenged by arguing that the aftereffects can also be accounted for by an alternative model based on repulsion (in which facial ages above or below the adapting age are biased away from the adaptor). However, we show here that this challenge was based on allowing the fitted functions to take on values which are implausible and incompatible across the different adapting conditions. When the fits are constrained or interpreted in terms of standard assumptions about normalization and repulsion, then the two analyses both agree in pointing to a pattern of renormalization in age aftereffects. PMID:27551353
2014-01-01
Background Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. Results The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input–output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard
An atomic model for neutral and singly ionized uranium
NASA Technical Reports Server (NTRS)
Maceda, E. L.; Miley, G. H.
1979-01-01
A model for the atomic levels above ground state in neutral, U(0), and singly ionized, U(+), uranium is described based on identified atomic transitions. Some 168 states in U(0) and 95 in U(+) are found. A total of 1581 atomic transitions are used to complete this process. Also discussed are the atomic inverse lifetimes and line widths for the radiative transitions as well as the electron collisional cross sections.
Using LISREL to Fit Nonlinear Latent Curve Models
ERIC Educational Resources Information Center
Blozis, Shelley A.; Harring, Jeffrey R.; Mels, Gerhard
2008-01-01
Latent curve models offer a flexible approach to the study of longitudinal data when the form of change in a response is nonlinear. This article considers such models that are conditionally linear with regard to the random coefficients at the 2nd level. This framework allows fixed parameters to enter a model linearly or nonlinearly, and random…
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 < .001) emerged. Contrary to predictions, no significant relationships were found between "g" and either K or F (r = -.09, 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. PMID:20589987
A simple model of group selection that cannot be analyzed with inclusive fitness.
van Veelen, Matthijs; Luo, Shishi; Simon, Burton
2014-11-01
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, we show two distinct limitations that prevent recasting in terms of inclusive fitness. The first is a limitation across models. We show that if inclusive fitness is to always give the correct prediction, the definition of relatedness needs to change, continuously, along with changes in the parameters of the model. This results in infinitely many different definitions of relatedness - one for every parameter value - which strips relatedness of its meaning. The second limitation is across time. We show that one can find the trajectory for the group selection model by solving a partial differential equation, and that it is mathematically impossible to do this using inclusive fitness. PMID:25034338
ERIC Educational Resources Information Center
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,…
ERIC Educational Resources Information Center
Cai, Li; Lee, Taehun
2009-01-01
We apply the Supplemented EM algorithm (Meng & Rubin, 1991) to address a chronic problem with the "two-stage" fitting of covariance structure models in the presence of ignorable missing data: the lack of an asymptotically chi-square distributed goodness-of-fit statistic. We show that the Supplemented EM algorithm provides a convenient…
The Relation among Fit Indexes, Power, and Sample Size in Structural Equation Modeling
ERIC Educational Resources Information Center
Kim, Kevin H.
2005-01-01
The relation among fit indexes, power, and sample size in structural equation modeling is examined. The noncentrality parameter is required to compute power. The 2 existing methods of computing power have estimated the noncentrality parameter by specifying an alternative hypothesis or alternative fit. These methods cannot be implemented easily and…
Characterization of Titan 3-D acoustic pressure spectra by least-squares fit to theoretical model
NASA Astrophysics Data System (ADS)
Hartnett, E. B.; Carleen, E.
1980-01-01
A theoretical model for the acoustic spectra of undeflected rocket plumes is fitted to computed spectra of a Titan III-D at varying times after ignition, by a least-squares method. Tests for the goodness of the fit are made.
An experimentally determined evolutionary model dramatically improves phylogenetic fit.
Bloom, Jesse D
2014-08-01
All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here, I demonstrate an alternative: Experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. Emerging high-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic and genetic analyses. PMID:24859245
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. PMID:18643300
Individual Differences and Fitting Methods for the Two-Choice Diffusion Model of Decision Making
Ratcliff, Roger; Childers, Russ
2015-01-01
Methods of fitting the diffusion model were examined with a focus on what the model can tell us about individual differences. Diffusion model parameters were obtained from the fits to data from two experiments and consistency of parameter values, individual differences, and practice effects were examined using different numbers of observations from each subject. Two issues were examined, first, what sizes of differences between groups can be obtained to distinguish between groups and second, what sizes of differences would be needed to find individual subjects that had a deficit relative to a control group. The parameter values from the experiments provided ranges that were used in a simulation study to examine recovery of individual differences. This study used several diffusion model fitting programs, fitting methods, and published packages. In a second simulation study, 64 sets of simulated data from each of 48 sets of parameter values (spanning the range of typical values obtained from fits to data) were fit with the different methods and biases and standard deviations in recovered model parameters were compared across methods. Finally, in a third simulation study, a comparison between a standard chi-square method and a hierarchical Bayesian method was performed. The results from these studies can be used as a starting point for selecting fitting methods and as a basis for understanding the strengths and weaknesses of using diffusion model analyses to examine individual differences in clinical, neuropsychological, and educational testing. PMID:26236754
Fitting Partially Nonlinear Random Coefficient Models as SEMs
ERIC Educational Resources Information Center
Harring, Jeffrey R.; Cudeck, Robert; du Toit, Stephen H. C.
2006-01-01
The nonlinear random coefficient model has become increasingly popular as a method for describing individual differences in longitudinal research. Although promising, the nonlinear model it is not utilized as often as it might be because software options are still somewhat limited. In this article we show that a specialized version of the model…
Fitting Computational Models to fMRI Data
Ashby, F. Gregory; Waldschmidt, Jennifer G.
2008-01-01
Many computational models in psychology predict how neural activation in specific brain regions should change during certain cognitive tasks. The emergence of fMRI as a research tool provides an ideal vehicle to test these predictions. Before such tests are possible, however, significant methodological problems must be solved. These problems include transforming the neural activations predicted by the model into predicted BOLD responses, identifying the voxels within each region of interest against which to test the model, and comparing the observed and predicted BOLD responses in each of these regions. Methods are described for solving each of these problems. PMID:18697666
Fitting degradation of shoreline scarps by a nonlinear diffusion model
Andrews, D.J.; Buckna, R.C.
1987-01-01
The diffusion model of degradation of topographic features is a promising means by which vertical offsets on Holocene faults might be dated. In order to calibrate the method, we have examined present-day profiles of wave-cut shoreline scarps of late Pleistocene lakes Bonneville and Lahontan. A table is included that allows easy application of the model to scarps with simple initial shape. -from Authors
NASA Astrophysics Data System (ADS)
Jain, Jalaj; Prakash, Ram; Vyas, Gheesa Lal; Pal, Udit Narayan; Chowdhuri, Malay Bikas; Manchanda, Ranjana; Halder, Nilanjan; Choyal, Yaduvendra
2015-12-01
In the present work an effort has been made to estimate the plasma parameters simultaneously like—electron density, electron temperature, ground state atom density, ground state ion density and metastable state density from the observed visible spectra of penning plasma discharge (PPD) source using least square fitting. The analysis is performed for the prominently observed neutral helium lines. The atomic data and analysis structure (ADAS) database is used to provide the required collisional-radiative (CR) photon emissivity coefficients (PECs) values under the optical thin plasma condition in the analysis. With this condition the estimated plasma temperature from the PPD is found rather high. It is seen that the inclusion of opacity in the observed spectral lines through PECs and addition of diffusion of neutrals and metastable state species in the CR-model code analysis improves the electron temperature estimation in the simultaneous measurement.
Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits
NASA Technical Reports Server (NTRS)
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.
Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits
NASA Technical Reports Server (NTRS)
Kopasakis, George
2010-01-01
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.
Two Dimensional Non-commutative Space and Rydberg Atom Model
NASA Astrophysics Data System (ADS)
Chung, Won Sang
2015-06-01
In this paper we consider the case of only space-space non-commutativity in two dimension. We also discuss the Rydberg atom model in this space and use the linear realization of the coordinate and momentum operators to solve the Schrödinger equation for the Rydberg atom through the standard perturbation method. Finally, the thermodynamics for the Rydberg atom model is discussed.
A no-scale inflationary model to fit them all
Ellis, John; García, Marcos A.G.; Olive, Keith A.; Nanopoulos, Dimitri V. E-mail: garciagarcia@physics.umn.edu E-mail: olive@physics.umn.edu
2014-08-01
The magnitude of B-mode polarization in the cosmic microwave background as measured by BICEP2 favours models of chaotic inflation with a quadratic m{sup 2} φ{sup 2}/2 potential, whereas data from the Planck satellite favour a small value of the tensor-to-scalar perturbation ratio r that is highly consistent with the Starobinsky R +R{sup 2} model. Reality may lie somewhere between these two scenarios. In this paper we propose a minimal two-field no-scale supergravity model that interpolates between quadratic and Starobinsky-like inflation as limiting cases, while retaining the successful prediction n{sub s} ≅ 0.96.
Performance of Transit Model Fitting in Processing Four Years of Kepler Science Data
NASA Astrophysics Data System (ADS)
Li, Jie; Burke, Christopher J.; Jenkins, Jon Michael; Quintana, Elisa V.; Rowe, Jason; Seader, Shawn; Tenenbaum, Peter; Twicken, Joseph D.
2014-06-01
We present transit model fitting performance of the Kepler Science Operations Center (SOC) Pipeline in processing four years of science data, which were collected by the Kepler spacecraft from May 13, 2009 to May 12, 2013. Threshold Crossing Events (TCEs), which represent transiting planet detections, are generated by the Transiting Planet Search (TPS) component of the pipeline and subsequently processed in the Data Validation (DV) component. The transit model is used in DV to fit TCEs and derive parameters that are used in various diagnostic tests to validate planetary candidates. The standard transit model includes five fit parameters: transit epoch time (i.e. central time of first transit), orbital period, impact parameter, ratio of planet radius to star radius and ratio of semi-major axis to star radius. In the latest Kepler SOC pipeline codebase, the light curve of the target for which a TCE is generated is initially fitted by a trapezoidal model with four parameters: transit epoch time, depth, duration and ingress time. The trapezoidal model fit, implemented with repeated Levenberg-Marquardt minimization, provides a quick and high fidelity assessment of the transit signal. The fit parameters of the trapezoidal model with the minimum chi-square metric are converted to set initial values of the fit parameters of the standard transit model. Additional parameters, such as the equilibrium temperature and effective stellar flux of the planet candidate, are derived from the fit parameters of the standard transit model to characterize pipeline candidates for the search of Earth-size planets in the Habitable Zone. The uncertainties of all derived parameters are updated in the latest codebase to take into account for the propagated errors of the fit parameters as well as the uncertainties in stellar parameters. The results of the transit model fitting of the TCEs identified by the Kepler SOC Pipeline, including fitted and derived parameters, fit goodness metrics and
Design of spatial experiments: Model fitting and prediction
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.
Using proper regression methods for fitting the Langmuir model to sorption data
Technology Transfer Automated Retrieval System (TEKTRAN)
The Langmuir model, originally developed for the study of gas sorption to surfaces, is one of the most commonly used models for fitting phosphorus sorption data. There are good theoretical reasons, however, against applying this model to describe P sorption to soils. Nevertheless, the Langmuir model...
Perturbed atoms in molecules and solids: The PATMOS model
NASA Astrophysics Data System (ADS)
Røeggen, Inge; Gao, Bin
2013-09-01
A new computational method for electronic-structure studies of molecules and solids is presented. The key element in the new model - denoted the perturbed atoms in molecules and solids model - is the concept of a perturbed atom in a complex. The basic approximation of the new model is unrestricted Hartree Fock (UHF). The UHF orbitals are localized by the Edmiston-Ruedenberg procedure. The perturbed atoms are defined by distributing the orbitals among the nuclei in such a way that the sum of the intra-atomic UHF energies has a minimum. Energy corrections with respect to the UHF energy, are calculated within the energy incremental scheme. The most important three- and four-electron corrections are selected by introducing a modified geminal approach. Test calculations are performed on N2, Li2, and parallel arrays of hydrogen atoms. The character of the perturbed atoms is illustrated by calculations on H2, CH4, and C6H6.
Perturbed atoms in molecules and solids: The PATMOS model.
Røeggen, Inge; Gao, Bin
2013-09-01
A new computational method for electronic-structure studies of molecules and solids is presented. The key element in the new model - denoted the perturbed atoms in molecules and solids model - is the concept of a perturbed atom in a complex. The basic approximation of the new model is unrestricted Hartree Fock (UHF). The UHF orbitals are localized by the Edmiston-Ruedenberg procedure. The perturbed atoms are defined by distributing the orbitals among the nuclei in such a way that the sum of the intra-atomic UHF energies has a minimum. Energy corrections with respect to the UHF energy, are calculated within the energy incremental scheme. The most important three- and four-electron corrections are selected by introducing a modified geminal approach. Test calculations are performed on N2, Li2, and parallel arrays of hydrogen atoms. The character of the perturbed atoms is illustrated by calculations on H2, CH4, and C6H6. PMID:24028099
Fitting the Balding-Nichols model to forensic databases.
Rohlfs, Rori V; Aguiar, Vitor R C; Lohmueller, Kirk E; Castro, Amanda M; Ferreira, Alessandro C S; Almeida, Vanessa C O; Louro, Iuri D; Nielsen, Rasmus
2015-11-01
Large forensic databases provide an opportunity to compare observed empirical rates of genotype matching with those expected under forensic genetic models. A number of researchers have taken advantage of this opportunity to validate some forensic genetic approaches, particularly to ensure that estimated rates of genotype matching between unrelated individuals are indeed slight overestimates of those observed. However, these studies have also revealed systematic error trends in genotype probability estimates. In this analysis, we investigate these error trends and show how they result from inappropriate implementation of the Balding-Nichols model in the context of database-wide matching. Specifically, we show that in addition to accounting for increased allelic matching between individuals with recent shared ancestry, studies must account for relatively decreased allelic matching between individuals with more ancient shared ancestry. PMID:26186694
ERIC Educational Resources Information Center
Kiers, Henk A. L.
1989-01-01
An alternating least squares algorithm is offered for fitting the DEcomposition into DIrectional COMponents (DEDICOM) model for representing asymmetric relations among a set of objects via a set of coordinates for the objects on a limited number of dimensions. An algorithm is presented for fitting the IDIOSCAL model in the least squares sense.…
Parameter fitting for piano sound synthesis by physical modeling
NASA Astrophysics Data System (ADS)
Bensa, Julien; Gipouloux, Olivier; Kronland-Martinet, Richard
2005-07-01
A difficult issue in the synthesis of piano tones by physical models is to choose the values of the parameters governing the hammer-string model. In fact, these parameters are hard to estimate from static measurements, causing the synthesis sounds to be unrealistic. An original approach that estimates the parameters of a piano model, from the measurement of the string vibration, by minimizing a perceptual criterion is proposed. The minimization process that was used is a combination of a gradient method and a simulated annealing algorithm, in order to avoid convergence problems in case of multiple local minima. The criterion, based on the tristimulus concept, takes into account the spectral energy density in three bands, each allowing particular parameters to be estimated. The optimization process has been run on signals measured on an experimental setup. The parameters thus estimated provided a better sound quality than the one obtained using a global energetic criterion. Both the sound's attack and its brightness were better preserved. This quality gain was obtained for parameter values very close to the initial ones, showing that only slight deviations are necessary to make synthetic sounds closer to the real ones.
A model for programmatic assessment fit for purpose.
van der Vleuten, C P M; Schuwirth, L W T; Driessen, E W; Dijkstra, J; Tigelaar, D; Baartman, L K J; van Tartwijk, J
2012-01-01
We propose a model for programmatic assessment in action, which simultaneously optimises assessment for learning and assessment for decision making about learner progress. This model is based on a set of assessment principles that are interpreted from empirical research. It specifies cycles of training, assessment and learner support activities that are complemented by intermediate and final moments of evaluation on aggregated assessment data points. A key principle is that individual data points are maximised for learning and feedback value, whereas high-stake decisions are based on the aggregation of many data points. Expert judgement plays an important role in the programme. Fundamental is the notion of sampling and bias reduction to deal with the inevitable subjectivity of this type of judgement. Bias reduction is further sought in procedural assessment strategies derived from criteria for qualitative research. We discuss a number of challenges and opportunities around the proposed model. One of its prime virtues is that it enables assessment to move, beyond the dominant psychometric discourse with its focus on individual instruments, towards a systems approach to assessment design underpinned by empirically grounded theory. PMID:22364452
CPOPT : optimization for fitting CANDECOMP/PARAFAC models.
Dunlavy, Daniel M.; Kolda, Tamara Gibson; Acar, Evrim
2008-10-01
Tensor decompositions (e.g., higher-order analogues of matrix decompositions) are powerful tools for data analysis. In particular, the CANDECOMP/PARAFAC (CP) model has proved useful in many applications such chemometrics, signal processing, and web analysis; see for details. The problem of computing the CP decomposition is typically solved using an alternating least squares (ALS) approach. We discuss the use of optimization-based algorithms for CP, including how to efficiently compute the derivatives necessary for the optimization methods. Numerical studies highlight the positive features of our CPOPT algorithms, as compared with ALS and Gauss-Newton approaches.
"Piekara's Chair": Mechanical Model for Atomic Energy Levels.
ERIC Educational Resources Information Center
Golab-Meyer, Zofia
1991-01-01
Uses the teaching method of models or analogies, specifically the model called "Piekara's chair," to show how teaching classical mechanics can familiarize students with the notion of energy levels in atomic physics. (MDH)
Proposed reference models for atomic oxygen in the terrestrial atmosphere
NASA Technical Reports Server (NTRS)
Llewellyn, E. J.; Mcdade, I. C.; Lockerbie, M. D.
1989-01-01
A provisional Atomic Oxygen Reference model was derived from average monthly ozone profiles and the MSIS-86 reference model atmosphere. The concentrations are presented in tabular form for the altitude range 40 to 130 km.
The Quantum Atomic Model "Electronium": A Successful Teaching Tool.
ERIC Educational Resources Information Center
Budde, Marion; Niedderer, Hans; Scott, Philip; Leach, John
2002-01-01
Focuses on the quantum atomic model Electronium. Outlines the Bremen teaching approach in which this model is used, and analyzes the learning of two students as they progress through the teaching unit. (Author/MM)
Modeling epidemics of multidrug-resistant M. tuberculosis of heterogeneous fitness.
Cohen, Ted; Murray, Megan
2004-10-01
Mathematical models have recently been used to predict the future burden of multidrug-resistant tuberculosis (MDRTB). These models suggest the threat of multidrug resistance to TB control will depend on the relative 'fitness' of MDR strains and imply that if the average fitness of MDR strains is considerably less than that of drug-sensitive strains, the emergence of resistance will not jeopardize the success of tuberculosis control efforts. Multidrug resistance in M. tuberculosis is conferred by the sequential acquisition of a number of different single-locus mutations that have been shown to have heterogeneous phenotypic effects. Here we model the impact of initial fitness estimates on the emergence of MDRTB assuming that the relative fitness of MDR strains is heterogeneous. We find that even when the average relative fitness of MDR strains is low and a well-functioning control program is in place, a small subpopulation of a relatively fit MDR strain may eventually outcompete both the drug-sensitive strains and the less fit MDR strains. These results imply that current epidemiological measures and short-term trends in the burden of MDRTB do not provide evidence that MDRTB strains can be contained in the absence of specific efforts to limit transmission from those with MDR disease. PMID:15378056
Developing Models: What is the Atom Really Like?
ERIC Educational Resources Information Center
Records, Roger M.
1982-01-01
Five atomic theory activities feasible for high school students to perform are described based on the following models: (1) Dalton's Uniform Sphere Model; (2) Thomson's Raisin Pudding Model; (3) Rutherford's Nuclear Model; (4) Bohr's Energy Level Model, and (5) Orbital Model from quantum mechanics. (SK)
Sader, John E.; Yousefi, Morteza; Friend, James R.
2014-02-15
Thermal noise spectra of nanomechanical resonators are used widely to characterize their physical properties. These spectra typically exhibit a Lorentzian response, with additional white noise due to extraneous processes. Least-squares fits of these measurements enable extraction of key parameters of the resonator, including its resonant frequency, quality factor, and stiffness. Here, we present general formulas for the uncertainties in these fit parameters due to sampling noise inherent in all thermal noise spectra. Good agreement with Monte Carlo simulation of synthetic data and measurements of an Atomic Force Microscope (AFM) cantilever is demonstrated. These formulas enable robust interpretation of thermal noise spectra measurements commonly performed in the AFM and adaptive control of fitting procedures with specified tolerances.
Are pollination "syndromes" predictive? Asian dalechampia fit neotropical models.
Armbruster, W Scott; Gong, Yan-Bing; Huang, Shuang-Quan
2011-07-01
Using pollination syndrome parameters and pollinator correlations with floral phenotype from the Neotropics, we predicted that Dalechampia bidentata Blume (Euphorbiaceae) in southern China would be pollinated by female resin-collecting bees between 12 and 20 mm in length. Observations in southwestern Yunnan Province, China, revealed pollination primarily by resin-collecting female Megachile (Callomegachile) faceta Bingham (Hymenoptera: Megachilidae). These bees, at 14 mm in length, were in the predicted size range, confirming the utility of syndromes and models developed in distant regions. Phenotypic selection analyses and estimation of adaptive surfaces and adaptive accuracies together suggest that the blossoms of D. bidentata are well adapted to pollination by their most common floral visitors. PMID:21670584
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. PMID:25123507
Adaptation in Tunably Rugged Fitness Landscapes: The Rough Mount Fuji Model
Neidhart, Johannes; Szendro, Ivan G.; Krug, Joachim
2014-01-01
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. PMID:25123507
Martin, Guillaume; Lenormand, Thomas
2015-06-01
When are mutations beneficial in one environment and deleterious in another? More generally, what is the relationship between mutation effects across environments? These questions are crucial to predict adaptation in heterogeneous conditions in a broad sense. Empirical evidence documents various patterns of fitness effects across environments but we still lack a framework to analyze these multivariate data. In this article, we extend Fisher's geometrical model to multiple environments determining distinct peaks. We derive the fitness distribution, in one environment, among mutants with a given fitness in another and the bivariate distribution of random mutants' fitnesses across two or more environments. The geometry of the phenotype-fitness landscape is naturally interpreted in terms of fitness trade-offs between environments. These results may be used to fit/predict empirical distributions or to predict the pattern of adaptation across heterogeneous conditions. As an example, we derive the genomic rate of substitution and of adaptation in a metapopulation divided into two distinct habitats in a high migration regime and show that they depend critically on the geometry of the phenotype-fitness landscape. PMID:25908434
Marsh, Rebeccah E; Riauka, Terence A; McQuarrie, Steve A
2007-01-01
Increasingly, fractals are being incorporated into pharmacokinetic models to describe transport and chemical kinetic processes occurring in confined and heterogeneous spaces. However, fractal compartmental models lead to differential equations with power-law time-dependent kinetic rate coefficients that currently are not accommodated by common commercial software programs. This paper describes a parameter optimization method for fitting individual pharmacokinetic curves based on a simulated annealing (SA) algorithm, which always converged towards the global minimum and was independent of the initial parameter values and parameter bounds. In a comparison using a classical compartmental model, similar fits by the Gauss-Newton and Nelder-Mead simplex algorithms required stringent initial estimates and ranges for the model parameters. The SA algorithm is ideal for fitting a wide variety of pharmacokinetic models to clinical data, especially those for which there is weak prior knowledge of the parameter values, such as the fractal models. PMID:17706176
Early atomic models - from mechanical to quantum (1904-1913)
NASA Astrophysics Data System (ADS)
Baily, C.
2013-01-01
A complete history of early atomic models would fill volumes, but a reasonably coherent tale of the path from mechanical atoms to the quantum can be told by focusing on the relevant work of three great contributors to atomic physics, in the critically important years between 1904 and 1913: J.J. Thomson, Ernest Rutherford and Niels Bohr. We first examine the origins of Thomson's mechanical atomic models, from his ethereal vortex atoms in the early 1880's, to the myriad "corpuscular" atoms he proposed following the discovery of the electron in 1897. Beyond qualitative predictions for the periodicity of the elements, the application of Thomson's atoms to problems in scattering and absorption led to quantitative predictions that were confirmed by experiments with high-velocity electrons traversing thin sheets of metal. Still, the much more massive and energetic α-particles being studied by Rutherford were better suited for exploring the interior of the atom, and careful measurements on the angular dependence of their scattering eventually allowed him to infer the existence of an atomic nucleus. Niels Bohr was particularly troubled by the radiative instability inherent to any mechanical atom, and succeeded in 1913 where others had failed in the prediction of emission spectra, by making two bold hypotheses that were in contradiction to the laws of classical physics, but necessary in order to account for experimental facts.
Revisiting a Statistical Shortcoming When Fitting the Langmuir Model to Sorption Data
Technology Transfer Automated Retrieval System (TEKTRAN)
The Langmuir model is commonly used for describing sorption behavior of reactive solutes to surfaces. Fitting the Langmuir model to sorption data requires either the use of nonlinear regression or, alternatively, linear regression using one of the linearized versions of the model. Statistical limit...
Hydrothermal germination models: comparison of two data-fitting approaches with probit optimization
Technology Transfer Automated Retrieval System (TEKTRAN)
Probit models for estimating hydrothermal germination rate yield model parameters that have been associated with specific physiological processes. The desirability of linking germination response to seed physiology must be weighed against expectations of model fit and the relative accuracy of predi...
Asymptotic Fitness Distribution in the Bak-Sneppen Model of Biological Evolution with Four Species
NASA Astrophysics Data System (ADS)
Schlemm, Eckhard
2012-08-01
We suggest a new method to compute the asymptotic fitness distribution in the Bak-Sneppen model of biological evolution. As applications we derive the full asymptotic distribution in the four-species model, and give an explicit linear recurrence relation for a set of coefficients determining the asymptotic distribution in the five-species model.
Modified Likelihood-Based Item Fit Statistics for the Generalized Graded Unfolding Model
ERIC Educational Resources Information Center
Roberts, James S.
2008-01-01
Orlando and Thissen (2000) developed an item fit statistic for binary item response theory (IRT) models known as S-X[superscript 2]. This article generalizes their statistic to polytomous unfolding models. Four alternative formulations of S-X[superscript 2] are developed for the generalized graded unfolding model (GGUM). The GGUM is a…
NASA Astrophysics Data System (ADS)
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.
EFFICIENT FITTING OF MULTIPLANET KEPLERIAN MODELS TO RADIAL VELOCITY AND ASTROMETRY DATA
Wright, J. T.; Howard, A. W.
2009-05-15
We describe a technique for solving for the orbital elements of multiple planets from radial velocity (RV) and/or astrometric data taken with 1 m s{sup -1} and {mu}as precision, appropriate for efforts to detect Earth-massed planets in their stars' habitable zones, such as NASA's proposed Space Interferometry Mission. We include details of calculating analytic derivatives for use in the Levenberg-Marquardt (LM) algorithm for the problems of fitting RV and astrometric data separately and jointly. We also explicate the general method of separating the linear and nonlinear components of a model fit in the context of an LM fit, show how explicit derivatives can be calculated in such a model, and demonstrate the speed up and convergence improvements of such a scheme in the case of a five-planet fit to published RV data for 55 Cnc.
Transit Model Fitting in Processing Four Years of Kepler Science Data: New Features and Performance
NASA Astrophysics Data System (ADS)
Li, Jie; Burke, Christopher; Jenkins, Jon Michael; Quintana, Elisa; Rowe, Jason; Seader, Shawn; Tenenbaum, Peter; Twicken, Joseph
2015-08-01
We present new transit model fitting features and performance of the latest release (9.3, March 2015) of the Kepler Science Operations Center (SOC) Pipeline, which will be used for the final processing of four years of Kepler science data later this year. Threshold Crossing Events (TCEs), which represent transiting planet detections, are generated by the Transiting Planet Search (TPS) component of the pipeline and subsequently processed in the Data Validation (DV) component. The transit model is used in DV to fit TCEs and derive parameters that are used in various diagnostic tests to validate the planet detections. The standard limb-darkened transit model includes five fit parameters: transit epoch time (i.e. central time of first transit), orbital period, impact parameter, ratio of planet radius to star radius and ratio of semi-major axis to star radius. In the latest Kepler SOC pipeline codebase, the light curve of the target for which a TCE is generated is also fitted by a trapezoidal transit model with four parameters: transit epoch time, depth, duration and ratio of ingress time to duration. The fitted trapezoidal transit model is used in the diagnostic tests when the fit with the standard transit model fails or when the fit is not performed, e.g. for suspected eclipsing binaries. Additional parameters, such as the equilibrium temperature and effective stellar flux (i.e. insolation) of the planet candidate, are derived from the transit model fit parameters to characterize pipeline candidates for the search of Earth-size planets in the habitable zone. The uncertainties of all derived parameters are updated in the latest codebase to account for the propagated errors of the fit parameters as well as the uncertainties in stellar parameters. The results of the transit model fitting for the TCEs identified by the Kepler SOC Pipeline are included in the DV reports and one-page report summaries, which are accessible by the science community at NASA Exoplanet Archive
Packard, Gary C
2013-09-01
The ongoing debate about methods for fitting the two-parameter allometric equation y=ax(b) to bivariate data seemed to be resolved recently when three groups of investigators independently reported that statistical models fitted by the traditional allometric method (i.e., by back-transforming a linear model fitted to log-log transformations) typically are superior to models fitted by standard nonlinear regression. However, the narrow focus for the statistical analyses in these investigations compromised the most important of the ensuing conclusions. All the investigations focused on two-parameter power functions and excluded from consideration other simple functions that might better describe pattern in the data; and all relied on Akaike's Information Criterion instead of graphical validation to identify the better statistical model. My re-analysis of data from one of the studies (BMR vs. body mass in mustelid carnivores) revealed (1) that the best descriptor for pattern in the dataset is a straight line and not a two-parameter power function; (2) that a model with additive, normal, heteroscedastic error is superior to one with multiplicative, lognormal, heteroscedastic error; and (3) that Akaike's Information Criterion is not a generally reliable metric for discriminating between models fitted to different distributions. These findings have apparent implications for interpreting the outcomes of all three of the aforementioned studies. Future investigations of allometric variation should adopt a more holistic approach to analysis and not be wedded to the traditional allometric method. PMID:23688506
100th anniversary of Bohr's model of the atom.
Schwarz, W H Eugen
2013-11-18
In the fall of 1913 Niels Bohr formulated his atomic models at the age of 27. This Essay traces Bohr's fundamental reasoning regarding atomic structure and spectra, the periodic table of the elements, and chemical bonding. His enduring insights and superseded suppositions are also discussed. PMID:24123759
Project Physics Tests 5, Models of the Atom.
ERIC Educational Resources Information Center
Harvard Univ., Cambridge, MA. Harvard Project Physics.
Test items relating to Project Physics Unit 5 are presented in this booklet. Included are 70 multiple-choice and 23 problem-and-essay questions. Concepts of atomic model are examined on aspects of relativistic corrections, electron emission, photoelectric effects, Compton effect, quantum theories, electrolysis experiments, atomic number and mass,…
NASA Astrophysics Data System (ADS)
Farrell, Kathryn; Oden, J. Tinsley
2014-07-01
Coarse-grained models of atomic systems, created by aggregating groups of atoms into molecules to reduce the number of degrees of freedom, have been used for decades in important scientific and technological applications. In recent years, interest in developing a more rigorous theory for coarse graining and in assessing the predictivity of coarse-grained models has arisen. In this work, Bayesian methods for the calibration and validation of coarse-grained models of atomistic systems in thermodynamic equilibrium are developed. For specificity, only configurational models of systems in canonical ensembles are considered. Among major challenges in validating coarse-grained models are (1) the development of validation processes that lead to information essential in establishing confidence in the model's ability predict key quantities of interest and (2), above all, the determination of the coarse-grained model itself; that is, the characterization of the molecular architecture, the choice of interaction potentials and thus parameters, which best fit available data. The all-atom model is treated as the "ground truth," and it provides the basis with respect to which properties of the coarse-grained model are compared. This base all-atom model is characterized by an appropriate statistical mechanics framework in this work by canonical ensembles involving only configurational energies. The all-atom model thus supplies data for Bayesian calibration and validation methods for the molecular model. To address the first challenge, we develop priors based on the maximum entropy principle and likelihood functions based on Gaussian approximations of the uncertainties in the parameter-to-observation error. To address challenge (2), we introduce the notion of model plausibilities as a means for model selection. This methodology provides a powerful approach toward constructing coarse-grained models which are most plausible for given all-atom data. We demonstrate the theory and
Unifying distance-based goodness-of-fit indicators for hydrologic model assessment
NASA Astrophysics Data System (ADS)
Cheng, Qinbo; Reinhardt-Imjela, Christian; Chen, Xi; Schulte, Achim
2014-05-01
The goodness-of-fit indicator, i.e. efficiency criterion, is very important for model calibration. However, recently the knowledge about the goodness-of-fit indicators is all empirical and lacks a theoretical support. Based on the likelihood theory, a unified distance-based goodness-of-fit indicator termed BC-GED model is proposed, which uses the Box-Cox (BC) transformation to remove the heteroscedasticity of model errors and the generalized error distribution (GED) with zero-mean to fit the distribution of model errors after BC. The BC-GED model can unify all recent distance-based goodness-of-fit indicators, and reveals the mean square error (MSE) and the mean absolute error (MAE) that are widely used goodness-of-fit indicators imply statistic assumptions that the model errors follow the Gaussian distribution and the Laplace distribution with zero-mean, respectively. The empirical knowledge about goodness-of-fit indicators can be also easily interpreted by BC-GED model, e.g. the sensitivity to high flow of the goodness-of-fit indicators with large power of model errors results from the low probability of large model error in the assumed distribution of these indicators. In order to assess the effect of the parameters (i.e. the BC transformation parameter λ and the GED kurtosis coefficient β also termed the power of model errors) of BC-GED model on hydrologic model calibration, six cases of BC-GED model were applied in Baocun watershed (East China) with SWAT-WB-VSA model. Comparison of the inferred model parameters and model simulation results among the six indicators demonstrates these indicators can be clearly separated two classes by the GED kurtosis β: β >1 and β ≤ 1. SWAT-WB-VSA calibrated by the class β >1 of distance-based goodness-of-fit indicators captures high flow very well and mimics the baseflow very badly, but it calibrated by the class β ≤ 1 mimics the baseflow very well, because first the larger value of β, the greater emphasis is put on
Soft X-ray spectral fits of Geminga with model neutron star atmospheres
NASA Technical Reports Server (NTRS)
Meyer, R. D.; Pavlov, G. G.; Meszaros, P.
