Model of the final borehole geometry for helical laser drilling

NASA Astrophysics Data System (ADS)

Kroschel, Alexander; Michalowski, Andreas; Graf, Thomas

2018-05-01

A model for predicting the borehole geometry for laser drilling is presented based on the calculation of a surface of constant absorbed fluence. It is applicable to helical drilling of through-holes with ultrashort laser pulses. The threshold fluence describing the borehole surface is fitted for best agreement with experimental data in the form of cross-sections of through-holes of different shapes and sizes in stainless steel samples. The fitted value is similar to ablation threshold fluence values reported for laser ablation models.

Disproportionation of rosin on an industrial Pd/C catalyst: reaction pathway and kinetic model discrimination.

PubMed

Souto, Juan Carlos; Yustos, Pedro; Ladero, Miguel; Garcia-Ochoa, Felix

2011-02-01

In this work, a phenomenological study of the isomerisation and disproportionation of rosin acids using an industrial 5% Pd on charcoal catalyst from 200 to 240°C is carried out. Medium composition is determined by elemental microanalysis, GC-MS and GC-FID. Dehydrogenated and hydrogenated acid species molar amounts in the final product show that dehydrogenation is the main reaction. Moreover, both hydrogen and non-hydrogen concentration considering kinetic models are fitted to experimental data using a multivariable non-linear technique. Statistical discrimination among the proposed kinetic models lead to the conclusion hydrogen considering models fit much better to experimental results. The final kinetic model involves first-order isomerisation reactions of neoabietic and palustric acids to abietic acid, first-order dehydrogenation and hydrogenation of this latter acid, and hydrogenation of pimaric acids. Hydrogenation reactions are partial first-order regarding the acid and hydrogen. Copyright © 2010 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2013-02-01

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

Cox Proportional Hazards Models for Modeling the Time to Onset of Decompression Sickness in Hypobaric Environments

NASA Technical Reports Server (NTRS)

Thompson, Laura A.; Chhikara, Raj S.; Conkin, Johnny

2003-01-01

In this paper we fit Cox proportional hazards models to a subset of data from the Hypobaric Decompression Sickness Databank. The data bank contains records on the time to decompression sickness (DCS) and venous gas emboli (VGE) for over 130,000 person-exposures to high altitude in chamber tests. The subset we use contains 1,321 records, with 87% censoring, and has the most recent experimental tests on DCS made available from Johnson Space Center. We build on previous analyses of this data set by considering more expanded models and more detailed model assessments specific to the Cox model. Our model - which is stratified on the quartiles of the final ambient pressure at altitude - includes the final ambient pressure at altitude as a nonlinear continuous predictor, the computed tissue partial pressure of nitrogen at altitude, and whether exercise was done at altitude. We conduct various assessments of our model, many of which are recently developed in the statistical literature, and conclude where the model needs improvement. We consider the addition of frailties to the stratified Cox model, but found that no significant gain was attained above a model that does not include frailties. Finally, we validate some of the models that we fit.

Program to Optimize Simulated Trajectories II (POST2) Surrogate Models for Mars Ascent Vehicle (MAV) Performance Assessment

NASA Technical Reports Server (NTRS)

Zwack, M. R.; Dees, P. D.; Thomas, H. D.; Polsgrove, T. P.; Holt, J. B.

2017-01-01

The primary purpose of the multiPOST tool is to enable the execution of much larger sets of vehicle cases to allow for broader trade space exploration. However, this exploration is not achieved solely with the increased case throughput. The multiPOST tool is applied to carry out a Design of Experiments (DOE), which is a set of cases that have been structured to capture a maximum amount of information about the design space with minimal computational effort. The results of the DOE are then used to fit a surrogate model, ultimately enabling parametric design space exploration. The approach used for the MAV study includes both DOE and surrogate modeling. First, the primary design considerations for the vehicle were used to develop the variables and ranges for the multiPOST DOE. The final set of DOE variables were carefully selected in order to capture the desired vehicle trades and take into account any special considerations for surrogate modeling. Next, the DOE sets were executed through multiPOST. Following successful completion of the DOE cases, a manual verification trial was performed. The trial involved randomly selecting cases from the DOE set and running them by hand. The results from the human analyst's run and multiPOST were then compared to ensure that the automated runs were being executed properly. Completion of the verification trials was then followed by surrogate model fitting. After fits to the multiPOST data were successfully created, the surrogate models were used as a stand-in for POST2 to carry out the desired MAV trades. Using the surrogate models in lieu of POST2 allowed for visualization of vehicle sensitivities to the input variables as well as rapid evaluation of vehicle performance. Although the models introduce some error into the output of the trade study, they were very effective at identifying areas of interest within the trade space for further refinement by human analysts. The next section will cover all of the ground rules and assumptions associated with DOE setup and multiPOST execution. Section 3.1 gives the final DOE variables and ranges, while section 3.2 addresses the POST2 specific assumptions. The results of the verification trials are given in section 4. Section 5 gives the surrogate model fitting results, including the goodness-of-fit metrics for each fit. Finally, the MAV specific results are discussed in section 6.

3D Modeling of Iran and Surrounding Areas From Simultaneous Inversion of Multiple Geophysical Datasets

DTIC Science & Technology

2010-09-01

which are primarily sensitive to upper crustal structures, are difficult to measure and especially true in tectonically and geologically complex areas...slice through the model (compare Figure 6 and Figure 9). The fit to the receiver function is not perfect and the spread of the slower deep crustal ...Although the final fit is certainly not perfect, note the improvement in timing of the main crustal conversion and reverberation (vertical lines) from the

An application of model-fitting procedures for marginal structural models.

PubMed

Mortimer, Kathleen M; Neugebauer, Romain; van der Laan, Mark; Tager, Ira B

2005-08-15

Marginal structural models (MSMs) are being used more frequently to obtain causal effect estimates in observational studies. Although the principal estimator of MSM coefficients has been the inverse probability of treatment weight (IPTW) estimator, there are few published examples that illustrate how to apply IPTW or discuss the impact of model selection on effect estimates. The authors applied IPTW estimation of an MSM to observational data from the Fresno Asthmatic Children's Environment Study (2000-2002) to evaluate the effect of asthma rescue medication use on pulmonary function and compared their results with those obtained through traditional regression methods. Akaike's Information Criterion and cross-validation methods were used to fit the MSM. In this paper, the influence of model selection and evaluation of key assumptions such as the experimental treatment assignment assumption are discussed in detail. Traditional analyses suggested that medication use was not associated with an improvement in pulmonary function--a finding that is counterintuitive and probably due to confounding by symptoms and asthma severity. The final MSM estimated that medication use was causally related to a 7% improvement in pulmonary function. The authors present examples that should encourage investigators who use IPTW estimation to undertake and discuss the impact of model-fitting procedures to justify the choice of the final weights.

Using Random Forest Models to Predict Organizational Violence

NASA Technical Reports Server (NTRS)

Levine, Burton; Bobashev, Georgly

2012-01-01

We present a methodology to access the proclivity of an organization to commit violence against nongovernment personnel. We fitted a Random Forest model using the Minority at Risk Organizational Behavior (MAROS) dataset. The MAROS data is longitudinal; so, individual observations are not independent. We propose a modification to the standard Random Forest methodology to account for the violation of the independence assumption. We present the results of the model fit, an example of predicting violence for an organization; and finally, we present a summary of the forest in a "meta-tree,"

Social comparison and perceived breach of psychological contract: their effects on burnout in a multigroup analysis.

PubMed

Cantisano, Gabriela Topa; Domínguez, J Francisco Morales; García, J Luis Caeiro

2007-05-01

This study focuses on the mediator role of social comparison in the relationship between perceived breach of psychological contract and burnout. A previous model showing the hypothesized effects of perceived breach on burnout, both direct and mediated, is proposed. The final model reached an optimal fit to the data and was confirmed through multigroup analysis using a sample of Spanish teachers (N = 401) belonging to preprimary, primary, and secondary schools. Multigroup analyses showed that the model fit all groups adequately.

Estimating the decline in excess risk of cerebrovascular disease following quitting smoking--a systematic review based on the negative exponential model.

PubMed

Lee, Peter N; Fry, John S; Thornton, Alison J

2014-02-01

We attempted to quantify the decline in stroke risk following quitting using the negative exponential model, with methodology previously employed for IHD. We identified 22 blocks of RRs (from 13 studies) comparing current smokers, former smokers (by time quit) and never smokers. Corresponding pseudo-numbers of cases and controls/at risk formed the data for model-fitting. We tried to estimate the half-life (H, time since quit when the excess risk becomes half that for a continuing smoker) for each block. The method failed to converge or produced very variable estimates of H in nine blocks with a current smoker RR <1.40. Rejecting these, and combining blocks by amount smoked in one study where problems arose in model-fitting, the final analyses used 11 blocks. Goodness-of-fit was adequate for each block, the combined estimate of H being 4.78(95%CI 2.17-10.50) years. However, considerable heterogeneity existed, unexplained by any factor studied, with the random-effects estimate 3.08(1.32-7.16). Sensitivity analyses allowing for reverse causation or differing assumed times for the final quitting period gave similar results. The estimates of H are similar for stroke and IHD, and the individual estimates similarly heterogeneous. Fitting the model is harder for stroke, due to its weaker association with smoking. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Survival modeling for the estimation of transition probabilities in model-based economic evaluations in the absence of individual patient data: a tutorial.

PubMed

Diaby, Vakaramoko; Adunlin, Georges; Montero, Alberto J

2014-02-01

Survival modeling techniques are increasingly being used as part of decision modeling for health economic evaluations. As many models are available, it is imperative for interested readers to know about the steps in selecting and using the most suitable ones. The objective of this paper is to propose a tutorial for the application of appropriate survival modeling techniques to estimate transition probabilities, for use in model-based economic evaluations, in the absence of individual patient data (IPD). An illustration of the use of the tutorial is provided based on the final progression-free survival (PFS) analysis of the BOLERO-2 trial in metastatic breast cancer (mBC). An algorithm was adopted from Guyot and colleagues, and was then run in the statistical package R to reconstruct IPD, based on the final PFS analysis of the BOLERO-2 trial. It should be emphasized that the reconstructed IPD represent an approximation of the original data. Afterwards, we fitted parametric models to the reconstructed IPD in the statistical package Stata. Both statistical and graphical tests were conducted to verify the relative and absolute validity of the findings. Finally, the equations for transition probabilities were derived using the general equation for transition probabilities used in model-based economic evaluations, and the parameters were estimated from fitted distributions. The results of the application of the tutorial suggest that the log-logistic model best fits the reconstructed data from the latest published Kaplan-Meier (KM) curves of the BOLERO-2 trial. Results from the regression analyses were confirmed graphically. An equation for transition probabilities was obtained for each arm of the BOLERO-2 trial. In this paper, a tutorial was proposed and used to estimate the transition probabilities for model-based economic evaluation, based on the results of the final PFS analysis of the BOLERO-2 trial in mBC. The results of our study can serve as a basis for any model (Markov) that needs the parameterization of transition probabilities, and only has summary KM plots available.

Using R and WinBUGS to fit a Generalized Partial Credit Model for developing and evaluating patient-reported outcomes assessments

PubMed Central

Li, Yuelin; Baser, Ray

2013-01-01

The US Food and Drug Administration recently announced the final guidelines on the development and validation of Patient-Reported Outcomes (PROs) assessments in drug labeling and clinical trials. This guidance paper may boost the demand for new PRO survey questionnaires. Henceforth biostatisticians may encounter psychometric methods more frequently, particularly Item Response Theory (IRT) models to guide the shortening of a PRO assessment instrument. This article aims to provide an introduction on the theory and practical analytic skills in fitting a Generalized Partial Credit Model in IRT (GPCM). GPCM theory is explained first, with special attention to a clearer exposition of the formal mathematics than what is typically available in the psychometric literature. Then a worked example is presented, using self-reported responses taken from the International Personality Item Pool. The worked example contains step-by-step guides on using the statistical languages R and WinBUGS in fitting the GPCM. Finally, the Fisher information function of the GPCM model is derived and used to evaluate, as an illustrative example, the usefulness of assessment items by their information contents. This article aims to encourage biostatisticians to apply IRT models in the re-analysis of existing data and in future research. PMID:22362655

Using R and WinBUGS to fit a generalized partial credit model for developing and evaluating patient-reported outcomes assessments.

PubMed

Li, Yuelin; Baser, Ray

2012-08-15

The US Food and Drug Administration recently announced the final guidelines on the development and validation of patient-reported outcomes (PROs) assessments in drug labeling and clinical trials. This guidance paper may boost the demand for new PRO survey questionnaires. Henceforth, biostatisticians may encounter psychometric methods more frequently, particularly item response theory (IRT) models to guide the shortening of a PRO assessment instrument. This article aims to provide an introduction on the theory and practical analytic skills in fitting a generalized partial credit model (GPCM) in IRT. GPCM theory is explained first, with special attention to a clearer exposition of the formal mathematics than what is typically available in the psychometric literature. Then, a worked example is presented, using self-reported responses taken from the international personality item pool. The worked example contains step-by-step guides on using the statistical languages r and WinBUGS in fitting the GPCM. Finally, the Fisher information function of the GPCM model is derived and used to evaluate, as an illustrative example, the usefulness of assessment items by their information contents. This article aims to encourage biostatisticians to apply IRT models in the re-analysis of existing data and in future research. Copyright © 2012 John Wiley & Sons, Ltd.

A New Z Score Curve of the Coronary Arterial Internal Diameter Using the Lambda-Mu-Sigma Method in a Pediatric Population.

PubMed

Kobayashi, Tohru; Fuse, Shigeto; Sakamoto, Naoko; Mikami, Masashi; Ogawa, Shunichi; Hamaoka, Kenji; Arakaki, Yoshio; Nakamura, Tsuneyuki; Nagasawa, Hiroyuki; Kato, Taichi; Jibiki, Toshiaki; Iwashima, Satoru; Yamakawa, Masaru; Ohkubo, Takashi; Shimoyama, Shinya; Aso, Kentaro; Sato, Seiichi; Saji, Tsutomu

2016-08-01

Several coronary artery Z score models have been developed. However, a Z score model derived by the lambda-mu-sigma (LMS) method has not been established. Echocardiographic measurements of the proximal right coronary artery, left main coronary artery, proximal left anterior descending coronary artery, and proximal left circumflex artery were prospectively collected in 3,851 healthy children ≤18 years of age and divided into developmental and validation data sets. In the developmental data set, smooth curves were fitted for each coronary artery using linear, logarithmic, square-root, and LMS methods for both sexes. The relative goodness of fit of these models was compared using the Bayesian information criterion. The best-fitting model was tested for reproducibility using the validation data set. The goodness of fit of the selected model was visually compared with that of the previously reported regression models using a Q-Q plot. Because the internal diameter of each coronary artery was not similar between sexes, sex-specific Z score models were developed. The LMS model with body surface area as the independent variable showed the best goodness of fit; therefore, the internal diameter of each coronary artery was transformed into a sex-specific Z score on the basis of body surface area using the LMS method. In the validation data set, a Q-Q plot of each model indicated that the distribution of Z scores in the LMS models was closer to the normal distribution compared with previously reported regression models. Finally, the final models for each coronary artery in both sexes were developed using the developmental and validation data sets. A Microsoft Excel-based Z score calculator was also created, which is freely available online (http://raise.umin.jp/zsp/calculator/). Novel LMS models with which to estimate the sex-specific Z score of each internal coronary artery diameter were generated and validated using a large pediatric population. Copyright © 2016 American Society of Echocardiography. Published by Elsevier Inc. All rights reserved.

Fitting membrane resistance along with action potential shape in cardiac myocytes improves convergence: application of a multi-objective parallel genetic algorithm.

PubMed

Kaur, Jaspreet; Nygren, Anders; Vigmond, Edward J

2014-01-01

Fitting parameter sets of non-linear equations in cardiac single cell ionic models to reproduce experimental behavior is a time consuming process. The standard procedure is to adjust maximum channel conductances in ionic models to reproduce action potentials (APs) recorded in isolated cells. However, vastly different sets of parameters can produce similar APs. Furthermore, even with an excellent AP match in case of single cell, tissue behaviour may be very different. We hypothesize that this uncertainty can be reduced by additionally fitting membrane resistance (Rm). To investigate the importance of Rm, we developed a genetic algorithm approach which incorporated Rm data calculated at a few points in the cycle, in addition to AP morphology. Performance was compared to a genetic algorithm using only AP morphology data. The optimal parameter sets and goodness of fit as computed by the different methods were compared. First, we fit an ionic model to itself, starting from a random parameter set. Next, we fit the AP of one ionic model to that of another. Finally, we fit an ionic model to experimentally recorded rabbit action potentials. Adding the extra objective (Rm, at a few voltages) to the AP fit, lead to much better convergence. Typically, a smaller MSE (mean square error, defined as the average of the squared error between the target AP and AP that is to be fitted) was achieved in one fifth of the number of generations compared to using only AP data. Importantly, the variability in fit parameters was also greatly reduced, with many parameters showing an order of magnitude decrease in variability. Adding Rm to the objective function improves the robustness of fitting, better preserving tissue level behavior, and should be incorporated.

Universality Classes of Interaction Structures for NK Fitness Landscapes

NASA Astrophysics Data System (ADS)

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

2018-07-01

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

Universality Classes of Interaction Structures for NK Fitness Landscapes

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Approximations to galaxy star formation rate histories: properties and uses of two examples

NASA Astrophysics Data System (ADS)

Cohn, J. D.

2018-05-01

Galaxies evolve via a complex interaction of numerous different physical processes, scales and components. In spite of this, overall trends often appear. Simplified models for galaxy histories can be used to search for and capture such emergent trends, and thus to interpret and compare results of galaxy formation models to each other and to nature. Here, two approximations are applied to galaxy integrated star formation rate histories, drawn from a semi-analytic model grafted onto a dark matter simulation. Both a lognormal functional form and principal component analysis (PCA) approximate the integrated star formation rate histories fairly well. Machine learning, based upon simplified galaxy halo histories, is somewhat successful at recovering both fits. The fits to the histories give fixed time star formation rates which have notable scatter from their true final time rates, especially for quiescent and "green valley" galaxies, and more so for the PCA fit. For classifying galaxies into subfamilies sharing similar integrated histories, both approximations are better than using final stellar mass or specific star formation rate. Several subsamples from the simulation illustrate how these simple parameterizations provide points of contact for comparisons between different galaxy formation samples, or more generally, models. As a side result, the halo masses of simulated galaxies with early peak star formation rate (according to the lognormal fit) are bimodal. The galaxies with a lower halo mass at peak star formation rate appear to stall in their halo growth, even though they are central in their host halos.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, Tao; Li, Cheng; Huang, Can

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

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

DOE PAGES

Ding, Tao; Li, Cheng; Huang, Can; ...

2017-01-09

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

Percolation on fitness landscapes: effects of correlation, phenotype, and incompatibilities

PubMed Central

Gravner, Janko; Pitman, Damien; Gavrilets, Sergey

2009-01-01

We study how correlations in the random fitness assignment may affect the structure of fitness landscapes, in three classes of fitness models. The first is a phenotype space in which individuals are characterized by a large number n of continuously varying traits. In a simple model of random fitness assignment, viable phenotypes are likely to form a giant connected cluster percolating throughout the phenotype space provided the viability probability is larger than 1/2n. The second model explicitly describes genotype-to-phenotype and phenotype-to-fitness maps, allows for neutrality at both phenotype and fitness levels, and results in a fitness landscape with tunable correlation length. Here, phenotypic neutrality and correlation between fitnesses can reduce the percolation threshold, and correlations at the point of phase transition between local and global are most conducive to the formation of the giant cluster. In the third class of models, particular combinations of alleles or values of phenotypic characters are “incompatible” in the sense that the resulting genotypes or phenotypes have zero fitness. This setting can be viewed as a generalization of the canonical Bateson-Dobzhansky-Muller model of speciation and is related to K- SAT problems, prominent in computer science. We analyze the conditions for the existence of viable genotypes, their number, as well as the structure and the number of connected clusters of viable genotypes. We show that analysis based on expected values can easily lead to wrong conclusions, especially when fitness correlations are strong. We focus on pairwise incompatibilities between diallelic loci, but we also address multiple alleles, complex incompatibilities, and continuous phenotype spaces. In the case of diallelic loci, the number of clusters is stochastically bounded and each cluster contains a very large sub-cube. Finally, we demonstrate that the discrete NK model shares some signature properties of models with high correlations. PMID:17692873

Decomposition of mineral absorption bands using nonlinear least squares curve fitting: Application to Martian meteorites and CRISM data

NASA Astrophysics Data System (ADS)

Parente, Mario; Makarewicz, Heather D.; Bishop, Janice L.

2011-04-01

This study advances curve-fitting modeling of absorption bands of reflectance spectra and applies this new model to spectra of Martian meteorites ALH 84001 and EETA 79001 and data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM). This study also details a recently introduced automated parameter initialization technique. We assess the performance of this automated procedure by comparing it to the currently available initialization method and perform a sensitivity analysis of the fit results to variation in initial guesses. We explore the issues related to the removal of the continuum, offer guidelines for continuum removal when modeling the absorptions and explore different continuum-removal techniques. We further evaluate the suitability of curve fitting techniques using Gaussians/Modified Gaussians to decompose spectra into individual end-member bands. We show that nonlinear least squares techniques such as the Levenberg-Marquardt algorithm achieve comparable results to the MGM model ( Sunshine and Pieters, 1993; Sunshine et al., 1990) for meteorite spectra. Finally we use Gaussian modeling to fit CRISM spectra of pyroxene and olivine-rich terrains on Mars. Analysis of CRISM spectra of two regions show that the pyroxene-dominated rock spectra measured at Juventae Chasma were modeled well with low Ca pyroxene, while the pyroxene-rich spectra acquired at Libya Montes required both low-Ca and high-Ca pyroxene for a good fit.

Enzymes with lid-gated active sites must operate by an induced fit mechanism instead of conformational selection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sullivan, Sarah M.; Holyoak, Todd

2008-09-17

The induced fit and conformational selection/population shift models are two extreme cases of a continuum aimed at understanding the mechanism by which the final key-lock or active enzyme conformation is achieved upon formation of the correctly ligated enzyme. Structures of complexes representing the Michaelis and enolate intermediate complexes of the reaction catalyzed by phosphoenolpyruvate carboxykinase provide direct structural evidence for the encounter complex that is intrinsic to the induced fit model and not required by the conformational selection model. In addition, the structural data demonstrate that the conformational selection model is not sufficient to explain the correlation between dynamics andmore » catalysis in phosphoenolpyruvate carboxykinase and other enzymes in which the transition between the uninduced and the induced conformations occludes the active site from the solvent. The structural data are consistent with a model in that the energy input from substrate association results in changes in the free energy landscape for the protein, allowing for structural transitions along an induced fit pathway.« less

Enzymes With Lid-Gated Active Sites Must Operate By An Induced Fit Mechanism Instead of Conformational Selection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sullivan, S.M.; Holyoak, T.

2009-05-26

The induced fit and conformational selection/population shift models are two extreme cases of a continuum aimed at understanding the mechanism by which the final key-lock or active enzyme conformation is achieved upon formation of the correctly ligated enzyme. Structures of complexes representing the Michaelis and enolate intermediate complexes of the reaction catalyzed by phosphoenolpyruvate carboxykinase provide direct structural evidence for the encounter complex that is intrinsic to the induced fit model and not required by the conformational selection model. In addition, the structural data demonstrate that the conformational selection model is not sufficient to explain the correlation between dynamics andmore » catalysis in phosphoenolpyruvate carboxykinase and other enzymes in which the transition between the uninduced and the induced conformations occludes the active site from the solvent. The structural data are consistent with a model in that the energy input from substrate association results in changes in the free energy landscape for the protein, allowing for structural transitions along an induced fit pathway.« less

Modeling two strains of disease via aggregate-level infectivity curves.

PubMed

Romanescu, Razvan; Deardon, Rob

2016-04-01

Well formulated models of disease spread, and efficient methods to fit them to observed data, are powerful tools for aiding the surveillance and control of infectious diseases. Our project considers the problem of the simultaneous spread of two related strains of disease in a context where spatial location is the key driver of disease spread. We start our modeling work with the individual level models (ILMs) of disease transmission, and extend these models to accommodate the competing spread of the pathogens in a two-tier hierarchical population (whose levels we refer to as 'farm' and 'animal'). The postulated interference mechanism between the two strains is a period of cross-immunity following infection. We also present a framework for speeding up the computationally intensive process of fitting the ILM to data, typically done using Markov chain Monte Carlo (MCMC) in a Bayesian framework, by turning the inference into a two-stage process. First, we approximate the number of animals infected on a farm over time by infectivity curves. These curves are fit to data sampled from farms, using maximum likelihood estimation, then, conditional on the fitted curves, Bayesian MCMC inference proceeds for the remaining parameters. Finally, we use posterior predictive distributions of salient epidemic summary statistics, in order to assess the model fitted.

Exploring the measurement properties of the osteopathy clinical teaching questionnaire using Rasch analysis.

PubMed

Vaughan, Brett

2018-01-01

Clinical teaching evaluations are common in health profession education programs to ensure students are receiving a quality clinical education experience. Questionnaires students use to evaluate their clinical teachers have been developed in professions such as medicine and nursing. The development of a questionnaire that is specifically for the osteopathy on-campus, student-led clinic environment is warranted. Previous work developed the 30-item Osteopathy Clinical Teaching Questionnaire. The current study utilised Rasch analysis to investigate the construct validity of the Osteopathy Clinical Teaching Questionnaire and provide evidence for the validity argument through fit to the Rasch model. Senior osteopathy students at four institutions in Australia, New Zealand and the United Kingdom rated their clinical teachers using the Osteopathy Clinical Teaching Questionnaire. Three hundred and ninety-nine valid responses were received and the data were evaluated for fit to the Rasch model. Reliability estimations (Cronbach's alpha and McDonald's omega) were also evaluated for the final model. The initial analysis demonstrated the data did not fit the Rasch model. Accordingly, modifications to the questionnaire were made including removing items, removing person responses, and rescoring one item. The final model contained 12 items and fit to the Rasch model was adequate. Support for unidimensionality was demonstrated through both the Principal Components Analysis/t-test, and the Cronbach's alpha and McDonald's omega reliability estimates. Analysis of the questionnaire using McDonald's omega hierarchical supported a general factor (quality of clinical teaching in osteopathy). The evidence for unidimensionality and the presence of a general factor support the calculation of a total score for the questionnaire as a sufficient statistic. Further work is now required to investigate the reliability of the 12-item Osteopathy Clinical Teaching Questionnaire to provide evidence for the validity argument.

A crystal plasticity model for slip in hexagonal close packed metals based on discrete dislocation simulations

NASA Astrophysics Data System (ADS)

Messner, Mark C.; Rhee, Moono; Arsenlis, Athanasios; Barton, Nathan R.

2017-06-01

This work develops a method for calibrating a crystal plasticity model to the results of discrete dislocation (DD) simulations. The crystal model explicitly represents junction formation and annihilation mechanisms and applies these mechanisms to describe hardening in hexagonal close packed metals. The model treats these dislocation mechanisms separately from elastic interactions among populations of dislocations, which the model represents through a conventional strength-interaction matrix. This split between elastic interactions and junction formation mechanisms more accurately reproduces the DD data and results in a multi-scale model that better represents the lower scale physics. The fitting procedure employs concepts of machine learning—feature selection by regularized regression and cross-validation—to develop a robust, physically accurate crystal model. The work also presents a method for ensuring the final, calibrated crystal model respects the physical symmetries of the crystal system. Calibrating the crystal model requires fitting two linear operators: one describing elastic dislocation interactions and another describing junction formation and annihilation dislocation reactions. The structure of these operators in the final, calibrated model reflect the crystal symmetry and slip system geometry of the DD simulations.

Basal glycogenolysis in mouse skeletal muscle: in vitro model predicts in vivo fluxes

NASA Technical Reports Server (NTRS)

Lambeth, Melissa J.; Kushmerick, Martin J.; Marcinek, David J.; Conley, Kevin E.

2002-01-01

A previously published mammalian kinetic model of skeletal muscle glycogenolysis, consisting of literature in vitro parameters, was modified by substituting mouse specific Vmax values. The model demonstrates that glycogen breakdown to lactate is under ATPase control. Our criteria to test whether in vitro parameters could reproduce in vivo dynamics was the ability of the model to fit phosphocreatine (PCr) and inorganic phosphate (Pi) dynamic NMR data from ischemic basal mouse hindlimbs and predict biochemically-assayed lactate concentrations. Fitting was accomplished by optimizing four parameters--the ATPase rate coefficient, fraction of activated glycogen phosphorylase, and the equilibrium constants of creatine kinase and adenylate kinase (due to the absence of pH in the model). The optimized parameter values were physiologically reasonable, the resultant model fit the [PCr] and [Pi] timecourses well, and the model predicted the final measured lactate concentration. This result demonstrates that additional features of in vivo enzyme binding are not necessary for quantitative description of glycogenolytic dynamics.

The structural invariance of the Temporal Experience of Pleasure Scale across time and culture.

PubMed

Li, Zhi; Shi, Hai-Song; Elis, Ori; Yang, Zhuo-Ya; Wang, Ya; Lui, Simon S Y; Cheung, Eric F C; Kring, Ann M; Chan, Raymond C K

2018-06-01

The Temporal Experience of Pleasure Scale (TEPS) is a self-report instrument that assesses pleasure experience. Initial scale development and validation in the United States yielded a two-factor solution comprising anticipatory and consummatory pleasure. However, a four-factor model that further parsed anticipatory and consummatory pleasure experience into abstract and contextual components was a better model fit in China. In this study, we tested both models using confirmatory factor analysis in an American and a Chinese sample and examined the configural measurement invariance of both models across culture. We also examined the temporal stability of the four-factor model in the Chinese sample. The results indicated that the four-factor model of the TEPS was a better fit than the two-factor model in the Chinese sample. In contrast, both models fit the American sample, which also included many Asian American participants. The four-factor model fit both the Asian American and Chinese samples equally well. Finally, the four-factor model demonstrated good measurement and structural invariance across culture and time, suggesting that this model may be applicable in both cross-cultural and longitudinal studies. © 2018 The Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Nonbleeding adenomas: Evidence of systematic false-negative fecal immunochemical test results and their implications for screening effectiveness-A modeling study.

PubMed

van der Meulen, Miriam P; Lansdorp-Vogelaar, Iris; van Heijningen, Else-Mariëtte B; Kuipers, Ernst J; van Ballegooijen, Marjolein

2016-06-01

If some adenomas do not bleed over several years, they will cause systematic false-negative fecal immunochemical test (FIT) results. The long-term effectiveness of FIT screening has been estimated without accounting for such systematic false-negativity. There are now data with which to evaluate this issue. The authors developed one microsimulation model (MISCAN [MIcrosimulation SCreening ANalysis]-Colon) without systematic false-negative FIT results and one model that allowed a percentage of adenomas to be systematically missed in successive FIT screening rounds. Both variants were adjusted to reproduce the first-round findings of the Dutch CORERO FIT screening trial. The authors then compared simulated detection rates in the second screening round with those observed, and adjusted the simulated percentage of systematically missed adenomas to those data. Finally, the authors calculated the impact of systematic false-negative FIT results on the effectiveness of repeated FIT screening. The model without systematic false-negativity simulated higher detection rates in the second screening round than observed. These observed rates could be reproduced when assuming that FIT systematically missed 26% of advanced and 73% of nonadvanced adenomas. To reduce the false-positive rate in the second round to the observed level, the authors also had to assume that 30% of false-positive findings were systematically false-positive. Systematic false-negative FIT testing limits the long-term reduction of biennial FIT screening in the incidence of colorectal cancer (35.6% vs 40.9%) and its mortality (55.2% vs 59.0%) in participants. The results of the current study provide convincing evidence based on the combination of real-life and modeling data that a percentage of adenomas are systematically missed by repeat FIT screening. This impairs the efficacy of FIT screening. Cancer 2016;122:1680-8. © 2016 American Cancer Society. © 2016 American Cancer Society.

Using the Mixed Rasch Model to analyze data from the beliefs and attitudes about memory survey.

PubMed

Smith, Everett V; Ying, Yuping; Brown, Scott W

2012-01-01

In this study, we used the Mixed Rasch Model (MRM) to analyze data from the Beliefs and Attitudes About Memory Survey (BAMS; Brown, Garry, Silver, and Loftus, 1997). We used the original 5-point BAMS data to investigate the functioning of the "Neutral" category via threshold analysis under a 2-class MRM solution. The "Neutral" category was identified as not eliciting the model expected responses and observations in the "Neutral" category were subsequently treated as missing data. For the BAMS data without the "Neutral" category, exploratory MRM analyses specifying up to 5 latent classes were conducted to evaluate data-model fit using the consistent Akaike information criterion (CAIC). For each of three BAMS subscales, a two latent class solution was identified as fitting the mixed Rasch rating scale model the best. Results regarding threshold analysis, person parameters, and item fit based on the final models are presented and discussed as well as the implications of this study.

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

NASA Astrophysics Data System (ADS)

Barker, Hallie; Paust, Nathaniel E. Q.

2018-03-01

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

The structural relationships between organizational commitment, global job satisfaction, developmental experiences, work values, organizational support, and person-organization fit among nursing faculty.

PubMed

Gutierrez, Antonio P; Candela, Lori L; Carver, Lara

2012-07-01

GUTIERAIM: The aim of this correlational study was to examine the relations between organizational commitment, perceived organizational support, work values, person-organization fit, developmental experiences, and global job satisfaction among nursing faculty. The global nursing shortage is well documented. At least 57 countries have reported critical shortages. The lack of faculty is finally being recognized as a major issue directly influencing the ability to admit and graduate adequate numbers of nurses. As efforts increase to both recruit and retain faculty, the concept of organizational commitment and what it means to them is important to consider. A cross-sectional correlational design was used. The present study investigated the underlying structure of various organizational factors using structural equation modelling. Data were collected from a stratified random sample of nurse faculty during the academic year 2006-2007. The final model demonstrated that perceived organizational support, developmental experiences, person-organization fit, and global job satisfaction positively predicted nurse faculty's organizational commitment to the academic organization. Cross-validation results indicated that the final full SEM is valid and reliable. Nursing faculty administrators able to use mentoring skills are well equipped to build positive relationships with nursing faculty, which in turn, can lead to increased organizational commitment, productivity, job satisfaction, and perceived organizational support, among others. © 2012 Blackwell Publishing Ltd.

Regression Models for Identifying Noise Sources in Magnetic Resonance Images

PubMed Central

Zhu, Hongtu; Li, Yimei; Ibrahim, Joseph G.; Shi, Xiaoyan; An, Hongyu; Chen, Yashen; Gao, Wei; Lin, Weili; Rowe, Daniel B.; Peterson, Bradley S.

2009-01-01

Stochastic noise, susceptibility artifacts, magnetic field and radiofrequency inhomogeneities, and other noise components in magnetic resonance images (MRIs) can introduce serious bias into any measurements made with those images. We formally introduce three regression models including a Rician regression model and two associated normal models to characterize stochastic noise in various magnetic resonance imaging modalities, including diffusion-weighted imaging (DWI) and functional MRI (fMRI). Estimation algorithms are introduced to maximize the likelihood function of the three regression models. We also develop a diagnostic procedure for systematically exploring MR images to identify noise components other than simple stochastic noise, and to detect discrepancies between the fitted regression models and MRI data. The diagnostic procedure includes goodness-of-fit statistics, measures of influence, and tools for graphical display. The goodness-of-fit statistics can assess the key assumptions of the three regression models, whereas measures of influence can isolate outliers caused by certain noise components, including motion artifacts. The tools for graphical display permit graphical visualization of the values for the goodness-of-fit statistic and influence measures. Finally, we conduct simulation studies to evaluate performance of these methods, and we analyze a real dataset to illustrate how our diagnostic procedure localizes subtle image artifacts by detecting intravoxel variability that is not captured by the regression models. PMID:19890478

Scaling analysis and model estimation of solar corona index

NASA Astrophysics Data System (ADS)

Ray, Samujjwal; Ray, Rajdeep; Khondekar, Mofazzal Hossain; Ghosh, Koushik

2018-04-01

A monthly average solar green coronal index time series for the period from January 1939 to December 2008 collected from NOAA (The National Oceanic and Atmospheric Administration) has been analysed in this paper in perspective of scaling analysis and modelling. Smoothed and de-noising have been done using suitable mother wavelet as a pre-requisite. The Finite Variance Scaling Method (FVSM), Higuchi method, rescaled range (R/S) and a generalized method have been applied to calculate the scaling exponents and fractal dimensions of the time series. Autocorrelation function (ACF) is used to find autoregressive (AR) process and Partial autocorrelation function (PACF) has been used to get the order of AR model. Finally a best fit model has been proposed using Yule-Walker Method with supporting results of goodness of fit and wavelet spectrum. The results reveal an anti-persistent, Short Range Dependent (SRD), self-similar property with signatures of non-causality, non-stationarity and nonlinearity in the data series. The model shows the best fit to the data under observation.

76 FR 31936 - Non-Malleable Cast Iron Pipe Fittings From the People's Republic of China: Final Results of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-02

... Fittings From the People's Republic of China: Final Results of Antidumping Duty Administrative Review... (``pipe fittings'') from the People's Republic of China (``PRC'').\\1\\ We gave interested parties an... Fittings From the People's Republic of China: Preliminary Results of Antidumping Duty Administrative Review...

Bak-Sneppen model: Local equilibrium and critical value.

PubMed

Fraiman, Daniel

2018-04-01

The Bak-Sneppen (BS) model is a very simple model that exhibits all the richness of self-organized criticality theory. At the thermodynamic limit, the BS model converges to a situation where all particles have a fitness that is uniformly distributed between a critical value p_{c} and 1. The p_{c} value is unknown, as are the variables that influence and determine this value. Here we study the BS model in the case in which the lowest fitness particle interacts with an arbitrary even number of m nearest neighbors. We show that p_{c} verifies a simple local equilibrium relation. Based on this relation, we can determine bounds for p_{c} of the BS model and exact results for some BS-like models. Finally, we show how transformations of the original BS model can be done without altering the model's complex dynamics.

Bak-Sneppen model: Local equilibrium and critical value

NASA Astrophysics Data System (ADS)

Fraiman, Daniel

2018-04-01

The Bak-Sneppen (BS) model is a very simple model that exhibits all the richness of self-organized criticality theory. At the thermodynamic limit, the BS model converges to a situation where all particles have a fitness that is uniformly distributed between a critical value pc and 1. The pc value is unknown, as are the variables that influence and determine this value. Here we study the BS model in the case in which the lowest fitness particle interacts with an arbitrary even number of m nearest neighbors. We show that pc verifies a simple local equilibrium relation. Based on this relation, we can determine bounds for pc of the BS model and exact results for some BS-like models. Finally, we show how transformations of the original BS model can be done without altering the model's complex dynamics.

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.

Model-Free Estimation of Tuning Curves and Their Attentional Modulation, Based on Sparse and Noisy Data.

PubMed

Helmer, Markus; Kozyrev, Vladislav; Stephan, Valeska; Treue, Stefan; Geisel, Theo; Battaglia, Demian

2016-01-01

Tuning curves are the functions that relate the responses of sensory neurons to various values within one continuous stimulus dimension (such as the orientation of a bar in the visual domain or the frequency of a tone in the auditory domain). They are commonly determined by fitting a model e.g. a Gaussian or other bell-shaped curves to the measured responses to a small subset of discrete stimuli in the relevant dimension. However, as neuronal responses are irregular and experimental measurements noisy, it is often difficult to determine reliably the appropriate model from the data. We illustrate this general problem by fitting diverse models to representative recordings from area MT in rhesus monkey visual cortex during multiple attentional tasks involving complex composite stimuli. We find that all models can be well-fitted, that the best model generally varies between neurons and that statistical comparisons between neuronal responses across different experimental conditions are affected quantitatively and qualitatively by specific model choices. As a robust alternative to an often arbitrary model selection, we introduce a model-free approach, in which features of interest are extracted directly from the measured response data without the need of fitting any model. In our attentional datasets, we demonstrate that data-driven methods provide descriptions of tuning curve features such as preferred stimulus direction or attentional gain modulations which are in agreement with fit-based approaches when a good fit exists. Furthermore, these methods naturally extend to the frequent cases of uncertain model selection. We show that model-free approaches can identify attentional modulation patterns, such as general alterations of the irregular shape of tuning curves, which cannot be captured by fitting stereotyped conventional models. Finally, by comparing datasets across different conditions, we demonstrate effects of attention that are cell- and even stimulus-specific. Based on these proofs-of-concept, we conclude that our data-driven methods can reliably extract relevant tuning information from neuronal recordings, including cells whose seemingly haphazard response curves defy conventional fitting approaches.

Model-Free Estimation of Tuning Curves and Their Attentional Modulation, Based on Sparse and Noisy Data

PubMed Central

Helmer, Markus; Kozyrev, Vladislav; Stephan, Valeska; Treue, Stefan; Geisel, Theo; Battaglia, Demian

2016-01-01

Tuning curves are the functions that relate the responses of sensory neurons to various values within one continuous stimulus dimension (such as the orientation of a bar in the visual domain or the frequency of a tone in the auditory domain). They are commonly determined by fitting a model e.g. a Gaussian or other bell-shaped curves to the measured responses to a small subset of discrete stimuli in the relevant dimension. However, as neuronal responses are irregular and experimental measurements noisy, it is often difficult to determine reliably the appropriate model from the data. We illustrate this general problem by fitting diverse models to representative recordings from area MT in rhesus monkey visual cortex during multiple attentional tasks involving complex composite stimuli. We find that all models can be well-fitted, that the best model generally varies between neurons and that statistical comparisons between neuronal responses across different experimental conditions are affected quantitatively and qualitatively by specific model choices. As a robust alternative to an often arbitrary model selection, we introduce a model-free approach, in which features of interest are extracted directly from the measured response data without the need of fitting any model. In our attentional datasets, we demonstrate that data-driven methods provide descriptions of tuning curve features such as preferred stimulus direction or attentional gain modulations which are in agreement with fit-based approaches when a good fit exists. Furthermore, these methods naturally extend to the frequent cases of uncertain model selection. We show that model-free approaches can identify attentional modulation patterns, such as general alterations of the irregular shape of tuning curves, which cannot be captured by fitting stereotyped conventional models. Finally, by comparing datasets across different conditions, we demonstrate effects of attention that are cell- and even stimulus-specific. Based on these proofs-of-concept, we conclude that our data-driven methods can reliably extract relevant tuning information from neuronal recordings, including cells whose seemingly haphazard response curves defy conventional fitting approaches. PMID:26785378

Prediction uncertainty and optimal experimental design for learning dynamical systems.

PubMed

Letham, Benjamin; Letham, Portia A; Rudin, Cynthia; Browne, Edward P

2016-06-01

Dynamical systems are frequently used to model biological systems. When these models are fit to data, it is necessary to ascertain the uncertainty in the model fit. Here, we present prediction deviation, a metric of uncertainty that determines the extent to which observed data have constrained the model's predictions. This is accomplished by solving an optimization problem that searches for a pair of models that each provides a good fit for the observed data, yet has maximally different predictions. We develop a method for estimating a priori the impact that additional experiments would have on the prediction deviation, allowing the experimenter to design a set of experiments that would most reduce uncertainty. We use prediction deviation to assess uncertainty in a model of interferon-alpha inhibition of viral infection, and to select a sequence of experiments that reduces this uncertainty. Finally, we prove a theoretical result which shows that prediction deviation provides bounds on the trajectories of the underlying true model. These results show that prediction deviation is a meaningful metric of uncertainty that can be used for optimal experimental design.

Development of a Self-Report Physical Function Instrument for Disability Assessment: Item Pool Construction and Factor Analysis

PubMed Central

McDonough, Christine M.; Jette, Alan M.; Ni, Pengsheng; Bogusz, Kara; Marfeo, Elizabeth E; Brandt, Diane E; Chan, Leighton; Meterko, Mark; Haley, Stephen M.; Rasch, Elizabeth K.

2014-01-01

Objectives To build a comprehensive item pool representing work-relevant physical functioning and to test the factor structure of the item pool. These developmental steps represent initial outcomes of a broader project to develop instruments for the assessment of function within the context of Social Security Administration (SSA) disability programs. Design Comprehensive literature review; gap analysis; item generation with expert panel input; stakeholder interviews; cognitive interviews; cross-sectional survey administration; and exploratory and confirmatory factor analyses to assess item pool structure. Setting In-person and semi-structured interviews; internet and telephone surveys. Participants A sample of 1,017 SSA claimants, and a normative sample of 999 adults from the US general population. Interventions Not Applicable. Main Outcome Measure Model fit statistics Results The final item pool consisted of 139 items. Within the claimant sample 58.7% were white; 31.8% were black; 46.6% were female; and the mean age was 49.7 years. Initial factor analyses revealed a 4-factor solution which included more items and allowed separate characterization of: 1) Changing and Maintaining Body Position, 2) Whole Body Mobility, 3) Upper Body Function and 4) Upper Extremity Fine Motor. The final 4-factor model included 91 items. Confirmatory factor analyses for the 4-factor models for the claimant and the normative samples demonstrated very good fit. Fit statistics for claimant and normative samples respectively were: Comparative Fit Index = 0.93 and 0.98; Tucker-Lewis Index = 0.92 and 0.98; Root Mean Square Error Approximation = 0.05 and 0.04. Conclusions The factor structure of the Physical Function item pool closely resembled the hypothesized content model. The four scales relevant to work activities offer promise for providing reliable information about claimant physical functioning relevant to work disability. PMID:23542402

Development of a self-report physical function instrument for disability assessment: item pool construction and factor analysis.