1994-01-01
The spectrum of the soft X-ray pulsar Geminga consists of two components, a softer one which can be interpreted as thermal-like radiation from the surface of the neutron star, and a harder one interpreted as radiation from a polar cap heated by relativistic particles. We have fitted the soft spectrum using a detailed magnetized hydrogen atmosphere model. The fitting parameters are the hydrogen column density, the effective temperature T(sub eff), the gravitational redshift z, and the distance to radius ratio, for different values of the magnetic field B. The best fits for this model are obtained when B less than or approximately 1 x 10(exp 12) G and z lies on the upper boundary of the explored range (z = 0.45). The values of T(sub eff) approximately = (2-3) x 10(exp 5) K are a factor of 2-3 times lower than the value of T(sub eff) obtained for blackbody fits with the same z. The lower T(sub eff) increases the compatibility with some proposed schemes for fast neutrino cooling of neutron stars (NSs) by the direct Urca process or by exotic matter, but conventional cooling cannot be excluded. The hydrogen atmosphere fits also imply a smaller distance to Geminga than that inferred from a blackbody fit. An accurate evaluation of the distance would require a better knowledge of the ROSAT Position Sensitive Proportional Counter (PSPC) response to the low-energy region of the incident spectrum. Our modeling of the soft component with a cooler magnetized atmosphere also implies that the hard-component fit requires a characteristic temperature which is higher (by a factor of approximately 2-3) and a surface area which is smaller (by a factor of 10(exp 3), compared to previous blackbody fits.
Fast numerical algorithms for fitting multiresolution hybrid shape models to brain MRI.
Vemuri, B C; Guo, Y; Lai, S H; Leonard, C M
1997-09-01
In this paper, we present new and fast numerical algorithms for shape recovery from brain MRI using multiresolution hybrid shape models. In this modeling framework, shapes are represented by a core rigid shape characterized by a superquadric function and a superimposed displacement function which is characterized by a membrane spline discretized using the finite-element method. Fitting the model to brain MRI data is cast as an energy minimization problem which is solved numerically. We present three new computational methods for model fitting to data. These methods involve novel mathematical derivations that lead to efficient numerical solutions of the model fitting problem. The first method involves using the nonlinear conjugate gradient technique with a diagonal Hessian preconditioner. The second method involves the nonlinear conjugate gradient in the outer loop for solving global parameters of the model and a preconditioned conjugate gradient scheme for solving the local parameters of the model. The third method involves the nonlinear conjugate gradient in the outer loop for solving the global parameters and a combination of the Schur complement formula and the alternating direction-implicit method for solving the local parameters of the model. We demonstrate the efficiency of our model fitting methods via experiments on several MR brain scans. PMID:9873915
Collisional radiative average atom code based on a relativistic Screened Hydrogenic Model
NASA Astrophysics Data System (ADS)
Benita, A. J.; Mínguez, E.; Mendoza, M. A.; Rubiano, J. G.; Gil, J. M.; Rodríguez, R.; Martel, P.
2015-03-01
A steady-state and time-dependent collisional-radiative ''average-atom'' (AA) model (ATMED CR) is presented for the calculation of atomic and radiative properties of plasmas for a wide range of laboratory and theoretical conditions: coronal, local thermodynamic equilibrium or nonlocal thermodynamic equilibrium, optically thin or thick plasmas and photoionized plasmas. The radiative and collisional rates are a set of analytical approximations that compare well with more sophisticated quantum treatment of atomic rates that yield fast calculations. The atomic model is based on a new Relativistic Screened Hydrogenic Model (NRSHM) with a set of universal screening constants including nlj-splitting that has been obtained by fitting to a large database of ionization potentials and excitation energies compiled from the National Institute of Standards and Technology (NIST) database and the Flexible Atomic Code (FAC). The model NRSHM has been validated by comparing the results with ionization energies, transition energies and wave functions computed using sophisticated self-consistent codes and experimental data. All the calculations presented in this work were performed using ATMED CR code.
Development and design of a late-model fitness test instrument based on LabView
NASA Astrophysics Data System (ADS)
Xie, Ying; Wu, Feiqing
2010-12-01
Undergraduates are pioneers of China's modernization program and undertake the historic mission of rejuvenating our nation in the 21st century, whose physical fitness is vital. A smart fitness test system can well help them understand their fitness and health conditions, thus they can choose more suitable approaches and make practical plans for exercising according to their own situation. following the future trends, a Late-model fitness test Instrument based on LabView has been designed to remedy defects of today's instruments. The system hardware consists of fives types of sensors with their peripheral circuits, an acquisition card of NI USB-6251 and a computer, while the system software, on the basis of LabView, includes modules of user register, data acquisition, data process and display, and data storage. The system, featured by modularization and an open structure, is able to be revised according to actual needs. Tests results have verified the system's stability and reliability.
Mimno, David; Blei, David M.; Engelhardt, Barbara E.
2015-01-01
Admixture models are a ubiquitous approach to capture latent population structure in genetic samples. Despite the widespread application of admixture models, little thought has been devoted to the quality of the model fit or the accuracy of the estimates of parameters of interest for a particular study. Here we develop methods for validating admixture models based on posterior predictive checks (PPCs), a Bayesian method for assessing the quality of fit of a statistical model to a specific dataset. We develop PPCs for five population-level statistics of interest: within-population genetic variation, background linkage disequilibrium, number of ancestral populations, between-population genetic variation, and the downstream use of admixture parameters to correct for population structure in association studies. Using PPCs, we evaluate the quality of the admixture model fit to four qualitatively different population genetic datasets: the population reference sample (POPRES) European individuals, the HapMap phase 3 individuals, continental Indians, and African American individuals. We found that the same model fitted to different genomic studies resulted in highly study-specific results when evaluated using PPCs, illustrating the utility of PPCs for model-based analyses in large genomic studies. PMID:26071445
An Assessment of the Nonparametric Approach for Evaluating the Fit of Item Response Models
ERIC Educational Resources Information Center
Liang, Tie; Wells, Craig S.; Hambleton, Ronald K.
2014-01-01
As item response theory has been more widely applied, investigating the fit of a parametric model becomes an important part of the measurement process. There is a lack of promising solutions to the detection of model misfit in IRT. Douglas and Cohen introduced a general nonparametric approach, RISE (Root Integrated Squared Error), for detecting…
Mimno, David; Blei, David M; Engelhardt, Barbara E
2015-06-30
Admixture models are a ubiquitous approach to capture latent population structure in genetic samples. Despite the widespread application of admixture models, little thought has been devoted to the quality of the model fit or the accuracy of the estimates of parameters of interest for a particular study. Here we develop methods for validating admixture models based on posterior predictive checks (PPCs), a Bayesian method for assessing the quality of fit of a statistical model to a specific dataset. We develop PPCs for five population-level statistics of interest: within-population genetic variation, background linkage disequilibrium, number of ancestral populations, between-population genetic variation, and the downstream use of admixture parameters to correct for population structure in association studies. Using PPCs, we evaluate the quality of the admixture model fit to four qualitatively different population genetic datasets: the population reference sample (POPRES) European individuals, the HapMap phase 3 individuals, continental Indians, and African American individuals. We found that the same model fitted to different genomic studies resulted in highly study-specific results when evaluated using PPCs, illustrating the utility of PPCs for model-based analyses in large genomic studies. PMID:26071445
Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes
ERIC Educational Resources Information Center
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…
ERIC Educational Resources Information Center
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…
Optimization-Based Model Fitting for Latent Class and Latent Profile Analyses
ERIC Educational Resources Information Center
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…
Shot model parameters for Cygnus X-1 through phase portrait fitting
Lochner, J.C.; Swank, J.H.; Szymkowiak, A.E. )
1991-07-01
Shot models for systems having about 1/f power density spectrum are developed by utilizing a distribution of shot durations. Parameters of the distribution are determined by fitting the power spectrum either with analytic forms for the spectrum of a shot model with a given shot profile, or with the spectrum derived from numerical realizations of trial shot models. The shot fraction is specified by fitting the phase portrait, which is a plot of intensity at a given time versus intensity at a delayed time and in principle is sensitive to different shot profiles. These techniques have been extensively applied to the X-ray variability of Cygnus X-1, using HEAO 1 A-2 and an Exosat ME observation. The power spectra suggest models having characteristic shot durations lasting from milliseconds to a few seconds, while the phase portrait fits give shot fractions of about 50 percent. Best fits to the portraits are obtained if the amplitude of the shot is a power-law function of the duration of the shot. These fits prefer shots having a symmetric exponential rise and decay. Results are interpreted in terms of a distribution of magnetic flares in the accretion disk. 30 refs.
The Predicting Model of E-commerce Site Based on the Ideas of Curve Fitting
NASA Astrophysics Data System (ADS)
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.
Curve fitting toxicity test data: Which comes first, the dose response or the model?
Gully, J.; Baird, R.; Bottomley, J.
1995-12-31
The probit model frequently does not fit the concentration-response curve of NPDES toxicity test data and non-parametric models must be used instead. The non-parametric models, trimmed Spearman-Karber, IC{sub p}, and linear interpolation, all require a monotonic concentration-response. Any deviation from a monotonic response is smoothed to obtain the desired concentration-response characteristics. Inaccurate point estimates may result from such procedures and can contribute to imprecision in replicate tests. The following study analyzed reference toxicant and effluent data from giant kelp (Macrocystis pyrifera), purple sea urchin (Strongylocentrotus purpuratus), red abalone (Haliotis rufescens), and fathead minnow (Pimephales promelas) bioassays using commercially available curve fitting software. The purpose was to search for alternative parametric models which would reduce the use of non-parametric models for point estimate analysis of toxicity data. Two non-linear models, power and logistic dose-response, were selected as possible alternatives to the probit model based upon their toxicological plausibility and ability to model most data sets examined. Unlike non-parametric procedures, these and all parametric models can be statistically evaluated for fit and significance. The use of the power or logistic dose response models increased the percentage of parametric model fits for each protocol and toxicant combination examined. The precision of the selected non-linear models was also compared with the EPA recommended point estimation models at several effect.levels. In general, precision of the alternative models was equal to or better than the traditional methods. Finally, use of the alternative models usually produced more plausible point estimates in data sets where the effects of smoothing and non-parametric modeling made the point estimate results suspect.
Optimization of Active Muscle Force-Length Models Using Least Squares Curve Fitting.
Mohammed, Goran Abdulrahman; Hou, Ming
2016-03-01
The objective of this paper is to propose an asymmetric Gaussian function as an alternative to the existing active force-length models, and to optimize this model along with several other existing models by using the least squares curve fitting method. The minimal set of coefficients is identified for each of these models to facilitate the least squares curve fitting. Sarcomere simulated data and one set of rabbits extensor digitorum II experimental data are used to illustrate optimal curve fitting of the selected force-length functions. The results shows that all the curves fit reasonably well with the simulated and experimental data, while the Gordon-Huxley-Julian model and asymmetric Gaussian function are better than other functions in terms of statistical test scores root mean squared error and R-squared. However, the differences in RMSE scores are insignificant (0.3-6%) for simulated data and (0.2-5%) for experimental data. The proposed asymmetric Gaussian model and the method of parametrization of this and the other force-length models mentioned above can be used in the studies on active force-length relationships of skeletal muscles that generate forces to cause movements of human and animal bodies. PMID:26276984
Detailed atomic modeling of Sn plasmas for the EUV source
NASA Astrophysics Data System (ADS)
Sasaki, A.; Sunahara, A.; Nishihawra, K.; Nishikawa, T.; Koike, F.; Tanuma, H.
2008-05-01
An atomic model of Sn plasmas is developed to calculate coefficients of radiative transfer, based on the calculated atomic data using the Hullac code. We find that the emission spectrum and conversion efficiency depend critically on the wavelength and spectral structure of the 4d-4f transition arrays. Satellite lines, which have a significant contribution to the emission, are determined after iterative calculations by changing the number of levels in the atomic model. We also correct transition wavelengths through comparison with experiments. Using the present emissivity and opacity, the radiation hydrodynamics simulation will be carried out toward the optimization of the EUV source.
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
Soluble Model of Evolution and Extinction Dynamics in a Rugged Fitness Landscape
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Chaney, Andrea; Espinosa, James; Espinosa, James
2006-10-01
At the turn of the twentieth century, physicists and chemists were developing atomic models. Some of the phenomena that they had to explain were the periodic table, the stability of the atom, and the emission spectra. Niels Bohr is known as making the first modern picture that accounted for these. Unknown to much of the physics community is the work of Walter Ritz. His model explained more emission spectra and predates Bohr's work. We will fit several spectra using Ritz's magnetic model for the atom. The problems of stability and chemical periodicity will be shown to be challenges that this model has difficulty solving, but we will present some potentially useful adaptations to the Ritzian atom that can account for them.
Alpha-cluster model of atomic nuclei
NASA Astrophysics Data System (ADS)
Sosin, Zbigniew; Błocki, Jan; Kallunkathariyil, Jinesh; Łukasik, Jerzy; Pawłowski, Piotr
2016-05-01
The description of a nuclear system in its ground state and at low excitations based on the equation of state (EoS) around normal density is presented. In the expansion of the EoS around the saturation point, additional spin polarization terms are taken into account. These terms, together with the standard symmetry term, are responsible for the appearance of the α-like clusters in the ground-state configurations of the N = Z even-even nuclei. At the nuclear surface these clusters can be identified as alpha particles. A correction for the surface effects is introduced for atomic nuclei. Taking into account an additional interaction between clusters the binding energies and sizes of the considered nuclei are very accurately described. The limits of the EoS parameters are established from the properties of the α, 3He and t particles.
MEAMfit: A reference-free modified embedded atom method (RF-MEAM) energy and force-fitting code
NASA Astrophysics Data System (ADS)
Duff, Andrew Ian
2016-06-01
MEAMfit v1.02. Changes: various bug fixes; speed of single-shot energy and force calculations (not optimization) increased by × 10; elements up to Cn (Z = 112) now correctly read from vasprun.xml files; EAM fits now produce Camelion output files; changed max number of vasprun.xml files to 10,000 (an unnecessary lower limit of 10 was allowed in the previous version).
The FIT 2.0 Model - Fuel-cycle Integration and Tradeoffs
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.
Fitting the linear quadratic model to detailed data sets for different dose ranges
NASA Astrophysics Data System (ADS)
Garcia, L. M.; Leblanc, J.; Wilkins, D.; Raaphorst, G. P.
2006-06-01
Survival curve behaviour and degree of correspondence between the linear-quadratic (LQ) model and experimental data in an extensive dose range for high dose rates were analysed. Detailed clonogenic assays with irradiation given in 0.5 Gy increments and a total dose range varying from 10.5 to 16 Gy were performed. The cell lines investigated were: CHOAA8 (Chinese hamster fibroblast cells), U373MG (human glioblastoma cells), CP3 and DU145 (human prostate carcinoma cell lines). The analyses were based on χ2-statistics and Monte Carlo simulation of the experiments. A decline of LQ fit quality at very low doses (<2 Gy) is observed. This result can be explained by the hypersensitive effect observed in CHOAA8, U373MG and DU145 data and an adaptive-type response in the CP3 cell line. A clear improvement of the fit is discerned by removing the low dose data points. The fit worsening at high doses also shows that LQ cannot explain this region. This shows that the LQ model fits better the middle dose region of the survival curve. The analysis conducted in our study reveals a dose dependency of the LQ fit in different cell lines.
Clavijo-Baque, Sabrina; Bozinovic, Francisco
2012-01-01
The origin of endothermy is a puzzling phenomenon in the evolution of vertebrates. To address this issue several explicative models have been proposed. The main models proposed for the origin of endothermy are the aerobic capacity, the thermoregulatory and the parental care models. Our main proposal is that to compare the alternative models, a critical aspect is to determine how strongly natural selection was influenced by body temperature, and basal and maximum metabolic rates during the evolution of endothermy. We evaluate these relationships in the context of three main hypotheses aimed at explaining the evolution of endothermy, namely the parental care hypothesis and two hypotheses related to the thermoregulatory model (thermogenic capacity and higher body temperature models). We used data on basal and maximum metabolic rates and body temperature from 17 rodent populations, and used intrinsic population growth rate (Rmax) as a global proxy of fitness. We found greater support for the thermogenic capacity model of the thermoregulatory model. In other words, greater thermogenic capacity is associated with increased fitness in rodent populations. To our knowledge, this is the first test of the fitness consequences of the thermoregulatory and parental care models for the origin of endothermy. PMID:22606328
Burnham, A K
2006-05-17
Chemical kinetic modeling has been used for many years in process optimization, estimating real-time material performance, and lifetime prediction. Chemists have tended towards developing detailed mechanistic models, while engineers have tended towards global or lumped models. Many, if not most, applications use global models by necessity, since it is impractical or impossible to develop a rigorous mechanistic model. Model fitting acquired a bad name in the thermal analysis community after that community realized a decade after other disciplines that deriving kinetic parameters for an assumed model from a single heating rate produced unreliable and sometimes nonsensical results. In its place, advanced isoconversional methods (1), which have their roots in the Friedman (2) and Ozawa-Flynn-Wall (3) methods of the 1960s, have become increasingly popular. In fact, as pointed out by the ICTAC kinetics project in 2000 (4), valid kinetic parameters can be derived by both isoconversional and model fitting methods as long as a diverse set of thermal histories are used to derive the kinetic parameters. The current paper extends the understanding from that project to give a better appreciation of the strengths and weaknesses of isoconversional and model-fitting approaches. Examples are given from a variety of sources, including the former and current ICTAC round-robin exercises, data sets for materials of interest, and simulated data sets.
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
Aeroelastic modeling for the FIT team F/A-18 simulation
NASA Technical Reports Server (NTRS)
Zeiler, Thomas A.; Wieseman, Carol D.
1989-01-01
Some details of the aeroelastic modeling of the F/A-18 aircraft done for the Functional Integration Technology (FIT) team's research in integrated dynamics modeling and how these are combined with the FIT team's integrated dynamics model are described. Also described are mean axis corrections to elastic modes, the addition of nonlinear inertial coupling terms into the equations of motion, and the calculation of internal loads time histories using the integrated dynamics model in a batch simulation program. A video tape made of a loads time history animation was included as a part of the oral presentation. Also discussed is work done in one of the areas of unsteady aerodynamic modeling identified as needing improvement, specifically, in correction factor methodologies for improving the accuracy of stability derivatives calculated with a doublet lattice code.
Model fitting of the kinematics of ten superluminal components in blazar 3C 279
NASA Astrophysics Data System (ADS)
Qian, Shan-Jie
2013-07-01
The kinematics of ten superluminal components (C11- C16, C18, C20, C21 and C24) of blazar 3C 279 are studied from VLBI observations. It is shown that their initial trajectory, distance from the core and apparent speed can be well fitted by the precession model proposed by Qian. Combined with the results of the model fit for the six superluminal components (C3, C4, C7a, C8, C9 and C10) already published, the kinematics of sixteen superluminal components can now be consistently interpreted in the precession scenario with their ejection times spanning more than 25 yr (or more than one precession period). The results from model fitting show the possible existence of a common precessing trajectory for these knots within a projected core distance of ~0.2-0.4 mas. In the framework of the jet-precession scenario, we can, for the first time, identify three classes of trajectories which are characterized by their collimation parameters. These different trajectories could be related to the helical structure of magnetic fields in the jet. Through fitting the model, the bulk Lorentz factor, Doppler factor and viewing angle of these knots are derived. It is found that there is no evidence for any correlation between the bulk Lorentz factor of the components and their precession phase (or ejection time). In a companion paper, the kinematics of another seven components (C5a, C6, C7, C17, C19, C22 and C23) have been derived from model fitting, and a binary black-hole/jet scenario was envisaged. The precession model proposed by Qian would be useful for understanding the kinematics of superluminal components in blazar 3C 279 derived from VLBI observations, by disentangling different mechanisms and ingredients. More generally, it might also be helpful for studying the mechanism of jet swing (wobbling) in other blazars.
Impact of Missing Data on Person-Model Fit and Person Trait Estimation
ERIC Educational Resources Information Center
Zhang, Bo; Walker, Cindy M.
2008-01-01
The purpose of this research was to examine the effects of missing data on person-model fit and person trait estimation in tests with dichotomous items. Under the missing-completely-at-random framework, four missing data treatment techniques were investigated including pairwise deletion, coding missing responses as incorrect, hotdeck imputation,…
ERIC Educational Resources Information Center
Harris, Carole Ruth
2010-01-01
This article presents the author's comments on Hisham Ghassib's article entitled "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?" In his article, Ghassib (2010) provides an overview of the philosophical foundations that led to exact science, its role in what was later to become a driving force in the modern…
A Bayesian Approach to Person Fit Analysis in Item Response Theory Models. Research Report.
ERIC Educational Resources Information Center
Glas, Cees A. W.; Meijer, Rob R.
A Bayesian approach to the evaluation of person fit in item response theory (IRT) models is presented. In a posterior predictive check, the observed value on a discrepancy variable is positioned in its posterior distribution. In a Bayesian framework, a Markov Chain Monte Carlo procedure can be used to generate samples of the posterior distribution…
IRT Model Fit Evaluation from Theory to Practice: Progress and Some Unanswered Questions
ERIC Educational Resources Information Center
Cai, Li; Monroe, Scott
2013-01-01
In this commentary, the authors congratulate Professor Alberto Maydeu-Olivares on his article [EJ1023617: "Goodness-of-Fit Assessment of Item Response Theory Models, Measurement: Interdisciplinary Research and Perspectives," this issue] as it provides a much needed overview on the mathematical underpinnings of the theory behind the…
Universal Screening for Emotional and Behavioral Problems: Fitting a Population-Based Model
ERIC Educational Resources Information Center
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…
Examining Creative Performance in the Workplace through a Person-Environment Fit Model.
ERIC Educational Resources Information Center
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…
On Fitting Nonlinear Latent Curve Models to Multiple Variables Measured Longitudinally
ERIC Educational Resources Information Center
Blozis, Shelley A.
2007-01-01
This article shows how nonlinear latent curve models may be fitted for simultaneous analysis of multiple variables measured longitudinally using Mx statistical software. Longitudinal studies often involve observation of several variables across time with interest in the associations between change characteristics of different variables measured…
ERIC Educational Resources Information Center
Wang, Chee Keng John; Pyun, Do Young; Liu, Woon Chia; Lim, Boon San Coral; Li, Fuzhong
2013-01-01
Using a multilevel latent growth curve modeling (LGCM) approach, this study examined longitudinal change in levels of physical fitness performance over time (i.e. four years) in young adolescents aged from 12-13 years. The sample consisted of 6622 students from 138 secondary schools in Singapore. Initial analyses found between-school variation on…
Super Kids--Superfit. A Comprehensive Fitness Intervention Model for Elementary Schools.
ERIC Educational Resources Information Center
Virgilio, Stephen J.; Berenson, Gerald S.
1988-01-01
Objectives and activities of the cardiovascular (CV) fitness program Super Kids--Superfit are related in this article. This exercise program is one component of the Heart Smart Program, a CV health intervention model for elementary school students. Program evaluation, parent education, and school and community intervention strategies are…
Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee
2013-07-01
Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models. PMID:25106393
ERIC Educational Resources Information Center
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…
ERIC Educational Resources Information Center
Neber, Heinz
2010-01-01
In this article, the author presents his comments on Hisham Ghassib's article entitled "Where Does Creativity Fit into the Productivist Industrial Model of Knowledge Production?" Ghassib (2010) describes historical transformations of science from a marginal and non-autonomous activity which had been constrained by traditions to a self-autonomous,…
Small-Sample Robust Estimators of Noncentrality-Based and Incremental Model Fit
ERIC Educational Resources Information Center
Herzog, Walter; Boomsma, Anne
2009-01-01
Traditional estimators of fit measures based on the noncentral chi-square distribution (root mean square error of approximation [RMSEA], Steiger's [gamma], 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 (2005), or Swain's (1975) correction of the…
NASA Astrophysics Data System (ADS)
Flipo, N.; Monteil, C.; Poulin, M.; de Fouquet, C.; Krimissa, M.
2012-05-01
This study aims at analyzing the water budget of the unconfined Beauce aquifer (8000 km2) over a 35 year period, by modeling the hydrological functioning and quantifying exchanged water fluxes inside the system. A distributed process-based model (DPBM) is implemented to model the surface, the unsaturated zone and the aquifer subsystems. Based on an extensive literature review on multiparameter optimization and inverse problem, a pragmatic hybrid fitting method that couples manual and automatic calibration is developed. Three data subsets are used for calibration (10 year), validation (10 year) and test (35 year). The global piezometric head root-mean-square error is around 2.5 m for the three subsets and is rather uniformly spatially distributed over 78 piezometers. The sensitivity of the simulation to the different steps of the calibration process is investigated. The transmissivity field permits the fitting of the low-frequency signal for long-term filtering of the recharge signal, whereas the storage coefficient filters the signal with a higher frequency. For long-term insight into aquifer system functioning, the priority is thus to first fit the transmissivity field and to assess the distributed aquifer recharge accurately. The fitted DPBM, coupled with a linear model of coregionalization, is then used to quantify the hydrosystem water mass balance between 1974 and 2009, indicating that there is yet no trend of water resources decrease neither due to climate nor to human activities.
A Nonparametric Approach for Assessing Goodness-of-Fit of IRT Models in a Mixed Format Test
ERIC Educational Resources Information Center
Liang, Tie; Wells, Craig S.
2015-01-01
Investigating the fit of a parametric model plays a vital role in validating an item response theory (IRT) model. An area that has received little attention is the assessment of multiple IRT models used in a mixed-format test. The present study extends the nonparametric approach, proposed by Douglas and Cohen (2001), to assess model fit of three…
Wadehn, Federico; Carnal, David; Loeliger, Hans-Andrea
2015-08-01
Heart rate variability is one of the key parameters for assessing the health status of a subject's cardiovascular system. This paper presents a local model fitting algorithm used for finding single heart beats in photoplethysmogram recordings. The local fit of exponentially decaying cosines of frequencies within the physiological range is used to detect the presence of a heart beat. Using 42 subjects from the CapnoBase database, the average heart rate error was 0.16 BPM and the standard deviation of the absolute estimation error was 0.24 BPM. PMID:26737125
Modeling of pharmaceuticals mixtures toxicity with deviation ratio and best-fit functions models.
Wieczerzak, Monika; Kudłak, Błażej; Yotova, Galina; Nedyalkova, Miroslava; Tsakovski, Stefan; Simeonov, Vasil; Namieśnik, Jacek
2016-11-15
The present study deals with assessment of ecotoxicological parameters of 9 drugs (diclofenac (sodium salt), oxytetracycline hydrochloride, fluoxetine hydrochloride, chloramphenicol, ketoprofen, progesterone, estrone, androstenedione and gemfibrozil), present in the environmental compartments at specific concentration levels, and their mutual combinations by couples against Microtox® and XenoScreen YES/YAS® bioassays. As the quantitative assessment of ecotoxicity of drug mixtures is an complex and sophisticated topic in the present study we have used two major approaches to gain specific information on the mutual impact of two separate drugs present in a mixture. The first approach is well documented in many toxicological studies and follows the procedure for assessing three types of models, namely concentration addition (CA), independent action (IA) and simple interaction (SI) by calculation of a model deviation ratio (MDR) for each one of the experiments carried out. The second approach used was based on the assumption that the mutual impact in each mixture of two drugs could be described by a best-fit model function with calculation of weight (regression coefficient or other model parameter) for each of the participants in the mixture or by correlation analysis. It was shown that the sign and the absolute value of the weight or the correlation coefficient could be a reliable measure for the impact of either drug A on drug B or, vice versa, of B on A. Results of studies justify the statement, that both of the approaches show similar assessment of the mode of mutual interaction of the drugs studied. It was found that most of the drug mixtures exhibit independent action and quite few of the mixtures show synergic or dependent action. PMID:27479466
Modeling sympathetic cooling of molecules by ultracold atoms
NASA Astrophysics Data System (ADS)
Lim, Jongseok; Frye, Matthew D.; Hutson, Jeremy M.; Tarbutt, M. R.
2015-11-01
We model sympathetic cooling of ground-state CaF molecules by ultracold Li and Rb atoms. The molecules are moving in a microwave trap, while the atoms are trapped magnetically. We calculate the differential elastic cross sections for CaF-Li and CaF-Rb collisions, using model Lennard-Jones potentials adjusted to give typical values for the s -wave scattering length. Together with trajectory calculations, these differential cross sections are used to simulate the cooling of the molecules, the heating of the atoms, and the loss of atoms from the trap. We show that a hard-sphere collision model based on an energy-dependent momentum transport cross section accurately predicts the molecule cooling rate but underestimates the rates of atom heating and loss. Our simulations suggest that Rb is a more effective coolant than Li for ground-state molecules, and that the cooling dynamics is less sensitive to the exact value of the s -wave scattering length when Rb is used. Using realistic experimental parameters, we find that molecules can be sympathetically cooled to 100 μ K in about 10 s. By applying evaporative cooling to the atoms, the cooling rate can be increased and the final temperature of the molecules can be reduced to 1 μ K within 30 s.
Surface Adsorption in Nonpolarizable Atomic Models.
Whitmer, Jonathan K; Joshi, Abhijeet A; Carlton, Rebecca J; Abbott, Nicholas L; de Pablo, Juan J
2014-12-01
Many ionic solutions exhibit species-dependent properties, including surface tension and the salting-out of proteins. These effects may be loosely quantified in terms of the Hofmeister series, first identified in the context of protein solubility. Here, our interest is to develop atomistic models capable of capturing Hofmeister effects rigorously. Importantly, we aim to capture this dependence in computationally cheap "hard" ionic models, which do not exhibit dynamic polarization. To do this, we have performed an investigation detailing the effects of the water model on these properties. Though incredibly important, the role of water models in simulation of ionic solutions and biological systems is essentially unexplored. We quantify this via the ion-dependent surface attraction of the halide series (Cl, Br, I) and, in so doing, determine the relative importance of various hypothesized contributions to ionic surface free energies. Importantly, we demonstrate surface adsorption can result in hard ionic models combined with a thermodynamically accurate representation of the water molecule (TIP4Q). The effect observed in simulations of iodide is commensurate with previous calculations of the surface potential of mean force in rigid molecular dynamics and polarizable density-functional models. Our calculations are direct simulation evidence of the subtle but sensitive role of water thermodynamics in atomistic simulations. PMID:26583244
Grievink, Liat Shavit; Penny, David; Hendy, Michael D.; Holland, Barbara R.
2010-01-01
Commonly used phylogenetic models assume a homogeneous process through time in all parts of the tree. However, it is known that these models can be too simplistic as they do not account for nonhomogeneous lineage-specific properties. In particular, it is now widely recognized that as constraints on sequences evolve, the proportion and positions of variable sites can vary between lineages causing heterotachy. The extent to which this model misspecification affects tree reconstruction is still unknown. Here, we evaluate the effect of changes in the proportions and positions of variable sites on model fit and tree estimation. We consider 5 current models of nucleotide sequence evolution in a Bayesian Markov chain Monte Carlo framework as well as maximum parsimony (MP). We show that for a tree with 4 lineages where 2 nonsister taxa undergo a change in the proportion of variable sites tree reconstruction under the best-fitting model, which is chosen using a relative test, often results in the wrong tree. In this case, we found that an absolute test of model fit is a better predictor of tree estimation accuracy. We also found further evidence that MP is not immune to heterotachy. In addition, we show that increased sampling of taxa that have undergone a change in proportion and positions of variable sites is critical for accurate tree reconstruction. PMID:20525636
Enhanced NLTE Atomic Kinetics Modeling Capabilities in HYDRA
NASA Astrophysics Data System (ADS)
Patel, Mehul V.; Scott, Howard A.; Marinak, Michael M.
2014-10-01
In radiation hydrodynamics modeling of ICF targets, an NLTE treatment of atomic kinetics is necessary for modeling high-Z hohlraum wall materials, high-Z dopants mixed in the central gas hotspot, and is potentially needed for accurate modeling of outer layers of the capsule ablator. Over the past several years, the NLTE DCA atomic physics capabilities in the 3D ICF radiation hydrodynamics code HYDRA have been significantly enhanced. The underlying atomic models have been improved, additional kinetics options including the ability to run DCA in cells with dynamic mixing of species has been added, and the computational costs have been significantly reduced using OpenMP threading. To illustrate the improved capabilities, we will show higher fidelity results from simulations of ICF hohlraum energetics, laser irradiated sphere experiments, and ICF capsule implosions. Prepared by LLNL under Contract DE-AC52-07NA27344.
Empirical wind models from detailed UV-line FITS - Tau Scorpii
NASA Astrophysics Data System (ADS)
Hamann, W.-R.
Lamers and Rogerson (1978) have conducted a study of the main-sequence BO star Tau Sco. However, the line formation was calculated according to the Sobolev approximation method, and the line fit was, therefore, restricted to the blue wings of the UV resonance lines. The present investigation of this star is based on an employment of the comoving-frame (CMF) method, which was extended to the treatment of overlapping doublets. It has been shown by Hamann (1980) that the results of the CMF method may differ considerably from those of the Sobolev procedure. It is found in the current investigation that the observed UV resonance lines of Tau Sco are well reproduced by theoretical profiles. The CMF calculations allow for a fit of the entire profile range and a correct treatment of the doublets. An empirical model which distinguishes three zones is derived. The line fits firmly establish a large microturbulence of 100 km/s in zones I and II.
Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy
NASA Astrophysics Data System (ADS)
Nabizadeh, Nooshin; John, Nigel
2014-03-01
Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.
A Predictive Study of Dirichlet Process Mixture Models for Curve Fitting
WADE, SARA; WALKER, STEPHEN G.; PETRONE, SONIA
2013-01-01
This paper examines the use of Dirichlet process (DP) mixtures for curve fitting. An important modelling aspect in this setting is the choice between constant or covariate-dependent weights. By examining the problem of curve fitting from a predictive perspective, we show the advantages of using covariate-dependent weights. These advantages are a result of the incorporation of covariate proximity in the latent partition. However, closer examination of the partition yields further complications, which arise from the vast number of total partitions. To overcome this, we propose to modify the probability law of the random partition to strictly enforce the notion of covariate proximity, while still maintaining certain properties of the DP. This allows the distribution of the partition to depend on the covariate in a simple manner and greatly reduces the total number of possible partitions, resulting in improved curve fitting and faster computations. Numerical illustrations are presented. PMID:25395718
A two-component model for fitting light curves of core-collapse supernovae
NASA Astrophysics Data System (ADS)
Nagy, A. P.; Vinkó, J.
2016-05-01
We present an improved version of a light curve model that is able to estimate the physical properties of different types of core-collapse supernovae that have double-peaked light curves and do so in a quick and efficient way. The model is based on a two-component configuration consisting of a dense inner region and an extended low-mass envelope. Using this configuration, we estimate the initial parameters of the progenitor by fitting the shape of the quasi-bolometric light curves of 10 SNe, including Type IIP and IIb events, with model light curves. In each case we compare the fitting results with available hydrodynamic calculations and also match the derived expansion velocities with the observed ones. Furthermore, we compare our calculations with hydrodynamic models derived by the SNEC code and examine the uncertainties of the estimated physical parameters caused by the assumption of constant opacity and the inaccurate knowledge of the moment of explosion.
Fitting the distribution of dry and wet spells with alternative probability models
NASA Astrophysics Data System (ADS)
Deni, Sayang Mohd; Jemain, Abdul Aziz
2009-06-01
The development of the rainfall occurrence model is greatly important not only for data-generation purposes, but also in providing informative resources for future advancements in water-related sectors, such as water resource management and the hydrological and agricultural sectors. Various kinds of probability models had been introduced to a sequence of dry (wet) days by previous researchers in the field. Based on the probability models developed previously, the present study is aimed to propose three types of mixture distributions, namely, the mixture of two log series distributions (LSD), the mixture of the log series Poisson distribution (MLPD), and the mixture of the log series and geometric distributions (MLGD), as the alternative probability models to describe the distribution of dry (wet) spells in daily rainfall events. In order to test the performance of the proposed new models with the other nine existing probability models, 54 data sets which had been published by several authors were reanalyzed in this study. Also, the new data sets of daily observations from the six selected rainfall stations in Peninsular Malaysia for the period 1975-2004 were used. In determining the best fitting distribution to describe the observed distribution of dry (wet) spells, a Chi-square goodness-of-fit test was considered. The results revealed that the new method proposed that MLGD and MLPD showed a better fit as more than half of the data sets successfully fitted the distribution of dry and wet spells. However, the existing models, such as the truncated negative binomial and the modified LSD, were also among the successful probability models to represent the sequence of dry (wet) days in daily rainfall occurrence.
Modelling spectral properties of non-equilibrium atomic hydrogen plasma
NASA Astrophysics Data System (ADS)
D'Ammando, G.; Pietanza, L. D.; Colonna, G.; Longo, S.; Capitelli, M.
2010-02-01
A model to predict the emissivity and absorption coefficient of atomic hydrogen plasma is presented in detail. Non-equilibrium plasma is studied through coupling of the model with a collisional-radiative code for the excited states population as well as with the Boltzmann equation for the electron energy distribution function.
Fitting complex population models by combining particle filters with Markov chain Monte Carlo.
Knape, Jonas; de Valpine, Perry
2012-02-01
We show how a recent framework combining Markov chain Monte Carlo (MCMC) with particle filters (PFMCMC) may be used to estimate population state-space models. With the purpose of utilizing the strengths of each method, PFMCMC explores hidden states by particle filters, while process and observation parameters are estimated using an MCMC algorithm. PFMCMC is exemplified by analyzing time series data on a red kangaroo (Macropus rufus) population in New South Wales, Australia, using MCMC over model parameters based on an adaptive Metropolis-Hastings algorithm. We fit three population models to these data; a density-dependent logistic diffusion model with environmental variance, an unregulated stochastic exponential growth model, and a random-walk model. Bayes factors and posterior model probabilities show that there is little support for density dependence and that the random-walk model is the most parsimonious model. The particle filter Metropolis-Hastings algorithm is a brute-force method that may be used to fit a range of complex population models. Implementation is straightforward and less involved than standard MCMC for many models, and marginal densities for model selection can be obtained with little additional effort. The cost is mainly computational, resulting in long running times that may be improved by parallelizing the algorithm. PMID:22624307
When should a model be rejected as not fit-for-purpose?
NASA Astrophysics Data System (ADS)
Beven, Keith; Lane, Stuart
2015-04-01
There are many models used in the geosciences that are actually not very good at predicting available observations, even after calibration or inversion that allows for some stochastic error model. This may be for very good reasons: because there is some difficulty in implementing perceptual understanding into quantitative model representations, because the initial and boundary conditions are subject to both aleatory and epistemic uncertainties (particularly in respect of the future); because there are computational constraints on model resolution or identification strategies; or because there are commensurability issues in relating measured and model parameter values. But models are very rarely rejected, even when it is clear that they are not really fit-for-purpose. Increasingly, any model limitations are compensated by some form of uncertainty estimation (perhaps including bias and other corrections). But if a model is not fit-for-purpose it might be dangerous to base decisions on the basis of its prediction, even with some form of uncertainty assessment. This presentation will consider how a framework for model rejection might work, taking account of the various sources of uncertainty in the model process. It turns out that this puts emphasis back on the quality of the data sets for model testing in not rejecting potentially useful models just because the input data are poor.
Fitting parametric models of diffusion MRI in regions of partial volume
NASA Astrophysics Data System (ADS)
Eaton-Rosen, Zach; Cardoso, M. J.; Melbourne, Andrew; Orasanu, Eliza; Bainbridge, Alan; Kendall, Giles S.; Robertson, Nicola J.; Marlow, Neil; Ourselin, Sebastien
2016-03-01
Regional analysis is normally done by fitting models per voxel and then averaging over a region, accounting for partial volume (PV) only to some degree. In thin, folded regions such as the cerebral cortex, such methods do not work well, as the partial volume confounds parameter estimation. Instead, we propose to fit the models per region directly with explicit PV modeling. In this work we robustly estimate region-wise parameters whilst explicitly accounting for partial volume effects. We use a high-resolution segmentation from a T1 scan to assign each voxel in the diffusion image a probabilistic membership to each of k tissue classes. We rotate the DW signal at each voxel so that it aligns with the z-axis, then model the signal at each voxel as a linear superposition of a representative signal from each of the k tissue types. Fitting involves optimising these representative signals to best match the data, given the known probabilities of belonging to each tissue type that we obtained from the segmentation. We demonstrate this method improves parameter estimation in digital phantoms for the diffusion tensor (DT) and `Neurite Orientation Dispersion and Density Imaging' (NODDI) models. The method provides accurate parameter estimates even in regions where the normal approach fails completely, for example where partial volume is present in every voxel. Finally, we apply this model to brain data from preterm infants, where the thin, convoluted, maturing cortex necessitates such an approach.
Fitting a three-component scattering model to polarimetric SAR data
NASA Technical Reports Server (NTRS)
Freeman, A.; Durden, S.
1992-01-01
A new technique for fitting a three-component scattering mechanism model to the polarimetric synthetic aperture radar (SAR) data itself, without utilizing any ground truth measurements, is presented. The three scattering mechanism components included in the model are volume scatter from randomly oriented dipoles, first-order Bragg surface scatter and a dihedral scattering mechanism for two surfaces with different dielectric constants. The model fit yields an estimate of the contribution to the total backscatter of each of the three components. The backscatter contributions can also be compared to give the relative percentage weight of each. The model fit has an equal number of input parameters (the polarimetric radar backscatter measurements) and output parameters (the backscatter parameters describing them). The model can be applied to entire images or to small areas within an image to give a first-order estimate of the relevant scattering mechanisms. The model was applied to many C-, L- and P-band Airborne SAR (AIRSAR) images of different types of terrain. Results were presented at the workshop.
Omarjee, Saleha; Walker, Bruce D.; Chakraborty, Arup; Ndung'u, Thumbi
2014-01-01
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
ERIC Educational Resources Information Center
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 (1PL) estimated by (marginal) maximum…
DiMaio, Frank; Song, Yifan; Li, Xueming; Brunner, Matthias J; Xu, Chunfu; Conticello, Vincent; Egelman, Edward; Marlovits, Thomas C; Cheng, Yifan; Baker, David
2015-04-01
We describe a general approach for refining protein structure models on the basis of cryo-electron microscopy maps with near-atomic resolution. The method integrates Monte Carlo sampling with local density-guided optimization, Rosetta all-atom refinement and real-space B-factor fitting. In tests on experimental maps of three different systems with 4.5-Å resolution or better, the method consistently produced models with atomic-level accuracy largely independently of starting-model quality, and it outperformed the molecular dynamics-based MDFF method. Cross-validated model quality statistics correlated with model accuracy over the three test systems. PMID:25707030
A flexible, interactive software tool for fitting the parameters of neuronal models.
Friedrich, Péter; Vella, Michael; Gulyás, Attila I; Freund, Tamás F; Káli, Szabolcs
2014-01-01
The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool. PMID
A flexible, interactive software tool for fitting the parameters of neuronal models
Friedrich, Péter; Vella, Michael; Gulyás, Attila I.; Freund, Tamás F.; Káli, Szabolcs
2014-01-01
The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool. PMID
Atomic-scale modeling of cellulose nanocrystals
NASA Astrophysics Data System (ADS)
Wu, Xiawa
Cellulose nanocrystals (CNCs), the most abundant nanomaterials in nature, are recognized as one of the most promising candidates to meet the growing demand of green, bio-degradable and sustainable nanomaterials for future applications. CNCs draw significant interest due to their high axial elasticity and low density-elasticity ratio, both of which are extensively researched over the years. In spite of the great potential of CNCs as functional nanoparticles for nanocomposite materials, a fundamental understanding of CNC properties and their role in composite property enhancement is not available. In this work, CNCs are studied using molecular dynamics simulation method to predict their material' behaviors in the nanoscale. (a) Mechanical properties include tensile deformation in the elastic and plastic regions using molecular mechanics, molecular dynamics and nanoindentation methods. This allows comparisons between the methods and closer connectivity to experimental measurement techniques. The elastic moduli in the axial and transverse directions are obtained and the results are found to be in good agreement with previous research. The ultimate properties in plastic deformation are reported for the first time and failure mechanism are analyzed in details. (b) The thermal expansion of CNC crystals and films are studied. It is proposed that CNC film thermal expansion is due primarily to single crystal expansion and CNC-CNC interfacial motion. The relative contributions of inter- and intra-crystal responses to heating are explored. (c) Friction at cellulose-CNCs and diamond-CNCs interfaces is studied. The effects of sliding velocity, normal load, and relative angle between sliding surfaces are predicted. The Cellulose-CNC model is analyzed in terms of hydrogen bonding effect, and the diamond-CNC model compliments some of the discussion of the previous model. In summary, CNC's material properties and molecular models are both studied in this research, contributing to
Physically representative atomistic modeling of atomic-scale friction
NASA Astrophysics Data System (ADS)
Dong, Yalin
Nanotribology is a research field to study friction, adhesion, wear and lubrication occurred between two sliding interfaces at nano scale. This study is motivated by the demanding need of miniaturization mechanical components in Micro Electro Mechanical Systems (MEMS), improvement of durability in magnetic storage system, and other industrial applications. Overcoming tribological failure and finding ways to control friction at small scale have become keys to commercialize MEMS with sliding components as well as to stimulate the technological innovation associated with the development of MEMS. In addition to the industrial applications, such research is also scientifically fascinating because it opens a door to understand macroscopic friction from the most bottom atomic level, and therefore serves as a bridge between science and engineering. This thesis focuses on solid/solid atomic friction and its associated energy dissipation through theoretical analysis, atomistic simulation, transition state theory, and close collaboration with experimentalists. Reduced-order models have many advantages for its simplification and capacity to simulating long-time event. We will apply Prandtl-Tomlinson models and their extensions to interpret dry atomic-scale friction. We begin with the fundamental equations and build on them step-by-step from the simple quasistatic one-spring, one-mass model for predicting transitions between friction regimes to the two-dimensional and multi-atom models for describing the effect of contact area. Theoretical analysis, numerical implementation, and predicted physical phenomena are all discussed. In the process, we demonstrate the significant potential for this approach to yield new fundamental understanding of atomic-scale friction. Atomistic modeling can never be overemphasized in the investigation of atomic friction, in which each single atom could play a significant role, but is hard to be captured experimentally. In atomic friction, the
The Beta Problem: The Incompatibility of X-ray and Sunyaev-Zeldovich Model Fitting
NASA Astrophysics Data System (ADS)
Burns, Jack O.; Hallman, E.; Motl, P.; Norman, M.
2006-12-01
We describe an analysis of a large sample of numerically simulated clusters which demonstrates the effects of using X-ray fitted beta-model parameters with Sunyaev-Zeldovich effect (SZE) data. There is a fundamental incompatibility between beta-model fits to X-ray surface brightness profiles and those done with SZE profiles. Since observational SZE radial profiles are in short supply, the X-ray parameters are often used in SZE analysis. We show that this leads to biased estimates of the integrated Compton y-parameter inside r500 and the value of the Hubble constant calculated from clusters. We suggest a simple scaling of the X-ray beta-model parameters which brings these calculated quantities into close agreement with the true values.
The Blazar 3C 66A in 2003-2004: hadronic versus leptonic model fits
Reimer, A.
2008-12-24
The low-frequency peaked BL Lac object 3C 66A was the subject of an extensive multi-wavelength campaign from July 2003 till April 2004, which included quasi-simultaneous observations at optical, X-rays and very high energy gamma-rays. Here we apply the hadronic Synchrotron-Proton Blazar (SPB) model to the observed spectral energy distribution time-averaged over a flaring state, and compare the resulting model fits to those obtained from the application of the leptonic Synchrotron-Self-Compton (SSC) model. The results are used to identify diagnostic key predictions of the two blazar models for future multi-wavelength observations.
Array-based evolution of DNA aptamers allows modelling of an explicit sequence-fitness landscape
Knight, Christopher G.; Platt, Mark; Rowe, William; Wedge, David C.; Khan, Farid; Day, Philip J. R.; McShea, Andy; Knowles, Joshua; Kell, Douglas B.
2009-01-01
Mapping the landscape of possible macromolecular polymer sequences to their fitness in performing biological functions is a challenge across the biosciences. A paradigm is the case of aptamers, nucleic acids that can be selected to bind particular target molecules. We have characterized the sequence-fitness landscape for aptamers binding allophycocyanin (APC) protein via a novel Closed Loop Aptameric Directed Evolution (CLADE) approach. In contrast to the conventional SELEX methodology, selection and mutation of aptamer sequences was carried out in silico, with explicit fitness assays for 44 131 aptamers of known sequence using DNA microarrays in vitro. We capture the landscape using a predictive machine learning model linking sequence features and function and validate this model using 5500 entirely separate test sequences, which give a very high observed versus predicted correlation of 0.87. This approach reveals a complex sequence-fitness mapping, and hypotheses for the physical basis of aptameric binding; it also enables rapid design of novel aptamers with desired binding properties. We demonstrate an extension to the approach by incorporating prior knowledge into CLADE, resulting in some of the tightest binding sequences. PMID:19029139
A goodness-of-fit test for occupancy models with correlated within-season revisits.
Wright, Wilson J; Irvine, Kathryn M; Rodhouse, Thomas J
2016-08-01
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 goodness-of-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
ERIC Educational Resources Information Center
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…
The chaotic atom model via a fractal approximation of motion
NASA Astrophysics Data System (ADS)
Agop, M.; Nica, P.; Gurlui, S.; Focsa, C.; Magop, D.; Borsos, Z.
2011-10-01
A new model of the atom is built based on a complete and detailed nonlinear dynamics analysis (complete time series, Poincaré sections, complete phase space, Lyapunov exponents, bifurcation diagrams and fractal analysis), through the correlation of the chaotic-stochastic model with a fractal one. Some specific mechanisms that ensure the atom functionality are proposed: gun, chaotic gun and multi-gun effects for the excited states (the classical analogue of quantum absorption) and the fractalization of the trajectories for the stationary states (a natural way of introducing the quantification).
Testing the validity of the International Atomic Energy Agency (IAEA) safety culture model.
López de Castro, Borja; Gracia, Francisco J; Peiró, José M; Pietrantoni, Luca; Hernández, Ana
2013-11-01
This paper takes the first steps to empirically validate the widely used model of safety culture of the International Atomic Energy Agency (IAEA), composed of five dimensions, further specified by 37 attributes. To do so, three independent and complementary studies are presented. First, 290 students serve to collect evidence about the face validity of the model. Second, 48 experts in organizational behavior judge its content validity. And third, 468 workers in a Spanish nuclear power plant help to reveal how closely the theoretical five-dimensional model can be replicated. Our findings suggest that several attributes of the model may not be related to their corresponding dimensions. According to our results, a one-dimensional structure fits the data better than the five dimensions proposed by the IAEA. Moreover, the IAEA model, as it stands, seems to have rather moderate content validity and low face validity. Practical implications for researchers and practitioners are included. PMID:24076304
Seeking for Spin-Opposite-Scaled Double-Hybrid Models Free of Fitted Parameters.
Alipour, Mojtaba
2016-05-26
On the basis of theoretical arguments, a new exchange-correlation energy expression free of any fitted parameter has been proposed for spin-opposite-scaled double-hybrid density functionals (SOS0-DHs). Employing the recently presented DHs, the working expressions for SOS0-DH functionals are obtained and benchmarked numerically against several standard databases. Our test calculations show that for some cases such as interaction energies and barrier heights the SOS0-DHs without dispersion corrections perform better than their non-SOS counterparts. On the other hand, for other properties like atomization energies, the conventional DHs provide reliable results. We hope that the findings of this work can excite further developments of DH functionals in the framework of SOS scheme for a wide variety of applications resolving the failures at a reasonable computational cost. It seems that a bright future lies ahead in this arena. PMID:27163506
NASA Astrophysics Data System (ADS)
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.
Model based control of dynamic atomic force microscope
Lee, Chibum; Salapaka, Srinivasa M.
2015-04-15
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H{sub ∞} control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.
Model based control of dynamic atomic force microscope.
Lee, Chibum; Salapaka, Srinivasa M
2015-04-01
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H(∞) control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments. PMID:25933864
NASA Astrophysics Data System (ADS)
Ritter, Axel; Muñoz-Carpena, Rafael
2013-02-01
SummarySuccess in the use of computer models for simulating environmental variables and processes requires objective model calibration and verification procedures. Several methods for quantifying the goodness-of-fit of observations against model-calculated values have been proposed but none of them is free of limitations and are often ambiguous. When a single indicator is used it may lead to incorrect verification of the model. Instead, a combination of graphical results, absolute value error statistics (i.e. root mean square error), and normalized goodness-of-fit statistics (i.e. Nash-Sutcliffe Efficiency coefficient, NSE) is currently recommended. Interpretation of NSE values is often subjective, and may be biased by the magnitude and number of data points, data outliers and repeated data. The statistical significance of the performance statistics is an aspect generally ignored that helps in reducing subjectivity in the proper interpretation of the model performance. In this work, approximated probability distributions for two common indicators (NSE and root mean square error) are derived with bootstrapping (block bootstrapping when dealing with time series), followed by bias corrected and accelerated calculation of confidence intervals. Hypothesis testing of the indicators exceeding threshold values is proposed in a unified framework for statistically accepting or rejecting the model performance. It is illustrated how model performance is not linearly related with NSE, which is critical for its proper interpretation. Additionally, the sensitivity of the indicators to model bias, outliers and repeated data is evaluated. The potential of the difference between root mean square error and mean absolute error for detecting outliers is explored, showing that this may be considered a necessary but not a sufficient condition of outlier presence. The usefulness of the approach for the evaluation of model performance is illustrated with case studies including those with
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. PMID:26613830
Efficient Constrained Local Model Fitting for Non-Rigid Face Alignment
Wang, Yang; Cox, Mark; Sridharan, Sridha; Cohn, Jeffery F.
2009-01-01
Active appearance models (AAMs) have demonstrated great utility when being employed for non-rigid face alignment/tracking. The “simultaneous” algorithm for fitting an AAM achieves good non-rigid face registration performance, but has poor real time performance (2-3 fps). The “project-out” algorithm for fitting an AAM achieves faster than real time performance (> 200 fps) but suffers from poor generic alignment performance. In this paper we introduce an extension to a discriminative method for non-rigid face registration/tracking referred to as a constrained local model (CLM). Our proposed method is able to achieve superior performance to the “simultaneous” AAM algorithm along with real time fitting speeds (35 fps). We improve upon the canonical CLM formulation, to gain this performance, in a number of ways by employing: (i) linear SVMs as patch-experts, (ii) a simplified optimization criteria, and (iii) a composite rather than additive warp update step. Most notably, our simplified optimization criteria for fitting the CLM divides the problem of finding a single complex registration/warp displacement into that of finding N simple warp displacements. From these N simple warp displacements, a single complex warp displacement is estimated using a weighted least-squares constraint. Another major advantage of this simplified optimization lends from its ability to be parallelized, a step which we also theoretically explore in this paper. We refer to our approach for fitting the CLM as the “exhaustive local search” (ELS) algorithm. Experiments were conducted on the CMU Multi-PIE database. PMID:20046797
NASA Astrophysics Data System (ADS)
Mandal, S.; Choudhury, B. U.
2015-07-01
Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.
Agricultural case studies of classification accuracy, spectral resolution, and model over-fitting.
Nansen, Christian; Geremias, Leandro Delalibera; Xue, Yingen; Huang, Fangneng; Parra, Jose Roberto
2013-11-01
This paper describes the relationship between spectral resolution and classification accuracy in analyses of hyperspectral imaging data acquired from crop leaves. The main scope is to discuss and reduce the risk of model over-fitting. Over-fitting of a classification model occurs when too many and/or irrelevant model terms are included (i.e., a large number of spectral bands), and it may lead to low robustness/repeatability when the classification model is applied to independent validation data. We outline a simple way to quantify the level of model over-fitting by comparing the observed classification accuracies with those obtained from explanatory random data. Hyperspectral imaging data were acquired from two crop-insect pest systems: (1) potato psyllid (Bactericera cockerelli) infestations of individual bell pepper plants (Capsicum annuum) with the acquisition of hyperspectral imaging data under controlled-light conditions (data set 1), and (2) sugarcane borer (Diatraea saccharalis) infestations of individual maize plants (Zea mays) with the acquisition of hyperspectral imaging data from the same plants under two markedly different image-acquisition conditions (data sets 2a and b). For each data set, reflectance data were analyzed based on seven spectral resolutions by dividing 160 spectral bands from 405 to 907 nm into 4, 16, 32, 40, 53, 80, or 160 bands. In the two data sets, similar classification results were obtained with spectral resolutions ranging from 3.1 to 12.6 nm. Thus, the size of the initial input data could be reduced fourfold with only a negligible loss of classification accuracy. In the analysis of data set 1, several validation approaches all demonstrated consistently that insect-induced stress could be accurately detected and that therefore there was little indication of model over-fitting. In the analyses of data set 2, inconsistent validation results were obtained and the observed classification accuracy (81.06%) was only a few percentage
Bias in fitting the ETAS model: a case study based on New Zealand seismicity
NASA Astrophysics Data System (ADS)
Harte, D. S.
2013-01-01
We fit various forms of the ETAS model to a large region that includes all of the most seismically active areas of New Zealand. The ETAS model contains two components: a component describing background or immigrant events, and a part describing aftershocks of the background events and aftershocks of the aftershocks. We refer to the first part as the background part and the second as the ETAS part. Generally all of the sophistication, and the bulk of the model parameters, lies in the ETAS part of the model. The background component is generally treated as a nuisance component and is often very simplistic. While the main interest lies in the ETAS part of the model, the poor model description of the background part imposes considerable bias on the ETAS part of the model. For example, a poorly specified spatial density of the background events causes many of the background events to be seen as ETAS events. It can also cause the estimated Omori power-law decay p to be too small, and hence the aftershock sequences appear to continue for too long. On the other hand, the boundary of the observation region can impose a reverse bias which causes aftershocks that are close but within the boundary to be seen as background events. In almost all of the large NZ event sequences since 1965, the model consistently under-fits these sequences. Consequently, it over-fits those space-time regions where there is `normal' seismicity with no major events present. This may indicate that the space-time region of a major event sequence is much closer to criticality, in that aftershock events appear to be much more easily initiated. The standard ETAS model does not reflect this observation.
Aeroelastic modeling for the FIT (Functional Integration Technology) team F/A-18 simulation
NASA Technical Reports Server (NTRS)
Zeiler, Thomas A.; Wieseman, Carol D.
1989-01-01
As part of Langley Research Center's commitment to developing multidisciplinary integration methods to improve aerospace systems, the Functional Integration Technology (FIT) team was established to perform dynamics integration research using an existing aircraft configuration, the F/A-18. An essential part of this effort has been the development of a comprehensive simulation modeling capability that includes structural, control, and propulsion dynamics as well as steady and unsteady aerodynamics. The structural and unsteady aerodynamics contributions come from an aeroelastic mode. Some details of the aeroelastic modeling done for the Functional Integration Technology (FIT) team research are presented. Particular attention is given to work done in the area of correction factors to unsteady aerodynamics data.
Advanced material modelling in numerical simulation of primary acetabular press-fit cup stability.
Souffrant, R; Zietz, C; Fritsche, A; Kluess, D; Mittelmeier, W; Bader, R
2012-01-01
Primary stability of artificial acetabular cups, used for total hip arthroplasty, is required for the subsequent osteointegration and good long-term clinical results of the implant. Although closed-cell polymer foams represent an adequate bone substitute in experimental studies investigating primary stability, correct numerical modelling of this material depends on the parameter selection. Material parameters necessary for crushable foam plasticity behaviour were originated from numerical simulations matched with experimental tests of the polymethacrylimide raw material. Experimental primary stability tests of acetabular press-fit cups consisting of static shell assembly with consecutively pull-out and lever-out testing were subsequently simulated using finite element analysis. Identified and optimised parameters allowed the accurate numerical reproduction of the raw material tests. Correlation between experimental tests and the numerical simulation of primary implant stability depended on the value of interference fit. However, the validated material model provides the opportunity for subsequent parametric numerical studies. PMID:22817471
Parameter fitting in three-flavor Nambu-Jona-Lasinio model with various regularizations
NASA Astrophysics Data System (ADS)
Kohyama, H.; Kimura, D.; Inagaki, T.
2016-05-01
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.
NASA Technical Reports Server (NTRS)
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.
Atmospheric turbulence optical model (ATOM) based on fractal theory
NASA Astrophysics Data System (ADS)
Jaenisch, Holger M.; Handley, James W.; Scoggins, Jim; Carroll, Marvin P.
1994-06-01
An Atmospheric Turbulence Optical Model (ATOM) is presented that used cellular automata (CA) rules as the basis for modeling synthetic phase sheets. This method allows image fracture, scintillation and blur to be correctly models using the principle of convolution with a complex kernel derived from CA rules interaction. The model takes into account the changing distribution of turbules from micro-turbule domination at low altitudes to macro-domination at high altitudes. The wavelength of propagating images (such as a coherent laser beam) and the range are taken into account. The ATOM model is written in standard FORTRAN 77 and enables high-speed in-line calculation of atmospheric effects to be performed without resorting to computationally intensive solutions of Navier Stokes equations or Cn2 profiles.
Fitting a Two-Component Scattering Model to Polarimetric SAR Data
NASA Technical Reports Server (NTRS)
Freeman, A.
1998-01-01
Classification, decomposition and modeling of polarimetric SAR data has received a great deal of attention in the recent literature. The objective behind these efforts is to better understand the scattering mechanisms which give rise to the polarimetric signatures seen in SAR image data. In this Paper an approach is described, which involves the fit of a combination of two simple scattering mechanisms to polarimetric SAR observations. The mechanisms am canopy scatter from a cloud of randomly oriented oblate spheroids, and a ground scatter term, which can represent double-bounce scatter from a pair of orthogonal surfaces with different dielectric constants or Bragg scatter from a moderately rough surface, seen through a layer of vertically oriented scatterers. An advantage of this model fit approach is that the scattering contributions from the two basic scattering mechanisms can be estimated for clusters of pixels in polarimetric SAR images. The solution involves the estimation of four parameters from four separate equations. The model fit can be applied to polarimetric AIRSAR data at C-, L- and P-Band.
NASA Astrophysics Data System (ADS)
Cheng, Yuan-Chieh; Chen, Jia-Hong; Chang, Rong-Jie; Wang, Chung-Yen; Hsu, Wei-Yao; Wang, Pei-Jen
2015-09-01
Contact lenses are typically measured by the wet-box method because of the high optical power resulting from the anterior central curvature of cornea, even though the back vertex power of the lenses are small. In this study, an optical measurement system based on the Shack-Hartmann wavefront principle was established to investigate the aberrations of soft contact lenses. Fitting conditions were micmicked to study the optical design of an eye model with various topographical shapes in the anterior cornea. Initially, the contact lenses were measured by the wet-box method, and then by fitting the various topographical shapes of cornea to the eye model. In addition, an optics simulation program was employed to determine the sources of errors and assess the accuracy of the system. Finally, samples of soft contact lenses with various Diopters were measured; and, both simulations and experimental results were compared for resolving the controversies of fitting contact lenses to an eye model for optical measurements. More importantly, the results show that the proposed system can be employed for study of primary aberrations in contact lenses.
Efficient parallel implementation of active appearance model fitting algorithm on GPU.
Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou
2014-01-01
The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures. PMID:24723812
Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU
Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou
2014-01-01
The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures. PMID:24723812
Modeling and optimizing of the random atomic spin gyroscope drift based on the atomic spin gyroscope
Quan, Wei; Lv, Lin Liu, Baiqi
2014-11-15
In order to improve the atom spin gyroscope's operational accuracy and compensate the random error caused by the nonlinear and weak-stability characteristic of the random atomic spin gyroscope (ASG) drift, the hybrid random drift error model based on autoregressive (AR) and genetic programming (GP) + genetic algorithm (GA) technique is established. The time series of random ASG drift is taken as the study object. The time series of random ASG drift is acquired by analyzing and preprocessing the measured data of ASG. The linear section model is established based on AR technique. After that, the nonlinear section model is built based on GP technique and GA is used to optimize the coefficients of the mathematic expression acquired by GP in order to obtain a more accurate model. The simulation result indicates that this hybrid model can effectively reflect the characteristics of the ASG's random drift. The square error of the ASG's random drift is reduced by 92.40%. Comparing with the AR technique and the GP + GA technique, the random drift is reduced by 9.34% and 5.06%, respectively. The hybrid modeling method can effectively compensate the ASG's random drift and improve the stability of the system.
ATOMIC DATA AND SPECTRAL MODEL FOR Fe III
Bautista, Manuel A.; Ballance, Connor P.; Quinet, Pascal
2010-08-01
We present new atomic data (radiative transitions rates and collision strengths) from large-scale calculations and a non-LTE spectral model for Fe III. This model is in very good agreement with observed astronomical emission spectra, in contrast with previous models that yield large discrepancies in observations. The present atomic computations employ a combination of atomic physics methods, e.g., relativistic Hartree-Fock, the Thomas-Fermi-Dirac potential, and Dirac-Fock computation of A-values and the R-matrix with intermediate coupling frame transformation and the Dirac R-matrix. We study advantages and shortcomings of each method. It is found that the Dirac R-matrix collision strengths yield excellent agreement with observations, much improved over previously available models. By contrast, the transformation of the LS-coupling R-matrix fails to yield accurate effective collision strengths at around 10{sup 4} K, despite using very large configuration expansions, due to the limited treatment of spin-orbit effects in the near-threshold resonances of the collision strengths. The present work demonstrates that accurate atomic data for low-ionization iron-peak species are now within reach.
A Nonlinear Model for Fuel Atomization in Spray Combustion
NASA Technical Reports Server (NTRS)
Liu, Nan-Suey (Technical Monitor); Ibrahim, Essam A.; Sree, Dave
2003-01-01
Most gas turbine combustion codes rely on ad-hoc statistical assumptions regarding the outcome of fuel atomization processes. The modeling effort proposed in this project is aimed at developing a realistic model to produce accurate predictions of fuel atomization parameters. The model involves application of the nonlinear stability theory to analyze the instability and subsequent disintegration of the liquid fuel sheet that is produced by fuel injection nozzles in gas turbine combustors. The fuel sheet is atomized into a multiplicity of small drops of large surface area to volume ratio to enhance the evaporation rate and combustion performance. The proposed model will effect predictions of fuel sheet atomization parameters such as drop size, velocity, and orientation as well as sheet penetration depth, breakup time and thickness. These parameters are essential for combustion simulation codes to perform a controlled and optimized design of gas turbine fuel injectors. Optimizing fuel injection processes is crucial to improving combustion efficiency and hence reducing fuel consumption and pollutants emissions.
NASA Astrophysics Data System (ADS)
Frenken, Koen
2001-06-01
The biological evolution of complex organisms, in which the functioning of genes is interdependent, has been analyzed as "hill-climbing" on NK fitness landscapes through random mutation and natural selection. In evolutionary economics, NK fitness landscapes have been used to simulate the evolution of complex technological systems containing elements that are interdependent in their functioning. In these models, economic agents randomly search for new technological design by trial-and-error and run the risk of ending up in sub-optimal solutions due to interdependencies between the elements in a complex system. These models of random search are legitimate for reasons of modeling simplicity, but remain limited as these models ignore the fact that agents can apply heuristics. A specific heuristic is one that sequentially optimises functions according to their ranking by users of the system. To model this heuristic, a generalized NK-model is developed. In this model, core elements that influence many functions can be distinguished from peripheral elements that affect few functions. The concept of paradigmatic search can then be analytically defined as search that leaves core elements in tact while concentrating on improving functions by mutation of peripheral elements.
Li, Xueming; Brunner, Matthias J.; Xu, Chunfu; Conticello, Vincent; Egelman, Edward; Marlovits, Thomas; Cheng, Yifan; Baker, David
2015-01-01
Direct electron detectors have made it possible to generate electron density maps at near atomic resolution using cryo-electron microscopy single particle reconstructions. Critical current questions include how best to build models into these maps, how high quality a map is required to generate an accurate model, and how to cross-validate models in a system independent way. We describe a modeling approach that integrates Monte Carlo optimization with local density guided moves, Rosetta all-atom refinement, and real space B-factor fitting, yielding accurate models from experimental maps for three different systems with resolutions 4.5 Å or higher. We characterize model accuracy as a function of data quality, and present a model validation statistic that correlates with model accuracy over the three test systems. PMID:25707030
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. PMID:26194861
Modeling atomic hydrogen diffusion in GaAs
NASA Astrophysics Data System (ADS)
Kagadei, Valerii A.; Nefyodtsev, E.
2004-05-01
The hydrogen diffusion model in GaAs in conditions of an intense flow of penetrating atoms has been developed. It is shown that the formation undersurface diffusion barrier layer from immobile interstitial molecules of hydrogen reduce probability of atoms penetration into crystal and rate of their diffusion in GaAs, and influence on the process of shallow- and/or deep-centers passivation. It is exhibited that the influence of diffusion barrier should be taken into account at optimum mode selection of GaAs structure hydrogenation.
Transferable Atomic Multipole Machine Learning Models for Small Organic Molecules.
Bereau, Tristan; Andrienko, Denis; von Lilienfeld, O Anatole
2015-07-14
Accurate representation of the molecular electrostatic potential, which is often expanded in distributed multipole moments, is crucial for an efficient evaluation of intermolecular interactions. Here we introduce a machine learning model for multipole coefficients of atom types H, C, O, N, S, F, and Cl in any molecular conformation. The model is trained on quantum-chemical results for atoms in varying chemical environments drawn from thousands of organic molecules. Multipoles in systems with neutral, cationic, and anionic molecular charge states are treated with individual models. The models' predictive accuracy and applicability are illustrated by evaluating intermolecular interaction energies of nearly 1,000 dimers and the cohesive energy of the benzene crystal. PMID:26575759
A collisional-radiative average atom model for hot plasmas
Rozsnyai, B.F.
1996-10-17
A collisional-radiative `average atom` (AA) model is presented for the calculation of opacities of hot plasmas not in the condition of local thermodynamic equilibrium (LTE). The electron impact and radiative rate constants are calculated using the dipole oscillator strengths of the average atom. A key element of the model is the photon escape probability which at present is calculated for a semi infinite slab. The Fermi statistics renders the rate equation for the AA level occupancies nonlinear, which requires iterations until the steady state. AA level occupancies are found. Detailed electronic configurations are built into the model after the self-consistent non-LTE AA state is found. The model shows a continuous transition from the non-LTE to the LTE state depending on the optical thickness of the plasma. 22 refs., 13 figs., 1 tab.