PubMed

McDonough, Christine M; Jette, Alan M; Ni, Pengsheng; Bogusz, Kara; Marfeo, Elizabeth E; Brandt, Diane E; Chan, Leighton; Meterko, Mark; Haley, Stephen M; Rasch, Elizabeth K

2013-09-01

To build a comprehensive item pool representing work-relevant physical functioning and to test the factor structure of the item pool. These developmental steps represent initial outcomes of a broader project to develop instruments for the assessment of function within the context of Social Security Administration (SSA) disability programs. Comprehensive literature review; gap analysis; item generation with expert panel input; stakeholder interviews; cognitive interviews; cross-sectional survey administration; and exploratory and confirmatory factor analyses to assess item pool structure. In-person and semistructured interviews and Internet and telephone surveys. Sample of SSA claimants (n=1017) and a normative sample of adults from the U.S. general population (n=999). Not applicable. Model fit statistics. The final item pool consisted of 139 items. Within the claimant sample, 58.7% were white; 31.8% were black; 46.6% were women; and the mean age was 49.7 years. Initial factor analyses revealed a 4-factor solution, which included more items and allowed separate characterization of: (1) changing and maintaining body position, (2) whole body mobility, (3) upper body function, and (4) upper extremity fine motor. The final 4-factor model included 91 items. Confirmatory factor analyses for the 4-factor models for the claimant and the normative samples demonstrated very good fit. Fit statistics for claimant and normative samples, respectively, were: Comparative Fit Index=.93 and .98; Tucker-Lewis Index=.92 and .98; and root mean square error approximation=.05 and .04. The factor structure of the physical function item pool closely resembled the hypothesized content model. The 4 scales relevant to work activities offer promise for providing reliable information about claimant physical functioning relevant to work disability. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Adaptive evolutionary walks require neutral intermediates in RNA fitness landscapes.

PubMed

Rendel, Mark D

2011-01-01

In RNA fitness landscapes with interconnected networks of neutral mutations, neutral precursor mutations can play an important role in facilitating the accessibility of epistatic adaptive mutant combinations. I use an exhaustively surveyed fitness landscape model based on short sequence RNA genotypes (and their secondary structure phenotypes) to calculate the minimum rate at which mutants initially appearing as neutral are incorporated into an adaptive evolutionary walk. I show first, that incorporating neutral mutations significantly increases the number of point mutations in a given evolutionary walk when compared to estimates from previous adaptive walk models. Second, that incorporating neutral mutants into such a walk significantly increases the final fitness encountered on that walk - indeed evolutionary walks including neutral steps often reach the global optimum in this model. Third, and perhaps most importantly, evolutionary paths of this kind are often extremely winding in their nature and have the potential to undergo multiple mutations at a given sequence position within a single walk; the potential of these winding paths to mislead phylogenetic reconstruction is briefly considered. Copyright © 2010 Elsevier Inc. All rights reserved.

A single factor underlies the metabolic syndrome: a confirmatory factor analysis.

PubMed

Pladevall, Manel; Singal, Bonita; Williams, L Keoki; Brotons, Carlos; Guyer, Heidi; Sadurni, Josep; Falces, Carles; Serrano-Rios, Manuel; Gabriel, Rafael; Shaw, Jonathan E; Zimmet, Paul Z; Haffner, Steven

2006-01-01

Confirmatory factor analysis (CFA) was used to test the hypothesis that the components of the metabolic syndrome are manifestations of a single common factor. Three different datasets were used to test and validate the model. The Spanish and Mauritian studies included 207 men and 203 women and 1,411 men and 1,650 women, respectively. A third analytical dataset including 847 men was obtained from a previously published CFA of a U.S. population. The one-factor model included the metabolic syndrome core components (central obesity, insulin resistance, blood pressure, and lipid measurements). We also tested an expanded one-factor model that included uric acid and leptin levels. Finally, we used CFA to compare the goodness of fit of one-factor models with the fit of two previously published four-factor models. The simplest one-factor model showed the best goodness-of-fit indexes (comparative fit index 1, root mean-square error of approximation 0.00). Comparisons of one-factor with four-factor models in the three datasets favored the one-factor model structure. The selection of variables to represent the different metabolic syndrome components and model specification explained why previous exploratory and confirmatory factor analysis, respectively, failed to identify a single factor for the metabolic syndrome. These analyses support the current clinical definition of the metabolic syndrome, as well as the existence of a single factor that links all of the core components.

Dissemination Strategies and Devices, Part Four, Final Report for Phase I, Rural Shared Services.

ERIC Educational Resources Information Center

Northern Montana Coll., Havre.

Part Four of a four-part report, designed to identify, synthesize, and evaluate shared services research and development efforts throughout the nation, presents a model to disseminate information concerning shared services information to rural educators. The discussion does not prescribe a "best-fit" model but presents several with an expanded…

The p-wave upper mantle structure beneath an active spreading centre - The Gulf of California

NASA Technical Reports Server (NTRS)

Walck, M. C.

1984-01-01

Over 1400 seismograms of earthquakes in Mexico are analyzed and data sets for the travel time, apparent phase velocity, and relative amplitude information are utilized to produce a tightly constrained, detailed model for depths to 900 km beneath an active oceanic ridge region, the Gulf of California. The data are combined by first inverting the travel times, perturbing that model to fit the p-delta data, and then performing trial and error synthetic seismogram modelling to fit the short-period waveforms. The final model satisfies all three data sets. The ridge model is similar to existing upper mantle models for shield, tectonic-continental, and arc-trench regimes below 400 km, but differs significantly in the upper 350 km. Ridge model velocities are very low in this depth range; the model 'catches up' with the others with a very large velocity gradient from 225 to 390 km.

Hot Dust in Panchromatic SED Fitting: Identification of Active Galactic Nuclei and Improved Galaxy Properties

NASA Astrophysics Data System (ADS)

Leja, Joel; Johnson, Benjamin D.; Conroy, Charlie; van Dokkum, Pieter

2018-02-01

Forward modeling of the full galaxy SED is a powerful technique, providing self-consistent constraints on stellar ages, dust properties, and metallicities. However, the accuracy of these results is contingent on the accuracy of the model. One significant source of uncertainty is the contribution of obscured AGN, as they are relatively common and can produce substantial mid-IR (MIR) emission. Here we include emission from dusty AGN torii in the Prospector SED-fitting framework, and fit the UV–IR broadband photometry of 129 nearby galaxies. We find that 10% of the fitted galaxies host an AGN contributing >10% of the observed galaxy MIR luminosity. We demonstrate the necessity of this AGN component in the following ways. First, we compare observed spectral features to spectral features predicted from our model fit to the photometry. We find that the AGN component greatly improves predictions for observed Hα and Hβ luminosities, as well as mid-infrared Akari and Spitzer/IRS spectra. Second, we show that inclusion of the AGN component changes stellar ages and SFRs by up to a factor of 10, and dust attenuations by up to a factor of 2.5. Finally, we show that the strength of our model AGN component correlates with independent AGN indicators, suggesting that these galaxies truly host AGN. Notably, only 46% of the SED-detected AGN would be detected with a simple MIR color selection. Based on these results, we conclude that SED models which fit MIR data without AGN components are vulnerable to substantial bias in their derived parameters.

Estimation of retinal vessel caliber using model fitting and random forests

NASA Astrophysics Data System (ADS)

Araújo, Teresa; Mendonça, Ana Maria; Campilho, Aurélio

2017-03-01

Retinal vessel caliber changes are associated with several major diseases, such as diabetes and hypertension. These caliber changes can be evaluated using eye fundus images. However, the clinical assessment is tiresome and prone to errors, motivating the development of automatic methods. An automatic method based on vessel crosssection intensity profile model fitting for the estimation of vessel caliber in retinal images is herein proposed. First, vessels are segmented from the image, vessel centerlines are detected and individual segments are extracted and smoothed. Intensity profiles are extracted perpendicularly to the vessel, and the profile lengths are determined. Then, model fitting is applied to the smoothed profiles. A novel parametric model (DoG-L7) is used, consisting on a Difference-of-Gaussians multiplied by a line which is able to describe profile asymmetry. Finally, the parameters of the best-fit model are used for determining the vessel width through regression using ensembles of bagged regression trees with random sampling of the predictors (random forests). The method is evaluated on the REVIEW public dataset. A precision close to the observers is achieved, outperforming other state-of-the-art methods. The method is robust and reliable for width estimation in images with pathologies and artifacts, with performance independent of the range of diameters.

Cognitive and affective influences on perceived risk of ovarian cancer†

PubMed Central

Peipins, Lucy A.; McCarty, Frances; Hawkins, Nikki A.; Rodriguez, Juan L.; Scholl, Lawrence E.; Leadbetter, Steven

2015-01-01

Introduction Studies suggest that both affective and cognitive processes are involved in the perception of vulnerability to cancer and that affect has an early influence in this assessment of risk. We constructed a path model based on a conceptual framework of heuristic reasoning (affect, resemblance, and availability) coupled with cognitive processes involved in developing personal models of cancer causation. Methods From an eligible cohort of 16 700 women in a managed care organization, we randomly selected 2524 women at high, elevated, and average risk of ovarian cancer and administered a questionnaire to test our model (response rate 76.3%). Path analysis delineated the relationships between personal and cognitive characteristics (number of relatives with cancer, age, ideas about cancer causation, perceived resemblance to an affected friend or relative, and ovarian cancer knowledge) and emotional constructs (closeness to an affected relative or friend, time spent processing the cancer experience, and cancer worry) on perceived risk of ovarian cancer. Results Our final model fit the data well (root mean square error of approximation (RMSEA) = 0.028, comparative fit index (CFI) = 0.99, normed fit index (NFI) = 0.98). This final model (1) demonstrated the nature and direction of relationships between cognitive characteristics and perceived risk; (2) showed that time spent processing the cancer experience was associated with cancer worry; and (3) showed that cancer worry moderately influenced perceived risk. Discussion Our results highlight the important role that family cancer experience has on cancer worry and shows how cancer experience translates into personal risk perceptions. This understanding informs the discordance between medical or objective risk assessment and personal risk assessment. PMID:24916837

In vitro differential diagnosis of clavus and verruca by a predictive model generated from electrical impedance.

PubMed

Hung, Chien-Ya; Sun, Pei-Lun; Chiang, Shu-Jen; Jaw, Fu-Shan

2014-01-01

Similar clinical appearances prevent accurate diagnosis of two common skin diseases, clavus and verruca. In this study, electrical impedance is employed as a novel tool to generate a predictive model for differentiating these two diseases. We used 29 clavus and 28 verruca lesions. To obtain impedance parameters, a LCR-meter system was applied to measure capacitance (C), resistance (Re), impedance magnitude (Z), and phase angle (θ). These values were combined with lesion thickness (d) to characterize the tissue specimens. The results from clavus and verruca were then fitted to a univariate logistic regression model with the generalized estimating equations (GEE) method. In model generation, log ZSD and θSD were formulated as predictors by fitting a multiple logistic regression model with the same GEE method. The potential nonlinear effects of covariates were detected by fitting generalized additive models (GAM). Moreover, the model was validated by the goodness-of-fit (GOF) assessments. Significant mean differences of the index d, Re, Z, and θ are found between clavus and verruca (p<0.001). A final predictive model is established with Z and θ indices. The model fits the observed data quite well. In GOF evaluation, the area under the receiver operating characteristics (ROC) curve is 0.875 (>0.7), the adjusted generalized R2 is 0.512 (>0.3), and the p value of the Hosmer-Lemeshow GOF test is 0.350 (>0.05). This technique promises to provide an approved model for differential diagnosis of clavus and verruca. It could provide a rapid, relatively low-cost, safe and non-invasive screening tool in clinic use.

Forecasting incidence of hemorrhagic fever with renal syndrome in China using ARIMA model

PubMed Central

2011-01-01

Background China is a country that is most seriously affected by hemorrhagic fever with renal syndrome (HFRS) with 90% of HFRS cases reported globally. At present, HFRS is getting worse with increasing cases and natural foci in China. Therefore, there is an urgent need for monitoring and predicting HFRS incidence to make the control of HFRS more effective. In this study, we applied a stochastic autoregressive integrated moving average (ARIMA) model with the objective of monitoring and short-term forecasting HFRS incidence in China. Methods Chinese HFRS data from 1975 to 2008 were used to fit ARIMA model. Akaike Information Criterion (AIC) and Ljung-Box test were used to evaluate the constructed models. Subsequently, the fitted ARIMA model was applied to obtain the fitted HFRS incidence from 1978 to 2008 and contrast with corresponding observed values. To assess the validity of the proposed model, the mean absolute percentage error (MAPE) between the observed and fitted HFRS incidence (1978-2008) was calculated. Finally, the fitted ARIMA model was used to forecast the incidence of HFRS of the years 2009 to 2011. All analyses were performed using SAS9.1 with a significant level of p < 0.05. Results The goodness-of-fit test of the optimum ARIMA (0,3,1) model showed non-significant autocorrelations in the residuals of the model (Ljung-Box Q statistic = 5.95,P = 0.3113). The fitted values made by ARIMA (0,3,1) model for years 1978-2008 closely followed the observed values for the same years, with a mean absolute percentage error (MAPE) of 12.20%. The forecast values from 2009 to 2011 were 0.69, 0.86, and 1.21per 100,000 population, respectively. Conclusion ARIMA models applied to historical HFRS incidence data are an important tool for HFRS surveillance in China. This study shows that accurate forecasting of the HFRS incidence is possible using an ARIMA model. If predicted values from this study are accurate, China can expect a rise in HFRS incidence. PMID:21838933

The Chandra Source Catalog 2.0: Spectral Properties

NASA Astrophysics Data System (ADS)

McCollough, Michael L.; Siemiginowska, Aneta; Burke, Douglas; Nowak, Michael A.; Primini, Francis Anthony; Laurino, Omar; Nguyen, Dan T.; Allen, Christopher E.; Anderson, Craig S.; Budynkiewicz, Jamie A.; Chen, Judy C.; Civano, Francesca Maria; D'Abrusco, Raffaele; Doe, Stephen M.; Evans, Ian N.; Evans, Janet D.; Fabbiano, Giuseppina; Gibbs, Danny G., II; Glotfelty, Kenny J.; Graessle, Dale E.; Grier, John D.; Hain, Roger; Hall, Diane M.; Harbo, Peter N.; Houck, John C.; Lauer, Jennifer L.; Lee, Nicholas P.; Martínez-Galarza, Juan Rafael; McDowell, Jonathan C.; Miller, Joseph; McLaughlin, Warren; Morgan, Douglas L.; Mossman, Amy E.; Nichols, Joy S.; Paxson, Charles; Plummer, David A.; Rots, Arnold H.; Sundheim, Beth A.; Tibbetts, Michael; Van Stone, David W.; Zografou, Panagoula; Chandra Source Catalog Team

2018-01-01

The second release of the Chandra Source Catalog (CSC) contains all sources identified from sixteen years' worth of publicly accessible observations. The vast majority of these sources have been observed with the ACIS detector and have spectral information in 0.5-7 keV energy range. Here we describe the methods used to automatically derive spectral properties for each source detected by the standard processing pipeline and included in the final CSC. The sources with high signal to noise ratio (exceeding 150 net counts) were fit in Sherpa (the modeling and fitting application from the Chandra Interactive Analysis of Observations package) using wstat as a fit statistic and Bayesian draws method to determine errors. Three models were fit to each source: an absorbed power-law, blackbody, and Bremsstrahlung emission. The fitted parameter values for the power-law, blackbody, and Bremsstrahlung models were included in the catalog with the calculated flux for each model. The CSC also provides the source energy fluxes computed from the normalizations of predefined absorbed power-law, black-body, Bremsstrahlung, and APEC models needed to match the observed net X-ray counts. For sources that have been observed multiple times we performed a Bayesian Blocks analysis will have been performed (see the Primini et al. poster) and the most significant block will have a joint fit performed for the mentioned spectral models. In addition, we provide access to data products for each source: a file with source spectrum, the background spectrum, and the spectral response of the detector. Hardness ratios were calculated for each source between pairs of energy bands (soft, medium and hard). This work has been supported by NASA under contract NAS 8-03060 to the Smithsonian Astrophysical Observatory for operation of the Chandra X-ray Center.

Measuring implementation behaviour of menu guidelines in the childcare setting: confirmatory factor analysis of a theoretical domains framework questionnaire (TDFQ).

PubMed

Seward, Kirsty; Wolfenden, Luke; Wiggers, John; Finch, Meghan; Wyse, Rebecca; Oldmeadow, Christopher; Presseau, Justin; Clinton-McHarg, Tara; Yoong, Sze Lin

2017-04-04

While there are number of frameworks which focus on supporting the implementation of evidence based approaches, few psychometrically valid measures exist to assess constructs within these frameworks. This study aimed to develop and psychometrically assess a scale measuring each domain of the Theoretical Domains Framework for use in assessing the implementation of dietary guidelines within a non-health care setting (childcare services). A 75 item 14-domain Theoretical Domains Framework Questionnaire (TDFQ) was developed and administered via telephone interview to 202 centre based childcare service cooks who had a role in planning the service menu. Confirmatory factor analysis (CFA) was undertaken to assess the reliability, discriminant validity and goodness of fit of the 14-domain theoretical domain framework measure. For the CFA, five iterative processes of adjustment were undertaken where 14 items were removed, resulting in a final measure consisting of 14 domains and 61 items. For the final measure: the Chi-Square goodness of fit statistic was 3447.19; the Standardized Root Mean Square Residual (SRMR) was 0.070; the Root Mean Square Error of Approximation (RMSEA) was 0.072; and the Comparative Fit Index (CFI) had a value of 0.78. While only one of the three indices support goodness of fit of the measurement model tested, a 14-domain model with 61 items showed good discriminant validity and internally consistent items. Future research should aim to assess the psychometric properties of the developed TDFQ in other community-based settings.

Bayesian inference in an item response theory model with a generalized student t link function

NASA Astrophysics Data System (ADS)

Azevedo, Caio L. N.; Migon, Helio S.

2012-10-01

In this paper we introduce a new item response theory (IRT) model with a generalized Student t-link function with unknown degrees of freedom (df), named generalized t-link (GtL) IRT model. In this model we consider only the difficulty parameter in the item response function. GtL is an alternative to the two parameter logit and probit models, since the degrees of freedom (df) play a similar role to the discrimination parameter. However, the behavior of the curves of the GtL is different from those of the two parameter models and the usual Student t link, since in GtL the curve obtained from different df's can cross the probit curves in more than one latent trait level. The GtL model has similar proprieties to the generalized linear mixed models, such as the existence of sufficient statistics and easy parameter interpretation. Also, many techniques of parameter estimation, model fit assessment and residual analysis developed for that models can be used for the GtL model. We develop fully Bayesian estimation and model fit assessment tools through a Metropolis-Hastings step within Gibbs sampling algorithm. We consider a prior sensitivity choice concerning the degrees of freedom. The simulation study indicates that the algorithm recovers all parameters properly. In addition, some Bayesian model fit assessment tools are considered. Finally, a real data set is analyzed using our approach and other usual models. The results indicate that our model fits the data better than the two parameter models.

Project Target: Criterion-Referenced Physical Fitness Standards for Adolescents with Disabilities. Final Report.

ERIC Educational Resources Information Center

Winnick, Joseph P.; Short, Francis X.

This final report discusses the outcomes of a project designed to extend the nation's current emphasis on health-related, criterion-referenced fitness testing and programming to children and adolescents with disabilities. It summarizes project activities leading up to the Brockport Physical Fitness Test and related measures. Activities included:…

The Anomalous Accretion Disk of the Cataclysmic Variable RW Sextantis

NASA Astrophysics Data System (ADS)

Linnell, Albert P.; Godon, P.; Hubeny, I.; Sion, E. M.; Szkody, P.

2011-01-01

The standard model for stable Cataclysmic Variable (CV) accretion disks (Frank, King and Raine 1992) derives an explicit analytic expression for the disk effective temperature as function of radial distance from the white dwarf (WD). That model specifies that the effective temperature, Teff(R), varies with R as ()0.25, where () represents a combination of parameters including R, the mass transfer rate M(dot), and other parameters. It is well known that fits of standard model synthetic spectra to observed CV spectra find almost no instances of agreement. We have derived a generalized expression for the radial temperature gradient, which preserves the total disk luminosity as function of M(dot) but permits a different exponent from the theoretical value of 0.25, and have applied it to RW Sex (Linnell et al.,2010,ApJ, 719,271). We find an excellent fit to observed FUSE and IUE spectra for an exponent of 0.125, curiously close to 1/2 the theoretical value. Our annulus synthetic spectra, combined to represent the accretion disk, were produced with program TLUSTY, were non-LTE and included H, He, C, Mg, Al, Si, and Fe as explicit ions. We illustrate our results with a plot showing the failure to fit RW Sex for a range of M(dot) values, our model fit to the observations, and a chi2 plot showing the selection of the exponent 0.125 as the best fit for the M(dot) range shown. (For the final model parameters see the paper cited.)

The Theory of Planned Behavior as a Model of Heavy Episodic Drinking Among College Students

PubMed Central

Collins, Susan E.; Carey, Kate B.