Fitting a Two-Component Scattering Model to Polarimetric SAR Data from Forests
NASA Technical Reports Server (NTRS)
Freeman, Anthony
2007-01-01
Two simple scattering mechanisms are fitted to polarimetric synthetic aperture radar (SAR) observations of forests. The mechanisms are canopy scatter from a reciprocal medium with azimuthal symmetry and a ground scatter term that can represent double-bounce scatter from a pair of orthogonal surfaces with different dielectric constants or Bragg scatter from a moderately rough surface, which is seen through a layer of vertically oriented scatterers. The model is shown to represent the behavior of polarimetric backscatter from a tropical forest and two temperate forest sites by applying it to data from the National Aeronautic and Space Agency/Jet Propulsion Laboratory's Airborne SAR (AIRSAR) system. Scattering contributions from the two basic scattering mechanisms are estimated for clusters of pixels in polarimetric SAR images. The solution involves the estimation of four parameters from four separate equations. This model fit approach is justified as a simplification of more complicated scattering models, which require many inputs to solve the forward scattering problem. The model is used to develop an understanding of the ground-trunk double-bounce scattering that is present in the data, which is seen to vary considerably as a function of incidence angle. Two parameters in the model fit appear to exhibit sensitivity to vegetation canopy structure, which is worth further exploration. Results from the model fit for the ground scattering term are compared with estimates from a forward model and shown to be in good agreement. The behavior of the scattering from the ground-trunk interaction is consistent with the presence of a pseudo-Brewster angle effect for the air-trunk scattering interface. If the Brewster angle is known, it is possible to directly estimate the real part of the dielectric constant of the trunks, a key variable in forward modeling of backscatter from forests. It is also shown how, with a priori knowledge of the forest height, an estimate for the
Löscher, Wolfgang
2016-10-01
Animal seizure and epilepsy models continue to play an important role in the early discovery of new therapies for the symptomatic treatment of epilepsy. Since 1937, with the discovery of phenytoin, almost all anti-seizure drugs (ASDs) have been identified by their effects in animal models, and millions of patients world-wide have benefited from the successful translation of animal data into the clinic. However, several unmet clinical needs remain, including resistance to ASDs in about 30% of patients with epilepsy, adverse effects of ASDs that can reduce quality of life, and the lack of treatments that can prevent development of epilepsy in patients at risk following brain injury. The aim of this review is to critically discuss the translational value of currently used animal models of seizures and epilepsy, particularly what animal models can tell us about epilepsy therapies in patients and which limitations exist. Principles of translational medicine will be used for this discussion. An essential requirement for translational medicine to improve success in drug development is the availability of animal models with high predictive validity for a therapeutic drug response. For this requirement, the model, by definition, does not need to be a perfect replication of the clinical condition, but it is important that the validation provided for a given model is fit for purpose. The present review should guide researchers in both academia and industry what can and cannot be expected from animal models in preclinical development of epilepsy therapies, which models are best suited for which purpose, and for which aspects suitable models are as yet not available. Overall further development is needed to improve and validate animal models for the diverse areas in epilepsy research where suitable fit for purpose models are urgently needed in the search for more effective treatments. PMID:27505294
Bustamante, Carlos D.; Valero-Cuevas, Francisco J.
2010-01-01
The field of complex biomechanical modeling has begun to rely on Monte Carlo techniques to investigate the effects of parameter variability and measurement uncertainty on model outputs, search for optimal parameter combinations, and define model limitations. However, advanced stochastic methods to perform data-driven explorations, such as Markov chain Monte Carlo (MCMC), become necessary as the number of model parameters increases. Here, we demonstrate the feasibility and, what to our knowledge is, the first use of an MCMC approach to improve the fitness of realistically large biomechanical models. We used a Metropolis–Hastings algorithm to search increasingly complex parameter landscapes (3, 8, 24, and 36 dimensions) to uncover underlying distributions of anatomical parameters of a “truth model” of the human thumb on the basis of simulated kinematic data (thumbnail location, orientation, and linear and angular velocities) polluted by zero-mean, uncorrelated multivariate Gaussian “measurement noise.” Driven by these data, ten Markov chains searched each model parameter space for the subspace that best fit the data (posterior distribution). As expected, the convergence time increased, more local minima were found, and marginal distributions broadened as the parameter space complexity increased. In the 36-D scenario, some chains found local minima but the majority of chains converged to the true posterior distribution (confirmed using a cross-validation dataset), thus demonstrating the feasibility and utility of these methods for realistically large biomechanical problems. PMID:19272906
Computational Software for Fitting Seismic Data to Epidemic-Type Aftershock Sequence Models
NASA Astrophysics Data System (ADS)
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.
Quantum Transport Modeling of Atomic Nanostructures on Silicon
NASA Astrophysics Data System (ADS)
Smeu, Manuel
Surface effects can adversely influence the performance of a nanoelectronic device, but may also lead to new functionality. The focus of this thesis is to theoretically study the role of surfaces in nanoelectronics. Our theoretical analysis is from atomic first principles achieved by combining density functional theory with the Keldysh nonequilibrium Green's function approach. This technique allows for all atoms in a system to be treated on an equal footing without any phenomenological parameters. The first part of the thesis considers conduction through a molecule with no substrate to illustrate the sort of system typically modeled in transport calculations. Two Au electrodes are bridged by a substituted benzenediamine molecule (R = CH3, NH2, OH) where an H atom is removed to form a radical that may behave as a spin filter, depending on the R group. Next is considered a π-stacked line of ethylbenzene molecules on the Si(100) surface, where the Si atoms are explicitly included in the calculation. Although the molecules conduct electrons at certain energies, a channel occurs through the substrate, which can dominate the conductance. The use of substituent groups to modulate the electron transport properties of such wires is also investigated, showing that the conductance of the molecular wire could be tuned to dominate over the substrate. Finally, the conductance of the Si(111)-7 × 7 metallic surface is studied. Inspired by experiments suggesting that atomic steps reduce the surface conductance, the atomic structure and transport properties of such steps are examined, revealing that dimer atom buckling along the step edges is the primary culprit since it leads to an opening of a local band gap at the step.
Agirrezabala, Xabier; Velázquez-Muriel, Javier A; Gómez-Puertas, Paulino; Scheres, Sjors H W; Carazo, José M; Carrascosa, José L
2007-04-01
The existence of similar folds among major structural subunits of viral capsids has shown unexpected evolutionary relationships suggesting common origins irrespective of the capsids' host life domain. Tailed bacteriophages are emerging as one such family, and we have studied the possible existence of the HK97-like fold in bacteriophage T7. The procapsid structure at approximately 10 A resolution was used to obtain a quasi-atomic model by fitting a homology model of the T7 capsid protein gp10 that was based on the atomic structure of the HK97 capsid protein. A number of fold similarities, such as the fitting of domains A and P into the L-shaped procapsid subunit, are evident between both viral systems. A different feature is related to the presence of the amino-terminal domain of gp10 found at the inner surface of the capsid that might play an important role in the interaction of capsid and scaffolding proteins. PMID:17437718
Exactly solvable models for atom-molecule Hamiltonians.
Dukelsky, J; Dussel, G G; Esebbag, C; Pittel, S
2004-07-30
We present a family of exactly solvable generalizations of the Jaynes-Cummings model involving the interaction of an ensemble of SU(2) or SU(1,1) quasispins with a single boson field. They are obtained from the trigonometric Richardson-Gaudin models by replacing one of the SU(2) or SU(1,1) degrees of freedom by an ideal boson. The application to a system of bosonic atoms and molecules is reported. PMID:15323678
Atomic scale modeling of boron transient diffusion in silicon
Caturla, M. J.; Diaz de la Rubia, T.; Foad, M.; Giles, M.; Johnson, M. D.; Law, M.; Lilak, A.
1998-06-17
We presents results from a predictive atomic level simulation of Boron diffusion in Silicon under a wide variety of implant and annealing conditions. The parameters for this simulation have been extracted from first principle approximation models and molecular dynamics simulations. The results are compared with experiments showing good agreement in all cases. The parameters and reactions used have been implemented into a continuum-level model simulator.
Kinetic Modeling and Fitting Software for Inter-connected Reaction Schemes: VisKin
Zhang, Xuan; Andrews, Jared N.; Pedersen, Steen E.
2007-01-01
Reaction kinetics for complex, highly-interconnected kinetic schemes are modeled using analytical solutions to a system of ordinary differential equations. The algorithm employs standard linear algebra methods that are implemented using MatLab functions in a Visual Basic interface. A graphical user interface for simple entry of reaction schemes facilitates comparison of a variety of reaction schemes. To ensure microscopic balance, graph theory algorithms are used to determine violations of thermodynamic cycle constraints. Analytical solutions based on linear differential equations result in fast comparisons of first order kinetic rates and amplitudes as a function of changing ligand concentrations. For analysis of higher order kinetics, we also implemented a solution using numerical integration. In order to determine rate constants from experimental data, fitting algorithms using the Levenberg-Marquardt algorithm or using Broyden-Fletcher-Goldfarb-Shanno (BFGS) methods were implemented that adjust rate constants to fit the model to imported data. We have included the ability to carry out global fitting of data sets obtained at varying ligand concentrations. These tools are combined in a single package, which we have dubbed VisKin, to guide and analyze kinetic experiments. The software is available online for use on PCs. PMID:17207764
Kinetic modeling and fitting software for interconnected reaction schemes: VisKin.
Zhang, Xuan; Andrews, Jared N; Pedersen, Steen E
2007-02-15
Reaction kinetics for complex, highly interconnected kinetic schemes are modeled using analytical solutions to a system of ordinary differential equations. The algorithm employs standard linear algebra methods that are implemented using MatLab functions in a Visual Basic interface. A graphical user interface for simple entry of reaction schemes facilitates comparison of a variety of reaction schemes. To ensure microscopic balance, graph theory algorithms are used to determine violations of thermodynamic cycle constraints. Analytical solutions based on linear differential equations result in fast comparisons of first order kinetic rates and amplitudes as a function of changing ligand concentrations. For analysis of higher order kinetics, we also implemented a solution using numerical integration. To determine rate constants from experimental data, fitting algorithms that adjust rate constants to fit the model to imported data were implemented using the Levenberg-Marquardt algorithm or using Broyden-Fletcher-Goldfarb-Shanno methods. We have included the ability to carry out global fitting of data sets obtained at varying ligand concentrations. These tools are combined in a single package, which we have dubbed VisKin, to guide and analyze kinetic experiments. The software is available online for use on PCs. PMID:17207764
Goodness-of-fit tests for open capture-recapture models
Pollock, K.H.; Hines, J.E.; Nichols, J.D.
1985-01-01
General goodness-of-fit tests for the Jolly-Seber model are proposed. These tests are based on conditional arguments using minimal sufficient statistics. The tests are shown to be of simple hypergeometric form so that a series of independent contingency table chi-square tests can be performed. The relationship of these tests to other proposed tests is discussed. This is followed by a simulation study of the power of the tests to detect departures from the assumptions of the Jolly-Seber model. Some meadow vole capture-recapture data are used to illustrate the testing procedure which has been implemented in a computer program available from the authors.
The New Vector Fitting Approach to Multiple Convex Obstacles Modeling for UWB Propagation Channels
NASA Astrophysics Data System (ADS)
Górniak, P.; Bandurski, W.
This chapter presents the new approach to time-domain modeling of UWB channels containing multiple convex obstacles. Vector fitting (VF) algorithm (rational approximation) was used for deriving the closed form impulse response of multiple diffraction ray creeping on a cascade of convex obstacles. VF algorithm was performed with respect to new generalized variables proportional to frequency but including geometrical parameters of the obstacles also. The limits of approximation domain for vector fitting algorithm follow the range of ultra-wideband (UWB) channel parameters that can be met in practical UWB channel scenarios. Finally, the closed form impulse response of a creeping UTD ray was obtained. As the result we obtained impulse response of the channel as a function of normalized, with respect to geometrical parameters of the obstacles, time. It permits for calculation of channel responses for various objects without changing the body of a rational function. In that way the presented approach is general, simple, and effective.
The joys and perils of flexible fitting.
Volkmann, Niels
2014-01-01
While performing their functions, biological macromolecules often form large, dynamically changing macromolecular assemblies. Only a relatively small number of such assemblies have been accessible to the atomic-resolution techniques X-ray crystallography and NMR. Electron microscopy in conjunction with image reconstruction has become the preferred alternative for revealing the structures of such macromolecular complexes. However, for most assemblies the achievable resolution is too low to allow accurate atomic modeling directly from the data. Yet, useful models often can be obtained by fitting atomic models of individual components into a low-resolution reconstruction of the entire assembly. Several algorithms for achieving optimal fits in this context were developed recently, many allowing considerable degrees of flexibility to account for binding-induced conformational changes of the assembly components. This chapter describes the advantages and potential pitfalls of these methods and puts them into perspective with alternative approaches such as iterative modular fitting of rigid-body domains. PMID:24446360
Fitted Hanbury-Brown Twiss radii versus space-time variances in flow-dominated models
NASA Astrophysics Data System (ADS)
Frodermann, Evan; Heinz, Ulrich; Lisa, Michael Annan
2006-04-01
The inability of otherwise successful dynamical models to reproduce the Hanbury-Brown Twiss (HBT) radii extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the RHIC HBT Puzzle. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source that can be directly computed from the emission function without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models, some of which exhibit significant deviations from simple Gaussian behavior. By Fourier transforming the emission function, we compute the two-particle correlation function, and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and the measured HBT radii remain, we show that a more apples-to-apples comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data.
Fitted Hanbury-Brown-Twiss radii versus space-time variances in flow-dominated models
Frodermann, Evan; Heinz, Ulrich; Lisa, Michael Annan
2006-04-15
The inability of otherwise successful dynamical models to reproduce the Hanbury-Brown-Twiss (HBT) radii extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the RHIC HBT Puzzle. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source that can be directly computed from the emission function without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models, some of which exhibit significant deviations from simple Gaussian behavior. By Fourier transforming the emission function, we compute the two-particle correlation function, and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and the measured HBT radii remain, we show that a more apples-to-apples comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data.
Mukherjee, Goutam; Patra, Niladri; Barua, Poranjyoti; Jayaram, B
2011-04-15
We report here a new and fast approach [Transferable Partial Atomic Charge Model (TPACM4)-upto four bonds] for deriving the partial atomic charges of small molecules for use in protein/DNA-ligand docking and scoring. We have created a look-up table of 5302 atom types to cover the chemical space of C, H, O, N, S, P, F, Cl, and Br atoms in small molecules together with their quantum mechanical RESP fit charges. The atom types defined span diverse plausible chemical environments of each atom in a molecule. The partial charge on any atom in a given molecule is then assigned by a reference to the look-up table. We tested the sensitivity of the TPACM4 partial charges in estimates of hydrogen bond dimers energies, solvation free energies and protein-ligand binding free energies. An average error ±1.11 kcal/mol and a correlation coefficient of 0.90 is obtained in the calculated protein-ligand binding free energies vis-à-vis an RMS error of ±1.02 kcal/mol and a correlation coefficient of 0.92 obtained with RESP fit charges in comparison to experiment. Similar accuracies are realized in predictions of hydrogen bond energies and solvation free energies of small molecules. For a molecule containing 50-55 atoms, the method takes on the order of milliseconds on a single processor machine to assign partial atomic charges. The TPACM4 programme has been web-enabled and made freely accessible at http://www.scfbio-iitd.res.in/software/drugdesign/charge.jsp. PMID:21341292
A constructive model potential method for atomic interactions
NASA Technical Reports Server (NTRS)
Bottcher, C.; Dalgarno, A.
1974-01-01
A model potential method is presented that can be applied to many electron single centre and two centre systems. The development leads to a Hamiltonian with terms arising from core polarization that depend parametrically upon the positions of the valence electrons. Some of the terms have been introduced empirically in previous studies. Their significance is clarified by an analysis of a similar model in classical electrostatics. The explicit forms of the expectation values of operators at large separations of two atoms given by the model potential method are shown to be equivalent to the exact forms when the assumption is made that the energy level differences of one atom are negligible compared to those of the other.
Dufour, C.; Le-Huy, H.; El Hakimi, A.; Soumagne, J.C.
1996-01-01
Real-time simulation of a small power network containing a Marti modeled transmission line is made using 2 parallel DSP`s. A new fitting method is used in the modeling of the Marti line which is optimized with regards to the fitting error curve. Results are presented which show the time costs of the Marti line modeling versus constant-parameter line modeling and the time savings by using two parallel DSP`s.
Modeling of Turbulence Effect on Liquid Jet Atomization
NASA Technical Reports Server (NTRS)
Trinh, H. P.
2007-01-01
Recent studies indicate that turbulence behaviors within a liquid jet have considerable effect on the atomization process. Such turbulent flow phenomena are encountered in most practical applications of common liquid spray devices. This research aims to model the effects of turbulence occurring inside a cylindrical liquid jet to its atomization process. The two widely used atomization models Kelvin-Helmholtz (KH) instability of Reitz and the Taylor analogy breakup (TAB) of O'Rourke and Amsden portraying primary liquid jet disintegration and secondary droplet breakup, respectively, are examined. Additional terms are formulated and appropriately implemented into these two models to account for the turbulence effect. Results for the flow conditions examined in this study indicate that the turbulence terms are significant in comparison with other terms in the models. In the primary breakup regime, the turbulent liquid jet tends to break up into large drops while its intact core is slightly shorter than those without turbulence. In contrast, the secondary droplet breakup with the inside liquid turbulence consideration produces smaller drops. Computational results indicate that the proposed models provide predictions that agree reasonably well with available measured data.
Atomic Data and the Modeling of Supernova Spectra
NASA Astrophysics Data System (ADS)
Fontes, Christopher
2012-06-01
The modeling of supernovae (SNe) incorporates a variety of disciplines, including hydrodynamics, radiation transport, nuclear physics and atomic physics. These efforts require numerical simulation of the final stages of a star's life, the supernova explosion phase, and the radiation that is subsequently emitted by the supernova remnant, which can occur over a time span of tens of thousands of years. While there are several different types of SNe, they all emit radiation in some form. The measurement and interpretation of these spectra provide important information about the structure of the exploding star and the supernova engine. In this talk, the role of atomic data is highlighted as it pertains to the modeling of supernova spectra. Recent applications [1,2] involve the Los Alamos OPLIB opacity database, which has been used to provide atomic opacities for modeling supernova plasmas under local thermodynamic equilibrium (LTE) conditions. Ongoing work includes the application of atomic data generated by the Los Alamos suite of atomic physics codes under more complicated, non-LTE conditions [3]. As a specific, recent example, a portion of the x-ray spectrum produced by Tycho's supernova remnant (SN 1572) will be discussed [4].[4pt] [1] C.L. Fryer et al., Astrophys. J. 707, 193 (2009).[0pt] [2] C.L. Fryer et al., Astrophys. J. 725, 296 (2009).[0pt] [3] C.J. Fontes et al., Conference Proceedings for ICPEAC XXVII (Belfast, Northern Ireland), in press, (2011).[0pt] [4] K.A. Eriksen et al., Presentation at the 2012 AAS Meeting (Austin, TX).
Atmospheric Properties of T Dwarfs Inferred from Model Fits at Low Spectral Resolution
NASA Astrophysics Data System (ADS)
Godfrey, Paige A.; Rice, Emily L.; Filippazzo, Joe; Douglas, Stephanie; BDNYC
2016-01-01
Brown dwarfs are substellar objects that cool over time because they are not massive enough to sustain hydrogen fusion at their cores. While spectral types (M, L, T, Y) generally correlate with decreasing temperature, spectral subclasses (T0, T1, T2, etc.) do not, suggesting that secondary parameters (gravity, metallicity, dust) play a role in the spectral type-temperature relationship. We investigate this relationship for T dwarfs, which make up the coolest fully-populated spectral class of substellar objects. Our sample consists of 154 T dwarfs with low resolution (R~75-100) near-infrared (~0.8-2.5 micron) spectra from the SpeX Prism Library and the literature. We compare each observed spectrum to synthetic spectra from four model grids using a Markov-Chain Monte Carlo analysis to determine robust best-fit parameters and uncertainties. We evaluate the best fit parameters from each model grid per object to constrain how spectral type relates to decreasing temperature and increasing surface gravity and to compare the consistency of each model grid. To test for discrepant results when fitting to relatively narrow wavelength ranges, this analysis is performed on the full spectrum of the Y, J, H, and K bands and on each band separately. New detections of cooler objects extending into the Y dwarf and exoplanet regimes motivate our model comparisons and search for trends with spectral type and other observational properties across the decreasing temperatures in order to better understand the atmospheres of substellar objects, including cool gas giant exoplanets.
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.
2014-01-01
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 Ea and frequency factor A) were carefully examined. We propose a simplified correlated parameter fit to the Arrhenius model by treating Ea, 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 Ea 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. PMID:25205396
A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit
NASA Technical Reports Server (NTRS)
Kim, K. Han; Young, Karen S.; Bernal, Yaritza; Boppana, Abhishektha; Vu, Linh Q.; Benson, Elizabeth A.; Jarvis, Sarah; Rajulu, Sudhakar L.
2016-01-01
Shoulder injury is one of the most severe risks that have the potential to impair crewmembers' performance and health in long duration space flight. Overall, 64% of crewmembers experience shoulder pain after extra-vehicular training in a space suit, and 14% of symptomatic crewmembers require surgical repair (Williams & Johnson, 2003). Suboptimal suit fit, in particular at the shoulder region, has been identified as one of the predominant risk factors. However, traditional suit fit assessments and laser scans represent only a single person's data, and thus may not be generalized across wide variations of body shapes and poses. The aim of this work is to develop a software tool based on a statistical analysis of a large dataset of crewmember body shapes. This tool can accurately predict the skin deformation and shape variations for any body size and shoulder pose for a target population, from which the geometry can be exported and evaluated against suit models in commercial CAD software. A preliminary software tool was developed by statistically analyzing 150 body shapes matched with body dimension ranges specified in the Human-Systems Integration Requirements of NASA ("baseline model"). Further, the baseline model was incorporated with shoulder joint articulation ("articulation model"), using additional subjects scanned in a variety of shoulder poses across a pre-specified range of motion. Scan data was cleaned and aligned using body landmarks. The skin deformation patterns were dimensionally reduced and the co-variation with shoulder angles was analyzed. A software tool is currently in development and will be presented in the final proceeding. This tool would allow suit engineers to parametrically generate body shapes in strategically targeted anthropometry dimensions and shoulder poses. This would also enable virtual fit assessments, with which the contact volume and clearance between the suit and body surface can be predictively quantified at reduced time and
Blowout Jets: Hinode X-Ray Jets that Don't Fit the Standard Model
NASA Technical Reports Server (NTRS)
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
NASA Astrophysics Data System (ADS)
Duckstein, L.; Bobée, B.; Ashkar, F.
1991-09-01
The problem of fitting a probability distribution, here log-Pearson Type III distribution, to extreme floods is considered from the point of view of two numerical and three non-numerical criteria. The six techniques of fitting considered include classical techniques (maximum likelihood, moments of logarithms of flows) and new methods such as mixed moments and the generalized method of moments developed by two of the co-authors. The latter method consists of fitting the distribution using moments of different order, in particular the SAM method (Sundry Averages Method) uses the moments of order 0 (geometric mean), 1 (arithmetic mean), -1 (harmonic mean) and leads to a smaller variance of the parameters. The criteria used to select the method of parameter estimation are: - the two statistical criteria of mean square error and bias; - the two computational criteria of program availability and ease of use; - the user-related criterion of acceptability. These criteria are transformed into value functions or fuzzy set membership functions and then three Multiple Criteria Decision Modelling (MCDM) techniques, namely, composite programming, ELECTRE, and MCQA, are applied to rank the estimation techniques.
Jochens, Arne; Caliebe, Amke; Rösler, Uwe; Krawczak, Michael
2011-12-01
The rate of microsatellite mutation is dependent upon both the allele length and the repeat motif, but the exact nature of this relationship is still unknown. We analyzed data on the inheritance of human Y-chromosomal microsatellites in father-son duos, taken from 24 published reports and comprising 15,285 directly observable meioses. At the six microsatellites analyzed (DYS19, DYS389I, DYS390, DYS391, DYS392, and DYS393), a total of 162 mutations were observed. For each locus, we employed a maximum-likelihood approach to evaluate one of several single-step mutation models on the basis of the data. For five of the six loci considered, a novel logistic mutation model was found to provide the best fit according to Akaike's information criterion. This implies that the mutation probability at the loci increases (nonlinearly) with allele length at a rate that differs between upward and downward mutations. For DYS392, the best fit was provided by a linear model in which upward and downward mutation probabilities increase equally with allele length. This is the first study to empirically compare different microsatellite mutation models in a locus-specific fashion. PMID:21968190
Jochens, Arne; Caliebe, Amke; Rösler, Uwe; Krawczak, Michael
2011-01-01
The rate of microsatellite mutation is dependent upon both the allele length and the repeat motif, but the exact nature of this relationship is still unknown. We analyzed data on the inheritance of human Y-chromosomal microsatellites in father–son duos, taken from 24 published reports and comprising 15,285 directly observable meioses. At the six microsatellites analyzed (DYS19, DYS389I, DYS390, DYS391, DYS392, and DYS393), a total of 162 mutations were observed. For each locus, we employed a maximum-likelihood approach to evaluate one of several single-step mutation models on the basis of the data. For five of the six loci considered, a novel logistic mutation model was found to provide the best fit according to Akaike’s information criterion. This implies that the mutation probability at the loci increases (nonlinearly) with allele length at a rate that differs between upward and downward mutations. For DYS392, the best fit was provided by a linear model in which upward and downward mutation probabilities increase equally with allele length. This is the first study to empirically compare different microsatellite mutation models in a locus-specific fashion. PMID:21968190
Veres, Peter; Meszaros, Peter; Zhang, Bin-Bin
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.
NASA Astrophysics Data System (ADS)
Arsenault, Richard; Brissette, François P.; Poulin, Annie; Côté, Pascal; Martel, Jean-Luc
2014-05-01
The process of hydrological model parameter calibration is routinely performed with the help of stochastic optimization algorithms. Many such algorithms have been created and they sometimes provide varying levels of performance (as measured by an efficiency metric such as Nash-Sutcliffe). This is because each algorithm is better suited for one type of optimization problem rather than another. This research project's aim was twofold. First, it was sought upon to find various features in the calibration problem fitness landscapes to map the encountered problem types to the best possible optimization algorithm. Second, the optimal number of model evaluations in order to minimize resources usage and maximize overall model quality was investigated. A total of five stochastic optimization algorithms (SCE-UA, CMAES, DDS, PSO and ASA) were used to calibrate four lumped hydrological models (GR4J, HSAMI, HMETS and MOHYSE) on 421 basins from the US MOPEX database. Each of these combinations was performed using three objective functions (Log(RMSE), NSE, and a metric combining NSE, RMSE and BIAS) to add sufficient diversity to the fitness landscapes. Each run was performed 30 times for statistical analysis. With every parameter set tested during the calibration process, the validation value was taken on a separate period. It was then possible to outline the calibration skill versus the validation skill for the different algorithms. Fitness landscapes were characterized by various metrics, such as the dispersion metric, the mean distance between random points and their respective local minima (found through simple hill-climbing algorithms) and the mean distance between the local minima and the best local optimum found. These metrics were then compared to the calibration score of the various optimization algorithms. Preliminary results tend to show that fitness landscapes presenting a globally convergent structure are more prevalent than other types of landscapes in this
Fitting a Two- Component Scattering Model to Polarimetric SAR Data from Forests
NASA Astrophysics Data System (ADS)
Freeman, A.
2007-03-01
Two simple scattering mechanisms are f itted to polarimetric SAR observations of forests. The mechanisms are canopy scatter from a reciprocal medium with azimuthal symmetry, and a ground scatter term, which can represent double-bounce scatter from a pair of orthogonal surfaces with different d ielectric constants or Bragg scatter from a moderately rough surface, seen through a layer of vertically oriented scatterers. The model is shown to represent the behavior of polarimetric backscatter from a tropical forest and two temperate forest sites, by applying it to data from NASA/JPL's AIRSAR system. Scattering contributions from the two basic scattering mechanisms are estimated for clusters of pixels in polarimetric SAR images. The solution involves the estimation of four parameters from four separate equations. This model fit approach is justified as a simplification of more complicated scattering models, which require many inputs to solve the forward scattering problem. The model is used to develop an understanding of the ground-trunk, double-bounce scattering present in the data, which is seen to vary considerably as a function of incidence angle. Two parameters in the model fit appear to exhibit sensitivity to vegetation canopy structure, which is worth further exploration. Results from the model fit for the ground scattering term are compared with estimates from a forward model and shown to be in good agreement. The behavior of the scattering from the ground-trunk interaction is consistent with the presence of a pseudo-Brewster angle effect for the air- trunk scattering interface. If the Brewster angle is known, it is possible to directly estimate the real part of the dielectric constant of the trunks, a key variable in forward modeling of backscatter from forests. It is also shown how, with a priori knowledge of the forest height, an estimate for the attenuation coefficient of the canopy can be obtained directly from the multi-incidence angle, polarimetric
Semirelativistic model for ionization of atomic hydrogen by electron impact
Attaourti, Y.; Taj, S.; Manaut, B.
2005-06-15
We present a semirelativistic model for the description of the ionization process of atomic hydrogen by electron impact in the first Born approximation by using the Darwin wave function to describe the bound state of atomic hydrogen and the Sommerfeld-Maue wave function to describe the ejected electron. This model, accurate to first order in Z/c in the relativistic correction, shows that, even at low kinetic energies of the incident electron, spin effects are small but not negligible. These effects become noticeable with increasing incident electron energies. All analytical calculations are exact and our semirelativistic results are compared with the results obtained in the nonrelativistic Coulomb Born approximation both for the coplanar asymmetric and the binary coplanar geometries.
Empirical model of atomic nitrogen in the upper thermosphere
NASA Technical Reports Server (NTRS)
Engebretson, M. J.; Mauersberger, K.; Kayser, D. C.; Potter, W. E.; Nier, A. O.
1977-01-01
Atomic nitrogen number densities in the upper thermosphere measured by the open source neutral mass spectrometer (OSS) on Atmosphere Explorer-C during 1974 and part of 1975 have been used to construct a global empirical model at an altitude of 375 km based on a spherical harmonic expansion. The most evident features of the model are large diurnal and seasonal variations of atomic nitrogen and only a moderate and latitude-dependent density increase during periods of geomagnetic activity. Maximum and minimum N number densities at 375 km for periods of low solar activity are 3.6 x 10 to the 6th/cu cm at 1500 LST (local solar time) and low latitude in the summer hemisphere and 1.5 x 10 to the 5th/cu cm at 0200 LST at mid-latitudes in the winter hemisphere.
Extended Bose-Hubbard models with ultracold magnetic atoms
NASA Astrophysics Data System (ADS)
Baier, S.; Mark, M. J.; Petter, D.; Aikawa, K.; Chomaz, L.; Cai, Z.; Baranov, M.; Zoller, P.; Ferlaino, F.
2016-04-01
The Hubbard model underlies our understanding of strongly correlated materials. Whereas its standard form only comprises interactions between particles at the same lattice site, extending it to encompass long-range interactions is predicted to profoundly alter the quantum behavior of the system. We realize the extended Bose-Hubbard model for an ultracold gas of strongly magnetic erbium atoms in a three-dimensional optical lattice. Controlling the orientation of the atomic dipoles, we reveal the anisotropic character of the onsite interaction and hopping dynamics and their influence on the superfluid-to-Mott insulator quantum phase transition. Moreover, we observe nearest-neighbor interactions, a genuine consequence of the long-range nature of dipolar interactions. Our results lay the groundwork for future studies of exotic many-body quantum phases.
Generalized Kronig-Penney model for ultracold atomic quantum systems
NASA Astrophysics Data System (ADS)
Negretti, A.; Gerritsma, R.; Idziaszek, Z.; Schmidt-Kaler, F.; Calarco, T.
2014-10-01
We study the properties of a quantum particle interacting with a one-dimensional structure of equidistant scattering centers. We derive an analytical expression for the dispersion relation and for the Bloch functions in the presence of both even and odd scattering waves within the pseudopotential approximation. This generalizes the well-known solid-state physics textbook result known as the Kronig-Penney model. Our generalized model can be used to describe systems such as degenerate Fermi gases interacting with ions or with another neutral atomic species confined in an optical lattice, thus enabling the investigation of polaron or Kondo physics within a simple formalism. We focus our attention on the specific atom-ion system and compare our findings with quantum defect theory. Excellent agreement is obtained within the regime of validity of the pseudopotential approximation. This enables us to derive a Bose-Hubbard Hamiltonian for a degenerate quantum Bose gas in a linear chain of ions.
Extended Bose-Hubbard models with ultracold magnetic atoms.
Baier, S; Mark, M J; Petter, D; Aikawa, K; Chomaz, L; Cai, Z; Baranov, M; Zoller, P; Ferlaino, F
2016-04-01
The Hubbard model underlies our understanding of strongly correlated materials. Whereas its standard form only comprises interactions between particles at the same lattice site, extending it to encompass long-range interactions is predicted to profoundly alter the quantum behavior of the system. We realize the extended Bose-Hubbard model for an ultracold gas of strongly magnetic erbium atoms in a three-dimensional optical lattice. Controlling the orientation of the atomic dipoles, we reveal the anisotropic character of the onsite interaction and hopping dynamics and their influence on the superfluid-to-Mott insulator quantum phase transition. Moreover, we observe nearest-neighbor interactions, a genuine consequence of the long-range nature of dipolar interactions. Our results lay the groundwork for future studies of exotic many-body quantum phases. PMID:27124454
ERIC Educational Resources Information Center
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…
Trajectory fitting in function space with application to analytic modeling of surfaces
NASA Technical Reports Server (NTRS)
Barger, Raymond L.
1992-01-01
A theory for representing a parameter-dependent function as a function trajectory is described. Additionally, a theory for determining a piecewise analytic fit to the trajectory is described. An example is given that illustrates the application of the theory to generating a smooth surface through a discrete set of input cross-section shapes. A simple procedure for smoothing in the parameter direction is discussed, and a computed example is given. Application of the theory to aerodynamic surface modeling is demonstrated by applying it to a blended wing-fuselage surface.
Current status of the standard model CKM fit and constraints on Δ F =2 new physics
NASA Astrophysics Data System (ADS)
Charles, J.; Deschamps, O.; Descotes-Genon, S.; Lacker, H.; Menzel, A.; Monteil, S.; Niess, V.; Ocariz, J.; Orloff, J.; Perez, A.; Qian, W.; Tisserand, V.; Trabelsi, K.; Urquijo, P.; Vale Silva, L.; CKMfitter Group
2015-04-01
This article summarizes the status of the global fit of the Cabibbo-Kobayashi-Maskawa (CKM) parameters within the Standard Model performed by the CKMfitter group. Special attention is paid to the inputs for the CKM angles α and γ and the status of Bs→μ μ and Bd→μ μ decays. We illustrate the current situation for other unitarity triangles. We also discuss the constraints on generic Δ F =2 new physics. All results have been obtained with the CKMfitter analysis package, featuring the frequentist statistical approach and using Rfit to handle theoretical uncertainties.
Crystallographic observation of 'induced fit' in a cryptophane host–guest model system
Taratula, Olena; Hill, P. Aru; Khan, Najat S.; Carroll, Patrick J.; Dmochowski, Ivan J.
2010-01-01
Cryptophane-A, comprised of two cyclotriguaiacylenes joined by three ethylene linkers, is a prototypal organic host molecule that binds reversibly to neutral small molecules via London forces. Of note are trifunctionalized, water-soluble cryptophane-A derivatives, which exhibit exceptional affinity for xenon in aqueous solution. In this paper, we report high-resolution X-ray structures of cryptophane-A and trifunctionalized derivatives in crown–crown and crown–saddle conformations, as well as in complexes with water, methanol, xenon or chloroform. Cryptophane internal volume varied by more than 20% across this series, which exemplifies 'induced fit' in a model host–guest system. PMID:21266998
Fitting optimum order of Markov chain models for daily rainfall occurrences in Peninsular Malaysia
NASA Astrophysics Data System (ADS)
Deni, Sayang Mohd; Jemain, Abdul Aziz; Ibrahim, Kamarulzaman
2009-06-01
The analysis of the daily rainfall occurrence behavior is becoming more important, particularly in water-related sectors. Many studies have identified a more comprehensive pattern of the daily rainfall behavior based on the Markov chain models. One of the aims in fitting the Markov chain models of various orders to the daily rainfall occurrence is to determine the optimum order. In this study, the optimum order of the Markov chain models for a 5-day sequence will be examined in each of the 18 rainfall stations in Peninsular Malaysia, which have been selected based on the availability of the data, using the Akaike’s (AIC) and Bayesian information criteria (BIC). The identification of the most appropriate order in describing the distribution of the wet (dry) spells for each of the rainfall stations is obtained using the Kolmogorov-Smirnov goodness-of-fit test. It is found that the optimum order varies according to the levels of threshold used (e.g., either 0.1 or 10.0 mm), the locations of the region and the types of monsoon seasons. At most stations, the Markov chain models of a higher order are found to be optimum for rainfall occurrence during the northeast monsoon season for both levels of threshold. However, it is generally found that regardless of the monsoon seasons, the first-order model is optimum for the northwestern and eastern regions of the peninsula when the level of thresholds of 10.0 mm is considered. The analysis indicates that the first order of the Markov chain model is found to be most appropriate for describing the distribution of wet spells, whereas the higher-order models are found to be adequate for the dry spells in most of the rainfall stations for both threshold levels and monsoon seasons.
Bajzer, Željko; Gibbons, Simon J.; Coleman, Heidi D.; Linden, David R.
2015-01-01
Noninvasive breath tests for gastric emptying are important techniques for understanding the changes in gastric motility that occur in disease or in response to drugs. Mice are often used as an animal model; however, the gamma variate model currently used for data analysis does not always fit the data appropriately. The aim of this study was to determine appropriate mathematical models to better fit mouse gastric emptying data including when two peaks are present in the gastric emptying curve. We fitted 175 gastric emptying data sets with two standard models (gamma variate and power exponential), with a gamma variate model that includes stretched exponential and with a proposed two-component model. The appropriateness of the fit was assessed by the Akaike Information Criterion. We found that extension of the gamma variate model to include a stretched exponential improves the fit, which allows for a better estimation of T1/2 and Tlag. When two distinct peaks in gastric emptying are present, a two-component model is required for the most appropriate fit. We conclude that use of a stretched exponential gamma variate model and when appropriate a two-component model will result in a better estimate of physiologically relevant parameters when analyzing mouse gastric emptying data. PMID:26045615
Limited-information goodness-of-fit testing of hierarchical item factor models.
Cai, Li; Hansen, Mark
2013-05-01
In applications of item response theory, assessment of model fit is a critical issue. Recently, limited-information goodness-of-fit testing has received increased attention in the psychometrics literature. In contrast to full-information test statistics such as Pearson's X(2) or the likelihood ratio G(2) , these limited-information tests utilize lower-order marginal tables rather than the full contingency table. A notable example is Maydeu-Olivares and colleagues'M2 family of statistics based on univariate and bivariate margins. When the contingency table is sparse, tests based on M2 retain better Type I error rate control than the full-information tests and can be more powerful. While in principle the M2 statistic can be extended to test hierarchical multidimensional item factor models (e.g., bifactor and testlet models), the computation is non-trivial. To obtain M2 , a researcher often has to obtain (many thousands of) marginal probabilities, derivatives, and weights. Each of these must be approximated with high-dimensional numerical integration. We propose a dimension reduction method that can take advantage of the hierarchical factor structure so that the integrals can be approximated far more efficiently. We also propose a new test statistic that can be substantially better calibrated and more powerful than the original M2 statistic when the test is long and the items are polytomous. We use simulations to demonstrate the performance of our new methods and illustrate their effectiveness with applications to real data. PMID:22642552
Charged Neutrinos and Atoms in the Standard Model
NASA Astrophysics Data System (ADS)
Takasugi, E.; Tanaka, M.
1992-03-01
The possibility of the charge quantization in the standard model is examined in the absence of the ``generation as copies'' rule. It is shown that neutrinos and atoms can have mini-charges, while neutron is neutral. If a triplet Higgs boson is introduced, neutrinos have masses. Two neutrinos form a Konopinski-Mahmoud Dirac particle and the other becomes a Majorana particle due to the hidden local anomaly free U(1) symmetry.
AtomDB and PyAtomDB: Atomic Data and Modelling Tools for High Energy and Non-Maxwellian Plasmas
NASA Astrophysics Data System (ADS)
Foster, Adam; Smith, Randall K.; Brickhouse, Nancy S.; Cui, Xiaohong
2016-04-01
The release of AtomDB 3 included a large wealth of inner shell ionization and excitation data allowing accurate modeling of non-equilibrium plasmas. We describe the newly calculated data and compare it to published literature data. We apply the new models to existing supernova remnant data such as W49B and N132D. We further outline progress towards AtomDB 3.1, including a new energy-dependent charge exchange cross sections.We present newly developed models for the spectra of electron-electron bremsstrahlung and those due to non-Maxwellian electron distributions.Finally, we present our new atomic database access tools, released as PyAtomDB, allowing powerful use of the underlying fundamental atomic data as well as the spectral emissivities.
SpectrRelax: An application for Mössbauer spectra modeling and fitting
NASA Astrophysics Data System (ADS)
Matsnev, M. E.; Rusakov, V. S.
2012-10-01
The SpectrRelax application was created for analysis and fitting of absorption and emission Mossbauer spectra of isotopes with 1/2 ↔ 3/2 transitions. Available models include a single Pseudo-Voigt line, doublet, and a sextet, a number of relaxation models, and a distribution of hyperfine/relaxation parameters of any model. SpectRelax can evaluate user supplied analytical expressions of model parameters and their error estimates. Complex parameter constraints or even new models can be implemented by setting parameter values to analytical expressions. Optimal model parameters search is performed using a maximum likelihood criterion in a Levenberg-Marquardt (L-M) algorithm. In the search process, a matrix of linear correlation coefficients between model parameters is calculated along with the error estimates, which allows better understanding of the optimized results. Partial derivatives of the model functions are evaluated using a "dual numbers" algorithm, which provides exact derivatives values at any point and improves the L-M method convergence. SpectrRelax runs under Windows operating systems by Microsoft. The application has a modern graphical user interface with extensive model editing and preview capabilities.
Modeling of Turbulence Effects on Liquid Jet Atomization and Breakup
NASA Technical Reports Server (NTRS)
Trinh, Huu P.; Chen, C. P.
2005-01-01
Recent experimental investigations and physical modeling studies have indicated that turbulence behaviors within a liquid jet have considerable effects on the atomization process. This study aims to model the turbulence effect in the atomization process of a cylindrical liquid jet. Two widely used models, the Kelvin-Helmholtz (KH) instability of Reitz (blob model) and the Taylor-Analogy-Breakup (TAB) secondary droplet breakup by O Rourke et al, are further extended to include turbulence effects. In the primary breakup model, the level of the turbulence effect on the liquid breakup depends on the characteristic scales and the initial flow conditions. For the secondary breakup, an additional turbulence force acted on parent drops is modeled and integrated into the TAB governing equation. The drop size formed from this breakup regime is estimated based on the energy balance before and after the breakup occurrence. This paper describes theoretical development of the current models, called "T-blob" and "T-TAB", for primary and secondary breakup respectivety. Several assessment studies are also presented in this paper.
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 carbon-limited environments with two characteristics driving fungal growth, namely the carbon decomposition rate and a measure of carbon use efficiency. The dynamics of fungal spread through a population of sites with either low (0.0074 mg) or high (0.016 mg) carbon content were well described by the simplified model with faster colonization for the carbon-rich environment. Rhizoctonia solani responded to a lower carbon availability by increasing the carbon use efficiency and the carbon decomposition rate following colonization. The results are discussed in relation to fungal invasion thresholds in terms of carbon nutrition. PMID:18312538
NASA Astrophysics Data System (ADS)
González-Oreja, José Antonio; Saiz-Salinas, José Ignacio
1999-07-01
Models of the macrozoobenthic community responses to abiotic variables measured in the polluted Bilbao estuary were obtained by multiple linear regression analyses. Total, Oligochaeta and Nematoda abundance and biomass were considered as dependent variables. Intertidal level, dissolved oxygen at the bottom of the water column (DOXB) and organic content of the sediment were selected by the analyses as the three principal explanatory variables. Goodness-of-fit of the models was high ( overlinex=71.3% ). Total abundance and biomass increased as a linear function of DOXB. The principal outcome of the vast sewage scheme currently in progress in the study area is an important contributor of increasing DOXB levels. The models exposed in this paper will serve as a tool to evaluate the expected changes in the near future.
A goodness-of-fit test for capture-recapture model M(t) under closure
Stanley, T.R.; Burnham, K.P.
1999-01-01
A new, fully efficient goodness-of-fit test for the time-specific closed-population capture-recapture model M(t) is presented. This test is based on the residual distribution of the capture history data given the maximum likelihood parameter estimates under model M(t), is partitioned into informative components, and is based on chi-square statistics. Comparison of this test with Leslie's test (Leslie, 1958, Journal of Animal Ecology 27, 84- 86) for model M(t), using Monte Carlo simulations, shows the new test generally outperforms Leslie's test. The new test is frequently computable when Leslie's test is not, has Type I error rates that are closer to nominal error rates than Leslie's test, and is sensitive to behavioral variation and heterogeneity in capture probabilities. Leslie's test is not sensitive to behavioral variation in capture probabilities but, when computable, has greater power to detect heterogeneity than the new test.
GRace: a MATLAB-based application for fitting the discrimination-association model.
Stefanutti, Luca; Vianello, Michelangelo; Anselmi, Pasquale; Robusto, Egidio
2014-01-01
The Implicit Association Test (IAT) is a computerized two-choice discrimination task in which stimuli have to be categorized as belonging to target categories or attribute categories by pressing, as quickly and accurately as possible, one of two response keys. The discrimination association model has been recently proposed for the analysis of reaction time and accuracy of an individual respondent to the IAT. The model disentangles the influences of three qualitatively different components on the responses to the IAT: stimuli discrimination, automatic association, and termination criterion. The article presents General Race (GRace), a MATLAB-based application for fitting the discrimination association model to IAT data. GRace has been developed for Windows as a standalone application. It is user-friendly and does not require any programming experience. The use of GRace is illustrated on the data of a Coca Cola-Pepsi Cola IAT, and the results of the analysis are interpreted and discussed. PMID:26054728
Fitting mathematical models to describe the rheological behaviour of chocolate pastes
NASA Astrophysics Data System (ADS)
Barbosa, Carla; Diogo, Filipa; Alves, M. Rui
2016-06-01
The flow behavior is of utmost importance for the chocolate industry. The objective of this work was to study two mathematical models, Casson and Windhab models that can be used to fit chocolate rheological data and evaluate which better infers or previews the rheological behaviour of different chocolate pastes. Rheological properties (viscosity, shear stress and shear rates) were obtained with a rotational viscometer equipped with a concentric cylinder. The chocolate samples were white chocolate and chocolate with varying percentages in cacao (55%, 70% and 83%). The results showed that the Windhab model was the best to describe the flow behaviour of all the studied samples with higher determination coefficients (r2 > 0.9).
Bloom, Jesse D
2014-10-01
Phylogenetic analyses of molecular data require a quantitative model for how sequences evolve. Traditionally, the details of the site-specific selection that governs sequence evolution are not known a priori, making it challenging to create evolutionary models that adequately capture the heterogeneity of selection at different sites. However, recent advances in high-throughput experiments have made it possible to quantify the effects of all single mutations on gene function. I have previously shown that such high-throughput experiments can be combined with knowledge of underlying mutation rates to create a parameter-free evolutionary model that describes the phylogeny of influenza nucleoprotein far better than commonly used existing models. Here, I extend this work by showing that published experimental data on TEM-1 beta-lactamase (Firnberg E, Labonte JW, Gray JJ, Ostermeier M. 2014. A comprehensive, high-resolution map of a gene's fitness landscape. Mol Biol Evol. 31:1581-1592) can be combined with a few mutation rate parameters to create an evolutionary model that describes beta-lactamase phylogenies much better than most common existing models. This experimentally informed evolutionary model is superior even for homologs that are substantially diverged (about 35% divergence at the protein level) from the TEM-1 parent that was the subject of the experimental study. These results suggest that experimental measurements can inform phylogenetic evolutionary models that are applicable to homologs that span a substantial range of sequence divergence. PMID:25063439
A History of Regression and Related Model-Fitting in the Earth Sciences (1636?-2000)
Howarth, Richard J.
2001-12-15
The (statistical) modeling of the behavior of a dependent variate as a function of one or more predictors provides examples of model-fitting which span the development of the earth sciences from the 17th Century to the present. The historical development of these methods and their subsequent application is reviewed. Bond's predictions (c. 1636 and 1668) of change in the magnetic declination at London may be the earliest attempt to fit such models to geophysical data. Following publication of Newton's theory of gravitation in 1726, analysis of data on the length of a 1{sup o} meridian arc, and the length of a pendulum beating seconds, as a function of sin{sup 2}(latitude), was used to determine the ellipticity of the oblate spheroid defining the Figure of the Earth. The pioneering computational methods of Mayer in 1750, Boscovich in 1755, and Lambert in 1765, and the subsequent independent discoveries of the principle of least squares by Gauss in 1799, Legendre in 1805, and Adrain in 1808, and its later substantiation on the basis of probability theory by Gauss in 1809 were all applied to the analysis of such geodetic and geophysical data. Notable later applications include: the geomagnetic survey of Ireland by Lloyd, Sabine, and Ross in 1836, Gauss's model of the terrestrial magnetic field in 1838, and Airy's 1845 analysis of the residuals from a fit to pendulum lengths, from which he recognized the anomalous character of measurements of gravitational force which had been made on islands. In the early 20th Century applications to geological topics proliferated, but the computational burden effectively held back applications of multivariate analysis. Following World War II, the arrival of digital computers in universities in the 1950s facilitated computation, and fitting linear or polynomial models as a function of geographic coordinates, trend surface analysis, became popular during the 1950-60s. The inception of geostatistics in France at this time by Matheron had
ERIC Educational Resources Information Center
Liguori, Lucia
2014-01-01
Atomic orbital theory is a difficult subject for many high school and beginning undergraduate students, as it includes mathematical concepts not yet covered in the school curriculum. Moreover, it requires certain ability for abstraction and imagination. A new atomic orbital model "the chocolate shop" created "by" students…
Atomic collision processes for modelling cool star spectra
NASA Astrophysics Data System (ADS)
Barklem, Paul
2015-05-01
The abundances of chemical elements in cool stars are very important in many problems in modern astrophysics. They provide unique insight into the chemical and dynamical evolution of the Galaxy, stellar processes such as mixing and gravitational settling, the Sun and its place in the Galaxy, and planet formation, to name a just few examples. Modern telescopes and spectrographs measure stellar spectral lines with precision of order 1 per cent, and planned surveys will provide such spectra for millions of stars. However, systematic errors in the interpretation of observed spectral lines leads to abundances with uncertainties greater than 20 per cent. Greater precision in the interpreted abundances should reasonably be expected to lead to significant discoveries, and improvements in atomic data used in stellar atmosphere models play a key role in achieving such advances in precision. In particular, departures from the classical assumption of local thermodynamic equilibrium (LTE) represent a significant uncertainty in the modelling of stellar spectra and thus derived chemical abundances. Non-LTE modelling requires large amounts of radiative and collisional data for the atomic species of interest. I will focus on inelastic collision processes due to electron and hydrogen atom impacts, the important perturbers in cool stars, and the progress that has been made. I will discuss the impact on non-LTE modelling, and what the modelling tells us about the types of collision processes that are important and the accuracy required. More specifically, processes of fundamentally quantum mechanical nature such as spin-changing collisions and charge transfer have been found to be very important in the non-LTE modelling of spectral lines of lithium, oxygen, sodium and magnesium.
Baghani, Ali; Salcudean, Septimiu; Honarvar, Mohammad; Sahebjavaher, Ramin S; Rohling, Robert; Sinkus, Ralph
2011-08-01
In this paper, a novel approach to the problem of elasticity reconstruction is introduced. In this approach, the solution of the wave equation is expanded as a sum of waves travelling in different directions sharing a common wave number. In particular, the solutions for the scalar and vector potentials which are related to the dilatational and shear components of the displacement respectively are expanded as sums of travelling waves. This solution is then used as a model and fitted to the measured displacements. The value of the shear wave number which yields the best fit is then used to find the elasticity at each spatial point. The main advantage of this method over direct inversion methods is that, instead of taking the derivatives of noisy measurement data, the derivatives are taken on the analytical model. This improves the results of the inversion. The dilatational and shear components of the displacement can also be computed as a byproduct of the method, without taking any derivatives. Experimental results show the effectiveness of this technique in magnetic resonance elastography. Comparisons are made with other state-of-the-art techniques. PMID:21813354
Modeling the Time Evolution of QSH Equilibria in MST Plasmas Using V3FIT
NASA Astrophysics Data System (ADS)
Boguski, J.; Nornberg, M.; Munaretto, S.; Chapman, B. E.; Cianciosa, M.; Terry, P. W.; Hanson, J.
2015-11-01
High current and low density RFP plasmas tend towards a 3D configuration, called Quasi-Single Helicity (QSH), characterized by a dominant core helical mode. V3FIT utilizes multiple internal and edge diagnostics to reconstruct the non-axisymmetric magnetic equilibrium of the QSH state. Performing multiple reconstructions at different stages in the QSH cycle is used to learn about the time dynamics of the QSH state. Recent work on modeling a shear-suppression mechanism for QSH formation has produced a predator-prey model of the time dynamics that reproduces the observed behavior, in particular the increased persistence of the QSH state with increased plasma current. Either magnetic or flow shear can facilitate QSH formation. The magnetic shear dependence of QSH is analyzed using V3FIT reconstructions of magnetic equilibrium constrained by internal measurements of density and temperature as well as soft x-ray emission. Fluctuations in the flux surface structure are compared against the measured temperature and density fluctuations and the reconstructed temperature and density profiles are examined to look for evidence of barriers to particle and heat transport. This material is based upon work supported by the U.S. DOE.
Romo, Tod D; Sacchettini, James C; Ioerger, Thomas R
2006-11-01
Automated methods for protein model building in X-ray crystallography typically use a two-phased approach that involves first modeling the protein backbone followed by building in the side chains. The latter phase requires the identification of the amino-acid side-chain type as well as fitting of the side-chain model into the observed electron density. While mistakes in identification of individual side chains are common for a number of reasons, sequence alignment can sometimes be used to correct errors by mapping fragments into the true (expected) amino-acid sequence and exploiting contiguity constraints among neighbors. However, side chains cannot always be confidently aligned; this depends on having sufficient accuracy in the initial calls. The recognition of amino-acid side-chains based on the surrounding pattern of electron density, whether by features, density correlation or free atoms, can be sensitive to inaccuracies in the coordinates of the predicted backbone C(alpha) atoms to which they are anchored. By incorporating a Nelder-Mead Simplex search into the side-chain identification and model-building routines of TEXTAL, it is demonstrated that this form of residue-by-residue rigid-body real-space refinement (in which the C(alpha) itself is allowed to shift) can improve the initial accuracy of side-chain selection by over 25% on average (from 25% average identity to 32% on a test set of five representative proteins, without corrections by sequence alignment). This improvement in amino-acid selection accuracy in TEXTAL is often sufficient to bring the pairwise amino-acid identity of chains in the model out of the so-called ;twilight zone' for sequence-alignment methods. When coupled with sequence alignment, use of the Simplex search yielded improvements in side-chain accuracy on average by over 13 percentage points (from 64 to 77%) and up to 38 percentage points (from 40 to 78%) in one case compared with using sequence alignment alone. PMID:17057345
Estimation of high-resolution dust column density maps. Empirical model fits
NASA Astrophysics Data System (ADS)
Juvela, M.; Montillaud, J.
2013-09-01
Context. Sub-millimetre dust emission is an important tracer of column density N of dense interstellar clouds. One has to combine surface brightness information at different spatial resolutions, and specific methods are needed to derive N at a resolution higher than the lowest resolution of the observations. Some methods have been discussed in the literature, including a method (in the following, method B) that constructs the N estimate in stages, where the smallest spatial scales being derived only use the shortest wavelength maps. Aims: We propose simple model fitting as a flexible way to estimate high-resolution column density maps. Our goal is to evaluate the accuracy of this procedure and to determine whether it is a viable alternative for making these maps. Methods: The new method consists of model maps of column density (or intensity at a reference wavelength) and colour temperature. The model is fitted using Markov chain Monte Carlo methods, comparing model predictions with observations at their native resolution. We analyse simulated surface brightness maps and compare its accuracy with method B and the results that would be obtained using high-resolution observations without noise. Results: The new method is able to produce reliable column density estimates at a resolution significantly higher than the lowest resolution of the input maps. Compared to method B, it is relatively resilient against the effects of noise. The method is computationally more demanding, but is feasible even in the analysis of large Herschel maps. Conclusions: The proposed empirical modelling method E is demonstrated to be a good alternative for calculating high-resolution column density maps, even with considerable super-resolution. Both methods E and B include the potential for further improvements, e.g., in the form of better a priori constraints.
Lifting a veil on diversity: a Bayesian approach to fitting relative-abundance models.
Golicher, Duncan J; O'Hara, Robert B; Ruíz-Montoya, Lorena; Cayuela, Luis
2006-02-01
Bayesian methods incorporate prior knowledge into a statistical analysis. This prior knowledge is usually restricted to assumptions regarding the form of probability distributions of the parameters of interest, leaving their values to be determined mainly through the data. Here we show how a Bayesian approach can be applied to the problem of drawing inference regarding species abundance distributions and comparing diversity indices between sites. The classic log series and the lognormal models of relative- abundance distribution are apparently quite different in form. The first is a sampling distribution while the other is a model of abundance of the underlying population. Bayesian methods help unite these two models in a common framework. Markov chain Monte Carlo simulation can be used to fit both distributions as small hierarchical models with shared common assumptions. Sampling error can be assumed to follow a Poisson distribution. Species not found in a sample, but suspected to be present in the region or community of interest, can be given zero abundance. This not only simplifies the process of model fitting, but also provides a convenient way of calculating confidence intervals for diversity indices. The method is especially useful when a comparison of species diversity between sites with different sample sizes is the key motivation behind the research. We illustrate the potential of the approach using data on fruit-feeding butterflies in southern Mexico. We conclude that, once all assumptions have been made transparent, a single data set may provide support for the belief that diversity is negatively affected by anthropogenic forest disturbance. Bayesian methods help to apply theory regarding the distribution of abundance in ecological communities to applied conservation. PMID:16705973
Observations from using models to fit the gas production of varying volume test cells and landfills.
Lamborn, Julia
2012-12-01
Landfill operators are looking for more accurate models to predict waste degradation and landfill gas production. The simple microbial growth and decay models, whilst being easy to use, have been shown to be inaccurate. Many of the newer and more complex (component) models are highly parameter hungry and many of the required parameters have not been collected or measured at full-scale landfills. This paper compares the results of using different models (LANDGEM, HBM, and two Monod models developed by the author) to fit the gas production of laboratory scale, field test cell and full-scale landfills and discusses some observations that can be made regarding the scalability of gas generation rates. The comparison of these results show that the fast degradation rate that occurs at laboratory scale is not replicated at field-test cell and full-scale landfills. At small scale, all the models predict a slower rate of gas generation than actually occurs. At field test cell and full-scale a number of models predict a faster gas generation than actually occurs. Areas for future work have been identified, which include investigations into the capture efficiency of gas extraction systems and into the parameter sensitivity and identification of the critical parameters for field-test cell and full-scale landfill predication. PMID:22796013
Fitting a 3-D analytic model of the coronal mass ejection to observations
NASA Technical Reports Server (NTRS)
Gibson, S. E.; Biesecker, D.; Fisher, R.; Howard, R. A.; Thompson, B. J.
1997-01-01
The application of an analytic magnetohydrodynamic model is presented to observations of the time-dependent explusion of 3D coronal mass ejections (CMEs) out of the solar corona. This model relates the white-light appearance of the CME to its internal magnetic field, which takes the form of a closed bubble, filled with a partly anchored, twisted magnetic flux rope and embedded in an otherwise open background field. The density distribution frozen into the expanding CME expanding field is fully 3D, and can be integrated along the line of sight to reproduce observations of scattered white light. The model is able to reproduce the three conspicuous features often associated with CMEs as observed with white-light coronagraphs: a surrounding high-density region, an internal low-density cavity, and a high-density core. The model also describes the self-similar radial expansion of these structures. By varying the model parameters, the model can be fitted directly to observations of CMEs. It is shown how the model can quantitatively match the polarized brightness contrast of a dark cavity emerging through the lower corona as observed by the HAO Mauna Loa K-coronameter to within the noise level of the data.
Atomic mechanism of internal friction in a model metallic glass
NASA Astrophysics Data System (ADS)
Yu, Hai-Bin; Samwer, Konrad
2014-10-01
Internal friction (IF) describes the ability of materials to damp out mechanical oscillations. It is a crucial engineering parameter and also conveys unique microscopic information about structural defects, transport phenomena, and phase transformations in solids. While IF predominately results from lattice defects in crystalline materials, the origin of IF remains unclear in disordered materials, like metallic glasses. In this paper, we study the atomic rearrangements that govern IF in a model metallic glass, via numerical simulations of dynamical mechanical spectroscopy together with structural analysis. We identify cooperative and avalanchelike thermal-driven excitations as an underlying mechanism and demonstrate a linearlike relation between the concentrations of these excitations and the values of IF. Structurally, these excitations can be hindered, and thus suppress IF, by slow atoms that usually associate with full icosahedral symmetry. Our results also provide practical guides in tuning IF in metallic glasses from atomistic perspectives.
Masses of atomic nuclei in the infinite nuclear matter model
Satpathy, L.; Nayak, R.C.
1988-07-01
We present mass excesses of 3481 nuclei in the range 18less than or equal toAless than or equal to267 using the infinite nuclear matter model based on the Hugenholtz-Van Hove theorem. In this model the ground-state energy of a nucleus of asymmetry ..beta.. is considered equivalent to the energy of a perfect sphere made up of the infinite nuclear matter of the same asymmetry plus the residual energy due to shell effects, deformation, etc., called the local energy eta. In this model there are two kinds of parameters: global and local. The five global parameters characterizing the properties of the above sphere are determined by fitting the mass of all nuclei (756) in the recent mass table of Wapstra et al. having error bar less than 30 keV. The local parameters are determined for 25 regions each spanning 8 or 10 A values. The total number of parameters including the five global ones is 238. The root-mean-square deviation for the calculated masses from experiment is 397 keV for the 1572 nuclei used in the least-squares fit. copyright 1988 Academic Press, Inc.
Theoretical model for electrophilic oxygen atom insertion into hydrocarbons
Bach, R.D.; Su, M.D. ); Andres, J.L. Wayne State Univ., Detroit, MI ); McDouall, J.J.W. )
1993-06-30
A theoretical model suggesting the mechanistic pathway for the oxidation of saturated-alkanes to their corresponding alcohols and ketones is described. Water oxide (H[sub 2]O-O) is employed as a model singlet oxygen atom donor. Molecular orbital calculations with the 6-31G basis set at the MP2, QCISD, QCISD(T), CASSCF, and MRCI levels of theory suggest that oxygen insertion by water oxide occurs by the interaction of an electrophilic oxygen atom with a doubly occupied hydrocarbon fragment orbital. The electrophilic oxygen approaches the hydrocarbon along the axis of the atomic carbon p orbital comprising a [pi]-[sub CH(2)] or [pi]-[sub CHCH(3)] fragment orbital to form a carbon-oxygen [sigma] bond. A concerted hydrogen migration to an adjacent oxygen lone pair of electrons affords the alcohol insertion product in a stereoselective fashion with predictable stereochemistry. Subsequent oxidation of the alcohol to a ketone (or aldehyde) occurs in a similar fashion and has a lower activation barrier. The calculated (MP4/6-31G*//MP2/6-31G*) activation barriers for oxygen atom insertion into the C-H bonds of methane, ethane, propane, butane, isobutane, and methanol are 10.7, 8.2, 3.9, 4.8, 4.5, and 3.3 kcal/mol, respectively. We use ab initio molecular orbital calculations in support of a frontier MO theory that provides a unique rationale for both the stereospecificity and the stereoselectivity of insertion of electrophilic oxygen and related electrophiles into the carbon-hydrogen bond. 13 refs., 7 figs., 2 tabs.
Improving the Fit of a Land-Surface Model to Data Using its Adjoint
NASA Astrophysics Data System (ADS)
Raoult, Nina; Jupp, Tim; Cox, Peter; Luke, Catherine
2016-04-01
Land-surface models (LSMs) are crucial components of the Earth System Models (ESMs) which are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. In this study, JULES is automatically differentiated using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed, to search for locally optimum parameter sets by calibrating against observations. We present an introduction to the adJULES system and demonstrate its ability to improve the model-data fit using eddy covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the 5 Plant Functional Types (PFTS) in JULES. The optimised PFT-specific parameters improve the performance of JULES over 90% of the FLUXNET sites used in the study. These reductions in error are shown and compared to reductions found due to site-specific optimisations. Finally, we show that calculation of the 2nd derivative of JULES allows us to produce posterior probability density functions of the parameters and how knowledge of parameter values is constrained by observations.
Rodrigue, Nicolas; Philippe, Hervé; Lartillot, Nicolas
2010-03-01
Modeling the interplay between mutation and selection at the molecular level is key to evolutionary studies. To this end, codon-based evolutionary models have been proposed as pertinent means of studying long-range evolutionary patterns and are widely used. However, these approaches have not yet consolidated results from amino acid level phylogenetic studies showing that selection acting on proteins displays strong site-specific effects, which translate into heterogeneous amino acid propensities across the columns of alignments; related codon-level studies have instead focused on either modeling a single selective context for all codon columns, or a separate selective context for each codon column, with the former strategy deemed too simplistic and the latter deemed overparameterized. Here, we integrate recent developments in nonparametric statistical approaches to propose a probabilistic model that accounts for the heterogeneity of amino acid fitness profiles across the coding positions of a gene. We apply the model to a dozen real protein-coding gene alignments and find it to produce biologically plausible inferences, for instance, as pertaining to site-specific amino acid constraints, as well as distributions of scaled selection coefficients. In their account of mutational features as well as the heterogeneous regimes of selection at the amino acid level, the modeling approaches studied here can form a backdrop for several extensions, accounting for other selective features, for variable population size, or for subtleties of mutational features, all with parameterizations couched within population-genetic theory. PMID:20176949
Bohr model and dimensional scaling analysis of atoms and molecules
NASA Astrophysics Data System (ADS)
Urtekin, Kerim
It is generally believed that the old quantum theory, as presented by Niels Bohr in 1913, fails when applied to many-electron systems, such as molecules, and nonhydrogenic atoms. It is the central theme of this dissertation to display with examples and applications the implementation of a simple and successful extension of Bohr's planetary model of the hydrogenic atom, which has recently been developed by an atomic and molecular theory group from Texas A&M University. This "extended" Bohr model, which can be derived from quantum mechanics using the well-known dimentional scaling technique is used to yield potential energy curves of H2 and several more complicated molecules, such as LiH, Li2, BeH, He2 and H3, with accuracies strikingly comparable to those obtained from the more lengthy and rigorous "ab initio" computations, and the added advantage that it provides a rather insightful and pictorial description of how electrons behave to form chemical bonds, a theme not central to "ab initio" quantum chemistry. Further investigation directed to CH, and the four-atom system H4 (with both linear and square configurations), via the interpolated Bohr model, and the constrained Bohr model (with an effective potential), respectively, is reported. The extended model is also used to calculate correlation energies. The model is readily applicable to the study of molecular species in the presence of strong magnetic fields, as is the case in the vicinities of white dwarfs and neutron stars. We find that magnetic field increases the binding energy and decreases the bond length. Finally, an elaborative review of doubly coupled quantum dots for a derivation of the electron exchange energy, a straightforward application of Heitler-London method of quantum molecular chemistry, concludes the dissertation. The highlights of the research are (1) a bridging together of the pre- and post quantum mechanical descriptions of the chemical bond (Bohr-Sommerfeld vs. Heisenberg-Schrodinger), and
Bohr model and dimensional scaling analysis of atoms and molecules
NASA Astrophysics Data System (ADS)
Svidzinsky, Anatoly; Chen, Goong; Chin, Siu; Kim, Moochan; Ma, Dongxia; Murawski, Robert; Sergeev, Alexei; Scully, Marlan; Herschbach, Dudley
It is generally believed that the old quantum theory, as presented by Niels Bohr in 1913, fails when applied to few electron systems, such as the H2 molecule. Here we review recent developments of the Bohr model that connect it with dimensional scaling procedures adapted from quantum chromodynamics. This approach treats electrons as point particles whose positions are determined by optimizing an algebraic energy function derived from the large-dimension limit of the Schrödinger equation. The calculations required are simple yet yield useful accuracy for molecular potential curves and bring out appealing heuristic aspects. We first examine the ground electronic states of H2, HeH, He2, LiH, BeH and Li2. Even a rudimentary Bohr model, employing interpolation between large and small internuclear distances, gives good agreement with potential curves obtained from conventional quantum mechanics. An amended Bohr version, augmented by constraints derived from Heitler-London or Hund-Mulliken results, dispenses with interpolation and gives substantial improvement for H2 and H3. The relation to D-scaling is emphasized. A key factor is the angular dependence of the Jacobian volume element, which competes with interelectron repulsion. Another version, incorporating principal quantum numbers in the D-scaling transformation, extends the Bohr model to excited S states of multielectron atoms. We also discuss kindred Bohr-style applications of D-scaling to the H atom subjected to superstrong magnetic fields or to atomic anions subjected to high frequency, superintense laser fields. In conclusion, we note correspondences to the prequantum bonding models of Lewis and Langmuir and to the later resonance theory of Pauling, and discuss prospects for joining D-scaling with other methods to extend its utility and scope.