2008-01-01

This study provided a simultaneous, confirmatory test of the theory of planned behavior (TPB) in predicting heavy episodic drinking (HED) among college students. It was hypothesized that past HED, drinking attitudes, subjective norms and drinking refusal self-efficacy would predict intention, which would in turn predict future HED. Participants consisted of 131 college drinkers (63% female) who reported having engaged in HED in the previous two weeks. Participants were recruited and completed questionnaires within the context of a larger intervention study (see Collins & Carey, 2005). Latent factor structural equation modeling was used to test the ability of the TPB to predict HED. Chi-square tests and fit indices indicated good fit for the final structural models. Self-efficacy and attitudes but not subjective norms significantly predicted baseline intention, and intention and past HED predicted future HED. Contrary to hypotheses, however, a structural model excluding past HED provided a better fit than a model including it. Although further studies must be conducted before a definitive conclusion is reached, a TPB model excluding past behavior, which is arguably more parsimonious and theory driven, may provide better prediction of HED among college drinkers than a model including past behavior. PMID:18072832

SU-E-T-598: Parametric Equation for Quick and Reliable Estimate of Stray Neutron Doses in Proton Therapy and Application for Intracranial Tumor Treatments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bonfrate, A; Farah, J; Sayah, R

2015-06-15

Purpose: Development of a parametric equation suitable for a daily use in routine clinic to provide estimates of stray neutron doses in proton therapy. Methods: Monte Carlo (MC) calculations using the UF-NCI 1-year-old phantom were exercised to determine the variation of stray neutron doses as a function of irradiation parameters while performing intracranial treatments. This was done by individually changing the proton beam energy, modulation width, collimator aperture and thickness, compensator thickness and the air gap size while their impact on neutron doses were put into a single equation. The variation of neutron doses with distance from the target volumemore » was also included in it. Then, a first step consisted in establishing the fitting coefficients by using 221 learning data which were neutron absorbed doses obtained with MC simulations while a second step consisted in validating the final equation. Results: The variation of stray neutron doses with irradiation parameters were fitted with linear, polynomial, etc. model while a power-law model was used to fit the variation of stray neutron doses with the distance from the target volume. The parametric equation fitted well MC simulations while establishing fitting coefficients as the discrepancies on the estimate of neutron absorbed doses were within 10%. The discrepancy can reach ∼25% for the bladder, the farthest organ from the target volume. Finally, the validation showed results in compliance with MC calculations since the discrepancies were also within 10% for head-and-neck and thoracic organs while they can reach ∼25%, again for pelvic organs. Conclusion: The parametric equation presents promising results and will be validated for other target sites as well as other facilities to go towards a universal method.« less

Fast and accurate fitting and filtering of noisy exponentials in Legendre space.

PubMed

Bao, Guobin; Schild, Detlev

2014-01-01

The parameters of experimentally obtained exponentials are usually found by least-squares fitting methods. Essentially, this is done by minimizing the mean squares sum of the differences between the data, most often a function of time, and a parameter-defined model function. Here we delineate a novel method where the noisy data are represented and analyzed in the space of Legendre polynomials. This is advantageous in several respects. First, parameter retrieval in the Legendre domain is typically two orders of magnitude faster than direct fitting in the time domain. Second, data fitting in a low-dimensional Legendre space yields estimates for amplitudes and time constants which are, on the average, more precise compared to least-squares-fitting with equal weights in the time domain. Third, the Legendre analysis of two exponentials gives satisfactory estimates in parameter ranges where least-squares-fitting in the time domain typically fails. Finally, filtering exponentials in the domain of Legendre polynomials leads to marked noise removal without the phase shift characteristic for conventional lowpass filters.

A measurement model of multiple intelligence profiles of management graduates

NASA Astrophysics Data System (ADS)

Krishnan, Heamalatha; Awang, Siti Rahmah

2017-05-01

In this study, developing a fit measurement model and identifying the best fitting items to represent Howard Gardner's nine intelligences namely, musical intelligence, bodily-kinaesthetic intelligence, mathematical/logical intelligence, visual/spatial intelligence, verbal/linguistic intelligence, interpersonal intelligence, intrapersonal intelligence, naturalist intelligence and spiritual intelligence are the main interest in order to enhance the opportunities of the management graduates for employability. In order to develop a fit measurement model, Structural Equation Modeling (SEM) was applied. A psychometric test which is the Ability Test in Employment (ATIEm) was used as the instrument to measure the existence of nine types of intelligence of 137 University Teknikal Malaysia Melaka (UTeM) management graduates for job placement purposes. The initial measurement model contains nine unobserved variables and each unobserved variable is measured by ten observed variables. Finally, the modified measurement model deemed to improve the Normed chi-square (NC) = 1.331; Incremental Fit Index (IFI) = 0.940 and Root Mean Square of Approximation (RMSEA) = 0.049 was developed. The findings showed that the UTeM management graduates possessed all nine intelligences either high or low. Musical intelligence, mathematical/logical intelligence, naturalist intelligence and spiritual intelligence contributed highest loadings on certain items. However, most of the intelligences such as bodily kinaesthetic intelligence, visual/spatial intelligence, verbal/linguistic intelligence interpersonal intelligence and intrapersonal intelligence possessed by UTeM management graduates are just at the borderline.

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm.

PubMed

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability.

On the the Contact Lens Problem: Modeling Rigid and Elastic Beams on Thin Films

NASA Astrophysics Data System (ADS)

Trinh, Philippe; Wilson, Stephen; Stone, Howard

2011-11-01

Generally, contact lenses are prescribed by the practitioner to fit each individual patient's eye, but these fitting-philosophies are based on empirical studies and a certain degree of trial-and-error. A badly fitted lens can cause a range of afflictions, which varies from mild dry-eye-discomfort, to more serious corneal diseases. Thus, at this heart of this problem, is the question of how a rigid or elastic plate interacts with the free-surface of a thin viscous film. In this talk, we present several mathematical models for the study of these plate-and-fluid problems. Asymptotic and numerical results are described, and we explain the role of elasticity, surface tension, viscosity, and pressure in determining the equilibrium solutions. Finally, we discuss the implications of our work on the contact lens problem, as well as on other coating processes which involve elastic substrates.

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm

PubMed Central

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability. PMID:26880881

77 FR 14002 - Stainless Steel Butt-Weld Pipe Fittings From Italy, Malaysia, and the Philippines: Final Results...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-08

... steel fittings of seamless and welded construction covered by the latest revision of ANSI B16.9, ANSI...] Stainless Steel Butt-Weld Pipe Fittings From Italy, Malaysia, and the Philippines: Final Results of the... Commerce (the Department) initiated sunset reviews of the antidumping duty orders on stainless steel butt...

The Physical Fitness of Adolescents with Cerebral Palsy. Project UNIQUE II. Final Report.

ERIC Educational Resources Information Center

Winnick, Joseph P.; Short, Francis X.

The final report describes a 2-year project of the State University of New York, College at Brockport, to study the physical fitness of nonretarded and retarded adolescents with cerebral palsy. The UNIQUE Physical Fitness Test was administered to 203 cerebral palsied adolescents throughout the United States and from segregated and nonsegregated…

Fitting C 2 Continuous Parametric Surfaces to Frontiers Delimiting Physiologic Structures

PubMed Central

Bayer, Jason D.

2014-01-01

We present a technique to fit C 2 continuous parametric surfaces to scattered geometric data points forming frontiers delimiting physiologic structures in segmented images. Such mathematical representation is interesting because it facilitates a large number of operations in modeling. While the fitting of C 2 continuous parametric curves to scattered geometric data points is quite trivial, the fitting of C 2 continuous parametric surfaces is not. The difficulty comes from the fact that each scattered data point should be assigned a unique parametric coordinate, and the fit is quite sensitive to their distribution on the parametric plane. We present a new approach where a polygonal (quadrilateral or triangular) surface is extracted from the segmented image. This surface is subsequently projected onto a parametric plane in a manner to ensure a one-to-one mapping. The resulting polygonal mesh is then regularized for area and edge length. Finally, from this point, surface fitting is relatively trivial. The novelty of our approach lies in the regularization of the polygonal mesh. Process performance is assessed with the reconstruction of a geometric model of mouse heart ventricles from a computerized tomography scan. Our results show an excellent reproduction of the geometric data with surfaces that are C 2 continuous. PMID:24782911

Perception of competence in middle school physical education: instrument development and validation.

PubMed

Scrabis-Fletcher, Kristin; Silverman, Stephen

2010-03-01

Perception of Competence (POC) has been studied extensively in physical activity (PA) research with similar instruments adapted for physical education (PE) research. Such instruments do not account for the unique PE learning environment. Therefore, an instrument was developed and the scores validated to measure POC in middle school PE. A multiphase design was used consisting of an intensive theoretical review, elicitation study, prepilot study, pilot study, content validation study, and final validation study (N=1281). Data analysis included a multistep iterative process to identify the best model fit. A three-factor model for POC was tested and resulted in root mean square error of approximation = .09, root mean square residual = .07, goodness offit index = .90, and adjusted goodness offit index = .86 values in the acceptable range (Hu & Bentler, 1999). A two-factor model was also tested and resulted in a good fit (two-factor fit indexes values = .05, .03, .98, .97, respectively). The results of this study suggest that an instrument using a three- or two-factor model provides reliable and valid scores ofPOC measurement in middle school PE.

Data Analysis & Statistical Methods for Command File Errors

NASA Technical Reports Server (NTRS)

Meshkat, Leila; Waggoner, Bruce; Bryant, Larry

2014-01-01

This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.

Modeling the Evolution of Female Meiotic Drive in Maize

PubMed Central

Hall, David W.; Dawe, R. Kelly

2017-01-01

Autosomal drivers violate Mendel’s law of segregation in that they are overrepresented in gametes of heterozygous parents. For drivers to be polymorphic within populations rather than fixing, their transmission advantage must be offset by deleterious effects on other fitness components. In this paper, we develop an analytical model for the evolution of autosomal drivers that is motivated by the neocentromere drive system found in maize. In particular, we model both the transmission advantage and deleterious fitness effects on seed viability, pollen viability, seed to adult survival mediated by maternal genotype, and seed to adult survival mediated by offspring genotype. We derive general, biologically intuitive conditions for the four most likely evolutionary outcomes and discuss the expected evolution of autosomal drivers given these conditions. Finally, we determine the expected equilibrium allele frequencies predicted by the model given recent estimates of fitness components for all relevant genotypes and show that the predicted equilibrium is within the range observed in maize land races for levels of drive at the low end of what has been observed. PMID:29122849

Calibration of the COBE FIRAS instrument

NASA Technical Reports Server (NTRS)

Fixsen, D. J.; Cheng, E. S.; Cottingham, D. A.; Eplee, R. E., Jr.; Hewagama, T.; Isaacman, R. B.; Jensen, K. A.; Mather, J. C.; Massa, D. L.; Meyer, S. S.

1994-01-01

The Far-Infrared Absolute Spectrophotometer (FIRAS) instrument on the Cosmic Background Explorer (COBE) satellite was designed to accurately measure the spectrum of the cosmic microwave background radiation (CMBR) in the frequency range 1-95/cm with an angular resolution of 7 deg. We describe the calibration of this instrument, including the method of obtaining calibration data, reduction of data, the instrument model, fitting the model to the calibration data, and application of the resulting model solution to sky observations. The instrument model fits well for calibration data that resemble sky condition. The method of propagating detector noise through the calibration process to yield a covariance matrix of the calibrated sky data is described. The final uncertainties are variable both in frequency and position, but for a typical calibrated sky 2.6 deg square pixel and 0.7/cm spectral element the random detector noise limit is of order of a few times 10(exp -7) ergs/sq cm/s/sr cm for 2-20/cm, and the difference between the sky and the best-fit cosmic blackbody can be measured with a gain uncertainty of less than 3%.

Statistical aspects of modeling the labor curve.

PubMed

Zhang, Jun; Troendle, James; Grantz, Katherine L; Reddy, Uma M

2015-06-01

In a recent review by Cohen and Friedman, several statistical questions on modeling labor curves were raised. This article illustrates that asking data to fit a preconceived model or letting a sufficiently flexible model fit observed data is the main difference in principles of statistical modeling between the original Friedman curve and our average labor curve. An evidence-based approach to construct a labor curve and establish normal values should allow the statistical model to fit observed data. In addition, the presence of the deceleration phase in the active phase of an average labor curve was questioned. Forcing a deceleration phase to be part of the labor curve may have artificially raised the speed of progression in the active phase with a particularly large impact on earlier labor between 4 and 6 cm. Finally, any labor curve is illustrative and may not be instructive in managing labor because of variations in individual labor pattern and large errors in measuring cervical dilation. With the tools commonly available, it may be more productive to establish a new partogram that takes the physiology of labor and contemporary obstetric population into account. Copyright © 2015 Elsevier Inc. All rights reserved.

Development of the Internet addiction scale based on the Internet Gaming Disorder criteria suggested in DSM-5.

PubMed

Cho, Hyun; Kwon, Min; Choi, Ji-Hye; Lee, Sang-Kyu; Choi, Jung Seok; Choi, Sam-Wook; Kim, Dai-Jin

2014-09-01

This study was conducted to develop and validate a standardized self-diagnostic Internet addiction (IA) scale based on the diagnosis criteria for Internet Gaming Disorder (IGD) in the Diagnostic and Statistical Manual of Mental Disorder, 5th edition (DSM-5). Items based on the IGD diagnosis criteria were developed using items of the previous Internet addiction scales. Data were collected from a community sample. The data were divided into two sets, and confirmatory factor analysis (CFA) was performed repeatedly. The model was modified after discussion with professionals based on the first CFA results, after which the second CFA was performed. The internal consistency reliability was generally good. The items that showed significantly low correlation values based on the item-total correlation of each factor were excluded. After the first CFA was performed, some factors and items were excluded. Seven factors and 26 items were prepared for the final model. The second CFA results showed good general factor loading, Squared Multiple Correlation (SMC) and model fit. The model fit of the final model was good, but some factors were very highly correlated. It is recommended that some of the factors be refined through further studies. Copyright © 2014. Published by Elsevier Ltd.

Understanding the persistence of measles: reconciling theory, simulation and observation.

PubMed Central

Keeling, Matt J; Grenfell, Bryan T

2002-01-01

Ever since the pattern of localized extinction associated with measles was discovered by Bartlett in 1957, many models have been developed in an attempt to reproduce this phenomenon. Recently, the use of constant infectious and incubation periods, rather than the more convenient exponential forms, has been presented as a simple means of obtaining realistic persistence levels. However, this result appears at odds with rigorous mathematical theory; here we reconcile these differences. Using a deterministic approach, we parameterize a variety of models to fit the observed biennial attractor, thus determining the level of seasonality by the choice of model. We can then compare fairly the persistence of the stochastic versions of these models, using the 'best-fit' parameters. Finally, we consider the differences between the observed fade-out pattern and the more theoretically appealing 'first passage time'. PMID:11886620

SELECTIVE ADVANTAGE OF RECOMBINATION IN EVOLVING PROTEIN POPULATIONS: A LATTICE MODEL STUDY

PubMed Central

WILLIAMS, PAUL D.; POLLOCK, DAVID D.

2010-01-01

Recent research has attempted to clarify the contributions of several mutational processes, such as substitutions or homologous recombination. Simplistic, tractable protein models, which determine the compact native structure phenotype from the sequence genotype, are well-suited to such studies. In this paper, we use a lattice-protein model to examine the effects of point mutation and homologous recombination on evolving populations of proteins. We find that while the majority of mutation and recombination events are neutral or deleterious, recombination is far more likely to be beneficial. This results in a faster increase in fitness during evolution, although the final fitness level is not significantly changed. This transient advantage provides an evolutionary advantage to subpopulations that undergo recombination, allowing fixation of recombination to occur in the population. PMID:25473139

Selective Advantage of Recombination in Evolving Protein Populations:. a Lattice Model Study

NASA Astrophysics Data System (ADS)

Williams, Paul D.; Pollock, David D.; Goldstein, Richard A.

Recent research has attempted to clarify the contributions of several mutational processes, such as substitutions or homologous recombination. Simplistic, tractable protein models, which determine the compact native structure phenotype from the sequence genotype, are well-suited to such studies. In this paper, we use a lattice-protein model to examine the effects of point mutation and homologous recombination on evolving populations of proteins. We find that while the majority of mutation and recombination events are neutral or deleterious, recombination is far more likely to be beneficial. This results in a faster increase in fitness during evolution, although the final fitness level is not significantly changed. This transient advantage provides an evolutionary advantage to subpopulations that undergo recombination, allowing fixation of recombination to occur in the population.

'Chain pooling' model selection as developed for the statistical analysis of a rotor burst protection experiment

NASA Technical Reports Server (NTRS)

Holms, A. G.

1977-01-01

A statistical decision procedure called chain pooling had been developed for model selection in fitting the results of a two-level fixed-effects full or fractional factorial experiment not having replication. The basic strategy included the use of one nominal level of significance for a preliminary test and a second nominal level of significance for the final test. The subject has been reexamined from the point of view of using as many as three successive statistical model deletion procedures in fitting the results of a single experiment. The investigation consisted of random number studies intended to simulate the results of a proposed aircraft turbine-engine rotor-burst-protection experiment. As a conservative approach, population model coefficients were chosen to represent a saturated 2 to the 4th power experiment with a distribution of parameter values unfavorable to the decision procedures. Three model selection strategies were developed.

Copula Entropy coupled with Wavelet Neural Network Model for Hydrological Prediction

NASA Astrophysics Data System (ADS)

Wang, Yin; Yue, JiGuang; Liu, ShuGuang; Wang, Li

2018-02-01

Artificial Neural network(ANN) has been widely used in hydrological forecasting. in this paper an attempt has been made to find an alternative method for hydrological prediction by combining Copula Entropy(CE) with Wavelet Neural Network(WNN), CE theory permits to calculate mutual information(MI) to select Input variables which avoids the limitations of the traditional linear correlation(LCC) analysis. Wavelet analysis can provide the exact locality of any changes in the dynamical patterns of the sequence Coupled with ANN Strong non-linear fitting ability. WNN model was able to provide a good fit with the hydrological data. finally, the hybrid model(CE+WNN) have been applied to daily water level of Taihu Lake Basin, and compared with CE ANN, LCC WNN and LCC ANN. Results showed that the hybrid model produced better results in estimating the hydrograph properties than the latter models.

Latest astronomical constraints on some non-linear parametric dark energy models

NASA Astrophysics Data System (ADS)

Yang, Weiqiang; Pan, Supriya; Paliathanasis, Andronikos

2018-04-01

We consider non-linear redshift-dependent equation of state parameters as dark energy models in a spatially flat Friedmann-Lemaître-Robertson-Walker universe. To depict the expansion history of the universe in such cosmological scenarios, we take into account the large-scale behaviour of such parametric models and fit them using a set of latest observational data with distinct origin that includes cosmic microwave background radiation, Supernove Type Ia, baryon acoustic oscillations, redshift space distortion, weak gravitational lensing, Hubble parameter measurements from cosmic chronometers, and finally the local Hubble constant from Hubble space telescope. The fitting technique avails the publicly available code Cosmological Monte Carlo (COSMOMC), to extract the cosmological information out of these parametric dark energy models. From our analysis, it follows that those models could describe the late time accelerating phase of the universe, while they are distinguished from the Λ-cosmology.

Peak fitting and integration uncertainties for the Aerodyne Aerosol Mass Spectrometer

NASA Astrophysics Data System (ADS)

Corbin, J. C.; Othman, A.; Haskins, J. D.; Allan, J. D.; Sierau, B.; Worsnop, D. R.; Lohmann, U.; Mensah, A. A.

2015-04-01

The errors inherent in the fitting and integration of the pseudo-Gaussian ion peaks in Aerodyne High-Resolution Aerosol Mass Spectrometers (HR-AMS's) have not been previously addressed as a source of imprecision for these instruments. This manuscript evaluates the significance of these uncertainties and proposes a method for their estimation in routine data analysis. Peak-fitting uncertainties, the most complex source of integration uncertainties, are found to be dominated by errors in m/z calibration. These calibration errors comprise significant amounts of both imprecision and bias, and vary in magnitude from ion to ion. The magnitude of these m/z calibration errors is estimated for an exemplary data set, and used to construct a Monte Carlo model which reproduced well the observed trends in fits to the real data. The empirically-constrained model is used to show that the imprecision in the fitted height of isolated peaks scales linearly with the peak height (i.e., as n1), thus contributing a constant-relative-imprecision term to the overall uncertainty. This constant relative imprecision term dominates the Poisson counting imprecision term (which scales as n0.5) at high signals. The previous HR-AMS uncertainty model therefore underestimates the overall fitting imprecision. The constant relative imprecision in fitted peak height for isolated peaks in the exemplary data set was estimated as ~4% and the overall peak-integration imprecision was approximately 5%. We illustrate the importance of this constant relative imprecision term by performing Positive Matrix Factorization (PMF) on a~synthetic HR-AMS data set with and without its inclusion. Finally, the ability of an empirically-constrained Monte Carlo approach to estimate the fitting imprecision for an arbitrary number of known overlapping peaks is demonstrated. Software is available upon request to estimate these error terms in new data sets.

Simplified process model discovery based on role-oriented genetic mining.

PubMed

Zhao, Weidong; Liu, Xi; Dai, Weihui

2014-01-01

Process mining is automated acquisition of process models from event logs. Although many process mining techniques have been developed, most of them are based on control flow. Meanwhile, the existing role-oriented process mining methods focus on correctness and integrity of roles while ignoring role complexity of the process model, which directly impacts understandability and quality of the model. To address these problems, we propose a genetic programming approach to mine the simplified process model. Using a new metric of process complexity in terms of roles as the fitness function, we can find simpler process models. The new role complexity metric of process models is designed from role cohesion and coupling, and applied to discover roles in process models. Moreover, the higher fitness derived from role complexity metric also provides a guideline for redesigning process models. Finally, we conduct case study and experiments to show that the proposed method is more effective for streamlining the process by comparing with related studies.

Spatio-temporal Bayesian model selection for disease mapping

PubMed Central

Carroll, R; Lawson, AB; Faes, C; Kirby, RS; Aregay, M; Watjou, K

2016-01-01

Spatio-temporal analysis of small area health data often involves choosing a fixed set of predictors prior to the final model fit. In this paper, we propose a spatio-temporal approach of Bayesian model selection to implement model selection for certain areas of the study region as well as certain years in the study time line. Here, we examine the usefulness of this approach by way of a large-scale simulation study accompanied by a case study. Our results suggest that a special case of the model selection methods, a mixture model allowing a weight parameter to indicate if the appropriate linear predictor is spatial, spatio-temporal, or a mixture of the two, offers the best option to fitting these spatio-temporal models. In addition, the case study illustrates the effectiveness of this mixture model within the model selection setting by easily accommodating lifestyle, socio-economic, and physical environmental variables to select a predominantly spatio-temporal linear predictor. PMID:28070156

Calibration of GRB Luminosity Relations with Cosmography

NASA Astrophysics Data System (ADS)

Gao, He; Liang, Nan; Zhu, Zong-Hong

For the use of gamma-ray bursts (GRBs) to probe cosmology in a cosmology-independent way, a new method has been proposed to obtain luminosity distances of GRBs by interpolating directly from the Hubble diagram of SNe Ia, and then calibrating GRB relations at high redshift. In this paper, following the basic assumption in the interpolation method that objects at the same redshift should have the same luminosity distance, we propose another approach to calibrate GRB luminosity relations with cosmographic fitting directly from SN Ia data. In cosmography, there is a well-known fitting formula which can reflect the Hubble relation between luminosity distance and redshift with cosmographic parameters which can be fitted from observation data. Using the Cosmographic fitting results from the Union set of SNe Ia, we calibrate five GRB relations using GRB sample at z ≤ 1.4 and deduce distance moduli of GRBs at 1.4 < z ≤ 6.6 by generalizing above calibrated relations at high redshift. Finally, we constrain the dark energy parameterization models of the Chevallier-Polarski-Linder (CPL) model, the Jassal-Bagla-Padmanabhan (JBP) model and the Alam model with GRB data at high redshift, as well as with the cosmic microwave background radiation (CMB) and the baryonic acoustic oscillation (BAO) observations, and we find the ΛCDM model is consistent with the current data in 1-σ confidence region.