Minimal non-Abelian model of atomic dark matter
NASA Astrophysics Data System (ADS)
Choquette, Jeremie; Cline, James M.
2015-12-01
A dark sector resembling the Standard Model, where the abundance of matter is explained by baryon and lepton asymmetries and stable constituents bind to form atoms, is a theoretically appealing possibility. We show that a minimal model with a hidden SU(2) gauge symmetry broken to U(1), with a Dirac fermion doublet, suffices to realize this scenario. Supplemented with a dark Higgs doublet that gets no vacuum expectation value, we readily achieve the dark matter asymmetry through leptogenesis. The model can simultaneously have three portals to the Standard Model, through the Higgs, non-Abelian kinetic mixing, and the heavy neutrino, with interesting phenomenology for direct and collider searches, as well as cosmologically relevant dark matter self-interactions. Exotic bound states consisting of two fermions and a doubly charged vector boson can exist in one phase of the theory.
Revised Parameters for the AMOEBA Polarizable Atomic Multipole Water Model.
Laury, Marie L; Wang, Lee-Ping; Pande, Vijay S; Head-Gordon, Teresa; Ponder, Jay W
2015-07-23
A set of improved parameters for the AMOEBA polarizable atomic multipole water model is developed. An automated procedure, ForceBalance, is used to adjust model parameters to enforce agreement with ab initio-derived results for water clusters and experimental data for a variety of liquid phase properties across a broad temperature range. The values reported here for the new AMOEBA14 water model represent a substantial improvement over the previous AMOEBA03 model. The AMOEBA14 model accurately predicts the temperature of maximum density and qualitatively matches the experimental density curve across temperatures from 249 to 373 K. Excellent agreement is observed for the AMOEBA14 model in comparison to experimental properties as a function of temperature, including the second virial coefficient, enthalpy of vaporization, isothermal compressibility, thermal expansion coefficient, and dielectric constant. The viscosity, self-diffusion constant, and surface tension are also well reproduced. In comparison to high-level ab initio results for clusters of 2-20 water molecules, the AMOEBA14 model yields results similar to AMOEBA03 and the direct polarization iAMOEBA models. With advances in computing power, calibration data, and optimization techniques, we recommend the use of the AMOEBA14 water model for future studies employing a polarizable water model. PMID:25683601
Explicit finite element modelling of the impaction of metal press-fit acetabular components.
Hothi, H S; Busfield, J J C; Shelton, J C
2011-03-01
Metal press-fit cups and shells are widely used in hip resurfacing and total hip replacement procedures. These acetabular components are inserted into a reamed acetabula cavity by either impacting their inner polar surface (shells) or outer rim (cups). Two-dimensional explicit dynamics axisymmetric finite element models were developed to simulate these impaction methods. Greater impact velocities were needed to insert the components when the interference fit was increased; a minimum velocity of 2 m/s was required to fully seat a component with a 2 mm interference between the bone and outer diameter. Changing the component material from cobalt-chromium to titanium alloy resulted in a reduction in the number of impacts on the pole to seat it from 14 to nine. Of greatest significance, it was found that locking a rigid cap to the cup or shell rim resulted in up to nine fewer impactions being necessary to seat it than impacting directly on the polar surface or using a cap free from the rim of the component, as is the case with many commercial resurfacing cup impaction devices currently used. This is important to impactor design and could make insertion easier and also reduce acetabula bone damage. PMID:21485331
Spectral Observations of Ellerman Bombs and Fitting with a Two-cloud Model
NASA Astrophysics Data System (ADS)
Hong, Jie; Ding, M. D.; Li, Ying; Fang, Cheng; Cao, Wenda
2014-09-01
We study the Hα and Ca II 8542 Å line spectra of four typical Ellerman bombs (EBs) in the active region NOAA 11765 on 2013 June 6, observed with the Fast Imaging Solar Spectrograph installed at the 1.6 m New Solar Telescope at Big Bear Solar Observatory. Considering that EBs may occur in a restricted region in the lower atmosphere, and that their spectral lines show particular features, we propose a two-cloud model to fit the observed line profiles. The lower cloud can account for the wing emission, and the upper cloud is mainly responsible for the absorption at line center. After choosing carefully the free parameters, we get satisfactory fitting results. As expected, the lower cloud shows an increase of the source function, corresponding to a temperature increase of 400-1000 K in EBs relative to the quiet Sun. This is consistent with previous results deduced from semi-empirical models and confirms that local heating occurs in the lower atmosphere during the appearance of EBs. We also find that the optical depths can increase to some extent in both the lower and upper clouds, which may result from either direct heating in the lower cloud, or illumination by an enhanced radiation on the upper cloud. The velocities derived from this method, however, are different from those obtained using the traditional bisector method, implying that one should be cautious when interpreting this parameter. The two-cloud model can thus be used as an efficient method to deduce the basic physical parameters of EBs.
Chatzopoulos, E.; Wheeler, J. Craig; Vinko, J.; Horvath, Z. L.; Nagy, A.
2013-08-10
We present fits of generalized semi-analytic supernova (SN) light curve (LC) models for a variety of power inputs including {sup 56}Ni and {sup 56}Co radioactive decay, magnetar spin-down, and forward and reverse shock heating due to supernova ejecta-circumstellar matter (CSM) interaction. We apply our models to the observed LCs of the H-rich superluminous supernovae (SLSN-II) SN 2006gy, SN 2006tf, SN 2008am, SN 2008es, CSS100217, the H-poor SLSN-I SN 2005ap, SCP06F6, SN 2007bi, SN 2010gx, and SN 2010kd, as well as to the interacting SN 2008iy and PTF 09uj. Our goal is to determine the dominant mechanism that powers the LCs of these extraordinary events and the physical conditions involved in each case. We also present a comparison of our semi-analytical results with recent results from numerical radiation hydrodynamics calculations in the particular case of SN 2006gy in order to explore the strengths and weaknesses of our models. We find that CS shock heating produced by ejecta-CSM interaction provides a better fit to the LCs of most of the events we examine. We discuss the possibility that collision of supernova ejecta with hydrogen-deficient CSM accounts for some of the hydrogen-deficient SLSNe (SLSN-I) and may be a plausible explanation for the explosion mechanism of SN 2007bi, the pair-instability supernova candidate. We characterize and discuss issues of parameter degeneracy.
Spectral observations of Ellerman bombs and fitting with a two-cloud model
Hong, Jie; Ding, M. D.; Li, Ying; Fang, Cheng; Cao, Wenda
2014-09-01
We study the Hα and Ca II 8542 Å line spectra of four typical Ellerman bombs (EBs) in the active region NOAA 11765 on 2013 June 6, observed with the Fast Imaging Solar Spectrograph installed at the 1.6 m New Solar Telescope at Big Bear Solar Observatory. Considering that EBs may occur in a restricted region in the lower atmosphere, and that their spectral lines show particular features, we propose a two-cloud model to fit the observed line profiles. The lower cloud can account for the wing emission, and the upper cloud is mainly responsible for the absorption at line center. After choosing carefully the free parameters, we get satisfactory fitting results. As expected, the lower cloud shows an increase of the source function, corresponding to a temperature increase of 400-1000 K in EBs relative to the quiet Sun. This is consistent with previous results deduced from semi-empirical models and confirms that local heating occurs in the lower atmosphere during the appearance of EBs. We also find that the optical depths can increase to some extent in both the lower and upper clouds, which may result from either direct heating in the lower cloud, or illumination by an enhanced radiation on the upper cloud. The velocities derived from this method, however, are different from those obtained using the traditional bisector method, implying that one should be cautious when interpreting this parameter. The two-cloud model can thus be used as an efficient method to deduce the basic physical parameters of EBs.
NASA Technical Reports Server (NTRS)
Kuhlman, J. M.
1979-01-01
The aerodynamic design of a wind-tunnel model of a wing representative of that of a subsonic jet transport aircraft, fitted with winglets, was performed using two recently developed optimal wing-design computer programs. Both potential flow codes use a vortex lattice representation of the near-field of the aerodynamic surfaces for determination of the required mean camber surfaces for minimum induced drag, and both codes use far-field induced drag minimization procedures to obtain the required spanloads. One code uses a discrete vortex wake model for this far-field drag computation, while the second uses a 2-D advanced panel wake model. Wing camber shapes for the two codes are very similar, but the resulting winglet camber shapes differ widely. Design techniques and considerations for these two wind-tunnel models are detailed, including a description of the necessary modifications of the design geometry to format it for use by a numerically controlled machine for the actual model construction.
Electrically detected magnetic resonance modeling and fitting: An equivalent circuit approach
Leite, D. M. G.; Batagin-Neto, A.; Nunes-Neto, O.; Gómez, J. A.; Graeff, C. F. O.
2014-01-21
The physics of electrically detected magnetic resonance (EDMR) quadrature spectra is investigated. An equivalent circuit model is proposed in order to retrieve crucial information in a variety of different situations. This model allows the discrimination and determination of spectroscopic parameters associated to distinct resonant spin lines responsible for the total signal. The model considers not just the electrical response of the sample but also features of the measuring circuit and their influence on the resulting spectral lines. As a consequence, from our model, it is possible to separate different regimes, which depend basically on the modulation frequency and the RC constant of the circuit. In what is called the high frequency regime, it is shown that the sign of the signal can be determined. Recent EDMR spectra from Alq{sub 3} based organic light emitting diodes, as well as from a-Si:H reported in the literature, were successfully fitted by the model. Accurate values of g-factor and linewidth of the resonant lines were obtained.
Statistics of dark matter substructure - I. Model and universal fitting functions
NASA Astrophysics Data System (ADS)
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.
Comparing Smoothing Techniques for Fitting the Nonlinear Effect of Covariate in Cox Models
Roshani, Daem; Ghaderi, Ebrahim
2016-01-01
Background and Objective: 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. Material and Methods: 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. Results: 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. Conclusion: 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. PMID:27041809
Using colloids to model atomic thin film growth
NASA Astrophysics Data System (ADS)
Ganapathy, Rajesh; Buckley, Mark; Cohen, Itai
2009-03-01
We epitaxially grow colloidal thin films by sedimenting micron sized colloidal particles on a microfabricated substrate. The attractive interaction between the colloids, induced by a depletant polymer, leads to the nucleation of islands that grow and coalesce with one another. We use confocal microscopy and particle tracking to study the dynamics of the colloidal particles as they diffuse, aggregate and rearrange configurations during deposition. The saturation island density is estimated as a function of the deposition rate and depletant concentration. We find that our results are in excellent agreement with those obtained from atomic deposition experiments suggesting that our system can be used to model various phenomena that occur in atomic thin film growth. Furthermore, we quantify the Ehrlich-Schwoebel step edge barrier by using holographic optical tweezers to create artificial islands and study the dynamics of colloidal monomers placed on the edge of these islands. Owing to the short-range of the attractive interaction in our system, the origin of the step edge barrier in colloids is strikingly different from atoms.
Assessment of Some Atomization Models Used in Spray Calculations
NASA Technical Reports Server (NTRS)
Raju, M. S.; Bulzin, Dan
2011-01-01
The paper presents the results from a validation study undertaken as a part of the NASA s fundamental aeronautics initiative on high altitude emissions in order to assess the accuracy of several atomization models used in both non-superheat and superheat spray calculations. As a part of this investigation we have undertaken the validation based on four different cases to investigate the spray characteristics of (1) a flashing jet generated by the sudden release of pressurized R134A from cylindrical nozzle, (2) a liquid jet atomizing in a subsonic cross flow, (3) a Parker-Hannifin pressure swirl atomizer, and (4) a single-element Lean Direct Injector (LDI) combustor experiment. These cases were chosen because of their importance in some aerospace applications. The validation is based on some 3D and axisymmetric calculations involving both reacting and non-reacting sprays. In general, the predicted results provide reasonable agreement for both mean droplet sizes (D32) and average droplet velocities but mostly underestimate the droplets sizes in the inner radial region of a cylindrical jet.
Fitting Data to Model: Structural Equation Modeling Diagnosis Using Two Scatter Plots
ERIC Educational Resources Information Center
Yuan, Ke-Hai; Hayashi, Kentaro
2010-01-01
This article introduces two simple scatter plots for model diagnosis in structural equation modeling. One plot contrasts a residual-based M-distance of the structural model with the M-distance for the factor score. It contains information on outliers, good leverage observations, bad leverage observations, and normal cases. The other plot contrasts…
Woody, Michael S; Lewis, John H; Greenberg, Michael J; Goldman, Yale E; Ostap, E Michael
2016-07-26
We present MEMLET (MATLAB-enabled maximum-likelihood estimation tool), a simple-to-use and powerful program for utilizing maximum-likelihood estimation (MLE) for parameter estimation from data produced by single-molecule and other biophysical experiments. The program is written in MATLAB and includes a graphical user interface, making it simple to integrate into the existing workflows of many users without requiring programming knowledge. We give a comparison of MLE and other fitting techniques (e.g., histograms and cumulative frequency distributions), showing how MLE often outperforms other fitting methods. The program includes a variety of features. 1) MEMLET fits probability density functions (PDFs) for many common distributions (exponential, multiexponential, Gaussian, etc.), as well as user-specified PDFs without the need for binning. 2) It can take into account experimental limits on the size of the shortest or longest detectable event (i.e., instrument "dead time") when fitting to PDFs. The proper modification of the PDFs occurs automatically in the program and greatly increases the accuracy of fitting the rates and relative amplitudes in multicomponent exponential fits. 3) MEMLET offers model testing (i.e., single-exponential versus double-exponential) using the log-likelihood ratio technique, which shows whether additional fitting parameters are statistically justifiable. 4) Global fitting can be used to fit data sets from multiple experiments to a common model. 5) Confidence intervals can be determined via bootstrapping utilizing parallel computation to increase performance. Easy-to-follow tutorials show how these features can be used. This program packages all of these techniques into a simple-to-use and well-documented interface to increase the accessibility of MLE fitting. PMID:27463130
A new fit-for-purpose model testing framework: Decision Crash Tests
NASA Astrophysics Data System (ADS)
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
NASA Technical Reports Server (NTRS)
Fu, Lee-Lueng; Vazquez, Jorge; Perigaud, Claire
1991-01-01
Free, equatorially trapped sinusoidal wave solutions to a linear model on an equatorial beta plane are used to fit the Geosat altimetric sea level observations in the tropical Pacific Ocean. The Kalman filter technique is used to estimate the wave amplitude and phase from the data. The estimation is performed at each time step by combining the model forecast with the observation in an optimal fashion utilizing the respective error covariances. The model error covariance is determined such that the performance of the model forecast is optimized. It is found that the dominant observed features can be described qualitatively by basin-scale Kelvin waves and the first meridional-mode Rossby waves. Quantitatively, however, only 23 percent of the signal variance can be accounted for by this simple model.
Modeling atomization processes in high-pressure vaporizing sprays
NASA Astrophysics Data System (ADS)
Reitz, Rolf D.
The theoretical basis and numerical implementation of KIVA, a multidimensional computer code for the simulation of atomization and vaporization processes in the injection of a liquid through a round hole into a compressed gas, are described. KIVA is based on the blob-injection model of Reitz and Diwakar (1987), taking into account the effects of liquid inertia, surface tension, and the aerodynamic forces on the jet, as well as drop collision and coalescence and the effect of drops on turbulence in the gas. The predictions of KIVA for different injection regimes are compared with published experimental data in extensive graphs, and good agreement is demonstrated.
Quantitative Modeling of Single Atom High Harmonic Generation
Gordon, Ariel; Kaertner, Franz X.
2005-11-25
It is shown by comparison with numerical solutions of the Schroedinger equation that the three step model (TSM) of high harmonic generation (HHG) can be improved to give a quantitatively reliable description of the process. Excellent agreement is demonstrated for the H atom and the H{sub 2}{sup +} molecular ion. It is shown that the standard TSM heavily distorts the HHG spectra, especially of H{sub 2}{sup +}, and an explanation is presented for this behavior. Key to the improvement is the use of the Ehrenfest theorem in the TSM.
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. PMID:23464238
Photothermal model fitting in the complex plane for thermal properties determination in solids
NASA Astrophysics Data System (ADS)
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.
SCAN-based hybrid and double-hybrid density functionals from models without fitted parameters.
Hui, Kerwin; Chai, Jeng-Da
2016-01-28
By incorporating the nonempirical strongly constrained and appropriately normed (SCAN) semilocal density functional [J. Sun, A. Ruzsinszky, and J. P. Perdew, Phys. Rev. Lett. 115, 036402 (2015)] in the underlying expression of four existing hybrid and double-hybrid models, we propose one hybrid (SCAN0) and three double-hybrid (SCAN0-DH, SCAN-QIDH, and SCAN0-2) density functionals, which are free from any fitted parameters. The SCAN-based double-hybrid functionals consistently outperform their parent SCAN semilocal functional for self-interaction problems and noncovalent interactions. In particular, SCAN0-2, which includes about 79% of Hartree-Fock exchange and 50% of second-order Møller-Plesset correlation, is shown to be reliably accurate for a very diverse range of applications, such as thermochemistry, kinetics, noncovalent interactions, and self-interaction problems. PMID:26827209
Low energy neutral atoms in the earth's magnetosphere: Modeling
Moore, K.R.; McComas, D.J.; Funsten, H.O.; Thomsen, M.F.
1992-01-01
Detection of low energy neutral atoms (LENAs) produced by the interaction of the Earth's geocorona with ambient space plasma has been proposed as a technique to obtain global information about the magnetosphere. Recent instrumentation advances reported previously and in these proceedings provide an opportunity for detecting LENAs in the energy range of <1 keV to {approximately}50 keV. In this paper, we present results from a numerical model which calculates line of sight LENA fluxes expected at a remote orbiting spacecraft for various magnetospheric plasma regimes. This model uses measured charge exchange cross sections, either of two neural hydrogen geocorona models, and various empirical modes of the ring current and plasma sheet to calculate the contribution to the integrated directional flux from each point along the line of sight of the instrument. We discuss implications for LENA imaging of the magnetosphere based on these simulations. 22 refs.
Numerical modeling for primary atomization of liquid jets
NASA Technical Reports Server (NTRS)
Przekwas, A. J.; Chuech, S. G.; Singhal, A. K.
1989-01-01
In the proposed numerical model for primary atomization, surface-wave dispersion equations are solved in conjunction with the jet-embedding technique of solving mean flow equations of a liquid jet. Linear and approximate nonlinear models have been considered. In each case, the dispersion equation is solved over the whole wavelength spectrum to predict drop sizes, frequency, and liquid-mass breakup rates without using any empirical constants. The present model has been applied to several low-speed and high-speed jets. For the high-speed case (the LOX/H2 coaxial injector of the Space Shuttle Main Engine Preburner), predicted drop sizes and liquid breakup rates are in good agreement with the results of the CICM code, which have been calibrated against measured data.
Molecular mechanisms of protein aggregation from global fitting of kinetic models.
Meisl, Georg; Kirkegaard, Julius B; Arosio, Paolo; Michaels, Thomas C T; Vendruscolo, Michele; Dobson, Christopher M; Linse, Sara; Knowles, Tuomas P J
2016-02-01
The elucidation of the molecular mechanisms by which soluble proteins convert into their amyloid forms is a fundamental prerequisite for understanding and controlling disorders that are linked to protein aggregation, such as Alzheimer's and Parkinson's diseases. However, because of the complexity associated with aggregation reaction networks, the analysis of kinetic data of protein aggregation to obtain the underlying mechanisms represents a complex task. Here we describe a framework, using quantitative kinetic assays and global fitting, to determine and to verify a molecular mechanism for aggregation reactions that is compatible with experimental kinetic data. We implement this approach in a web-based software, AmyloFit. Our procedure starts from the results of kinetic experiments that measure the concentration of aggregate mass as a function of time. We illustrate the approach with results from the aggregation of the β-amyloid (Aβ) peptides measured using thioflavin T, but the method is suitable for data from any similar kinetic experiment measuring the accumulation of aggregate mass as a function of time; the input data are in the form of a tab-separated text file. We also outline general experimental strategies and practical considerations for obtaining kinetic data of sufficient quality to draw detailed mechanistic conclusions, and the procedure starts with instructions for extensive data quality control. For the core part of the analysis, we provide an online platform (http://www.amylofit.ch.cam.ac.uk) that enables robust global analysis of kinetic data without the need for extensive programming or detailed mathematical knowledge. The software automates repetitive tasks and guides users through the key steps of kinetic analysis: determination of constraints to be placed on the aggregation mechanism based on the concentration dependence of the aggregation reaction, choosing from several fundamental models describing assembly into linear aggregates and
Fitting a groundwater contaminant transport model by L1 and L2 parameter estimators
NASA Astrophysics Data System (ADS)
Xiang, Yanyong; Thomson, N. R.; Sykes, J. F.
This paper presents a study on the use of linear and nonlinear L1-norm parameter estimators to fit an analytical groundwater contaminant transport model with nonuniform contaminant source distributions. The model solution is obtained as a superposition of an analytical solution developed by Cleary (Cleary, R.W., Analytical Models for Groundwater Pollution and Hydrology, 208 Long Island Groundwater Pollution Study, draft report, vol. 3, Princeton University, NJ, 1978). Comparisons with the commonly used linear and nonlinear L2-norm estimators are conducted. The posterior statistical inference theory by Nyquist (Nyquist, H., Commun. Statist.-Theor. Meth., 1983, 12, 2511-24) and Gonin and Money (Gonin, G. & Money, A.H., Commun. Statist.-Theor. Meth., 1985, 14, 827-40) is used to provide the posterior covariance matrix and the probability distribution for the unknown parameter vector. As the conclusion, it is suggested that in view of the nature of groundwater contaminant transport modeling, L1-norm estimators may be preferred as robust alternatives to L2-norm estimators in solving parameter estimation problems.
A simple algorithm for optimization and model fitting: AGA (asexual genetic algorithm)
NASA Astrophysics Data System (ADS)
Cantó, J.; Curiel, S.; Martínez-Gómez, E.
2009-07-01
Context: Mathematical optimization can be used as a computational tool to obtain the optimal solution to a given problem in a systematic and efficient way. For example, in twice-differentiable functions and problems with no constraints, the optimization consists of finding the points where the gradient of the objective function is zero and using the Hessian matrix to classify the type of each point. Sometimes, however it is impossible to compute these derivatives and other type of techniques must be employed such as the steepest descent/ascent method and more sophisticated methods such as those based on the evolutionary algorithms. Aims: We present a simple algorithm based on the idea of genetic algorithms (GA) for optimization. We refer to this algorithm as AGA (asexual genetic algorithm) and apply it to two kinds of problems: the maximization of a function where classical methods fail and model fitting in astronomy. For the latter case, we minimize the chi-square function to estimate the parameters in two examples: the orbits of exoplanets by taking a set of radial velocity data, and the spectral energy distribution (SED) observed towards a YSO (Young Stellar Object). Methods: The algorithm AGA may also be called genetic, although it differs from standard genetic algorithms in two main aspects: a) the initial population is not encoded; and b) the new generations are constructed by asexual reproduction. Results: Applying our algorithm in optimizing some complicated functions, we find the global maxima within a few iterations. For model fitting to the orbits of exoplanets and the SED of a YSO, we estimate the parameters and their associated errors.
The Kunming CalFit study: modeling dietary behavioral patterns using smartphone data.
Seto, Edmund; Hua, Jenna; Wu, Lemuel; Bestick, Aaron; Shia, Victor; Eom, Sue; Han, Jay; Wang, May; Li, Yan
2014-01-01
Human behavioral interventions aimed at improving health can benefit from objective wearable sensor data and mathematical models. Smartphone-based sensing is particularly practical for monitoring behavioral patterns because smartphones are fairly common, are carried by individuals throughout their daily lives, offer a variety of sensing modalities, and can facilitate various forms of user feedback for intervention studies. We describe our findings from a smartphone-based study, in which an Android-based application we developed called CalFit was used to collect information related to young adults' dietary behaviors. In addition to monitoring dietary patterns, we were interested in understanding contextual factors related to when and where an individual eats, as well as how their dietary intake relates to physical activity (which creates energy demand) and psychosocial stress. 12 participants were asked to use CalFit to record videos of their meals over two 1-week periods, which were translated into nutrient intake by trained dietitians. During this same period, triaxial accelerometry was used to assess each subject's energy expenditure, and GPS was used to record time-location patterns. Ecological momentary assessment was also used to prompt subjects to respond to questions on their phone about their psychological state. The GPS data were processed through a web service we developed called Foodscoremap that is based on the Google Places API to characterize food environments that subjects were exposed to, which may explain and influence dietary patterns. Furthermore, we describe a modeling framework that incorporates all of these information to dynamically infer behavioral patterns that may be used for future intervention studies. PMID:25571578
Whitford, Paul C; Noel, Jeffrey K; Gosavi, Shachi; Schug, Alexander; Sanbonmatsu, Kevin Y; Onuchic, José N
2009-05-01
Protein dynamics take place on many time and length scales. Coarse-grained structure-based (Go) models utilize the funneled energy landscape theory of protein folding to provide an understanding of both long time and long length scale dynamics. All-atom empirical forcefields with explicit solvent can elucidate our understanding of short time dynamics with high energetic and structural resolution. Thus, structure-based models with atomic details included can be used to bridge our understanding between these two approaches. We report on the robustness of folding mechanisms in one such all-atom model. Results for the B domain of Protein A, the SH3 domain of C-Src Kinase, and Chymotrypsin Inhibitor 2 are reported. The interplay between side chain packing and backbone folding is explored. We also compare this model to a C(alpha) structure-based model and an all-atom empirical forcefield. Key findings include: (1) backbone collapse is accompanied by partial side chain packing in a cooperative transition and residual side chain packing occurs gradually with decreasing temperature, (2) folding mechanisms are robust to variations of the energetic parameters, (3) protein folding free-energy barriers can be manipulated through parametric modifications, (4) the global folding mechanisms in a C(alpha) model and the all-atom model agree, although differences can be attributed to energetic heterogeneity in the all-atom model, and (5) proline residues have significant effects on folding mechanisms, independent of isomerization effects. Because this structure-based model has atomic resolution, this work lays the foundation for future studies to probe the contributions of specific energetic factors on protein folding and function. PMID:18837035
ERIC Educational Resources Information Center
Wang, Wen-Chung; Chen, Cheng-Te
2005-01-01
This study investigates item parameter recovery, standard error estimates, and fit statistics yielded by the WINSTEPS program under the Rasch model and the rating scale model through Monte Carlo simulations. The independent variables were item response model, test length, and sample size. WINSTEPS yielded practically unbiased estimates for the…
On the Model-Based Bootstrap with Missing Data: Obtaining a "P"-Value for a Test of Exact Fit
ERIC Educational Resources Information Center
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…
A Cautionary Note on Using G[squared](dif) to Assess Relative Model Fit in Categorical Data Analysis
ERIC Educational Resources Information Center
Maydeu-Olivares, Albert; Cai, Li
2006-01-01
The likelihood ratio test statistic G[squared](dif) is widely used for comparing the fit of nested models in categorical data analysis. In large samples, this statistic is distributed as a chi-square with degrees of freedom equal to the difference in degrees of freedom between the tested models, but only if the least restrictive model is correctly…
Guillera-Arroita, Gurutzeta; Lahoz-Monfort, José J; MacKenzie, Darryl I; Wintle, Brendan A; McCarthy, Michael A
2014-01-01
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. PMID:25075615
Heliospheric Propagation of Coronal Mass Ejections: Drag-based Model Fitting
NASA Astrophysics Data System (ADS)
Žic, T.; Vršnak, B.; Temmer, M.
2015-06-01
The so-called drag-based model (DBM) simulates analytically the propagation of coronal mass ejections (CMEs) in interplanetary space and allows the prediction of their arrival times and impact speeds at any point in the heliosphere (“target”). The DBM is based on the assumption that beyond a distance of about 20 solar radii from the Sun, the dominant force acting on CMEs is the “aerodynamic” drag force. In the standard form of DBM, the user provisionally chooses values for the model input parameters, by which the kinematics of the CME over the entire Sun-“target” distance range is defined. The choice of model input parameters is usually based on several previously undertaken statistical studies. In other words, the model is used by ad hoc implementation of statistics-based values of the input parameters, which are not necessarily appropriate for the CME under study. Furthermore, such a procedure lacks quantitative information on how well the simulation reproduces the coronagraphically observed kinematics of the CME, and thus does not provide an estimate of the reliability of the arrival prediction. In this paper we advance the DBM by adopting it in a form that employs the CME observations over a given distance range to evaluate the most suitable model input parameters for a given CME by means of least-squares fitting. Furthermore, the new version of the model automatically responds to any significant change of the conditions in the ambient medium (solar wind speed, density, CME-CME interactions, etc.) by changing the model input parameters according to changes in the CME kinematics. The advanced DBM is shaped in a form that can be readily employed in an operational system for real-time space-weather forecasting by promptly adjusting to a successively expanding observational data set, thus providing a successively improving prediction of the CME arrival.
Bevilacqua, Philip C; Cerrone-Szakal, Andrea L; Siegfried, Nathan A
2007-02-01
The RNA World hypothesis posits that life emerged from self-replicating RNA molecules. For any single biopolymer to be the basis for life, it must both store information and perform diverse functions. It is well known that RNA can store information. Advances in recent years have revealed that RNA can exhibit remarkable functional versatility as well. In an effort to judge the functional versatility of RNA and thereby the plausibility that RNA was at one point the basis for life, a statistical chemical approach is adopted. Essential biological functions are reduced to simple molecular models in a minimalist, biopolymer-independent fashion. The models dictate requisite states, populations of states, and physical and chemical changes occurring between the states. Next, equations are derived from the models, which lead to complex phenomenological constants such as observed and functional constants that are defined in terms of familiar elementary chemical descriptors: intrinsic rate constants, microscopic ligand equilibrium constants, secondary structure stability, and ligand concentration. Using these equations, simulations of functional behavior are performed. These functional models provide practical frameworks for fitting and organizing real data on functional RNAs such as ribozymes and riboswitches. At the same time, the models allow the suitability of RNA as a basis for life to be judged. We conclude that RNA, while inferior to extant proteins in most, but not all, functional respects, may be more versatile than proteins, performing a wider range of elementary biological functions at a tolerable level. Inspection of the functional models and various RNA structures uncovers several surprising ways in which the nucleobases can conspire to afford chemical catalysis and evolvability. These models support the plausibility that RNA, or a closely related informational biopolymer, could serve as the basis for a fairly simple form of life. PMID:17391549
A generalized model of atomic processes in dense plasmas
NASA Astrophysics Data System (ADS)
Chung, Hyun-Kyung; Chen, M.; Ciricosta, O.; Vinko, S.; Wark, J.; Lee, R. W.
2015-11-01
A generalized model of atomic processes in plasmas, FLYCHK, has been developed over a decade to provide experimentalists fast and simple but reasonable predictions of atomic properties of plasmas. For a given plasma condition, it provides charge state distributions and spectroscopic properties, which have been extensively used for experimental design and data analysis and currently available through NIST web site. In recent years, highly transient and non-equilibrium plasmas have been created with X-ray free electron lasers (XFEL). As high intensity x-rays interact with matter, the inner-shell electrons are ionized and Auger electrons and photo electrons are generated. With time, electrons participate in the ionization processes and collisional ionization by these electrons dominates photoionization as electron density increases. To study highly complex XFEL produced plasmas, SCFLY, an extended version of FLYCHK code has been used. The code accepts the time-dependent history of x-ray energy and intensity to compute population distribution and ionization distribution self-consistently with electron temperature and density assuming an instantaneous equilibration. The model and its applications to XFEL experiments will be presented as well as its limitations.
Modeling and fitting protein-protein complexes to predict change of binding energy
Dourado, Daniel F.A.R.; Flores, Samuel Coulbourn
2016-01-01
It is possible to accurately and economically predict change in protein-protein interaction energy upon mutation (ΔΔG), when a high-resolution structure of the complex is available. This is of growing usefulness for design of high-affinity or otherwise modified binding proteins for therapeutic, diagnostic, industrial, and basic science applications. Recently the field has begun to pursue ΔΔG prediction for homology modeled complexes, but so far this has worked mostly for cases of high sequence identity. If the interacting proteins have been crystallized in free (uncomplexed) form, in a majority of cases it is possible to find a structurally similar complex which can be used as the basis for template-based modeling. We describe how to use MMB to create such models, and then use them to predict ΔΔG, using a dataset consisting of free target structures, co-crystallized template complexes with sequence identify with respect to the targets as low as 44%, and experimental ΔΔG measurements. We obtain similar results by fitting to a low-resolution Cryo-EM density map. Results suggest that other structural constraints may lead to a similar outcome, making the method even more broadly applicable. PMID:27173910
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
Kondric, Miran; Trajkovski, Biljana; Strbad, Maja; Foretić, Nikola; Zenić, Natasa
2013-12-01
There is evident lack of studies which investigated morphological influence on physical fitness (PF) among preschool children. The aim of this study was to (1) calculate and interpret linear and nonlinear relationships between simple anthropometric predictors and PF criteria among preschoolers of both genders, and (2) to find critical values of the anthropometric predictors which should be recognized as the breakpoint of the negative influence on the PF. The sample of subjects consisted of 413 preschoolers aged 4 to 6 (mean age, 5.08 years; 176 girls and 237 boys), from Rijeka, Croatia. The anthropometric variables included body height (BH), body weight (BW), sum of triceps and subscapular skinfold (SUMSF), and calculated BMI (BMI = BW (kg)/BH (m)2). The PF was screened throughout testing of flexibility, repetitive strength, explosive strength, and agility. Linear and nonlinear (general quadratic model y = a + bx + cx2) regressions were calculated and interpreted simultaneously. BH and BW are far better predictors of the physical fitness status than BMI and SUMSF. In all calculated regressions excluding flexibility criterion, linear and nonlinear prediction of the PF throughout BH and BW reached statistical significance, indicating influence of the advancement in maturity status on PF variables Differences between linear and nonlinear regressions are smaller in males than in females. There are some indices that the age of 4 to 6 years is a critical period in the prevention of obesity, mostly because the extensively studied and proven negative influence of overweight and adiposity on PF tests is not yet evident. In some cases we have found evident regression breakpoints (approximately 25 kg in boys), which should be interpreted as critical values of the anthropometric measures for the studied sample of subjects. PMID:24611341
Model of spacecraft atomic oxygen and solar exposure microenvironments
NASA Technical Reports Server (NTRS)
Bourassa, R. J.; Pippin, H. G.
1993-01-01
Computer models of environmental conditions in Earth orbit are needed for the following reasons: (1) derivation of material performance parameters from orbital test data, (2) evaluation of spacecraft hardware designs, (3) prediction of material service life, and (4) scheduling spacecraft maintenance. To meet these needs, Boeing has developed programs for modeling atomic oxygen (AO) and solar radiation exposures. The model allows determination of AO and solar ultraviolet (UV) radiation exposures for spacecraft surfaces (1) in arbitrary orientations with respect to the direction of spacecraft motion, (2) overall ranges of solar conditions, and (3) for any mission duration. The models have been successfully applied to prediction of experiment environments on the Long Duration Exposure Facility (LDEF) and for analysis of selected hardware designs for deployment on other spacecraft. The work on these models has been reported at previous LDEF conferences. Since publication of these reports, a revision has been made to the AO calculation for LDEF, and further work has been done on the microenvironments model for solar exposure.
Four-component united-atom model of bitumen.
Hansen, J S; Lemarchand, Claire A; Nielsen, Erik; Dyre, Jeppe C; Schrøder, Thomas
2013-03-01
We propose a four-component united-atom molecular model of bitumen. The model includes realistic chemical constituents and introduces a coarse graining level that suppresses the highest frequency modes. Molecular dynamics simulations of the model are carried out using graphic-processor-units based software in time spans in order of microseconds, which enables the study of slow relaxation processes characterizing bitumen. This paper also presents results of the model dynamics as expressed through the mean-square displacement, the stress autocorrelation function, and rotational relaxation. The diffusivity of the individual molecules changes little as a function of temperature and reveals distinct dynamical time scales. Different time scales are also observed for the rotational relaxation. The stress autocorrelation function features a slow non-exponential decay for all temperatures studied. From the stress autocorrelation function, the shear viscosity and shear modulus are evaluated, showing a viscous response at frequencies below 100 MHz. The model predictions of viscosity and diffusivities are compared to experimental data, giving reasonable agreement. The model shows that the asphaltene, resin, and resinous oil tend to form nano-aggregates. The characteristic dynamical relaxation time of these aggregates is larger than that of the homogeneously distributed parts of the system, leading to strong dynamical heterogeneity. PMID:23485314
Four-component united-atom model of bitumen
NASA Astrophysics Data System (ADS)
Hansen, J. S.; Lemarchand, Claire A.; Nielsen, Erik; Dyre, Jeppe C.; Schrøder, Thomas
2013-03-01
We propose a four-component united-atom molecular model of bitumen. The model includes realistic chemical constituents and introduces a coarse graining level that suppresses the highest frequency modes. Molecular dynamics simulations of the model are carried out using graphic-processor-units based software in time spans in order of microseconds, which enables the study of slow relaxation processes characterizing bitumen. This paper also presents results of the model dynamics as expressed through the mean-square displacement, the stress autocorrelation function, and rotational relaxation. The diffusivity of the individual molecules changes little as a function of temperature and reveals distinct dynamical time scales. Different time scales are also observed for the rotational relaxation. The stress autocorrelation function features a slow non-exponential decay for all temperatures studied. From the stress autocorrelation function, the shear viscosity and shear modulus are evaluated, showing a viscous response at frequencies below 100 MHz. The model predictions of viscosity and diffusivities are compared to experimental data, giving reasonable agreement. The model shows that the asphaltene, resin, and resinous oil tend to form nano-aggregates. The characteristic dynamical relaxation time of these aggregates is larger than that of the homogeneously distributed parts of the system, leading to strong dynamical heterogeneity.
Evapotranspiration measurement and modeling without fitting parameters in high-altitude grasslands
NASA Astrophysics Data System (ADS)
Ferraris, Stefano; Previati, Maurizio; Canone, Davide; Dematteis, Niccolò; Boetti, Marco; Balocco, Jacopo; Bechis, Stefano
2016-04-01
Mountain grasslands are important, also because one sixth of the world population lives inside watershed dominated by snowmelt. Also, grasslands provide food to both domestic and selvatic animals. The global warming will probably accelerate the hydrological cycle and increase the drought risk. The combination of measurements, modeling and remote sensing can furnish knowledge in such faraway areas (e.g.: Brocca et al., 2013). A better knowledge of water balance can also allow to optimize the irrigation (e.g.: Canone et al., 2015). This work is meant to build a model of water balance in mountain grasslands, ranging between 1500 and 2300 meters asl. The main input is the Digital Terrain Model, which is more reliable in grasslands than both in the woods and in the built environment. It drives the spatial variability of shortwave solar radiation. The other atmospheric forcings are more problematic to estimate, namely air temperature, wind and longwave radiation. Ad hoc routines have been written, in order to interpolate in space the meteorological hourly time variability. The soil hydraulic properties are less variable than in the plains, but the soil depth estimation is still an open issue. The soil vertical variability has been modeled taking into account the main processes: soil evaporation, root uptake, and fractured bedrock percolation. The time variability latent heat flux and soil moisture results have been compared with the data measured in an eddy covariance station. The results are very good, given the fact that the model has no fitting parameters. The space variability results have been compared with the results of a model based on Landsat 7 and 8 data, applied over an area of about 200 square kilometers. The spatial correlation is quite in agreement between the two models. Brocca et al. (2013). "Soil moisture estimation in alpine catchments through modelling and satellite observations". Vadose Zone Journal, 12(3), 10 pp. Canone et al. (2015). "Field
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. PMID:27230609
Monte Carlo modeling of atomic oxygen attack of polymers with protective coatings on LDEF
NASA Technical Reports Server (NTRS)
Banks, Bruce A.; Degroh, Kim K.; Auer, Bruce M.; Gebauer, Linda; Edwards, Jonathan L.
1993-01-01
Characterization of the behavior of atomic oxygen interaction with materials on the Long Duration Exposure Facility (LDEF) assists in understanding of the mechanisms involved. Thus the reliability of predicting in-space durability of materials based on ground laboratory testing should be improved. A computational model which simulates atomic oxygen interaction with protected polymers was developed using Monte Carlo techniques. Through the use of an assumed mechanistic behavior of atomic oxygen interaction based on in-space atomic oxygen erosion of unprotected polymers and ground laboratory atomic oxygen interaction with protected polymers, prediction of atomic oxygen interaction with protected polymers on LDEF was accomplished. However, the results of these predictions are not consistent with the observed LDEF results at defect sites in protected polymers. Improved agreement between observed LDEF results and predicted Monte Carlo modeling can be achieved by modifying of the atomic oxygen interactive assumptions used in the model. LDEF atomic oxygen undercutting results, modeling assumptions, and implications are presented.
Relativistic precessing jets in quasars and radio galaxies - Models to fit high resolution data
NASA Technical Reports Server (NTRS)
Gower, A. C.; Gregory, P. C.; Unruh, W. G.; Hutchings, J. B.
1982-01-01
The formulation of generalized models tracing the geometry and intensity of the synchrotron emission from precessing, twin, relativistic jets as projected on the plane of the sky is presented. It is shown that neither the shape of the image nor its relative intensities are altered by including the effects of a cosmological redshift and a relative velocity between the source and observer. The models are fitted to the available data for several quasars and radio galaxies and demonstrate the plausibility of the phenomenon. Probable selection effects are considered and diagnostics given for recognizing objects showing this behavior. In the radio galaxies considered, velocities up to about 0.2c and precession periods of 1,000,000 yr are deduced. In the QSOs investigated, velocities of 0.7c and greater are found and periods of order 10,000 yr. In some cases precession cone angles increase with time. Consequences in terms of lifetimes of QSO behavior and binary supermassive objects are discussed.
Model fitting using RANSAC for surgical tool localization in 3-D ultrasound images.
Uhercík, Marián; Kybic, Jan; Liebgott, Hervé; Cachard, Christian
2010-08-01
Ultrasound guidance is used for many surgical interventions such as biopsy and electrode insertion. We present a method to localize a thin surgical tool such as a biopsy needle or a microelectrode in a 3-D ultrasound image. The proposed method starts with thresholding and model fitting using random sample consensus for robust localization of the axis. Subsequent local optimization refines its position. Two different tool image models are presented: one is simple and fast and the second uses learned a priori information about the tool's voxel intensities and the background. Finally, the tip of the tool is localized by finding an intensity drop along the axis. The simulation study shows that our algorithm can localize the tool at nearly real-time speed, even using a MATLAB implementation, with accuracy better than 1 mm. In an experimental comparison with several alternative localization methods, our method appears to be the fastest and the most robust one. We also show the results on real 3-D ultrasound data from a PVA cryogel phantom, turkey breast, and breast biopsy. PMID:20483680
Model Order Selection for Short Data: An Exponential Fitting Test (EFT)
NASA Astrophysics Data System (ADS)
Quinlan, Angela; Barbot, Jean-Pierre; Larzabal, Pascal; Haardt, Martin
2006-12-01
High-resolution methods for estimating signal processing parameters such as bearing angles in array processing or frequencies in spectral analysis may be hampered by the model order if poorly selected. As classical model order selection methods fail when the number of snapshots available is small, this paper proposes a method for noncoherent sources, which continues to work under such conditions, while maintaining low computational complexity. For white Gaussian noise and short data we show that the profile of the ordered noise eigenvalues is seen to approximately fit an exponential law. This fact is used to provide a recursive algorithm which detects a mismatch between the observed eigenvalue profile and the theoretical noise-only eigenvalue profile, as such a mismatch indicates the presence of a source. Moreover this proposed method allows the probability of false alarm to be controlled and predefined, which is a crucial point for systems such as RADARs. Results of simulations are provided in order to show the capabilities of the algorithm.
Kügler, Philipp
2012-01-01
The inference of reaction rate parameters in biochemical network models from time series concentration data is a central task in computational systems biology. Under the assumption of well mixed conditions the network dynamics are typically described by the chemical master equation, the Fokker Planck equation, the linear noise approximation or the macroscopic rate equation. The inverse problem of estimating the parameters of the underlying network model can be approached in deterministic and stochastic ways, and available methods often compare individual or mean concentration traces obtained from experiments with theoretical model predictions when maximizing likelihoods, minimizing regularized least squares functionals, approximating posterior distributions or sequentially processing the data. In this article we assume that the biological reaction network can be observed at least partially and repeatedly over time such that sample moments of species molecule numbers for various time points can be calculated from the data. Based on the chemical master equation we furthermore derive closed systems of parameter dependent nonlinear ordinary differential equations that predict the time evolution of the statistical moments. For inferring the reaction rate parameters we suggest to not only compare the sample mean with the theoretical mean prediction but also to take the residual of higher order moments explicitly into account. Cost functions that involve residuals of higher order moments may form landscapes in the parameter space that have more pronounced curvatures at the minimizer and hence may weaken or even overcome parameter sloppiness and uncertainty. As a consequence both deterministic and stochastic parameter inference algorithms may be improved with respect to accuracy and efficiency. We demonstrate the potential of moment fitting for parameter inference by means of illustrative stochastic biological models from the literature and address topics for future
Mustard, Thomas J. L.; Wender, Paul A.; Cheong, Paul Ha-Yeon
2015-01-01
The origins of differential catalytic reactivities of four Rh(I) catalysts and their derivatives in the (5 + 2) cycloaddition reaction were elucidated using density functional theory. Computed free energy spans are in excellent agreement with known experimental rates. For every catalyst, the substrate geometries in the transition state remained constant (<0.1 Å RMSD for atoms involved in bond-making and -breaking processes). Catalytic efficiency is shown to be a function of how well the catalyst accommodates the substrate transition state geometry and electronics. This shows that the induced fit model for explaining biological catalysis may be relevant to transition metal catalysis. This could serve as a general model for understanding the origins of efficiencies of catalytic reactions. PMID:26146588
Schlemm, Eckhard
2015-09-01
The Bak-Sneppen model is an abstract representation of a biological system that evolves according to the Darwinian principles of random mutation and selection. The species in the system are characterized by a numerical fitness value between zero and one. We show that in the case of five species the steady-state fitness distribution can be obtained as a solution to a linear differential equation of order five with hypergeometric coefficients. Similar representations for the asymptotic fitness distribution in larger systems may help pave the way towards a resolution of the question of whether or not, in the limit of infinitely many species, the fitness is asymptotically uniformly distributed on the interval [fc, 1] with fc ≳ 2/3. PMID:26144945
ERIC Educational Resources Information Center
Fan, Xitao; And Others
A Monte Carlo study was conducted to assess the effects of some potential confounding factors on structural equation modeling (SEM) fit indices and parameter estimates for both true and misspecified models. The factors investigated were data nonnormality, SEM estimation method, and sample size. Based on the fully crossed and balanced 3x3x4x2…
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; Estépar, Raúl San José
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 proposed
Basch, Corey H; Hillyer, Grace Clarke; Ethan, Danna; Berdnik, Alyssa; Basch, Charles E
2015-07-01
Tanned skin has been associated with perceptions of fitness and social desirability. Portrayal of models in magazines may reflect and perpetuate these perceptions. Limited research has investigated tanning shade gradations of models in men's versus women's fitness and muscle enthusiast magazines. Such findings are relevant in light of increased incidence and prevalence of melanoma in the United States. This study evaluated and compared tanning shade gradations of adult Caucasian male and female model images in mainstream fitness and muscle enthusiast magazines. Sixty-nine U.S. magazine issues (spring and summer, 2013) were utilized. Two independent reviewers rated tanning shade gradations of adult Caucasian male and female model images on magazines' covers, advertisements, and feature articles. Shade gradations were assessed using stock photographs of Caucasian models with varying levels of tanned skin on an 8-shade scale. A total of 4,683 images were evaluated. Darkest tanning shades were found among males in muscle enthusiast magazines and lightest among females in women's mainstream fitness magazines. By gender, male model images were 54% more likely to portray a darker tanning shade. In this study, images in men's (vs. women's) fitness and muscle enthusiast magazines portrayed Caucasian models with darker skin shades. Despite these magazines' fitness-related messages, pro-tanning images may promote attitudes and behaviors associated with higher skin cancer risk. To date, this is the first study to explore tanning shades in men's magazines of these genres. Further research is necessary to identify effects of exposure to these images among male readers. PMID:25038234
Independent-particle models for light negative atomic ions
NASA Technical Reports Server (NTRS)
Ganas, P. S.; Talman, J. D.; Green, A. E. S.
1980-01-01
For the purposes of astrophysical, aeronomical, and laboratory application, a precise independent-particle model for electrons in negative atomic ions of the second and third period is discussed. The optimum-potential model (OPM) of Talman et al. (1979) is first used to generate numerical potentials for eight of these ions. Results for total energies and electron affinities are found to be very close to Hartree-Fock solutions. However, the OPM and HF electron affinities both depart significantly from experimental affinities. For this reason, two analytic potentials are developed whose inner energy levels are very close to the OPM and HF levels but whose last electron eigenvalues are adjusted precisely with the magnitudes of experimental affinities. These models are: (1) a four-parameter analytic characterization of the OPM potential and (2) a two-parameter potential model of the Green, Sellin, Zachor type. The system O(-) or e-O, which is important in upper atmospheric physics is examined in some detail.
Hybrid Thermal/Non-Thermal Model Fits to the X-Ray Spectra of GRS 1915+105
NASA Astrophysics Data System (ADS)
Maccarone, T. J.; Coppi, P. S.; Taam, R.
2000-10-01
We present the results of spectral fits to RXTE observations of GRS 1915+105 using the EQPAIR model of Coppi et al. (1999) to assess the effects of thermal and non-thermal Comptonization, as well as reflection. We note that such self-consistent models result in larger inner disk radii and lower disk temperatures than the previous fits using multicolor blackbody and power law models, thus solving the problem of inner disk radii at < ~ 1 Rsch. We also note that the major difference between the ``high" and ``low" states is the presence of a strong nonthermal spectral component in the low state and that the Compton y parameter remains fairly constant within the high state despite large variations in the optical depth and temperature. We discuss other observed correlations between the different fit parameters and consider possible implications for disk-jet interactions.
SLIMP: Strong laser interaction model package for atoms and molecules
NASA Astrophysics Data System (ADS)
Zhang, Bin; Zhao, Zengxiu
2015-07-01
We present the SLIMP package, which provides an efficient way for the calculation of strong-field ionization rate and high-order harmonic spectra based on the single active electron approximation. The initial states are taken as single-particle orbitals directly from output files of the general purpose quantum chemistry programs GAMESS, Firefly and Gaussian. For ionization, the molecular Ammosov-Delone-Krainov theory, and both the length gauge and velocity gauge Keldysh-Faisal-Reiss theories are implemented, while the Lewenstein model is used for harmonic spectra. Furthermore, it is also efficient for the evaluation of orbital coordinates wavefunction, momentum wavefunction, orbital dipole moment and calculation of orbital integrations. This package can be applied to quite large basis sets and complex molecules with many atoms, and is implemented to allow easy extensions for additional capabilities.
Simulating and Modeling Transport Through Atomically Thin Membranes
NASA Astrophysics Data System (ADS)
Ostrowski, Joseph; Eaves, Joel
2014-03-01
The world is running out of clean portable water. The efficacy of water desalination technologies using porous materials is a balance between membrane selectivity and solute throughput. These properties are just starting to be understood on the nanoscale, but in the limit of atomically thin membranes it is unclear whether one can apply typical continuous time random walk models. Depending on the size of the pore and thickness of the membrane, mass transport can range from single stochastic passage events to continuous flow describable by the usual hydrodynamic equations. We present a study of mass transport through membranes of various pore geometries using reverse nonequilibrium simulations, and analyze transport rates using stochastic master equations.
Atomic scale modelling of hexagonal structured metallic fission product alloys
Middleburgh, S. C.; King, D. M.; Lumpkin, G. R.
2015-01-01
Noble metal particles in the Mo-Pd-Rh-Ru-Tc system have been simulated on the atomic scale using density functional theory techniques for the first time. The composition and behaviour of the epsilon phases are consistent with high-entropy alloys (or multi-principal component alloys)—making the epsilon phase the only hexagonally close packed high-entropy alloy currently described. Configurational entropy effects were considered to predict the stability of the alloys with increasing temperatures. The variation of Mo content was modelled to understand the change in alloy structure and behaviour with fuel burnup (Mo molar content decreases in these alloys as burnup increases). The predicted structures compare extremely well with experimentally ascertained values. Vacancy formation energies and the behaviour of extrinsic defects (including iodine and xenon) in the epsilon phase were also investigated to further understand the impact that the metallic precipitates have on fuel performance. PMID:26064629
Atomic-level models of the bacterial carboxysome shell
Tanaka, S.; Kerfeld, C.A.; Sawaya, M.R.; Cai, F.; Heinhorst, S.; Cannon, G.C.; Yeates, T.O.
2008-06-03
The carboxysome is a bacterial microcompartment that functions as a simple organelle by sequestering enzymes involved in carbon fixation. The carboxysome shell is roughly 800 to 1400 angstroms in diameter and is assembled from several thousand protein subunits. Previous studies have revealed the three-dimensional structures of hexameric carboxysome shell proteins, which self-assemble into molecular layers that most likely constitute the facets of the polyhedral shell. Here, we report the three-dimensional structures of two proteins of previously unknown function, CcmL and OrfA (or CsoS4A), from the two known classes of carboxysomes, at resolutions of 2.4 and 2.15 angstroms. Both proteins assemble to form pentameric structures whose size and shape are compatible with formation of vertices in an icosahedral shell. Combining these pentamers with the hexamers previously elucidated gives two plausible, preliminary atomic models for the carboxysome shell.
Li, Z.; Eremin, V.; Harkonen, J.; Luukka, P.; Tuominen, E.; Tuovinen, E.; Verbitskaya, E.
2009-10-27
Modeling and simulations have been performed for the charge injected diodes (CID) for the application in SLHC. MIP-induced current and charges have been calculated for segmented detectors with various radiation fluences, up to the highest SLHC fluence of 1 x 10{sup 16} n{sub eq}/cm{sup 2}. Although the main advantage of CID detectors is their virtual full depletion at any radiation fluence at a modest bias voltage (<600 V), the simulation of CID and fitting to the existing data have shown that the CID operation mode also reduces the free carrier trapping, resulting in a much higher charge collection at the SLHC fluence than that in a standard Si detector. The reduction in free carrier trapping by almost one order of magnitude is due to the fact that the CID mode also pre-fills the traps, making them neutral and not active in trapping. It has been found that, electron traps can be pre-filled by injection of electrons from the n{sup +} contact, and hole traps can be pre-filled by injection of holes from the p{sup +} contact. The CID mode of detector operation can be achieved by a modestly low temperature of around -40 C, achievable by the proposed CO{sub 2} cooling for detector upgrades in SLHC. High charge collection comparable to the 3D electrode Si detectors makes the CID Si detector a valuable alternative for SLHC detectors for its much easier fabrication process.
Naegelen, Isabelle; Beaume, Nicolas; Plançon, Sébastien; Schenten, Véronique; Tschirhart, Eric J.; Bréchard, Sabrina
2015-01-01
Neutrophils participate in the maintenance of host integrity by releasing various cytotoxic proteins during degranulation. Due to recent advances, a major role has been attributed to neutrophil-derived cytokine secretion in the initiation, exacerbation, and resolution of inflammatory responses. Because the release of neutrophil-derived products orchestrates the action of other immune cells at the infection site and, thus, can contribute to the development of chronic inflammatory diseases, we aimed to investigate in more detail the spatiotemporal regulation of neutrophil-mediated release mechanisms of proinflammatory mediators. Purified human neutrophils were stimulated for different time points with lipopolysaccharide. Cells and supernatants were analyzed by flow cytometry techniques and used to establish secretion profiles of granules and cytokines. To analyze the link between cytokine release and degranulation time series, we propose an original strategy based on linear fitting, which may be used as a guideline, to (i) define the relationship of granule proteins and cytokines secreted to the inflammatory site and (ii) investigate the spatial regulation of neutrophil cytokine release. The model approach presented here aims to predict the correlation between neutrophil-derived cytokine secretion and degranulation and may easily be extrapolated to investigate the relationship between other types of time series of functional processes. PMID:26579547
Baek, Sun-Geun; Kim, Hye-Sook
2009-01-01
The main purpose of the study was to investigate empirically the relationship between classroom teacher's judgment and the item and person fit-statistics of the partial credit model. In this study, classroom teacher's judgments were made intuitively checking each item's consistency with the general response pattern and each student's need for additional treatment or advice. The item and person fit statistics of the partial credit model were estimated using the WINSTEPS program (Linacre, 2003). The subjects of this study were 321 sixth grade students in 9 classrooms within 3 elementary schools in Seoul, Korea. For this research, a performance assessment test for 6th grade mathematics was developed. It consisted of 20 polytomous response items and its total scores ranged between 0 and 50. In addition, the 9 classroom teachers made their judgments for each item of the test and for each student in their own classroom. They judged intuitively using 4 categories; (1) well fit, (2) fit, (3) misfit, and (4) badly misfit for each item as well as each student. Their judgments were scored from 1 to 4 for each item as well as each student. There are two significant findings in this study. First, there is a statistically significant relationship between the classroom teacher's judgment and item fit statistic for each item (The median correlation coefficient between the teacher's judgment and the item outfit ZSTD is 0.61). Second, there is a statistically significant relationship between the teacher's judgment and the person fit statistic for each student (The median correlation coefficient between the teacher's judgment and the person outfit ZSTD is 0.52). In conclusion, the item and person fit statistics of the partial credit model correspond with the teacher's judgments for each test item and each student. PMID:19299887
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. PMID:19237328
Jones, Simon R.
2010-01-01
The causes of auditory verbal hallucinations (AVHs) are still unclear. The evidence for 2 prominent cognitive models of AVHs, one based on inner speech, the other on intrusions from memory, is briefly reviewed. The fit of these models, as well as neurological models, to the phenomenology of AVHs is then critically examined. It is argued that only a minority of AVHs, such as those with content clearly relating to verbalizations experienced surrounding previous trauma, are consistent with cognitive AVHs-as-memories models. Similarly, it is argued that current neurological models are only phenomenologically consistent with a limited subset of AVHs. In contrast, the phenomenology of the majority of AVHs, which involve voices attempting to regulate the ongoing actions of the voice hearer, are argued to be more consistent with inner speech–based models. It is concluded that subcategorizations of AVHs may be necessary, with each underpinned by different neurocognitive mechanisms. The need to study what is termed the dynamic developmental progression of AVHs is also highlighted. Future empirical research is suggested in this area. PMID:18820262
The fitting of general force-of-infection models to wildlife disease prevalence data
Heisey, D.M.; Joly, D.O.; Messier, F.
2006-01-01
Researchers and wildlife managers increasingly find themselves in situations where they must deal with infectious wildlife diseases such as chronic wasting disease, brucellosis, tuberculosis, and West Nile virus. Managers are often charged with designing and implementing control strategies, and researchers often seek to determine factors that influence and control the disease process. All of these activities require the ability to measure some indication of a disease's foothold in a population and evaluate factors affecting that foothold. The most common type of data available to managers and researchers is apparent prevalence data. Apparent disease prevalence, the proportion of animals in a sample that are positive for the disease, might seem like a natural measure of disease's foothold, but several properties, in particular, its dependency on age structure and the biasing effects of disease-associated mortality, make it less than ideal. In quantitative epidemiology, the a??force of infection,a?? or infection hazard, is generally the preferred parameter for measuring a disease's foothold, and it can be viewed as the most appropriate way to a??adjusta?? apparent prevalence for age structure. The typical ecology curriculum includes little exposure to quantitative epidemiological concepts such as cumulative incidence, apparent prevalence, and the force of infection. The goal of this paper is to present these basic epidemiological concepts and resulting models in an ecological context and to illustrate how they can be applied to understand and address basic epidemiological questions. We demonstrate a practical approach to solving the heretofore intractable problem of fitting general force-of-infection models to wildlife prevalence data using a generalized regression approach. We apply the procedures to Mycobacterium bovis (bovine tuberculosis) prevalence in bison (Bison bison) in Wood Buffalo National Park, Canada, and demonstrate strong age dependency in the force of
The fitting of general force-of-infection models to wildlife disease prevalence data.
Heisey, Dennis M; Joly, Damien O; Messier, François
2006-09-01
Researchers and wildlife managers increasingly find themselves in situations where they must deal with infectious wildlife diseases such as chronic wasting disease, brucellosis, tuberculosis, and West Nile virus. Managers are often charged with designing and implementing control strategies, and researchers often seek to determine factors that influence and control the disease process. All of these activities require the ability to measure some indication of a disease's foothold in a population and evaluate factors affecting that foothold. The most common type of data available to managers and researchers is apparent prevalence data. Apparent disease prevalence, the proportion of animals in a sample that are positive for the disease, might seem like a natural measure of disease's foothold, but several properties, in particular, its dependency on age structure and the biasing effects of disease-associated mortality, make it less than ideal. In quantitative epidemiology, the "force of infection," or infection hazard, is generally the preferred parameter for measuring a disease's foothold, and it can be viewed as the most appropriate way to "adjust" apparent prevalence for age structure. The typical ecology curriculum includes little exposure to quantitative epidemiological concepts such as cumulative incidence, apparent prevalence, and the force of infection. The goal of this paper is to present these basic epidemiological concepts and resulting models in an ecological context and to illustrate how they can be applied to understand and address basic epidemiological questions. We demonstrate a practical approach to solving the heretofore intractable problem of fitting general force-of-infection models to wildlife prevalence data using a generalized regression approach. We apply the procedures to Mycobacterium bovis (bovine tuberculosis) prevalence in bison (Bison bison) in Wood Buffalo National Park, Canada, and demonstrate strong age dependency in the force of
Atomic-scale simulations of atomic and molecular mobility in models of interstellar ice
NASA Astrophysics Data System (ADS)
Andersson, Stefan
The mobility of atoms and molecular radicals at ice-covered dust particles controls the surprisingly rich chemistry of circumstellar and interstellar environments, where a large number of different organic molecules have been observed. Both thermal and non-thermal processes, for instance caused by UV radiation, have been inferred to play important roles in this chemistry. A growing number of experimental studies support previously suggested mechanisms and add to the understanding of possible astrochemical processes. Simulations, of both experiments and astrophysical environments, aid in interpreting experiments and suggesting important mechanisms. Still, the exact mechanisms behind the mobility of species in interstellar ice are far from fully understood. We have performed calculations at the molecular level on the mobility of H atoms and OH radicals at water ice surfaces of varying morphology. Calculations of binding energies and diffusion barriers of H atoms at crystalline and amorphous ice surfaces show that the experimentally observed slower diffusion at amorphous ice is due to considerably stronger binding energies and higher diffusion barriers than at crystalline ice. These results are in excellent agreement with recent experiments. It was also found that quantum tunneling is important for H atom mobility below 10 K. The binding energies and diffusion barriers of OH radicals at crystalline ice have been studied using the ONIOM(QM:AMOEBA) approach. Results indicate that OH diffusion over crystalline ice, contrary to the case of H atoms, might be slower at crystalline ice than at amorphous ice, due to a higher surface density of stronger binding sites at crystalline ice. We have also performed molecular dynamics simulations of the photoexcitation of vapor-deposited water at a range of surface temperatures. These results support that the experimentally observed desorption of H atoms following UV excitation is best explained by release of H atoms from
Development of a Stellar Model-Fitting Pipeline for Asteroseismic Data from the TESS Mission
NASA Astrophysics Data System (ADS)
Metcalfe, Travis
The launch of NASA's Kepler space telescope in 2009 revolutionized the quality and quantity of observational data available for asteroseismic analysis. Prior to the Kepler mission, solar-like oscillations were extremely difficult to observe, and data only existed for a handful of the brightest stars in the sky. With the necessity of studying one star at a time, the traditional approach to extracting the physical properties of the star from the observations was an uncomfortably subjective process. A variety of experts could use similar tools but come up with significantly different answers. Not only did this subjectivity have the potential to undermine the credibility of the technique, it also hindered the compilation of a uniform sample that could be used to draw broader physical conclusions from the ensemble of results. During a previous award from NASA, we addressed these issues by developing an automated and objective stellar model-fitting pipeline for Kepler data, and making it available through the Asteroseismic Modeling Portal (AMP). This community modeling tool has allowed us to derive reliable asteroseismic radii, masses and ages for large samples of stars (Metcalfe et al. 2014), but the most recent observations are so precise that we are now limited by systematic uncertainties associated with our stellar models. With a huge archive of Kepler data available for model validation, and the next planet-hunting satellite already approved for an expected launch in 2017, now is the time to incorporate what we have learned into the next generation of AMP. We propose to improve the reliability of our estimates of stellar properties over the next 4 years by collaborating with two open-source development projects that will augment and ultimately replace the stellar evolution and pulsation models that we now use in AMP. Our current treatment of the oscillations does not include the effects of radiative or convective heat-exchange, nor does it account for the influence
Tyteca, Eva; Desmet, Gert
2015-07-17
Some valuable insights have been obtained in the inherent fitting problems when trying to predict the retention time of complex, multi-modal retention modes such as encountered in HILIC and SFC. In this study, we used mathematical models with known input parameters to generate different sets of numerical test curves representative for systems exhibiting a complex, non-LSS dual retention behavior. Subsequently, we tried to fit these data sets using some popular (non-linear) literature models. Even in cases where a physical fitting model exists (e.g., the mixed model in case of pure additive adsorptive and partitioning retention), the fitting quality can only be expected to be relatively good (prediction errors expressed in terms of a normalized resolution error ɛRs) when carefully selecting the scouting runs and the appropriate starting values for the fitting algorithm. The latter can best be done using a comprehensive grid search scanning a wide range of different starting values. This becomes even more important when no good physical model is available and one has to use a non-physical fitting model, such as the empirical Neue-model. The use of higher-order models is found to be quasi indispensable to keep the prediction errors on the order of some ΔRs=0.05. Also, the choice of the scouting runs becomes even more important using these higher-order models. For highly retained compounds we recommend using scouting runs with long tG/t0-values or to include a run with a higher fraction of eluting solvent at the start of the gradient. When trying to predict gradient retention, errors with which the isocratic retention behavior is fitted are much less important for high retention factors k than errors made in the range of k near the one at the point of elution. The results obtained with a so-called segmented Neue-model (containing 7 parameters) were less good and thus practically not interesting (because of the high number of initial runs). PMID:26044381
A computer model for liquid jet atomization in rocket thrust chambers
NASA Astrophysics Data System (ADS)
Giridharan, M. G.; Lee, J. G.; Krishnan, A.; Yang, H. Q.; Ibrahim, E.; Chuech, S.; Przekwas, A. J.
1991-12-01
The process of atomization has been used as an efficient means of burning liquid fuels in rocket engines, gas turbine engines, internal combustion engines, and industrial furnaces. Despite its widespread application, this complex hydrodynamic phenomenon has not been well understood, and predictive models for this process are still in their infancy. The difficulty in simulating the atomization process arises from the relatively large number of parameters that influence it, including the details of the injector geometry, liquid and gas turbulence, and the operating conditions. In this study, numerical models are developed from first principles, to quantify factors influencing atomization. For example, the surface wave dynamics theory is used for modeling the primary atomization and the droplet energy conservation principle is applied for modeling the secondary atomization. The use of empirical correlations has been minimized by shifting the analyses to fundamental levels. During applications of these models, parametric studies are performed to understand and correlate the influence of relevant parameters on the atomization process. The predictions of these models are compared with existing experimental data. The main tasks of this study were the following: development of a primary atomization model; development of a secondary atomization model; development of a model for impinging jets; development of a model for swirling jets; and coupling of the primary atomization model with a CFD code.
Atomic Models of Strong Solids Interfaces Viewed as Composite Structures
NASA Astrophysics Data System (ADS)
Staffell, I.; Shang, J. L.; Kendall, K.
2014-02-01
This paper looks back through the 1960s to the invention of carbon fibres and the theories of Strong Solids. In particular it focuses on the fracture mechanics paradox of strong composites containing weak interfaces. From Griffith theory, it is clear that three parameters must be considered in producing a high strength composite:- minimising defects; maximising the elastic modulus; and raising the fracture energy along the crack path. The interface then introduces two further factors:- elastic modulus mismatch causing crack stopping; and debonding along a brittle interface due to low interface fracture energy. Consequently, an understanding of the fracture energy of a composite interface is needed. Using an interface model based on atomic interaction forces, it is shown that a single layer of contaminant atoms between the matrix and the reinforcement can reduce the interface fracture energy by an order of magnitude, giving a large delamination effect. The paper also looks to a future in which cars will be made largely from composite materials. Radical improvements in automobile design are necessary because the number of cars worldwide is predicted to double. This paper predicts gains in fuel economy by suggesting a new theory of automobile fuel consumption using an adaptation of Coulomb's friction law. It is demonstrated both by experiment and by theoretical argument that the energy dissipated in standard vehicle tests depends only on weight. Consequently, moving from metal to fibre construction can give a factor 2 improved fuel economy performance, roughly the same as moving from a petrol combustion drive to hydrogen fuel cell propulsion. Using both options together can give a factor 4 improvement, as demonstrated by testing a composite car using the ECE15 protocol.