ThermoFit: A Set of Software Tools, Protocols and Schema for the Organization of Thermodynamic Data and for the Development, Maintenance, and Distribution of Internally Consistent Thermodynamic Data/Model Collections

NASA Astrophysics Data System (ADS)

Ghiorso, M. S.

2013-12-01

Internally consistent thermodynamic databases are critical resources that facilitate the calculation of heterogeneous phase equilibria and thereby support geochemical, petrological, and geodynamical modeling. These 'databases' are actually derived data/model systems that depend on a diverse suite of physical property measurements, calorimetric data, and experimental phase equilibrium brackets. In addition, such databases are calibrated with the adoption of various models for extrapolation of heat capacities and volumetric equations of state to elevated temperature and pressure conditions. Finally, these databases require specification of thermochemical models for the mixing properties of solid, liquid, and fluid solutions, which are often rooted in physical theory and, in turn, depend on additional experimental observations. The process of 'calibrating' a thermochemical database involves considerable effort and an extensive computational infrastructure. Because of these complexities, the community tends to rely on a small number of thermochemical databases, generated by a few researchers; these databases often have limited longevity and are universally difficult to maintain. ThermoFit is a software framework and user interface whose aim is to provide a modeling environment that facilitates creation, maintenance and distribution of thermodynamic data/model collections. Underlying ThermoFit are data archives of fundamental physical property, calorimetric, crystallographic, and phase equilibrium constraints that provide the essential experimental information from which thermodynamic databases are traditionally calibrated. ThermoFit standardizes schema for accessing these data archives and provides web services for data mining these collections. Beyond simple data management and interoperability, ThermoFit provides a collection of visualization and software modeling tools that streamline the model/database generation process. Most notably, ThermoFit facilitates the rapid visualization of predicted model outcomes and permits the user to modify these outcomes using tactile- or mouse-based GUI interaction, permitting real-time updates that reflect users choices, preferences, and priorities involving derived model results. This ability permits some resolution of the problem of correlated model parameters in the common situation where thermodynamic models must be calibrated from inadequate data resources. The ability also allows modeling constraints to be imposed using natural data and observations (i.e. petrologic or geochemical intuition). Once formulated, ThermoFit facilitates deployment of data/model collections by automated creation of web services. Users consume these services via web-, excel-, or desktop-clients. ThermoFit is currently under active development and not yet generally available; a limited capability prototype system has been coded for Macintosh computers and utilized to construct thermochemical models for H2O-CO2 mixed fluid saturation in silicate liquids. The longer term goal is to release ThermoFit as a web portal application client with server-based cloud computations supporting the modeling environment.

Modeling the growth of individuals in plant populations: local density variation in a strand population of Xanthium strumarium (Asteraceae).

PubMed

Weiner, J; Kinsman, S; Williams, S

1998-11-01

We studied the growth of individual Xanthium strumarium plants growing at four naturally occurring local densities on a beach in Maine: (1) isolated plants, (2) pairs of plants ≤1 cm apart, (3) four plants within 4 cm of each other, and (4) discrete dense clumps of 10-39 plants. A combination of nondestructive measurements every 2 wk and parallel calibration harvests provided very good estimates of the growth in aboveground biomass of over 400 individual plants over 8 wk and afforded the opportunity to fit explicit growth models to 293 of them. There was large individual variation in growth and resultant size within the population and within all densities. Local crowding played a role in determining plant size within the population: there were significant differences in final size between all densities except pairs and quadruples, which were almost identical. Overall, plants growing at higher densities were more variable in growth and final size than plants growing at lower densities, but this was due to increased variation among groups (greater variation in local density and/or greater environmental heterogeneity), not to increased variation within groups. Thus, there was no evidence of size asymmetric competition in this population. The growth of most plants was close to exponential over the study period, but half the plants were slightly better fit by a sigmoidal (logistic) model. The proportion of plants better fit by the logistic model increased with density and with initial plant size. The use of explicit growth models over several growth intervals to describe stand development can provide more biological content and more statistical power than "growth-size" methods that analyze growth intervals separately.

xMDFF: molecular dynamics flexible fitting of low-resolution X-ray structures.

PubMed

McGreevy, Ryan; Singharoy, Abhishek; Li, Qufei; Zhang, Jingfen; Xu, Dong; Perozo, Eduardo; Schulten, Klaus

2014-09-01

X-ray crystallography remains the most dominant method for solving atomic structures. However, for relatively large systems, the availability of only medium-to-low-resolution diffraction data often limits the determination of all-atom details. A new molecular dynamics flexible fitting (MDFF)-based approach, xMDFF, for determining structures from such low-resolution crystallographic data is reported. xMDFF employs a real-space refinement scheme that flexibly fits atomic models into an iteratively updating electron-density map. It addresses significant large-scale deformations of the initial model to fit the low-resolution density, as tested with synthetic low-resolution maps of D-ribose-binding protein. xMDFF has been successfully applied to re-refine six low-resolution protein structures of varying sizes that had already been submitted to the Protein Data Bank. Finally, via systematic refinement of a series of data from 3.6 to 7 Å resolution, xMDFF refinements together with electrophysiology experiments were used to validate the first all-atom structure of the voltage-sensing protein Ci-VSP.

Fuzzy Analytic Hierarchy Process-based Chinese Resident Best Fitness Behavior Method Research.

PubMed

Wang, Dapeng; Zhang, Lan

2015-01-01

With explosive development in Chinese economy and science and technology, people's pursuit of health becomes more and more intense, therefore Chinese resident sports fitness activities have been rapidly developed. However, different fitness events popularity degrees and effects on body energy consumption are different, so bases on this, the paper researches on fitness behaviors and gets Chinese residents sports fitness behaviors exercise guide, which provides guidance for propelling to national fitness plan's implementation and improving Chinese resident fitness scientization. The paper starts from the perspective of energy consumption, it mainly adopts experience method, determines Chinese resident favorite sports fitness event energy consumption through observing all kinds of fitness behaviors energy consumption, and applies fuzzy analytic hierarchy process to make evaluation on bicycle riding, shadowboxing practicing, swimming, rope skipping, jogging, running, aerobics these seven fitness events. By calculating fuzzy rate model's membership and comparing their sizes, it gets fitness behaviors that are more helpful for resident health, more effective and popular. Finally, it gets conclusions that swimming is a best exercise mode and its membership is the highest. Besides, the memberships of running, rope skipping and shadowboxing practicing are also relative higher. It should go in for bodybuilding by synthesizing above several kinds of fitness events according to different physical conditions; different living conditions so that can better achieve the purpose of fitness exercises.

Parameterizing sorption isotherms using a hybrid global-local fitting procedure.

PubMed

Matott, L Shawn; Singh, Anshuman; Rabideau, Alan J

2017-05-01

Predictive modeling of the transport and remediation of groundwater contaminants requires an accurate description of the sorption process, which is usually provided by fitting an isotherm model to site-specific laboratory data. Commonly used calibration procedures, listed in order of increasing sophistication, include: trial-and-error, linearization, non-linear regression, global search, and hybrid global-local search. Given the considerable variability in fitting procedures applied in published isotherm studies, we investigated the importance of algorithm selection through a series of numerical experiments involving 13 previously published sorption datasets. These datasets, considered representative of state-of-the-art for isotherm experiments, had been previously analyzed using trial-and-error, linearization, or non-linear regression methods. The isotherm expressions were re-fit using a 3-stage hybrid global-local search procedure (i.e. global search using particle swarm optimization followed by Powell's derivative free local search method and Gauss-Marquardt-Levenberg non-linear regression). The re-fitted expressions were then compared to previously published fits in terms of the optimized weighted sum of squared residuals (WSSR) fitness function, the final estimated parameters, and the influence on contaminant transport predictions - where easily computed concentration-dependent contaminant retardation factors served as a surrogate measure of likely transport behavior. Results suggest that many of the previously published calibrated isotherm parameter sets were local minima. In some cases, the updated hybrid global-local search yielded order-of-magnitude reductions in the fitness function. In particular, of the candidate isotherms, the Polanyi-type models were most likely to benefit from the use of the hybrid fitting procedure. In some cases, improvements in fitness function were associated with slight (<10%) changes in parameter values, but in other cases significant (>50%) changes in parameter values were noted. Despite these differences, the influence of isotherm misspecification on contaminant transport predictions was quite variable and difficult to predict from inspection of the isotherms. Copyright © 2017 Elsevier B.V. All rights reserved.

On readout of vibrational qubits using quantum beats

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shyshlov, Dmytro; Babikov, Dmitri, E-mail: Dmitri.Babikov@mu.edu; Berrios, Eduardo

2014-12-14

Readout of the final states of qubits is a crucial step towards implementing quantum computation in experiment. Although not scalable to large numbers of qubits per molecule, computational studies show that molecular vibrations could provide a significant (factor 2–5 in the literature) increase in the number of qubits compared to two-level systems. In this theoretical work, we explore the process of readout from vibrational qubits in thiophosgene molecule, SCCl{sub 2}, using quantum beat oscillations. The quantum beats are measured by first exciting the superposition of the qubit-encoding vibrational states to the electronically excited readout state with variable time-delay pulses. Themore » resulting oscillation of population of the readout state is then detected as a function of time delay. In principle, fitting the quantum beat signal by an analytical expression should allow extracting the values of probability amplitudes and the relative phases of the vibrational qubit states. However, we found that if this procedure is implemented using the standard analytic expression for quantum beats, a non-negligible phase error is obtained. We discuss the origin and properties of this phase error, and propose a new analytical expression to correct the phase error. The corrected expression fits the quantum beat signal very accurately, which may permit reading out the final state of vibrational qubits in experiments by combining the analytic fitting expression with numerical modelling of the readout process. The new expression is also useful as a simple model for fitting any quantum beat experiments where more accurate phase information is desired.« less

Empirical calibration of the near-infrared Ca II triplet - III. Fitting functions

NASA Astrophysics Data System (ADS)

Cenarro, A. J.; Gorgas, J.; Cardiel, N.; Vazdekis, A.; Peletier, R. F.

2002-02-01

Using a near-infrared stellar library of 706 stars with a wide coverage of atmospheric parameters, we study the behaviour of the CaII triplet strength in terms of effective temperature, surface gravity and metallicity. Empirical fitting functions for recently defined line-strength indices, namely CaT*, CaT and PaT, are provided. These functions can be easily implemented into stellar population models to provide accurate predictions for integrated CaII strengths. We also present a thorough study of the various error sources and their relation to the residuals of the derived fitting functions. Finally, the derived functional forms and the behaviour of the predicted CaII are compared with those of previous works in the field.

VizieR Online Data Catalog: Metal enrichment in semi-analytical model (Cousin+, 2016)

NASA Astrophysics Data System (ADS)

Cousin, M.; Buat, V.; Boissier, S.; Bethermin, M.; Roehlly, Y. Genois M.

2016-04-01

The repository contains outputs from the different models: - m1: Classical (only hot gas) isotropic accretion scenario + Standard Shmidt Kennicutt law - m2: Bimodal accretion (cold streams) + Standard Shmidt Kennicutt law - m3: Classical (only hot gas) isotropic accretion scenario + ad-hoc non-star forming gas reservoir - m4: Bimodal accretion (cold streams) + ad-hoc non-star forming gas reservoir For each model of these models dada are saved in eGalICS_m*.fits file. All these fits-formated files are compatible with the TOPCAT software available on: http://www.star.bris.ac.uk/~mbt/topcat/ We also provide, for each Initial Mass Function available, a set of two fits-formated files associated to the chemodynamical library presented in the paper. For these two files, data are available for all metallicity bins used. - masslossrates_IMF.fits: The instantaneous total ejecta rate associated to a SSP for the six different main-ISM elements. - SNratesIMF.fits: The total SN rate (SNII+SNIa [nb/Gyr]) associated to a SSP, individual contribution of SNII and SNIa are also given. These files are available for four different IMFs: Salpeter+55 (1955ApJ...121..161S), Chabrier+03 (2003PASP..115..763C), Kroupa+93 (2001MNRAS.322..231K) and Scalo+98 (1998ASPC..142..201S. Both ejecta rates and SN rates are computed for the complete list of stellar ages provided in the BC03 spectra library. They are saved in fits-formated files and structured with different extensions corresponding to the different initial stellar metallicity bins. We finally provide the median star formation history, the median gas accretion history and the metal enrichment histories associated to our MW-sisters sample: MWsistershistories.dat If you used data associated to eGalICS semi-analytic model, please cite the following paper: Cousin et al., 2015A&A...575A..33C, "Toward a new modelling of gas flows in a semi-analytical model of galaxy formation and evolution" (3 data files).

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

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.

Limited-information goodness-of-fit testing of diagnostic classification item response models.

PubMed

Hansen, Mark; Cai, Li; Monroe, Scott; Li, Zhen

2016-11-01

Despite the growing popularity of diagnostic classification models (e.g., Rupp et al., 2010, Diagnostic measurement: theory, methods, and applications, Guilford Press, New York, NY) in educational and psychological measurement, methods for testing their absolute goodness of fit to real data remain relatively underdeveloped. For tests of reasonable length and for realistic sample size, full-information test statistics such as Pearson's X 2 and the likelihood ratio statistic G 2 suffer from sparseness in the underlying contingency table from which they are computed. Recently, limited-information fit statistics such as Maydeu-Olivares and Joe's (2006, Psychometrika, 71, 713) M 2 have been found to be quite useful in testing the overall goodness of fit of item response theory models. In this study, we applied Maydeu-Olivares and Joe's (2006, Psychometrika, 71, 713) M 2 statistic to diagnostic classification models. Through a series of simulation studies, we found that M 2 is well calibrated across a wide range of diagnostic model structures and was sensitive to certain misspecifications of the item model (e.g., fitting disjunctive models to data generated according to a conjunctive model), errors in the Q-matrix (adding or omitting paths, omitting a latent variable), and violations of local item independence due to unmodelled testlet effects. On the other hand, M 2 was largely insensitive to misspecifications in the distribution of higher-order latent dimensions and to the specification of an extraneous attribute. To complement the analyses of the overall model goodness of fit using M 2 , we investigated the utility of the Chen and Thissen (1997, J. Educ. Behav. Stat., 22, 265) local dependence statistic XLD2 for characterizing sources of misfit, an important aspect of model appraisal often overlooked in favour of overall statements. The XLD2 statistic was found to be slightly conservative (with Type I error rates consistently below the nominal level) but still useful in pinpointing the sources of misfit. Patterns of local dependence arising due to specific model misspecifications are illustrated. Finally, we used the M 2 and XLD2 statistics to evaluate a diagnostic model fit to data from the Trends in Mathematics and Science Study, drawing upon analyses previously conducted by Lee et al., (2011, IJT, 11, 144). © 2016 The British Psychological Society.

Visual recognition system of cherry picking robot based on Lab color model

NASA Astrophysics Data System (ADS)

Zhang, Qirong; Zuo, Jianjun; Yu, Tingzhong; Wang, Yan

2017-12-01

This paper designs a visual recognition system suitable for cherry picking. First, the system deals with the image using the vector median filter. And then it extracts a channel of Lab color model to divide the cherries and the background. The cherry contour was successfully fitted by the least square method, and the centroid and radius of the cherry were extracted. Finally, the cherry was successfully extracted.

Hierarchical data-driven approach to fitting numerical relativity data for nonprecessing binary black holes with an application to final spin and radiated energy

NASA Astrophysics Data System (ADS)

Jiménez-Forteza, Xisco; Keitel, David; Husa, Sascha; Hannam, Mark; Khan, Sebastian; Pürrer, Michael

2017-03-01

Numerical relativity is an essential tool in studying the coalescence of binary black holes (BBHs). It is still computationally prohibitive to cover the BBH parameter space exhaustively, making phenomenological fitting formulas for BBH waveforms and final-state properties important for practical applications. We describe a general hierarchical bottom-up fitting methodology to design and calibrate fits to numerical relativity simulations for the three-dimensional parameter space of quasicircular nonprecessing merging BBHs, spanned by mass ratio and by the individual spin components orthogonal to the orbital plane. Particular attention is paid to incorporating the extreme-mass-ratio limit and to the subdominant unequal-spin effects. As an illustration of the method, we provide two applications, to the final spin and final mass (or equivalently: radiated energy) of the remnant black hole. Fitting to 427 numerical relativity simulations, we obtain results broadly consistent with previously published fits, but improving in overall accuracy and particularly in the approach to extremal limits and for unequal-spin configurations. We also discuss the importance of data quality studies when combining simulations from diverse sources, how detailed error budgets will be necessary for further improvements of these already highly accurate fits, and how this first detailed study of unequal-spin effects helps in choosing the most informative parameters for future numerical relativity runs.

Using web search query data to monitor dengue epidemics: a new model for neglected tropical disease surveillance.

PubMed

Chan, Emily H; Sahai, Vikram; Conrad, Corrie; Brownstein, John S

2011-05-01

A variety of obstacles including bureaucracy and lack of resources have interfered with timely detection and reporting of dengue cases in many endemic countries. Surveillance efforts have turned to modern data sources, such as Internet search queries, which have been shown to be effective for monitoring influenza-like illnesses. However, few have evaluated the utility of web search query data for other diseases, especially those of high morbidity and mortality or where a vaccine may not exist. In this study, we aimed to assess whether web search queries are a viable data source for the early detection and monitoring of dengue epidemics. Bolivia, Brazil, India, Indonesia and Singapore were chosen for analysis based on available data and adequate search volume. For each country, a univariate linear model was then built by fitting a time series of the fraction of Google search query volume for specific dengue-related queries from that country against a time series of official dengue case counts for a time-frame within 2003-2010. The specific combination of queries used was chosen to maximize model fit. Spurious spikes in the data were also removed prior to model fitting. The final models, fit using a training subset of the data, were cross-validated against both the overall dataset and a holdout subset of the data. All models were found to fit the data quite well, with validation correlations ranging from 0.82 to 0.99. Web search query data were found to be capable of tracking dengue activity in Bolivia, Brazil, India, Indonesia and Singapore. Whereas traditional dengue data from official sources are often not available until after some substantial delay, web search query data are available in near real-time. These data represent valuable complement to assist with traditional dengue surveillance.

Interpretation of psychophysics response curves using statistical physics.

PubMed

Knani, S; Khalfaoui, M; Hachicha, M A; Mathlouthi, M; Ben Lamine, A

2014-05-15

Experimental gustatory curves have been fitted for four sugars (sucrose, fructose, glucose and maltitol), using a double layer adsorption model. Three parameters of the model are fitted, namely the number of molecules per site n, the maximum response RM and the concentration at half saturation C1/2. The behaviours of these parameters are discussed in relationship to each molecule's characteristics. Starting from the double layer adsorption model, we determined (in addition) the adsorption energy of each molecule on taste receptor sites. The use of the threshold expression allowed us to gain information about the adsorption occupation rate of a receptor site which fires a minimal response at a gustatory nerve. Finally, by means of this model we could calculate the configurational entropy of the adsorption system, which can describe the order and disorder of the adsorbent surface. Copyright © 2013 Elsevier Ltd. All rights reserved.

Bayesian component separation: The Planck experience

NASA Astrophysics Data System (ADS)

Wehus, Ingunn Kathrine; Eriksen, Hans Kristian

2018-05-01

Bayesian component separation techniques have played a central role in the data reduction process of Planck. The most important strength of this approach is its global nature, in which a parametric and physical model is fitted to the data. Such physical modeling allows the user to constrain very general data models, and jointly probe cosmological, astrophysical and instrumental parameters. This approach also supports statistically robust goodness-of-fit tests in terms of data-minus-model residual maps, which are essential for identifying residual systematic effects in the data. The main challenges are high code complexity and computational cost. Whether or not these costs are justified for a given experiment depends on its final uncertainty budget. We therefore predict that the importance of Bayesian component separation techniques is likely to increase with time for intensity mapping experiments, similar to what has happened in the CMB field, as observational techniques mature, and their overall sensitivity improves.

The structure of DSM-IV-TR personality disorder diagnoses in NESARC: a reanalysis.

PubMed

Trull, Timothy J; Vergés, Alvaro; Wood, Phillip K; Sher, Kenneth J

2013-12-01

Cox, Clara, Worobec, and Grant (2012) recently presented results from a series of analyses aimed at identifying the factor structure underlying the DSM-IV-TR (APA, 2000) personality diagnoses assessed in the large NESARC study. Cox et al. (2012) concluded that the best fitting model was one that modeled three lower-order factors (the three clusters of PDs as outlined by DSM-IV-TR), which in turn loaded on a single PD higher-order factor. Our reanalyses of the NESARC Wave 1 and Wave 2 data for personality disorder diagnoses revealed that the best fitting model was that of a general PD factor that spans each of the ten DSM-IV PD diagnoses, and our reanalyses do not support the three-cluster hierarchical structure outlined by Cox et al. (2012) and DSM-IV-TR. Finally, we note the importance of modeling the Wave 2 assessment method factor in analyses of NESARC PD data.

Uncertainty quantification of reaction mechanisms accounting for correlations introduced by rate rules and fitted Arrhenius parameters

DOE PAGES

Prager, Jens; Najm, Habib N.; Sargsyan, Khachik; ...

2013-02-23

We study correlations among uncertain Arrhenius rate parameters in a chemical model for hydrocarbon fuel-air combustion. We consider correlations induced by the use of rate rules for modeling reaction rate constants, as well as those resulting from fitting rate expressions to empirical measurements arriving at a joint probability density for all Arrhenius parameters. We focus on homogeneous ignition in a fuel-air mixture at constant-pressure. We also outline a general methodology for this analysis using polynomial chaos and Bayesian inference methods. Finally, we examine the uncertainties in both the Arrhenius parameters and in predicted ignition time, outlining the role of correlations,more » and considering both accuracy and computational efficiency.« less

Measuring Men's Gender Norms and Gender Role Conflict/Stress in a High HIV-Prevalence South African Setting.

PubMed

Gottert, Ann; Barrington, Clare; Pettifor, Audrey; McNaughton-Reyes, Heath Luz; Maman, Suzanne; MacPhail, Catherine; Kahn, Kathleen; Selin, Amanda; Twine, Rhian; Lippman, Sheri A

2016-08-01

Gender norms and gender role conflict/stress may influence HIV risk behaviors among men; however scales measuring these constructs need further development and evaluation in African settings. We conducted exploratory and confirmatory factor analyses to evaluate the Gender Equitable Men's Scale (GEMS) and the Gender Role Conflict/Stress (GRC/S) scale among 581 men in rural northeast South Africa. The final 17-item GEMS was unidimensional, with adequate model fit and reliability (alpha = 0.79). Factor loadings were low (0.2-0.3) for items related to violence and sexual relationships. The final 24-item GRC/S scale was multidimensional with four factors: Success, power, competition; Subordination to women; Restrictive emotionality; and Sexual prowess. The scale had adequate model fit and good reliability (alpha = 0.83). While GEMS is a good measure of inequitable gender norms, new or revised scale items may need to be explored in the South African context. Adding the GRC/S scale to capture men's strain related to gender roles could provide important insights into men's risk behaviors.

Fast and Accurate Fitting and Filtering of Noisy Exponentials in Legendre Space

PubMed Central

Bao, Guobin; Schild, Detlev

2014-01-01

The parameters of experimentally obtained exponentials are usually found by least-squares fitting methods. Essentially, this is done by minimizing the mean squares sum of the differences between the data, most often a function of time, and a parameter-defined model function. Here we delineate a novel method where the noisy data are represented and analyzed in the space of Legendre polynomials. This is advantageous in several respects. First, parameter retrieval in the Legendre domain is typically two orders of magnitude faster than direct fitting in the time domain. Second, data fitting in a low-dimensional Legendre space yields estimates for amplitudes and time constants which are, on the average, more precise compared to least-squares-fitting with equal weights in the time domain. Third, the Legendre analysis of two exponentials gives satisfactory estimates in parameter ranges where least-squares-fitting in the time domain typically fails. Finally, filtering exponentials in the domain of Legendre polynomials leads to marked noise removal without the phase shift characteristic for conventional lowpass filters. PMID:24603904

Quantitative pharmacokinetic-pharmacodynamic modelling of baclofen-mediated cardiovascular effects using BP and heart rate in rats.

PubMed

Kamendi, Harriet; Barthlow, Herbert; Lengel, David; Beaudoin, Marie-Eve; Snow, Debra; Mettetal, Jerome T; Bialecki, Russell A

2016-10-01

While the molecular pathways of baclofen toxicity are understood, the relationships between baclofen-mediated perturbation of individual target organs and systems involved in cardiovascular regulation are not clear. Our aim was to use an integrative approach to measure multiple cardiovascular-relevant parameters [CV: mean arterial pressure (MAP), systolic BP, diastolic BP, pulse pressure, heart rate (HR); CNS: EEG; renal: chemistries and biomarkers of injury] in tandem with the pharmacokinetic properties of baclofen to better elucidate the site(s) of baclofen activity. Han-Wistar rats were administered vehicle or ascending doses of baclofen (3, 10 and 30 mg·kg(-1) , p.o.) at 4 h intervals and baclofen-mediated changes in parameters recorded. A pharmacokinetic-pharmacodynamic model was then built by implementing an existing mathematical model of BP in rats. Final model fits resulted in reasonable parameter estimates and showed that the drug acts on multiple homeostatic processes. In addition, the models testing a single effect on HR, total peripheral resistance or stroke volume alone did not describe the data. A final population model was constructed describing the magnitude and direction of the changes in MAP and HR. The systems pharmacology model developed fits baclofen-mediated changes in MAP and HR well. The findings correlate with known mechanisms of baclofen pharmacology and suggest that similar models using limited parameter sets may be useful to predict the cardiovascular effects of other pharmacologically active substances. © 2016 The British Pharmacological Society.

Quantitative pharmacokinetic–pharmacodynamic modelling of baclofen‐mediated cardiovascular effects using BP and heart rate in rats

PubMed Central

Kamendi, Harriet; Barthlow, Herbert; Lengel, David; Beaudoin, Marie‐Eve; Snow, Debra

2016-01-01

Background and Purpose While the molecular pathways of baclofen toxicity are understood, the relationships between baclofen‐mediated perturbation of individual target organs and systems involved in cardiovascular regulation are not clear. Our aim was to use an integrative approach to measure multiple cardiovascular‐relevant parameters [CV: mean arterial pressure (MAP), systolic BP, diastolic BP, pulse pressure, heart rate (HR); CNS: EEG; renal: chemistries and biomarkers of injury] in tandem with the pharmacokinetic properties of baclofen to better elucidate the site(s) of baclofen activity. Experimental Approach Han‐Wistar rats were administered vehicle or ascending doses of baclofen (3, 10 and 30 mg·kg−1, p.o.) at 4 h intervals and baclofen‐mediated changes in parameters recorded. A pharmacokinetic–pharmacodynamic model was then built by implementing an existing mathematical model of BP in rats. Key Results Final model fits resulted in reasonable parameter estimates and showed that the drug acts on multiple homeostatic processes. In addition, the models testing a single effect on HR, total peripheral resistance or stroke volume alone did not describe the data. A final population model was constructed describing the magnitude and direction of the changes in MAP and HR. Conclusions and Implications The systems pharmacology model developed fits baclofen‐mediated changes in MAP and HR well. The findings correlate with known mechanisms of baclofen pharmacology and suggest that similar models using limited parameter sets may be useful to predict the cardiovascular effects of other pharmacologically active substances. PMID:27448216

Local polynomial estimation of heteroscedasticity in a multivariate linear regression model and its applications in economics.

PubMed

Su, Liyun; Zhao, Yanyong; Yan, Tianshun; Li, Fenglan

2012-01-01

Multivariate local polynomial fitting is applied to the multivariate linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to non-parametric technique of local polynomial estimation, it is unnecessary to know the form of heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we verify that the regression coefficients is asymptotic normal based on numerical simulations and normal Q-Q plots of residuals. Finally, the simulation results and the local polynomial estimation of real data indicate that our approach is surely effective in finite-sample situations.

Kinetic modeling of electro-Fenton reaction in aqueous solution.

PubMed

Liu, H; Li, X Z; Leng, Y J; Wang, C

2007-03-01

To well describe the electro-Fenton (E-Fenton) reaction in aqueous solution, a new kinetic model was established according to the generally accepted mechanism of E-Fenton reaction. The model has special consideration on the rates of hydrogen peroxide (H(2)O(2)) generation and consumption in the reaction solution. The model also embraces three key operating factors affecting the organic degradation in the E-Fenton reaction, including current density, dissolved oxygen concentration and initial ferrous ion concentration. This analytical model was then validated by the experiments of phenol degradation in aqueous solution. The experiments demonstrated that the H(2)O(2) gradually built up with time and eventually approached its maximum value in the reaction solution. The experiments also showed that phenol was degraded at a slow rate at the early stage of the reaction, a faster rate during the middle stage, and a slow rate again at the final stage. It was confirmed in all experiments that the curves of phenol degradation (concentration vs. time) appeared to be an inverted "S" shape. The experimental data were fitted using both the normal first-order model and our new model, respectively. The goodness of fittings demonstrated that the new model could better fit the experimental data than the first-order model appreciably, which indicates that this analytical model can better describe the kinetics of the E-Fenton reaction mathematically and also chemically.

A New Navigation Satellite Clock Bias Prediction Method Based on Modified Clock-bias Quadratic Polynomial Model

NASA Astrophysics Data System (ADS)

Wang, Y. P.; Lu, Z. P.; Sun, D. S.; Wang, N.

2016-01-01

In order to better express the characteristics of satellite clock bias (SCB) and improve SCB prediction precision, this paper proposed a new SCB prediction model which can take physical characteristics of space-borne atomic clock, the cyclic variation, and random part of SCB into consideration. First, the new model employs a quadratic polynomial model with periodic items to fit and extract the trend term and cyclic term of SCB; then based on the characteristics of fitting residuals, a time series ARIMA ~(Auto-Regressive Integrated Moving Average) model is used to model the residuals; eventually, the results from the two models are combined to obtain final SCB prediction values. At last, this paper uses precise SCB data from IGS (International GNSS Service) to conduct prediction tests, and the results show that the proposed model is effective and has better prediction performance compared with the quadratic polynomial model, grey model, and ARIMA model. In addition, the new method can also overcome the insufficiency of the ARIMA model in model recognition and order determination.

VizieR Online Data Catalog: Optical/NIR photometry of OGLE-2012-SN-006 (Pastorello+, 2015)

NASA Astrophysics Data System (ADS)

Pastorello, A.; Wyrzykowski, L.; Valenti, S.; Prieto, J. L.; Kozlowski, S.; Udalski, A.; Elias-Rosa, N.; Morales-Garoffolo, A.; Anderson, J. P.; Benetti, S.; Bersten, M.; Botticella, M. T.; Cappellaro, E.; Fasano, G.; Fraser, M.; Gal-Yam, A.; Gillone, M.; Graham, M. L.; Greiner, J.; Hachinger, S.; Howell, D. A.; Inserra, C.; Parrent, J.; Rau, A.; Schulze, S.; Smartt, S. J.; Smith, K. W.; Turatto, M.; Yaron, O.; Young, D. R.; Kubiak, M.; Szymanski, M. K.; Pietrzynski, G.; Soszynski, I.; Ulaczyk, K.; Poleski, R.; Pietrukowicz, P.; Skowron, J.; Mroz, P.

2017-11-01

Photometric measurements in the optical and NIR bands were obtained through the PSF-fitting technique. A template PSF was built using stars in the SN field. With this PSF model along with a low-order polynomial surface, we finally performed a fit to the SN and the underlying background. OGLE-IV photometry was obtained using the difference imaging analysis, which is a template subtraction method adapted to the OGLE data and detailed in Wyrzykowski et al. 2014, J/AcA/64/197 (see also Wozniak 2000, J/AcA/50/421). (2 data files).

μ SR and magnetometry study of superconducting 5% Pt-doped IrTe 2

DOE PAGES

Wilson, M. N.; Medina, T.; Munsie, T. J.; ...

2016-11-11

In this paper, we present magnetometry and muon spin rotation ( SR) measurements of the superconducting dichalcogenide Ir 0.95Pt 0.05Te 2. From both sets of measurements we calculate the penetration depth and thence superfluid density as a function of temperature. The temperature dependence of the superfluid densities from both sets of data indicate fully gapped superconductivity that can be fit to a conventional s-wave model and yield fitting parameters consistent with a BCS weak coupling superconductor. Finally, we therefore see no evidence for exotic superconductivity in Ir 0.95Pt 0.05Te 2.

Development and psychometric characteristics of the SCI-QOL Bladder Management Difficulties and Bowel Management Difficulties item banks and short forms and the SCI-QOL Bladder Complications scale.

PubMed

Tulsky, David S; Kisala, Pamela A; Tate, Denise G; Spungen, Ann M; Kirshblum, Steven C

2015-05-01

To describe the development and psychometric properties of the Spinal Cord Injury--Quality of Life (SCI-QOL) Bladder Management Difficulties and Bowel Management Difficulties item banks and Bladder Complications scale. Using a mixed-methods design, a pool of items assessing bladder and bowel-related concerns were developed using focus groups with individuals with spinal cord injury (SCI) and SCI clinicians, cognitive interviews, and item response theory (IRT) analytic approaches, including tests of model fit and differential item functioning. Thirty-eight bladder items and 52 bowel items were tested at the University of Michigan, Kessler Foundation Research Center, the Rehabilitation Institute of Chicago, the University of Washington, Craig Hospital, and the James J. Peters VA Medical Center, Bronx, NY. Seven hundred fifty-seven adults with traumatic SCI. The final item banks demonstrated unidimensionality (Bladder Management Difficulties CFI=0.965; RMSEA=0.093; Bowel Management Difficulties CFI=0.955; RMSEA=0.078) and acceptable fit to a graded response IRT model. The final calibrated Bladder Management Difficulties bank includes 15 items, and the final Bowel Management Difficulties item bank consists of 26 items. Additionally, 5 items related to urinary tract infections (UTI) did not fit with the larger Bladder Management Difficulties item bank but performed relatively well independently (CFI=0.992, RMSEA=0.050) and were thus retained as a separate scale. The SCI-QOL Bladder Management Difficulties and Bowel Management Difficulties item banks are psychometrically robust and are available as computer adaptive tests or short forms. The SCI-QOL Bladder Complications scale is a brief, fixed-length outcomes instrument for individuals with a UTI.

Fitting and Calibrating a Multilevel Mixed-Effects Stem Taper Model for Maritime Pine in NW Spain

PubMed Central

Arias-Rodil, Manuel; Castedo-Dorado, Fernando; Cámara-Obregón, Asunción; Diéguez-Aranda, Ulises

2015-01-01

Stem taper data are usually hierarchical (several measurements per tree, and several trees per plot), making application of a multilevel mixed-effects modelling approach essential. However, correlation between trees in the same plot/stand has often been ignored in previous studies. Fitting and calibration of a variable-exponent stem taper function were conducted using data from 420 trees felled in even-aged maritime pine (Pinus pinaster Ait.) stands in NW Spain. In the fitting step, the tree level explained much more variability than the plot level, and therefore calibration at plot level was omitted. Several stem heights were evaluated for measurement of the additional diameter needed for calibration at tree level. Calibration with an additional diameter measured at between 40 and 60% of total tree height showed the greatest improvement in volume and diameter predictions. If additional diameter measurement is not available, the fixed-effects model fitted by the ordinary least squares technique should be used. Finally, we also evaluated how the expansion of parameters with random effects affects the stem taper prediction, as we consider this a key question when applying the mixed-effects modelling approach to taper equations. The results showed that correlation between random effects should be taken into account when assessing the influence of random effects in stem taper prediction. PMID:26630156

Bifactor Structure for the Categorical Chinese Rosenberg Self-Esteem Scale.

PubMed

Xu, Menglin; Leung, Shing-On

2016-10-11

Recently, the bifactor model was suggested for the latent structure of the Rosenberg Self-Esteem Scale (RSES). The present paper investigates (i) the differences among bifactor, bifactor negative and other models; (ii) the effects of treating data as both categorical vs continuous; (iii) whether a problematic item in the Chinese RSES should be removed; and (iv) whether the final scoring would be affected. With a sample of 1.734 grade 4-6 school pupils in Hong Kong, we used BIC differences in addition to the usual model fit indices, and found that there was strong evidence for using the bifactor model (RMSEA = .052, 90% CI [.043, .062], CFI = .992, TLI = .984 for 9-item RSES categorical). Little difference is found between treating data as categorical or continuous for fit indices, but the factor loading patterns are better in categorical case. Keeping a problematic item has little effect on fit indices, but would lead to unexpected negative loading. The ranking of loadings within positive and negative items across different conditions are the same, which has important effects on scoring. Loadings in the method effects in the bifactor models are all positive (p < .001), which is different from previous research. All models show similar results on scoring, and support the usual simple sum score in most practice.

Biophysical Fitness Landscapes for Transcription Factor Binding Sites

PubMed Central

Haldane, Allan; Manhart, Michael; Morozov, Alexandre V.

2014-01-01

Phenotypic states and evolutionary trajectories available to cell populations are ultimately dictated by complex interactions among DNA, RNA, proteins, and other molecular species. Here we study how evolution of gene regulation in a single-cell eukaryote S. cerevisiae is affected by interactions between transcription factors (TFs) and their cognate DNA sites. Our study is informed by a comprehensive collection of genomic binding sites and high-throughput in vitro measurements of TF-DNA binding interactions. Using an evolutionary model for monomorphic populations evolving on a fitness landscape, we infer fitness as a function of TF-DNA binding to show that the shape of the inferred fitness functions is in broad agreement with a simple functional form inspired by a thermodynamic model of two-state TF-DNA binding. However, the effective parameters of the model are not always consistent with physical values, indicating selection pressures beyond the biophysical constraints imposed by TF-DNA interactions. We find little statistical support for the fitness landscape in which each position in the binding site evolves independently, indicating that epistasis is common in the evolution of gene regulation. Finally, by correlating TF-DNA binding energies with biological properties of the sites or the genes they regulate, we are able to rule out several scenarios of site-specific selection, under which binding sites of the same TF would experience different selection pressures depending on their position in the genome. These findings support the existence of universal fitness landscapes which shape evolution of all sites for a given TF, and whose properties are determined in part by the physics of protein-DNA interactions. PMID:25010228

Pathways From HIV-Related Stigma to Antiretroviral Therapy Measures in the HIV Care Cascade for Women Living With HIV in Canada.

PubMed

Logie, Carmen H; Lacombe-Duncan, Ashley; Wang, Ying; Kaida, Angela; Conway, Tracey; Webster, Kath; de Pokomandy, Alexandra; Loutfy, Mona R; Anema, Aranka; Becker, Denise; Brotto, Lori; Carter, Allison; Cardinal, Claudette; Colley, Guillaume; Ding, Erin; Duddy, Janice; Gataric, Nada; Hogg, Robert S; Hosward, Terry; Jabbari, Shahab; Jones, Evin; Kestler, Mary; Langlois, Andrea; Lima, Viviane; Lloyd-Smith, Elisa; Medjuck, Melissa; Miller, Cari; Money, Deborah; Nicholson, Valerie; Ogilvie, Gina; Patterson, Sophie; Pick, Neora; Roth, Eric; Salters, Kate; Sanchez, Margarite; Sas, Jacquie; Sereda, Paul; Summers, Marcie; Tom, Christina; Wang, Lu; Webster, Kath; Zhang, Wendy; Abdul-Noor, Rahma; Angel, Jonathan; Barry, Fatimatou; Bauer, Greta; Beaver, Kerrigan; Benoit, Anita; Bertozzi, Breklyn; Borton, Sheila; Bourque, Tammy; Brophy, Jason; Burchell, Ann; Carlson, Allison; Cioppa, Lynne; Cohen, Jeffrey; Conway, Tracey; Cooper, Curtis; Cotnam, Jasmine; Cousineau, Janette; Fraleigh, Annette; Gagnier, Brenda; Gasingirwa, Claudine; Greene, Saara; Hart, Trevor; Islam, Shazia; Kaushic, Charu; Kennedy, Logan; Kerr, Desiree; Kiboyogo, Maxime; Kwaramba, Gladys; Leonard, Lynne; Lewis, Johanna; Logie, Carmen; Margolese, Shari; Muchenje, Marvelous; Ndungʼu, Mary; OʼBrien, Kelly; Ouellette, Charlene; Powis, Jeff; Quan, Corinna; Raboud, Janet; Rachlis, Anita; Ralph, Edward; Rourke, Sean; Rueda, Sergio; Sandre, Roger; Smaill, Fiona; Smith, Stephanie; Tigere, Tsitsi; Tharao, Wangari; Walmsley, Sharon; Wobeser, Wendy; Yee, Jessica; Yudin, Mark; Baril, Jean-Guy; Burke, Nora Butler; Clément, Pierrette; Dayle, Janice; Dubuc, Danièle; Fernet, Mylène; Groleau, Danielle; Hot, Aurélie; Klein, Marina; Martin, Carrie; Massie, Lyne; Ménard, Brigitte; OʼBrien, Nadia; Otis, Joanne; Peltier, Doris; Pierre, Alie; Proulx-Boucher, Karène; Rouleau, Danielle; Savoie, Édénia; Tremblay, Cécile; Trottier, Benoit; Trottier, Sylvie; Tsoukas, Christos; Gahagan, Jacqueline; Hankins, Catherine; Masching, Renee; Ogunnaike-Cooke, Susanna

2018-02-01

Associations between HIV-related stigma and reduced antiretroviral therapy (ART) adherence are widely established, yet the mechanisms accounting for this relationship are underexplored. There has been less attention to HIV-related stigma and its associations with ART initiation and current ART use. We examined pathways from HIV-related stigma to ART initiation, current ART use, and ART adherence among women living with HIV in Canada. We used baseline survey data from a national cohort of women living with HIV in Canada (n = 1425). Structural equation modeling using weighted least squares estimation methods was conducted to test the direct effects of HIV-related stigma dimensions (personalized, negative self-image, and public attitudes) on ART initiation, current ART use, and 90% ART adherence, and indirect effects through depression and HIV disclosure concerns, adjusting for sociodemographic factors. In the final model, the direct paths from personalized stigma to ART initiation (β = -0.104, P < 0.05) and current ART use (β = -0.142, P < 0.01), and negative self-image to ART initiation (β = -0.113, P < 0.01) were significant, accounting for the mediation effects of depression and HIV disclosure concerns. Depression mediated the pathways from personalized stigma to ART adherence, and negative self-image to current ART use and ART adherence. Final model fit indices suggest that the model fit the data well [χ(25) = 90.251, P < 0.001; comparative fit index = 0.945; root-mean-square error of approximation = 0.044]. HIV-related stigma is associated with reduced likelihood of ART initiation and current ART use, and suboptimal ART adherence. To optimize the benefit of ART among women living with HIV, interventions should reduce HIV-related stigma and address depression.

Relationship between Mental Health and Burden among Primary Caregivers of Outpatients with Schizophrenia.

PubMed

Yu, Wenjun; Chen, Jia; Hu, Jize; Hu, JingChu

2018-01-24

There is growing recognition that caring for a patient with schizophrenia often results in high levels of perceived burden and poorer overall mental health for caregivers. A quantitative cross-sectional design and standardized instruments were used to collect data from 355 primary caregivers of adults in outpatient care with schizophrenia in China. Structural equation modeling was used to examine the association between caregiver burden and mental health among primary caregivers and whether this association is influenced by personality, coping style, and family functioning, based on a diathesis-stress perspective. Goodness-of-fit indices (χ 2 /df = 1.406, GFI = 0.919, CFI = 0.957, etc.) confirmed that the modified model fit the data well. In line with the diathesis-stress model, and with this study's hypotheses, we found that caregiver burden was significantly related to mental health outcomes directly. The final model showed that personality traits, coping style, and family function influenced the relationship between caregiver burden and mental health. The neuroticism personality traits have a direct effect on caregiver burden and family functioning in this sample. Coping style had a direct effect on the caregiver burden, and family functioning had a direct effect on the caregiver burden. Our final model about primary caregivers can be applied clinically to predict mental health outcomes from caregiver burden. © 2018 Family Process Institute.

The relationship between cost estimates reliability and BIM adoption: SEM analysis

NASA Astrophysics Data System (ADS)

Ismail, N. A. A.; Idris, N. H.; Ramli, H.; Rooshdi, R. R. Raja Muhammad; Sahamir, S. R.