Chylla, R A; Volkman, B F; Markley, J L
1998-08-01
A maximum likelihood (ML)-based approach has been established for the direct extraction of NMR parameters (e.g., frequency, amplitude, phase, and decay rate) simultaneously from all dimensions of a D-dimensional NMR spectrum. The approach, referred to here as HTFD-ML (hybrid time frequency domain maximum likelihood), constructs a time-domain model composed of a sum of exponentially-decaying sinusoidal signals. The apodized Fourier transform of this time-domain signal is a model spectrum that represents the 'best-fit' to the equivalent frequency-domain data spectrum. The desired amplitude and frequency parameters can be extracted directly from the signal model constructed by the HTFD-ML algorithm. The HTFD-ML approach presented here, as embodied in the software package CHIFIT, is designed to meet the challenges posed by model fitting of D-dimensional NMR data sets, where each consists of many data points (10(8) is not uncommon) encoding information about numerous signals (up to 10(5) for a protein of moderate size) that exhibit spectral overlap. The suitability of the approach is demonstrated by its application to the concerted analysis of a series of ten 2D 1H-15N HSQC experiments measuring 15N T1 relaxation. In addition to demonstrating the practicality of performing maximum likelihood analysis on large, multidimensional NMR spectra, the results demonstrate that this parametric model-fitting approach provides more accurate amplitude and frequency estimates than those obtained from conventional peak-based analysis of the FT spectrum. The improved performance of the model fitting approach derives from its ability to take into account the simultaneous contributions of all signals in a crowded spectral region (deconvolution) as well as to incorporate prior knowledge in constructing models to fit the data. PMID:9751999
Atomic-orbital expansion model for describing ion-atom collisions at intermediate and low energies
Lin, C.D.; Fritsch, W.
1983-01-01
In the description of inelastic processes in ion-atom collisions at moderate energies, the semiclassical close-coupling method is well established as the standard method. Ever since the pioneering work on H/sup +/ + H in the early 60's, the standard procedure is to expand the electronic wavefunction in terms of molecular orbitals (MO) or atomic orbitals (AO) for describing collisions at, respectively, low or intermediate velocities. It has been recognized since early days that traveling orbitals are needed in the expansions in order to represent the asymptotic states in the collisions correctly. While the adoption of such traveling orbitals presents no conceptual difficulties for expansions using atomic orbitals, the situation for molecular orbitals is less clear. In recent years, various forms of traveling MO's have been proposed, but conflicting results for several well-studied systems have been reported.
One-dimensional extended Hubbard model in the atomic limit
NASA Astrophysics Data System (ADS)
Mancini, F.; Mancini, F. P.
2008-06-01
We present the exact solution of the one-dimensional extended Hubbard model in the atomic limit within the Green’s function and equations of motion formalism. We provide a comprehensive and systematic analysis of the model by considering all the relevant response and correlation functions as well as thermodynamic quantities in the whole parameters space. At zero temperature we identify four phases in the plane (U,n) ( U is the on-site potential and n is the filling) and relative phase transitions as well as different types of charge ordering. These features are endorsed by investigating at T=0 the chemical potential and pertinent local correlators, the particle and double occupancy correlation functions, the entropy, and by studying the behavior in the limit T→0 of the charge and spin susceptibilities. A detailed study of the thermodynamic quantities is also presented at finite temperature. This study evidences that a finite-range order persists for a wide range of the temperature, as shown by the behavior of the correlation functions and by the two-peak structure exhibited by the charge susceptibility and by the entropy. Moreover, the equations of motion formalism, together with the use of composite operators, allows us to exactly determine the set of elementary excitations. As a result, the density of states can be determined and a detailed analysis of the specific heat allows for identifying the excitations and for ascribing its two-peak structure to a redistribution of the charge density.
Magnetic-sublevel atomic kinetics modeling for line polarization spectroscopy
Hakel, P.; Mancini, R. C.
2004-01-01
We discuss the mechanism of polarized X-ray line emission in plasmas, its connection to plasma anisotropy, and introduce an atomic kinetics model and code (POLAR) based on the population kinetics of magnetic sublevels. POLAR represents a multi-level, multi-process approach to the problem of polarized spectra in plasmas, and hence it is well suited for plasma applications where cascade effects and alignment transfer can become important. Polarization degrees of X-ray spectral lines computed with POLAR were successfully benchmarked against calculations done with other formalisms, and experimental results obtained at the EBIT facility of Lawrence Livermore National Laboratory. We also investigated the polarization of He-like Si X-ray satellite lines as spectral signatures of anisotropy in the electron distribution function. A comprehensive modeling study was performed taking into account hydrodynamics and electron kinetics. We find that two satellite lines connecting singlet states develop a noticeable polarization while the triplet lines remain unpolarized. These results suggest a scenario where triplet lines could be used as a reference while the singlets could be used as polarized markers of plasma anisotropy.
Madsen, Jonas S.; Lin, Yu-Cheng; Squyres, Georgia R.; Price-Whelan, Alexa; de Santiago Torio, Ana; Song, Angela; Cornell, William C.; Sørensen, Søren J.
2015-01-01
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. PMID:26431965
A Person-Centered Approach to P-E Fit Questions Using a Multiple-Trait Model.
ERIC Educational Resources Information Center
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…
ERIC Educational Resources Information Center
Tay, Louis; Drasgow, Fritz
2012-01-01
Two Monte Carlo simulation studies investigated the effectiveness of the mean adjusted X[superscript 2]/df statistic proposed by Drasgow and colleagues and, because of problems with the method, a new approach for assessing the goodness of fit of an item response theory model was developed. It has been previously recommended that mean adjusted…
ERIC Educational Resources Information Center
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…
ERIC Educational Resources Information Center
Song, Tian
2010-01-01
This study investigates the effect of fitting a unidimensional IRT model to multidimensional data in content-balanced computerized adaptive testing (CAT). Unconstrained CAT with the maximum information item selection method is chosen as the baseline, and the performances of three content balancing procedures, the constrained CAT (CCAT), the…
ERIC Educational Resources Information Center
O'Neill, James M.; Clark, Jeffrey K.; Jones, James A.
2016-01-01
Background: In elementary grades, comprehensive health education curricula have demonstrated effectiveness in addressing singular health issues. The Michigan Model for Health (MMH) was implemented and evaluated to determine its impact on nutrition, physical fitness, and safety knowledge and skills. Methods: Schools (N = 52) were randomly assigned…
ERIC Educational Resources Information Center
Meijer, Rob R.; Tendeiro, Jorge N.
2012-01-01
We extend a recent didactic by Magis, Raiche, and Beland on the use of the l[subscript z] and l[subscript z]* person-fit statistics. We discuss a number of possibly confusing details and show that it is important to first investigate item response theory model fit before assessing person fit. Furthermore, it is argued that appropriate…
Secondary Students' Mental Models of Atoms and Molecules: Implications for Teaching Chemistry.
ERIC Educational Resources Information Center
Harrison, Allan G.; Treagust, David F.
1996-01-01
Examines the reasoning behind views of atoms and molecules held by students (n=48) and investigates how mental models may assist or hamper further instruction in chemistry. Reports that students prefer models of atoms and molecules that depict them as discrete, concrete structures. Recommends that teachers develop student modeling skills and…
Development of a phenomenological model for coal slurry atomization
Dooher, J.P.
1995-11-01
Highly concentrated suspensions of coal particles in water or alternate fluids appear to have a wide range of applications for energy production. For enhanced implementation of coal slurry fuel technology, an understanding of coal slurry atomization as a function coal and slurry properties for specific mechanical configurations of nozzle atomizers should be developed.
Linking the Fits, Fitting the Links: Connecting Different Types of PO Fit to Attitudinal Outcomes
ERIC Educational Resources Information Center
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…
NASA Astrophysics Data System (ADS)
Luo, C.; Liang, E. P.
Cyg X-1 has been a black hole candidate for years and people have got its spectra from various high energy detectors such as HEAO series and recently OSSE (see Ling, J. C. et al. 1987 & Grabelsky et al. 1993). Although much work has been done to fit its spectrum, most of the work assumed a Sunyaev-Titarchuk (1980) type spectrum a priori and then obtained the temperature and Thomson depth. It is, however, well known that a single temperature fit fails in the high energy tail, i.e. above hundreds of keV. Here the authors use the radial-zoned model proposed by Wandel & Liang (1991) to redo the fitting.
Fast fitting of non-Gaussian state-space models to animal movement data via Template Model Builder.
Albertsen, Christoffer Moesgaard; Whoriskey, Kim; Yurkowski, David; Nielsen, Anders; Mills, Joanna
2015-10-01
State-space models (SSM) are often used for analyzing complex ecological processes that are not observed directly, such as marine animal movement. When outliers are present in the measurements, special care is needed in the analysis to obtain reliable location and process estimates. Here we recommend using the Laplace approximation combined with automatic differentiation (as implemented in the novel R package Template Model Builder; TMB) for the fast fitting of continuous-time multivariate non-Gaussian SSMs. Through Argos satellite tracking data, we demonstrate that the use of continuous-time t-distributed measurement errors for error-prone data is more robust to outliers and improves the location estimation compared to using discretized-time t-distributed errors (implemented with a Gibbs sampler) or using continuous-time Gaussian errors (as with the Kalman filter). Using TMB, we are able to estimate additional parameters compared to previous methods, all without requiring a substantial increase in computational time. The model implementation is made available through the R package argosTrack. PMID:26649381
Modeling Invasion Dynamics with Spatial Random-Fitness Due to Micro-Environment
Manem, V. S. K.; Kaveh, K.; Kohandel, M.; Sivaloganathan, S.
2015-01-01
Numerous experimental studies have demonstrated that the microenvironment is a key regulator influencing the proliferative and migrative potentials of species. Spatial and temporal disturbances lead to adverse and hazardous microenvironments for cellular systems that is reflected in the phenotypic heterogeneity within the system. In this paper, we study the effect of microenvironment on the invasive capability of species, or mutants, on structured grids (in particular, square lattices) under the influence of site-dependent random proliferation in addition to a migration potential. We discuss both continuous and discrete fitness distributions. Our results suggest that the invasion probability is negatively correlated with the variance of fitness distribution of mutants (for both advantageous and neutral mutants) in the absence of migration of both types of cells. A similar behaviour is observed even in the presence of a random fitness distribution of host cells in the system with neutral fitness rate. In the case of a bimodal distribution, we observe zero invasion probability until the system reaches a (specific) proportion of advantageous phenotypes. Also, we find that the migrative potential amplifies the invasion probability as the variance of fitness of mutants increases in the system, which is the exact opposite in the absence of migration. Our computational framework captures the harsh microenvironmental conditions through quenched random fitness distributions and migration of cells, and our analysis shows that they play an important role in the invasion dynamics of several biological systems such as bacterial micro-habitats, epithelial dysplasia, and metastasis. We believe that our results may lead to more experimental studies, which can in turn provide further insights into the role and impact of heterogeneous environments on invasion dynamics. PMID:26509572
NASA Astrophysics Data System (ADS)
Javernick, L. A.; Caruso, B. S.; Measures, R.; Hicks, M.; Brasington, J.
2013-12-01
During the past decade, the advances in survey and sensor technology and three-dimensional morphologic analysis have been partially driven by the need for high resolution topography for physical and numerical fluvial modelling and have in return created new opportunities to investigate and model the structure and dynamics of fluvial systems. While the potential of such revolutionary survey technologies such as GPS, LiDAR, and terrestrial laser scanners have proven to produce high resolution fluvial terrain models, their high hardware and facility costs or labor intensive methods restrict data acquisition; thus limiting the extent and frequency of surveys. However, recent advances in computer vision and image analysis have led to the development of a novel, fully automated photogrammetric method to generate dense 3d point cloud data. This approach, termed Structure-from-Motion or SfM, requires only limited ground-control and is ideally suited to imagery obtained from low-cost, non-metric cameras acquired either at close-range or using aerial platforms. With numerous survey technologies available, there is a need to determine if simpler and more affordable methods are fit for the purpose of numerical modelling. To address this demand, the hydrodynamic numerical model Delft3D was utilized to simulate various flow conditions of a SfM produced terrain model. Using the SfM software PhotoScan (version 0.9.0) and optical bathymetric mapping, a 0.5 m resolution terrain model was generated for a 1.6 km reach of the braided Ahuriri River, New Zealand. This topography was imported into Delft3D where a 1.5 m and 2.5 m grid resolutions were generated and utilized to simulate a low, medium, and high flow conditions. Following a stringent calibration, hydraulic conditions of velocity, depth, and inundation were tested. Results reveal that average modelled depth errors were comparable to the SfM uncertainty (0.14 m average error), velocity errors of a small anabranch produced
Curve fitting and modeling with splines using statistical variable selection techniques
NASA Technical Reports Server (NTRS)
Smith, P. L.
1982-01-01
The successful application of statistical variable selection techniques to fit splines is demonstrated. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs, using the B-spline basis, were developed. The program for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.
Multipole correction of atomic monopole models of molecular charge distribution. I. Peptides
NASA Technical Reports Server (NTRS)
Sokalski, W. A.; Keller, D. A.; Ornstein, R. L.; Rein, R.
1993-01-01
The defects in atomic monopole models of molecular charge distribution have been analyzed for several model-blocked peptides and compared with accurate quantum chemical values. The results indicate that the angular characteristics of the molecular electrostatic potential around functional groups capable of forming hydrogen bonds can be considerably distorted within various models relying upon isotropic atomic charges only. It is shown that these defects can be corrected by augmenting the atomic point charge models by cumulative atomic multipole moments (CAMMs). Alternatively, sets of off-center atomic point charges could be automatically derived from respective multipoles, providing approximately equivalent corrections. For the first time, correlated atomic multipoles have been calculated for N-acetyl, N'-methylamide-blocked derivatives of glycine, alanine, cysteine, threonine, leucine, lysine, and serine using the MP2 method. The role of the correlation effects in the peptide molecular charge distribution are discussed.
NASA Astrophysics Data System (ADS)
Roxburgh, Ian W.
2015-01-01
Aims: Our aim is to describe the theory of surface layer independent model fitting by phase matching and to apply this to the stars HD 49933 observed by CoRoT, and HD 177153 (aka Perky) observed by Kepler. Methods: We use theoretical analysis, phase shifts, and model fitting. Results: We define the inner and outer phase shifts of a frequency set of a model star and show that the outer phase shifts are (almost) independent of degree ℓ, and that a function of the inner phase shifts (the phase function) collapses to an ℓ independent function of frequency in the outer layers. We then show how to use this result in a model fitting technique to find a best fit model to an observed frequency set by calculating the inner phase shifts of a model using the observed frequencies and determining the extent to which the phase function collapses to a single function of frequency in the outer layers. This technique does not depend on the radial order n assigned to the observed frequencies. We give two examples applying this technique to the frequency sets of HD 49933 observed by CoRoT and HD 177153 (aka Perky) observed by Kepler, for which measurements of angular diameters and bolometric fluxes are available. For HD 49933 we find a very wide range of models to be consistent with the data (all with convective core overshooting) - and conclude that the data is not precise enough to make any useful restrictions on the structure of this star. For HD 177153 our best fit models have no convective cores, masses in the range 1.15-1.17 M⊙, ages of 4.45-4.70 × 109 yr, Z in the range 0.021-0.024, XH = 0.71-0.72, Y = 0.256 - 0.266 and mixing length parameter α = 1.8. We compare our results to those of previous studies. We contrast the phase matching technique to that using the ratios of small to large separations, showing that it avoids the problem of correlated errors in separation ratio fitting and of assigning radial order n to the modes.
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
Improving the Ni I atomic model for solar and stellar atmospheric models
Vieytes, M. C.; Fontenla, J. M. E-mail: johnf@digidyna.com
2013-06-01
Neutral nickel (Ni I) is abundant in the solar atmosphere and is one of the important elements that contribute to the emission and absorption of radiation in the spectral range between 1900 and 3900 Å. Previously, the Solar Radiation Physical Modeling (SRPM) models of the solar atmosphere only considered a few levels of this species. Here, we improve the Ni I atomic model by taking into account 61 levels and 490 spectral lines. We compute the populations of these levels in full NLTE using the SRPM code and compare the resulting emerging spectrum with observations. The present atomic model significantly improves the calculation of the solar spectral irradiance at near-UV wavelengths, which is important for Earth atmospheric studies, and particularly for ozone chemistry.
Operation of the computer model for direct atomic oxygen exposure of Earth satellites
NASA Technical Reports Server (NTRS)
Bourassa, R. J.; Gruenbaum, P. E.; Gillis, J. R.; Hargraves, C. R.
1995-01-01
One of the primary causes of material degradation in low Earth orbit (LEO) is exposure to atomic oxygen. When atomic oxygen molecules collide with an orbiting spacecraft, the relative velocity is 7 to 8 km/sec and the collision energy is 4 to 5 eV per atom. Under these conditions, atomic oxygen may initiate a number of chemical and physical reactions with exposed materials. These reactions contribute to material degradation, surface erosion, and contamination. Interpretation of these effects on materials and the design of space hardware to withstand on-orbit conditions requires quantitative knowledge of the atomic oxygen exposure environment. Atomic oxygen flux is a function of orbit altitude, the orientation of the orbit plan to the Sun, solar and geomagnetic activity, and the angle between exposed surfaces and the spacecraft heading. We have developed a computer model to predict the atomic oxygen exposure of spacecraft in low Earth orbit. The application of this computer model is discussed.
Work, Family, and Mental Health: Testing Different Models of Work-Family Fit.
ERIC Educational Resources Information Center
Grzywacz, Joseph G.; Bass, Brenda L.
2003-01-01
Using family resilience theory, this study examined the effects of work-family conflict and work-family facilitation on mental health among working adults to gain a better understanding of work-family fit. Results suggest that family to work facilitation is a family protective factor that offsets and buffers the deleterious effects of work-family…
Testing the Youth Physical Activity Promotion Model: Fatness and Fitness as Enabling Factors
ERIC Educational Resources Information Center
Chen, Senlin; Welk, Gregory J.; Joens-Matre, Roxane R.
2014-01-01
As the prevalence of childhood obesity increases, it is important to examine possible differences in psychosocial correlates of physical activity between normal weight and overweight children. The study examined fatness (weight status) and (aerobic) fitness as Enabling factors related to youth physical activity within the Youth Physical Activity…
Implementation of a Personal Fitness Unit Using the Personalized System of Instruction Model
ERIC Educational Resources Information Center
Prewitt, Steven; Hannon, James C.; Colquitt, Gavin; Brusseau, Timothy A.; Newton, Maria; Shaw, Janet
2015-01-01
Levels of physical activity and health-related fitness (HRF) are decreasing among adolescents in the United States. Several interventions have been implemented to reverse this downtrend. Traditionally, physical educators incorporate a direct instruction (DI) strategy, with teaching potentially leading students to disengage during class. An…
Gray Matter Correlates of Fluid, Crystallized, and Spatial Intelligence: Testing the P-FIT Model
ERIC Educational Resources Information Center
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…
ERIC Educational Resources Information Center
Cardinal, Bradley J.
2001-01-01
Investigated the physical activity and fitness promoting behaviors of health, physical education, recreation, and dance professionals and preprofessionals. Survey data indicated that most respondents were physically active. Overall, overweight and obesity rates were considerably lower than rates reported in the general U.S. adult population. Role…
Coupling of an average-atom model with a collisional-radiative equilibrium model
Faussurier, G. Blancard, C.; Cossé, P.
2014-11-15
We present a method to combine a collisional-radiative equilibrium model and an average-atom model to calculate bound and free electron wavefunctions in hot dense plasmas by taking into account screening. This approach allows us to calculate electrical resistivity and thermal conductivity as well as pressure in non local thermodynamic equilibrium plasmas. Illustrations of the method are presented for dilute titanium plasma.
Mesler, Robert A.; Pihlstroem, Ylva M.
2013-09-01
We perform calorimetry on the bright gamma-ray burst GRB 030329 by fitting simultaneously the broadband radio afterglow and the observed afterglow image size to a semi-analytic MHD and afterglow emission model. Our semi-analytic method is valid in both the relativistic and non-relativistic regimes, and incorporates a model of the interstellar scintillation that substantially effects the broadband afterglow below 10 GHz. The model is fitted to archival measurements of the afterglow flux from 1 day to 8.3 yr after the burst. Values for the initial burst parameters are determined and the nature of the circumburst medium is explored. Additionally, direct measurements of the lateral expansion rate of the radio afterglow image size allow us to estimate the initial Lorentz factor of the jet.
Kompaneets Model Fitting of the Orion-Eridanus Superbubble. II. Thinking Outside of Barnard’s Loop
NASA Astrophysics Data System (ADS)
Pon, Andy; Ochsendorf, Bram B.; Alves, João; Bally, John; Basu, Shantanu; Tielens, Alexander G. G. M.
2016-08-01
The Orion star-forming region is the nearest active high-mass star-forming region and has created a large superbubble, the Orion–Eridanus superbubble. Recent work by Ochsendorf et al. has extended the accepted boundary of the superbubble. We fit Kompaneets models of superbubbles expanding in exponential atmospheres to the new larger shape of the Orion–Eridanus superbubble. We find that this larger morphology of the superbubble is consistent with the evolution of the superbubble being primarily controlled by expansion into the exponential Galactic disk ISM if the superbubble is oriented with the Eridanus side farther from the Sun than the Orion side. Unlike previous Kompaneets model fits that required abnormally small scale heights for the Galactic disk (<40 pc), we find morphologically consistent models with scale heights of 80 pc, similar to that expected for the Galactic disk.
Ong, Kevin L; Rundell, Steve; Liepins, Imants; Laurent, Ryan; Markel, David; Kurtz, Steven M
2009-11-01
Press-fit implantation may result in acetabular component deformation between the ischial-ilial columns ("pinching"). The biomechanical and clinical consequences of liner pinching due to press-fit implantation have not been well studied. We compared the effects of pinching on the polyethylene fracture risk, potential wear rate, and stresses for two different thickness liners using computational methods. Line-to-line ("no pinch") reaming and 2 mm underreaming press fit ("pinch") conditions were examined for Trident cups with X3 polyethylene liner wall thicknesses of 5.9 mm (36E) and 3.8 mm (40E). Press-fit cup deformations were measured from a foam block configuration. A hybrid material model, calibrated to experimentally determined stress-strain behavior of sequentially annealed polyethylene, was applied to the computational model. Molecular chain stretch did not exceed the fracture threshold in any cases. Nominal shell pinch of 0.28 mm was estimated to increase the volumetric wear rate by 70% for both cups and peak contact stresses by 140 and 170% for the 5.9 and 3.8 mm-thick liners, respectively. Although pinching increases liner stresses, polyethylene fracture is highly unlikely, and the volumetric wear rates are likely to be low compared to conventional polyethylene. PMID:19489047
Ferreira, Abílio G T; Henrique, Douglas S; Vieira, Ricardo A M; Maeda, Emilyn M; Valotto, Altair A
2015-03-01
The objective of this study was to evaluate four mathematical models with regards to their fit to lactation curves of Holstein cows from herds raised in the southwestern region of the state of Parana, Brazil. Initially, 42,281 milk production records from 2005 to 2011 were obtained from "Associação Paranaense de Criadores de Bovinos da Raça Holandesa (APCBRH)". Data lacking dates of drying and total milk production at 305 days of lactation were excluded, resulting in a remaining 15,142 records corresponding to 2,441 Holstein cows. Data were sorted according to the parity order (ranging from one to six), and within each parity order the animals were divided into quartiles (Q25%, Q50%, Q75% and Q100%) corresponding to 305-day lactation yield. Within each parity order, for each quartile, four mathematical models were adjusted, two of which were predominantly empirical (Brody and Wood) whereas the other two presented more mechanistic characteristics (models Dijkstra and Pollott). The quality of fit was evaluated by the corrected Akaike information criterion. The Wood model showed the best fit in almost all evaluated situations and, therefore, may be considered as the most suitable model to describe, at least empirically, the lactation curves of Holstein cows raised in Southwestern Parana. PMID:25806994
NASA Astrophysics Data System (ADS)
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.
Seasonality of Influenza A(H7N9) Virus in China—Fitting Simple Epidemic Models to Human Cases
Lin, Qianying; Lin, Zhigui; Chiu, Alice P. Y.; He, Daihai
2016-01-01
Background Three epidemic waves of influenza A(H7N9) (hereafter ‘H7N9’) human cases have occurred between March 2013 and July 2015 in China. However, the underlying transmission mechanism remains unclear. Our main objective is to use mathematical models to study how seasonality, secular changes and environmental transmission play a role in the spread of H7N9 in China. Methods Data on human cases and chicken cases of H7N9 infection were downloaded from the EMPRES-i Global Animal Disease Information System. We modelled on chicken-to-chicken transmission, assuming a constant ratio of 10−6 human case per chicken case, and compared the model fit with the observed human cases. We developed three different modified Susceptible-Exposed-Infectious-Recovered-Susceptible models: (i) a non-periodic transmission rate model with an environmental class, (ii) a non-periodic transmission rate model without an environmental class, and (iii) a periodic transmission rate model with an environmental class. We then estimated the key epidemiological parameters and compared the model fit using Akaike Information Criterion and Bayesian Information Criterion. Results Our results showed that a non-periodic transmission rate model with an environmental class provided the best model fit to the observed human cases in China during the study period. The estimated parameter values were within biologically plausible ranges. Conclusions This study highlighted the importance of considering secular changes and environmental transmission in the modelling of human H7N9 cases. Secular changes were most likely due to control measures such as Live Poultry Markets closures that were implemented during the initial phase of the outbreaks in China. Our results suggested that environmental transmission via viral shedding of infected chickens had contributed to the spread of H7N9 human cases in China. PMID:26963937
'Bubble chamber model' of fast atom bombardment induced processes.
Kosevich, Marina V; Shelkovsky, Vadim S; Boryak, Oleg A; Orlov, Vadim V
2003-01-01
A hypothesis concerning FAB mechanisms, referred to as a 'bubble chamber FAB model', is proposed. This model can provide an answer to the long-standing question as to how fragile biomolecules and weakly bound clusters can survive under high-energy particle impact on liquids. The basis of this model is a simple estimation of saturated vapour pressure over the surface of liquids, which shows that all liquids ever tested by fast atom bombardment (FAB) and liquid secondary ion mass spectrometry (SIMS) were in the superheated state under the experimental conditions applied. The result of the interaction of the energetic particles with superheated liquids is known to be qualitatively different from that with equilibrium liquids. It consists of initiation of local boiling, i.e., in formation of vapour bubbles along the track of the energetic particle. This phenomenon has been extensively studied in the framework of nuclear physics and provides the basis for construction of the well-known bubble chamber detectors. The possibility of occurrence of similar processes under FAB of superheated liquids substantiates a conceptual model of emission of secondary ions suggested by Vestal in 1983, which assumes formation of bubbles beneath the liquid surface, followed by their bursting accompanied by release of microdroplets and clusters as a necessary intermediate step for the creation of molecular ions. The main distinctive feature of the bubble chamber FAB model, proposed here, is that the bubbles are formed not in the space and time-restricted impact-excited zone, but in the nearby liquid as a 'normal' boiling event, which implies that the temperature both within the bubble and in the droplets emerging on its burst is practically the same as that of the bulk liquid sample. This concept can resolve the paradox of survival of intact biomolecules under FAB, since the part of the sample participating in the liquid-gas transition via the bubble mechanism has an ambient temperature
Producing high-accuracy lattice models from protein atomic coordinates including side chains.
Mann, Martin; Saunders, Rhodri; Smith, Cameron; Backofen, Rolf; Deane, Charlotte M
2012-01-01
Lattice models are a common abstraction used in the study of protein structure, folding, and refinement. They are advantageous because the discretisation of space can make extensive protein evaluations computationally feasible. Various approaches to the protein chain lattice fitting problem have been suggested but only a single backbone-only tool is available currently. We introduce LatFit, a new tool to produce high-accuracy lattice protein models. It generates both backbone-only and backbone-side-chain models in any user defined lattice. LatFit implements a new distance RMSD-optimisation fitting procedure in addition to the known coordinate RMSD method. We tested LatFit's accuracy and speed using a large nonredundant set of high resolution proteins (SCOP database) on three commonly used lattices: 3D cubic, face-centred cubic, and knight's walk. Fitting speed compared favourably to other methods and both backbone-only and backbone-side-chain models show low deviation from the original data (~1.5 Å RMSD in the FCC lattice). To our knowledge this represents the first comprehensive study of lattice quality for on-lattice protein models including side chains while LatFit is the only available tool for such models. PMID:22934109
Producing High-Accuracy Lattice Models from Protein Atomic Coordinates Including Side Chains
Mann, Martin; Saunders, Rhodri; Smith, Cameron; Backofen, Rolf; Deane, Charlotte M.
2012-01-01
Lattice models are a common abstraction used in the study of protein structure, folding, and refinement. They are advantageous because the discretisation of space can make extensive protein evaluations computationally feasible. Various approaches to the protein chain lattice fitting problem have been suggested but only a single backbone-only tool is available currently. We introduce LatFit, a new tool to produce high-accuracy lattice protein models. It generates both backbone-only and backbone-side-chain models in any user defined lattice. LatFit implements a new distance RMSD-optimisation fitting procedure in addition to the known coordinate RMSD method. We tested LatFit's accuracy and speed using a large nonredundant set of high resolution proteins (SCOP database) on three commonly used lattices: 3D cubic, face-centred cubic, and knight's walk. Fitting speed compared favourably to other methods and both backbone-only and backbone-side-chain models show low deviation from the original data (~1.5 Å RMSD in the FCC lattice). To our knowledge this represents the first comprehensive study of lattice quality for on-lattice protein models including side chains while LatFit is the only available tool for such models. PMID:22934109
Implementation of the Iterative Proportion Fitting Algorithm for Geostatistical Facies Modeling
Li Yupeng Deutsch, Clayton V.
2012-06-15
In geostatistics, most stochastic algorithm for simulation of categorical variables such as facies or rock types require a conditional probability distribution. The multivariate probability distribution of all the grouped locations including the unsampled location permits calculation of the conditional probability directly based on its definition. In this article, the iterative proportion fitting (IPF) algorithm is implemented to infer this multivariate probability. Using the IPF algorithm, the multivariate probability is obtained by iterative modification to an initial estimated multivariate probability using lower order bivariate probabilities as constraints. The imposed bivariate marginal probabilities are inferred from profiles along drill holes or wells. In the IPF process, a sparse matrix is used to calculate the marginal probabilities from the multivariate probability, which makes the iterative fitting more tractable and practical. This algorithm can be extended to higher order marginal probability constraints as used in multiple point statistics. The theoretical framework is developed and illustrated with estimation and simulation example.
Kandris, K; Antoniou, K; Pantazidou, M; Mamais, D
2015-03-01
This work puts forth a heuristic approach for investigating compromises between quality of fit and parameter reliability for the Monod-type kinetics employed to model microbial reductive dechlorination of trichloroethene. The methodology is demonstrated with three models of increasing fidelity and complexity. Model parameters were estimated with a stochastic global optimization algorithm, using scarce and inherently noisy experimental data from a mixed anaerobic microbial culture, which dechlorinated trichloroethene to ethene completely. Parameter reliability of each model was assessed using a Monte Carlo technique. Finally, an alternate quantity of applied interest was evaluated in order to assist with model discrimination. Results from the application of our approach suggest that the modeler should examine the implementation of conceptually simple models, even if they are a crude abstraction of reality, as they can be computationally less demanding and adequately accurate when model performance is assessed with criteria of applied interest, such as chloroethene elimination time. PMID:25447439
Fast and accurate modeling of molecular atomization energies with machine learning.
Rupp, Matthias; Tkatchenko, Alexandre; Müller, Klaus-Robert; von Lilienfeld, O Anatole
2012-02-01
We introduce a machine learning model to predict atomization energies of a diverse set of organic molecules, based on nuclear charges and atomic positions only. The problem of solving the molecular Schrödinger equation is mapped onto a nonlinear statistical regression problem of reduced complexity. Regression models are trained on and compared to atomization energies computed with hybrid density-functional theory. Cross validation over more than seven thousand organic molecules yields a mean absolute error of ∼10 kcal/mol. Applicability is demonstrated for the prediction of molecular atomization potential energy curves. PMID:22400967
TEMPy: a Python library for assessment of three-dimensional electron microscopy density fits
Farabella, Irene; Vasishtan, Daven; Joseph, Agnel Praveen; Pandurangan, Arun Prasad; Sahota, Harpal; Topf, Maya
2015-01-01
Three-dimensional electron microscopy is currently one of the most promising techniques used to study macromolecular assemblies. Rigid and flexible fitting of atomic models into density maps is often essential to gain further insights into the assemblies they represent. Currently, tools that facilitate the assessment of fitted atomic models and maps are needed. TEMPy (template and electron microscopy comparison using Python) is a toolkit designed for this purpose. The library includes a set of methods to assess density fits in intermediate-to-low resolution maps, both globally and locally. It also provides procedures for single-fit assessment, ensemble generation of fits, clustering, and multiple and consensus scoring, as well as plots and output files for visualization purposes to help the user in analysing rigid and flexible fits. The modular nature of TEMPy helps the integration of scoring and assessment of fits into large pipelines, making it a tool suitable for both novice and expert structural biologists. PMID:26306092
NASA Technical Reports Server (NTRS)
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.
NASA Astrophysics Data System (ADS)
Jin, Lin; Auerbach, Scott M.; Monson, Peter A.
2011-04-01
We present an atomic lattice model for studying the polymerization of silicic acid in sol-gel and related processes for synthesizing silica materials. Our model is based on Si and O atoms occupying the sites of a body-centered-cubic lattice, with all atoms arranged in SiO4 tetrahedra. This is the simplest model that allows for variation in the Si-O-Si angle, which is largely responsible for the versatility in silica polymorphs. The model describes the assembly of polymerized silica structures starting from a solution of silicic acid in water at a given concentration and pH. This model can simulate related materials—chalcogenides and clays—by assigning energy penalties to particular ring geometries in the polymerized structures. The simplicity of this approach makes it possible to study the polymerization process to higher degrees of polymerization and larger system sizes than has been possible with previous atomistic models. We have performed Monte Carlo simulations of the model at two concentrations: a low density state similar to that used in the clear solution synthesis of silicalite-1, and a high density state relevant to experiments on silica gel synthesis. For the high concentration system where there are NMR data on the temporal evolution of the Qn distribution, we find that the model gives good agreement with the experimental data. The model captures the basic mechanism of silica polymerization and provides quantitative structural predictions on ring-size distributions in good agreement with x-ray and neutron diffraction data.
Hraiech, Sami; Roch, Antoine; Lepidi, Hubert; Atieh, Thérèse; Audoly, Gilles; Rolain, Jean-Marc; Raoult, Didier; Brunel, Jean-Michel; Papazian, Laurent
2013-01-01
We compared the fitness and lung pathogenicity of two isogenic clinical isolates of Acinetobacter baumannii, one resistant (ABCR) and the other susceptible (ABCS) to colistin. In vitro, ABCR exhibited slower growth kinetics than ABCS. In a rat model of pneumonia, ABCR was associated with less pronounced signs of infection (lung bacterial count, systemic dissemination, and lung damage) and a better outcome (ABCR and ABCS mortality rates, 20 and 50%, respectively [P = 0.03]). PMID:23836181