2018-02-01

This paper presents the usage of Structural Equation Modelling (SEM) approach in analysing the effects of Building Information Modelling (BIM) technology adoption in improving the reliability of cost estimates. Based on the questionnaire survey results, SEM analysis using SPSS-AMOS application examined the relationships between BIM-improved information and cost estimates reliability factors, leading to BIM technology adoption. Six hypotheses were established prior to SEM analysis employing two types of SEM models, namely the Confirmatory Factor Analysis (CFA) model and full structural model. The SEM models were then validated through the assessment on their uni-dimensionality, validity, reliability, and fitness index, in line with the hypotheses tested. The final SEM model fit measures are: P-value=0.000, RMSEA=0.079<0.08, GFI=0.824, CFI=0.962>0.90, TLI=0.956>0.90, NFI=0.935>0.90 and ChiSq/df=2.259; indicating that the overall index values achieved the required level of model fitness. The model supports all the hypotheses evaluated, confirming that all relationship exists amongst the constructs are positive and significant. Ultimately, the analysis verified that most of the respondents foresee better understanding of project input information through BIM visualization, its reliable database and coordinated data, in developing more reliable cost estimates. They also perceive to accelerate their cost estimating task through BIM adoption.

Training models of anatomic shape variability

PubMed Central

Merck, Derek; Tracton, Gregg; Saboo, Rohit; Levy, Joshua; Chaney, Edward; Pizer, Stephen; Joshi, Sarang

2008-01-01

Learning probability distributions of the shape of anatomic structures requires fitting shape representations to human expert segmentations from training sets of medical images. The quality of statistical segmentation and registration methods is directly related to the quality of this initial shape fitting, yet the subject is largely overlooked or described in an ad hoc way. This article presents a set of general principles to guide such training. Our novel method is to jointly estimate both the best geometric model for any given image and the shape distribution for the entire population of training images by iteratively relaxing purely geometric constraints in favor of the converging shape probabilities as the fitted objects converge to their target segmentations. The geometric constraints are carefully crafted both to obtain legal, nonself-interpenetrating shapes and to impose the model-to-model correspondences required for useful statistical analysis. The paper closes with example applications of the method to synthetic and real patient CT image sets, including same patient male pelvis and head and neck images, and cross patient kidney and brain images. Finally, we outline how this shape training serves as the basis for our approach to IGRT∕ART. PMID:18777919

[The mediating role of organizational citizenship behavior between organizational justice and organizational effectiveness in nursing organizations].

PubMed

Park, Wall Yun; Yoon, Sook Hee

2009-04-01

This study was a secondary analysis to verify the mediating role of organizational citizenship behavior (OCB) between organizational justice (OJ) and organizational effectiveness (OE) in nursing organizations. The RN-BSNs and their colleagues in Seoul and Busan were subjects. The data was collected for 20 days between September 13 and October 2, 2004. Two hundred eighty three data sets were used for the final analysis. The fitness of models were tested using AMOS 5. The fitness of hypothetical model was moderate. Procedural Justice (PJ), Interaction Justice (IJ) and Distributive Justice (DJ) had direct effects on Job Satisfaction (JS), Organizational Commitment (OC) and Turnover Intention (TI) in OE, and indirect effects on JS, OC and TI mediated by OCB. The modified model improved with ideal fitness showed the causal relations among OE. In modified model, PJ, IJ and DJ had direct positive effects on OCB and JS and OC in OE, and indirect effects on JS and OC mediated by OCB. JS and OC in OE had a direct negative effect on TI. OCB mediated the relationship between OJ and OE, so the nursing managers should enhance OCB of the nurses in order to improve OE.

Nonlinear dynamic evolution and control in CCFN with mixed attachment mechanisms

NASA Astrophysics Data System (ADS)

Wang, Jianrong; Wang, Jianping; Han, Dun

2017-01-01

In recent years, wireless communication plays an important role in our lives. Cooperative communication, is used by a mobile station with single antenna to share with each other forming a virtual MIMO antenna system, will become a development with a diversity gain for wireless communication in tendency future. In this paper, a fitness model of evolution network based on complex networks with mixed attachment mechanisms is devised in order to study an actual network-CCFN (cooperative communication fitness network). Firstly, the evolution of CCFN is given by four cases with different probabilities, and the rate equations of nodes degree are presented to analyze the evolution of CCFN. Secondly, the degree distribution is analyzed by calculating the rate equation and numerical simulation with the examples of four fitness distributions such as power law, uniform fitness distribution, exponential fitness distribution and Rayleigh fitness distribution. Finally, the robustness of CCFN is studied by numerical simulation with four fitness distributions under random attack and intentional attack to analyze the effects of degree distribution, average path length and average degree. The results of this paper offers insights for building CCFN systems in order to program communication resources.

Conjoined constraints on modified gravity from the expansion history and cosmic growth

NASA Astrophysics Data System (ADS)

Basilakos, Spyros; Nesseris, Savvas

2017-09-01

In this paper we present conjoined constraints on several cosmological models from the expansion history H (z ) and cosmic growth f σ8. The models we study include the CPL w0wa parametrization, the holographic dark energy (HDE) model, the time-varying vacuum (ΛtCDM ) model, the Dvali, Gabadadze and Porrati (DGP) and Finsler-Randers (FRDE) models, a power-law f (T ) model, and finally the Hu-Sawicki f (R ) model. In all cases we perform a simultaneous fit to the SnIa, CMB, BAO, H (z ) and growth data, while also following the conjoined visualization of H (z ) and f σ8 as in Linder (2017). Furthermore, we introduce the figure of merit (FoM) in the H (z )-f σ8 parameter space as a way to constrain models that jointly fit both probes well. We use both the latest H (z ) and f σ8 data, but also LSST-like mocks with 1% measurements, and we find that the conjoined method of constraining the expansion history and cosmic growth simultaneously is able not only to place stringent constraints on these parameters, but also to provide an easy visual way to discriminate cosmological models. Finally, we confirm the existence of a tension between the growth-rate and Planck CMB data, and we find that the FoM in the conjoined parameter space of H (z )-f σ8(z ) can be used to discriminate between the Λ CDM model and certain classes of modified gravity models, namely the DGP and f (T ).

Event generator tunes obtained from underlying event and multiparton scattering measurements.

PubMed

Khachatryan, V; Sirunyan, A M; Tumasyan, A; Adam, W; Asilar, E; Bergauer, T; Brandstetter, J; Brondolin, E; Dragicevic, M; Erö, J; Friedl, M; Frühwirth, R; Ghete, V M; Hartl, C; Hörmann, N; Hrubec, J; Jeitler, M; Knünz, V; König, A; Krammer, M; Krätschmer, I; Liko, D; Matsushita, T; Mikulec, I; Rabady, D; Rahbaran, B; Rohringer, H; Schieck, J; Schöfbeck, R; Strauss, J; Treberer-Treberspurg, W; Waltenberger, W; Wulz, C-E; Mossolov, V; Shumeiko, N; Suarez Gonzalez, J; Alderweireldt, S; Cornelis, T; De Wolf, E A; Janssen, X; Knutsson, A; Lauwers, J; Luyckx, S; Van De Klundert, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Van Spilbeeck, A; Abu Zeid, S; Blekman, F; D'Hondt, J; Daci, N; De Bruyn, I; Deroover, K; Heracleous, N; Keaveney, J; Lowette, S; Moreels, L; Olbrechts, A; Python, Q; Strom, D; Tavernier, S; Van Doninck, W; Van Mulders, P; Van Onsem, G P; Van Parijs, I; Barria, P; Brun, H; Caillol, C; Clerbaux, B; De Lentdecker, G; Fasanella, G; Favart, L; Grebenyuk, A; Karapostoli, G; Lenzi, T; Léonard, A; Maerschalk, T; Marinov, A; Perniè, L; Randle-Conde, A; Seva, T; Vander Velde, C; Yonamine, R; Vanlaer, P; Yonamine, R; Zenoni, F; Zhang, F; Adler, V; Beernaert, K; Benucci, L; Cimmino, A; Crucy, S; Dobur, D; Fagot, A; Garcia, G; Gul, M; Mccartin, J; Ocampo Rios, A A; Poyraz, D; Ryckbosch, D; Salva, S; Sigamani, M; Tytgat, M; Van Driessche, W; Yazgan, E; Zaganidis, N; Basegmez, S; Beluffi, C; Bondu, O; Brochet, S; Bruno, G; Caudron, A; Ceard, L; Da Silveira, G G; Delaere, C; Favart, D; Forthomme, L; Giammanco, A; Hollar, J; Jafari, A; Jez, P; Komm, M; Lemaitre, V; Mertens, A; Musich, M; Nuttens, C; Perrini, L; Pin, A; Piotrzkowski, K; Popov, A; Quertenmont, L; Selvaggi, M; Vidal Marono, M; Beliy, N; Hammad, G H; Júnior, W L Aldá; Alves, F L; Alves, G A; Brito, L; Correa Martins Junior, M; Hamer, M; Hensel, C; Moraes, A; Pol, M E; Rebello Teles, P; Belchior Batista Das Chagas, E; Carvalho, W; Chinellato, J; Custódio, A; Da Costa, E M; De Jesus Damiao, D; De Oliveira Martins, C; 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Cheung, H W K; Chlebana, F; Cihangir, S; Elvira, V D; Fisk, I; Freeman, J; Gottschalk, E; Gray, L; Green, D; Grünendahl, S; Gutsche, O; Hanlon, J; Hare, D; Harris, R M; Hasegawa, S; Hirschauer, J; Hu, Z; Jayatilaka, B; Jindariani, S; Johnson, M; Joshi, U; Jung, A W; Klima, B; Kreis, B; Lammel, S; Linacre, J; Lincoln, D; Lipton, R; Liu, T; Lopes De Sá, R; Lykken, J; Maeshima, K; Marraffino, J M; Martinez Outschoorn, V I; Maruyama, S; Mason, D; McBride, P; Merkel, P; Mishra, K; Mrenna, S; Nahn, S; Newman-Holmes, C; O'Dell, V; Pedro, K; Prokofyev, O; Rakness, G; Sexton-Kennedy, E; Soha, A; Spalding, W J; Spiegel, L; Strobbe, N; Taylor, L; Tkaczyk, S; Tran, N V; Uplegger, L; Vaandering, E W; Vernieri, C; Verzocchi, M; Vidal, R; Weber, H A; Whitbeck, A; Acosta, D; Avery, P; Bortignon, P; Bourilkov, D; Carnes, A; Carver, M; Curry, D; Das, S; Field, R D; Furic, I K; Gleyzer, S V; Hugon, J; Konigsberg, J; Korytov, A; Kotov, K; Low, J F; Ma, P; Matchev, K; Mei, H; Milenovic, P; Mitselmakher, G; Rank, D; Rossin, R; Shchutska, L; Snowball, M; Sperka, D; Terentyev, N; Thomas, L; Wang, J; Wang, S; Yelton, J; Hewamanage, S; Linn, S; Markowitz, P; Martinez, G; Rodriguez, J L; Adams, J R; Ackert, A; Adams, T; Askew, A; Bein, S; Bochenek, J; Diamond, B; Haas, J; Hagopian, S; Hagopian, V; Johnson, K F; Khatiwada, A; Prosper, H; Weinberg, M; Baarmand, M M; Bhopatkar, V; Colafranceschi, S; Hohlmann, M; Kalakhety, H; Noonan, D; Roy, T; Yumiceva, F; Adams, M R; Apanasevich, L; Berry, D; Betts, R R; Bucinskaite, I; Cavanaugh, R; Evdokimov, O; Gauthier, L; Gerber, C E; Hofman, D J; Kurt, P; O'Brien, C; Sandoval Gonzalez, L D; Silkworth, C; Turner, P; Varelas, N; Wu, Z; Zakaria, M; Bilki, B; Clarida, W; Dilsiz, K; Durgut, S; Gandrajula, R P; Haytmyradov, M; Khristenko, V; Merlo, J-P; Mermerkaya, H; Mestvirishvili, A; Moeller, A; Nachtman, J; Ogul, H; Onel, Y; Ozok, F; Penzo, A; Snyder, C; Tiras, E; Wetzel, J; Yi, K; Anderson, I; Anderson, I; Barnett, B A; Blumenfeld, B; Eminizer, N; Fehling, D; 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New sets of parameters ("tunes") for the underlying-event (UE) modelling of the pythia8, pythia6 and herwig++ Monte Carlo event generators are constructed using different parton distribution functions. Combined fits to CMS UE proton-proton ([Formula: see text]) data at [Formula: see text] and to UE proton-antiproton ([Formula: see text]) data from the CDF experiment at lower [Formula: see text], are used to study the UE models and constrain their parameters, providing thereby improved predictions for proton-proton collisions at 13[Formula: see text]. In addition, it is investigated whether the values of the parameters obtained from fits to UE observables are consistent with the values determined from fitting observables sensitive to double-parton scattering processes. Finally, comparisons are presented of the UE tunes to "minimum bias" (MB) events, multijet, and Drell-Yan ([Formula: see text] lepton-antilepton+jets) observables at 7 and 8[Formula: see text], as well as predictions for MB and UE observables at 13[Formula: see text].

The Chandra Source Catalog: Spectral Properties

NASA Astrophysics Data System (ADS)

Doe, Stephen; Siemiginowska, Aneta L.; Refsdal, Brian L.; Evans, Ian N.; Anderson, Craig S.; Bonaventura, Nina R.; Chen, Judy C.; Davis, John E.; Evans, Janet D.; Fabbiano, Giuseppina; Galle, Elizabeth C.; Gibbs, Danny G., II; Glotfelty, Kenny J.; Grier, John D.; Hain, Roger; Hall, Diane M.; Harbo, Peter N.; He, Xiang Qun (Helen); Houck, John C.; Karovska, Margarita; Kashyap, Vinay L.; Lauer, Jennifer; McCollough, Michael L.; McDowell, Jonathan C.; Miller, Joseph B.; Mitschang, Arik W.; Morgan, Douglas L.; Mossman, Amy E.; Nichols, Joy S.; Nowak, Michael A.; Plummer, David A.; Primini, Francis A.; Rots, Arnold H.; Sundheim, Beth A.; Tibbetts, Michael S.; van Stone, David W.; Winkelman, Sherry L.; Zografou, Panagoula

2009-09-01

The first release of the Chandra Source Catalog (CSC) contains all sources identified from eight years' worth of publicly accessible observations. The vast majority of these sources have been observed with the ACIS detector and have spectral information in 0.5-7 keV energy range. Here we describe the methods used to automatically derive spectral properties for each source detected by the standard processing pipeline and included in the final CSC. Hardness ratios were calculated for each source between pairs of energy bands (soft, medium and hard) using the Bayesian algorithm (BEHR, Park et al. 2006). The sources with high signal to noise ratio (exceeding 150 net counts) were fit in Sherpa (the modeling and fitting application from the Chandra Interactive Analysis of Observations package, developed by the Chandra X-ray Center; see Freeman et al. 2001). Two models were fit to each source: an absorbed power law and a blackbody emission. The fitted parameter values for the power-law and blackbody models were included in the catalog with the calculated flux for each model. The CSC also provides the source energy flux computed from the normalizations of predefined power-law and black-body models needed to match the observed net X-ray counts. In addition, we provide access to data products for each source: a file with source spectrum, the background spectrum, and the spectral response of the detector. This work is supported by NASA contract NAS8-03060 (CXC).

Statistical damage constitutive model for rocks subjected to cyclic stress and cyclic temperature

NASA Astrophysics Data System (ADS)

Zhou, Shu-Wei; Xia, Cai-Chu; Zhao, Hai-Bin; Mei, Song-Hua; Zhou, Yu

2017-10-01

A constitutive model of rocks subjected to cyclic stress-temperature was proposed. Based on statistical damage theory, the damage constitutive model with Weibull distribution was extended. Influence of model parameters on the stress-strain curve for rock reloading after stress-temperature cycling was then discussed. The proposed model was initially validated by rock tests for cyclic stress-temperature and only cyclic stress. Finally, the total damage evolution induced by stress-temperature cycling and reloading after cycling was explored and discussed. The proposed constitutive model is reasonable and applicable, describing well the stress-strain relationship during stress-temperature cycles and providing a good fit to the test results. Elastic modulus in the reference state and the damage induced by cycling affect the shape of reloading stress-strain curve. Total damage induced by cycling and reloading after cycling exhibits three stages: initial slow increase, mid-term accelerated increase, and final slow increase.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ballering, Nicholas P.; Su, Kate Y. L.; Rieke, George H.

We investigate whether varying the dust composition (described by the optical constants) can solve a persistent problem in debris disk modeling—the inability to fit the thermal emission without overpredicting the scattered light. We model five images of the β Pictoris disk: two in scattered light from the Hubble Space Telescope ( HST )/Space Telescope Imaging Spectrograph at 0.58 μ m and HST /Wide Field Camera 3 (WFC 3) at 1.16 μ m, and three in thermal emission from Spitzer /Multiband Imaging Photometer for Spitzer (MIPS) at 24 μ m, Herschel /PACS at 70 μ m, and Atacama Large Millimeter/submillimeter Arraymore » at 870 μ m. The WFC3 and MIPS data are published here for the first time. We focus our modeling on the outer part of this disk, consisting of a parent body ring and a halo of small grains. First, we confirm that a model using astronomical silicates cannot simultaneously fit the thermal and scattered light data. Next, we use a simple generic function for the optical constants to show that varying the dust composition can improve the fit substantially. Finally, we model the dust as a mixture of the most plausible debris constituents: astronomical silicates, water ice, organic refractory material, and vacuum. We achieve a good fit to all data sets with grains composed predominantly of silicates and organics, while ice and vacuum are, at most, present in small amounts. This composition is similar to one derived from previous work on the HR 4796A disk. Our model also fits the thermal spectral energy distribution, scattered light colors, and high-resolution mid-IR data from T-ReCS for this disk. Additionally, we show that sub-blowout grains are a necessary component of the halo.« less

Model Atmospheres for Massive Gas Giants with Thick Clouds: Application to the HR 8799 Planets and Predictions for Future Detections

NASA Astrophysics Data System (ADS)

Madhusudhan, Nikku; Burrows, Adam; Currie, Thayne

2011-08-01

We have generated an extensive new suite of massive giant planet atmosphere models and used it to obtain fits to photometric data for the planets HR 8799b, c, and d. We consider a wide range of cloudy and cloud-free models. The cloudy models incorporate different geometrical and optical thicknesses, modal particle sizes, and metallicities. For each planet and set of cloud parameters, we explore grids in gravity and effective temperature, with which we determine constraints on the planet's mass and age. Our new models yield statistically significant fits to the data, and conclusively confirm that the HR 8799 planets have much thicker clouds than those required to explain data for typical L and T dwarfs. Both models with (1) physically thick forsterite clouds and a 60 μm modal particle size and (2) clouds made of 1 μm sized pure iron droplets and 1% supersaturation fit the data. Current data are insufficient to accurately constrain the microscopic cloud properties, such as composition and particle size. The range of best-estimated masses for HR 8799b, HR 8799c, and HR 8799d conservatively span 2-12 MJ , 6-13 MJ , and 3-11 MJ , respectively, and imply coeval ages between ~10 and ~150 Myr, consistent with previously reported stellar ages. The best-fit temperatures and gravities are slightly lower than values obtained by Currie et al. using even thicker cloud models. Finally, we use these models to predict the near-to-mid-IR colors of soon-to-be imaged planets. Our models predict that planet-mass objects follow a locus in some near-to-mid-IR color-magnitude diagrams that is clearly separable from the standard L/T dwarf locus for field brown dwarfs.

R-matrix description of particle energy spectra produced by low-energy 3H + 3H reactions

DOE PAGES

Brune, C. R.; Caggiano, J. A.; Sayre, D. B.; ...

2015-07-20

An R-matrix model for three-body final states is presented and applied to a recent measurement of the neutron energy spectrum from the 3H + 3H→ 2n + α reaction. The calculation includes the n alpha and n n interactions in the final state, angular momentum conservation, antisymmetrization, and the interference between different channels. A good fit to the measured spectrum is obtained, where clear evidence for the 5He ground state is observed. The model is also used to predict the alpha-particle spectrum from 3H + 3H as well as particle spectra from 3He + 3He. The R-matrix approach presented heremore » is very general, and can be adapted to a wide variety of problems with three-body final states.« less

Construct Validity of the Autism Impact Measure (AIM).

PubMed

Mazurek, Micah O; Carlson, Coleen; Baker-Ericzén, Mary; Butter, Eric; Norris, Megan; Kanne, Stephen

2018-01-17

The Autism Impact Measure (AIM) was designed to track incremental change in frequency and impact of core ASD symptoms. The current study examined the structural and convergent validity of the AIM in a large sample of children with ASD. The results of a series of exploratory and confirmatory factor analyses yielded a final model with five theoretically and empirically meaningful subdomains: Repetitive Behavior, Atypical Behavior, Communication, Social Reciprocity, and Peer Interaction. The final model showed very good fit both overall and for each of the five factors, indicating excellent structural validity. AIM subdomain scores were significantly correlated with measures of similar constructs across all five domains. The results provide further support for the psychometric properties of the AIM.

On the convexity of ROC curves estimated from radiological test results.

PubMed

Pesce, Lorenzo L; Metz, Charles E; Berbaum, Kevin S

2010-08-01

Although an ideal observer's receiver operating characteristic (ROC) curve must be convex-ie, its slope must decrease monotonically-published fits to empirical data often display "hooks." Such fits sometimes are accepted on the basis of an argument that experiments are done with real, rather than ideal, observers. However, the fact that ideal observers must produce convex curves does not imply that convex curves describe only ideal observers. This article aims to identify the practical implications of nonconvex ROC curves and the conditions that can lead to empirical or fitted ROC curves that are not convex. This article views nonconvex ROC curves from historical, theoretical, and statistical perspectives, which we describe briefly. We then consider population ROC curves with various shapes and analyze the types of medical decisions that they imply. Finally, we describe how sampling variability and curve-fitting algorithms can produce ROC curve estimates that include hooks. We show that hooks in population ROC curves imply the use of an irrational decision strategy, even when the curve does not cross the chance line, and therefore usually are untenable in medical settings. Moreover, we sketch a simple approach to improve any nonconvex ROC curve by adding statistical variation to the decision process. Finally, we sketch how to test whether hooks present in ROC data are likely to have been caused by chance alone and how some hooked ROCs found in the literature can be easily explained as fitting artifacts or modeling issues. In general, ROC curve fits that show hooks should be looked on with suspicion unless other arguments justify their presence. 2010 AUR. Published by Elsevier Inc. All rights reserved.

On the convexity of ROC curves estimated from radiological test results

PubMed Central

Pesce, Lorenzo L.; Metz, Charles E.; Berbaum, Kevin S.

2010-01-01

Rationale and Objectives Although an ideal observer’s receiver operating characteristic (ROC) curve must be convex — i.e., its slope must decrease monotonically — published fits to empirical data often display “hooks.” Such fits sometimes are accepted on the basis of an argument that experiments are done with real, rather than ideal, observers. However, the fact that ideal observers must produce convex curves does not imply that convex curves describe only ideal observers. This paper aims to identify the practical implications of non-convex ROC curves and the conditions that can lead to empirical and/or fitted ROC curves that are not convex. Materials and Methods This paper views non-convex ROC curves from historical, theoretical and statistical perspectives, which we describe briefly. We then consider population ROC curves with various shapes and analyze the types of medical decisions that they imply. Finally, we describe how sampling variability and curve-fitting algorithms can produce ROC curve estimates that include hooks. Results We show that hooks in population ROC curves imply the use of an irrational decision strategy, even when the curve doesn’t cross the chance line, and therefore usually are untenable in medical settings. Moreover, we sketch a simple approach to improve any non-convex ROC curve by adding statistical variation to the decision process. Finally, we sketch how to test whether hooks present in ROC data are likely to have been caused by chance alone and how some hooked ROCs found in the literature can be easily explained as fitting artifacts or modeling issues. Conclusion In general, ROC curve fits that show hooks should be looked upon with suspicion unless other arguments justify their presence. PMID:20599155

Coarse-Grained Molecular Models of Water: A Review

PubMed Central

Hadley, Kevin R.; McCabe, Clare

2012-01-01

Coarse-grained (CG) models have proven to be very effective tools in the study of phenomena or systems that involve large time- and length-scales. By decreasing the degrees of freedom in the system and using softer interactions than seen in atomistic models, larger timesteps can be used and much longer simulation times can be studied. CG simulations are widely used to study systems of biological importance that are beyond the reach of atomistic simulation, necessitating a computationally efficient and accurate CG model for water. In this review, we discuss the methods used for developing CG water models and the relative advantages and disadvantages of the resulting models. In general, CG water models differ with regards to how many waters each CG group or bead represents, whether analytical or tabular potentials have been used to describe the interactions, and how the model incorporates electrostatic interactions. Finally, how the models are parameterized depends on their application, so, while some are fitted to experimental properties such as surface tension and density, others are fitted to radial distribution functions extracted from atomistic simulations. PMID:22904601

A laboratory-calibrated model of coho salmon growth with utility for ecological analyses

USGS Publications Warehouse

Manhard, Christopher V.; Som, Nicholas A.; Perry, Russell W.; Plumb, John M.

2018-01-01

We conducted a meta-analysis of laboratory- and hatchery-based growth data to estimate broadly applicable parameters of mass- and temperature-dependent growth of juvenile coho salmon (Oncorhynchus kisutch). Following studies of other salmonid species, we incorporated the Ratkowsky growth model into an allometric model and fit this model to growth observations from eight studies spanning ten different populations. To account for changes in growth patterns with food availability, we reparameterized the Ratkowsky model to scale several of its parameters relative to ration. The resulting model was robust across a wide range of ration allocations and experimental conditions, accounting for 99% of the variation in final body mass. We fit this model to growth data from coho salmon inhabiting tributaries and constructed ponds in the Klamath Basin by estimating habitat-specific indices of food availability. The model produced evidence that constructed ponds provided higher food availability than natural tributaries. Because of their simplicity (only mass and temperature are required as inputs) and robustness, ration-varying Ratkowsky models have utility as an ecological tool for capturing growth in freshwater fish populations.

Maximum Likelihood Analysis of Low Energy CDMS II Germanium Data

DOE PAGES

Agnese, R.

2015-03-30

We report on the results of a search for a Weakly Interacting Massive Particle (WIMP) signal in low-energy data of the Cryogenic Dark Matter Search experiment using a maximum likelihood analysis. A background model is constructed using GEANT4 to simulate the surface-event background from Pb210decay-chain events, while using independent calibration data to model the gamma background. Fitting this background model to the data results in no statistically significant WIMP component. In addition, we also perform fits using an analytic ad hoc background model proposed by Collar and Fields, who claimed to find a large excess of signal-like events in ourmore » data. Finally, we confirm the strong preference for a signal hypothesis in their analysis under these assumptions, but excesses are observed in both single- and multiple-scatter events, which implies the signal is not caused by WIMPs, but rather reflects the inadequacy of their background model.« less

Adaptation to nursing home: The role of leisure activities in light of motivation and relatedness.

PubMed

Altintas, Emin; De Benedetto, Giorgio; Gallouj, Karim

Based on the motivational sequence described in Self-Determination Theory, this study explored the relationship between relatedness, motivation, adaptation and leisure in nursing homes. We formulated the hypothesis that the variables of the study would be found in an integrative mediational sequence: Participation in leisure activities→Relatedness→Self-determined motivation→Adaptation to nursing homes. Participants (N=112, mean age=84.17) were invited to complete questionnaires assessing these variables. Results of the path analysis found an unsatisfactory fit for this model but revealed another model (Model 2) with a good fit index: Relatedness→Participation in leisure activities→Self-determined motivation→Adaptation to nursing homes→Relatedness. Model 2 fitted better than model 1: the Chi-square values were not significant, Chi 2 (df=2)=5.1, p=0.078 and other indices were satisfactory (CFI=0.930, RMSEA=0.049 and NFI=0.918). These results suggest that feeling connected and secure in the relationships with others, and integrated as an individual to the group contribute to enhance leisure practice, self-determined motivation, and finally adaptation to life environment. Consequently, the relatedness promotes leisure activities practice which represents a central adaptive behavior in nursing homes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Experimental study of the γ p →π0η p reaction with the A2 setup at the Mainz Microtron

NASA Astrophysics Data System (ADS)

Sokhoyan, V.; Prakhov, S.; Fix, A.; Abt, S.; Achenbach, P.; Adlarson, P.; Afzal, F.; Aguar-Bartolomé, P.; Ahmed, Z.; Ahrens, J.; Annand, J. R. M.; Arends, H. J.; Bantawa, K.; Bashkanov, M.; Beck, R.; Biroth, M.; Borisov, N. S.; Braghieri, A.; Briscoe, W. J.; Cherepnya, S.; Cividini, F.; Collicott, C.; Costanza, S.; Denig, A.; Dieterle, M.; Downie, E. J.; Drexler, P.; Ferretti Bondy, M. I.; Fil'kov, L. V.; Gardner, S.; Garni, S.; Glazier, D. I.; Gorodnov, I.; Gradl, W.; Günther, M.; Gurevich, G. M.; Hamill, C. B.; Heijkenskjöld, L.; Hornidge, D.; Huber, G. M.; Käser, A.; Kashevarov, V. L.; Kay, S.; Keshelashvili, I.; Kondratiev, R.; Korolija, M.; Krusche, B.; Lazarev, A.; Lisin, V.; Livingston, K.; Lutterer, S.; MacGregor, I. J. D.; Manley, D. M.; Martel, P. P.; McGeorge, J. C.; Middleton, D. G.; Miskimen, R.; Mornacchi, E.; Mushkarenkov, A.; Neganov, A.; Neiser, A.; Oberle, M.; Ostrick, M.; Otte, P. B.; Paudyal, D.; Pedroni, P.; Polonski, A.; Ron, G.; Rostomyan, T.; Sarty, A.; Sfienti, C.; Spieker, K.; Steffen, O.; Strakovsky, I. I.; Strandberg, B.; Strub, Th.; Supek, I.; Thiel, A.; Thiel, M.; Thomas, A.; Unverzagt, M.; Usov, Yu. A.; Wagner, S.; Walford, N. K.; Watts, D. P.; Werthmüller, D.; Wettig, J.; Witthauer, L.; Wolfes, M.; Zana, L. A.; A2 Collaboration at MAMI

2018-05-01

The data available from the A2 Collaboration at MAMI were analyzed to select the γ p →π0η p reaction on an event-by-event basis, which allows for partial-wave analyses of three-body final states to obtain more reliable results, compared to fits to measured distributions. These data provide the world's best statistical accuracy in the energy range from threshold to Eγ=1.45 GeV, allowing a finer energy binning in the measurement of all observables needed for understanding the reaction dynamics. The results obtained for the measured observables are compared to existing models, and the impact from the new data is checked by the fit with the revised Mainz model.

Dynamic Analysis of Recalescence Process and Interface Growth of Eutectic Fe82B17Si1 Alloy

NASA Astrophysics Data System (ADS)

Fan, Y.; Liu, A. M.; Chen, Z.; Li, P. Z.; Zhang, C. H.

2018-03-01

By employing the glass fluxing technique in combination with cyclical superheating, the microstructural evolution of the undercooled Fe82B17Si1 alloy in the obtained undercooling range was studied. With increase in undercooling, a transition of cooling curves was detected from one recalescence to two recalescences, followed by one recalescence. The two types of cooling curves were fitted by the break equation and the Johnson-Mehl-Avrami-Kolmogorov model. Based on the cooling curves at different undercoolings, the recalescence rate was calculated by the multi-logistic growth model and the Boettinger-Coriel-Trivedi model. Both the recalescence features and the interface growth kinetics of the eutectic Fe82B17Si1 alloy were explored. The fitting results that were obtained using TEM (SAED), SEM and XRD were consistent with the changing rule of microstructures. Finally, the relationship between the microstructure and hardness was also investigated.

An empirical exploration of the relations between the health components of the International Classification of Functioning, Disability and Health (ICF).

PubMed

Perenboom, Rom J M; Wijlhuizen, Gert Jan; Garre, Francisca Galindo; Heerkens, Yvonne F; van Meeteren, Nico L U

2012-01-01

The aim of this study was to investigate the relations between the ICF components from a subjective perspective. Data on health condition and perceived functioning were collected among 2941 individuals with at least one chronic disease or disorder. Path analysis was used with perceived level of participation as the final denominator. Three models were tested: one with the number of chronic diseases and disorders as an indicator of health condition, one with perceived health as indicator of health condition, and one with perceived health as part of the personal factors. Although all models showed a good fit, the model with the best fit was that with perceived health as an indicator of health condition. From a patient's perspective, components of the ICF scheme appear to be associated with each other, with perceived health being the best indicator of the health condition.

Impact of Pathogen Population Heterogeneity and Stress-Resistant Variants on Food Safety.

PubMed

Abee, T; Koomen, J; Metselaar, K I; Zwietering, M H; den Besten, H M W

2016-01-01

This review elucidates the state-of-the-art knowledge about pathogen population heterogeneity and describes the genotypic and phenotypic analyses of persister subpopulations and stress-resistant variants. The molecular mechanisms underlying the generation of persister phenotypes and genetic variants are identified. Zooming in on Listeria monocytogenes, a comparative whole-genome sequence analysis of wild types and variants that enabled the identification of mutations in variants obtained after a single exposure to lethal food-relevant stresses is described. Genotypic and phenotypic features are compared to those for persistent strains isolated from food processing environments. Inactivation kinetics, models used for fitting, and the concept of kinetic modeling-based schemes for detection of variants are presented. Furthermore, robustness and fitness parameters of L. monocytogenes wild type and variants are used to model their performance in food chains. Finally, the impact of stress-resistant variants and persistence in food processing environments on food safety is discussed.

Using Social Cognitive Theory to Explain the Intention of Final-year Pharmacy Students to Undertake a Higher Degree in Pharmacy Practice Research.

PubMed

Carter, Stephen R; Moles, Rebekah J; Krass, Ines; Kritikos, Vicki S

2016-08-25

Objective. To develop and test a conceptual model that hypothesized student intention to undertake a higher degree in pharmacy practice research (PPR) would be increased by self-efficacy, outcome expectancy, and the social influence of faculty members. Methods. Cross-sectional surveys were completed by 387 final-year pharmacy undergraduates enrolled in 2012 and 2013. Structural equation modeling was used to explore relationships between variables and intention. Results. Fit indices were good. The model explained 55% of the variation in intention. As hypothesized, faculty social influence increased self-efficacy and indirectly increased outcome expectancy and intention. Conclusion. To increase pharmacy students' orientation towards a career in PPR, faculty members could use their social influence by highlighting PPR in their teaching.

[A preliminary study on the forming quality of titanium alloy removable partial denture frameworks fabricated by selective laser melting].

PubMed

Liu, Y F; Yu, H; Wang, W N; Gao, B

2017-06-09

Objective: To evaluate the processing accuracy, internal quality and suitability of the titanium alloy frameworks of removable partial denture (RPD) fabricated by selective laser melting (SLM) technique, and to provide reference for clinical application. Methods: The plaster model of one clinical patient was used as the working model, and was scanned and reconstructed into a digital working model. A RPD framework was designed on it. Then, eight corresponding RPD frameworks were fabricated using SLM technique. Three-dimensional (3D) optical scanner was used to scan and obtain the 3D data of the frameworks and the data was compared with the original computer aided design (CAD) model to evaluate their processing precision. The traditional casting pure titanium frameworks was used as the control group, and the internal quality was analyzed by X-ray examination. Finally, the fitness of the frameworks was examined on the plaster model. Results: The overall average deviation of the titanium alloy RPD framework fabricated by SLM technology was (0.089±0.076) mm, the root mean square error was 0.103 mm. No visible pores, cracks and other internal defects was detected in the frameworks. The framework fits on the plaster model completely, and its tissue surface fitted on the plaster model well. There was no obvious movement. Conclusions: The titanium alloy RPD framework fabricated by SLM technology is of good quality.

A data-driven model for constraint of present-day glacial isostatic adjustment in North America

NASA Astrophysics Data System (ADS)

Simon, K. M.; Riva, R. E. M.; Kleinherenbrink, M.; Tangdamrongsub, N.

2017-09-01

Geodetic measurements of vertical land motion and gravity change are incorporated into an a priori model of present-day glacial isostatic adjustment (GIA) in North America via least-squares adjustment. The result is an updated GIA model wherein the final predicted signal is informed by both observational data, and prior knowledge (or intuition) of GIA inferred from models. The data-driven method allows calculation of the uncertainties of predicted GIA fields, and thus offers a significant advantage over predictions from purely forward GIA models. In order to assess the influence each dataset has on the final GIA prediction, the vertical land motion and GRACE-measured gravity data are incorporated into the model first independently (i.e., one dataset only), then simultaneously. The relative weighting of the datasets and the prior input is iteratively determined by variance component estimation in order to achieve the most statistically appropriate fit to the data. The best-fit model is obtained when both datasets are inverted and gives respective RMS misfits to the GPS and GRACE data of 1.3 mm/yr and 0.8 mm/yr equivalent water layer change. Non-GIA signals (e.g., hydrology) are removed from the datasets prior to inversion. The post-fit residuals between the model predictions and the vertical motion and gravity datasets, however, suggest particular regions where significant non-GIA signals may still be present in the data, including unmodeled hydrological changes in the central Prairies west of Lake Winnipeg. Outside of these regions of misfit, the posterior uncertainty of the predicted model provides a measure of the formal uncertainty associated with the GIA process; results indicate that this quantity is sensitive to the uncertainty and spatial distribution of the input data as well as that of the prior model information. In the study area, the predicted uncertainty of the present-day GIA signal ranges from ∼0.2-1.2 mm/yr for rates of vertical land motion, and from ∼3-4 mm/yr of equivalent water layer change for gravity variations.

Identification and quantification of ciprofloxacin in urine through excitation-emission fluorescence and three-way PARAFAC calibration.

PubMed

Ortiz, M C; Sarabia, L A; Sánchez, M S; Giménez, D

2009-05-29

Due to the second-order advantage, calibration models based on parallel factor analysis (PARAFAC) decomposition of three-way data are becoming important in routine analysis. This work studies the possibility of fitting PARAFAC models with excitation-emission fluorescence data for the determination of ciprofloxacin in human urine. The finally chosen PARAFAC decomposition is built with calibration samples spiked with ciprofloxacin, and with other series of urine samples that were also spiked. One of the series of samples has also another drug because the patient was taking mesalazine. The mesalazine is a fluorescent substance that interferes with the ciprofloxacin. Finally, the procedure is applied to samples of a patient who was being treated with ciprofloxacin. The trueness has been established by the regression "predicted concentration versus added concentration". The recovery factor is 88.3% for ciprofloxacin in urine, and the mean of the absolute value of the relative errors is 4.2% for 46 test samples. The multivariate sensitivity of the fit calibration model is evaluated by a regression between the loadings of PARAFAC linked to ciprofloxacin versus the true concentration in spiked samples. The multivariate capability of discrimination is near 8 microg L(-1) when the probabilities of false non-compliance and false compliance are fixed at 5%.

49 CFR 385.19 - Safety fitness information.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 5 2011-10-01 2011-10-01 false Safety fitness information. 385.19 Section 385.19... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION FEDERAL MOTOR CARRIER SAFETY REGULATIONS SAFETY FITNESS PROCEDURES General § 385.19 Safety fitness information. (a) Final safety ratings, remedial directives, and safety...

49 CFR 385.19 - Safety fitness information.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 5 2010-10-01 2010-10-01 false Safety fitness information. 385.19 Section 385.19... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION FEDERAL MOTOR CARRIER SAFETY REGULATIONS SAFETY FITNESS PROCEDURES General § 385.19 Safety fitness information. (a) Final safety ratings, remedial directives, and safety...

Rasch Model Analysis with the BICAL Computer Program

DTIC Science & Technology

1976-09-01

and persons which lead to measures that persist from trial to trial . The measurement model is essential in this process because it provides a framework...and his students. Section 15 two derives the estimating equations for the Bernoulli (i.e. one trial per task) form : " and then generalizes to the...Binomial form (several trials per task). Finall) goodness of fit tests are presented for assessing the adequacy of the calibration. t { ) I I I 41 CHAPTER

Carbon emissions risk map from deforestation in the tropical Amazon

NASA Astrophysics Data System (ADS)

Ometto, J.; Soler, L. S.; Assis, T. D.; Oliveira, P. V.; Aguiar, A. P.

2011-12-01

Assis, Pedro Valle This work aims to estimate the carbon emissions from tropical deforestation in the Brazilian Amazon associated to the risk assessment of future land use change. The emissions are estimated by incorporating temporal deforestation dynamics, accounting for the biophysical and socioeconomic heterogeneity in the region, as well secondary forest growth dynamic in abandoned areas. The land cover change model that supported the risk assessment of deforestation, was run based on linear regressions. This method takes into account spatial heterogeneity of deforestation as the spatial variables adopted to fit the final regression model comprise: environmental aspects, economic attractiveness, accessibility and land tenure structure. After fitting a suitable regression models for each land cover category, the potential of each cell to be deforested (25x25km and 5x5 km of resolution) in the near future was used to calculate the risk assessment of land cover change. The carbon emissions model combines high-resolution new forest clear-cut mapping and four alternative sources of spatial information on biomass distribution for different vegetation types. The risk assessment map of CO2 emissions, was obtained by crossing the simulation results of the historical land cover changes to a map of aboveground biomass contained in the remaining forest. This final map represents the risk of CO2 emissions at 25x25km and 5x5 km until 2020, under a scenario of carbon emission reduction target.

49 CFR 385.19 - Safety fitness information.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 5 2013-10-01 2013-10-01 false Safety fitness information. 385.19 Section 385.19... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION FEDERAL MOTOR CARRIER SAFETY REGULATIONS SAFETY FITNESS PROCEDURES General § 385.19 Safety fitness information. (a) Final ratings will be made available to other Federal and...

49 CFR 385.19 - Safety fitness information.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 5 2012-10-01 2012-10-01 false Safety fitness information. 385.19 Section 385.19... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION FEDERAL MOTOR CARRIER SAFETY REGULATIONS SAFETY FITNESS PROCEDURES General § 385.19 Safety fitness information. (a) Final ratings will be made available to other Federal and...

49 CFR 385.19 - Safety fitness information.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 5 2014-10-01 2014-10-01 false Safety fitness information. 385.19 Section 385.19... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION FEDERAL MOTOR CARRIER SAFETY REGULATIONS SAFETY FITNESS PROCEDURES General § 385.19 Safety fitness information. (a) Final ratings will be made available to other Federal and...

Improved parameter inference in catchment models: 1. Evaluating parameter uncertainty

NASA Astrophysics Data System (ADS)

Kuczera, George

1983-10-01

A Bayesian methodology is developed to evaluate parameter uncertainty in catchment models fitted to a hydrologic response such as runoff, the goal being to improve the chance of successful regionalization. The catchment model is posed as a nonlinear regression model with stochastic errors possibly being both autocorrelated and heteroscedastic. The end result of this methodology, which may use Box-Cox power transformations and ARMA error models, is the posterior distribution, which summarizes what is known about the catchment model parameters. This can be simplified to a multivariate normal provided a linearization in parameter space is acceptable; means of checking and improving this assumption are discussed. The posterior standard deviations give a direct measure of parameter uncertainty, and study of the posterior correlation matrix can indicate what kinds of data are required to improve the precision of poorly determined parameters. Finally, a case study involving a nine-parameter catchment model fitted to monthly runoff and soil moisture data is presented. It is shown that use of ordinary least squares when its underlying error assumptions are violated gives an erroneous description of parameter uncertainty.

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Relaxation Property and Stability Analysis of the Quasispecies Models

NASA Astrophysics Data System (ADS)

Feng, Xiao-Li; Li, Yu-Xiao; Gu, Jian-Zhong; Zhuo, Yi-Zhong

2009-10-01

The relaxation property of both Eigen model and Crow-Kimura model with a single peak fitness landscape is studied from phase transition point of view. We first analyze the eigenvalue spectra of the replication mutation matrices. For sufficiently long sequences, the almost crossing point between the largest and second-largest eigenvalues locates the error threshold at which critical slowing down behavior appears. We calculate the critical exponent in the limit of infinite sequence lengths and compare it with the result from numerical curve fittings at sufficiently long sequences. We find that for both models the relaxation time diverges with exponent 1 at the error (mutation) threshold point. Results obtained from both methods agree quite well. From the unlimited correlation length feature, the first order phase transition is further confirmed. Finally with linear stability theory, we show that the two model systems are stable for all ranges of mutation rate. The Eigen model is asymptotically stable in terms of mutant classes, and the Crow-Kimura model is completely stable.

Protonation of Different Goethite Surfaces - Unified Models for NaNO3 and NaCl Media.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lutzenkirchen, Johannes; Boily, Jean F.; Gunneriusson, Lars

2008-01-01

Acid-base titration data for two goethites samples in sodium nitrate and sodium chloride media are discussed. The data are modelled based on various surface complexation models in the framework of the MUlti SIte Complexation (MUSIC) model. Various assumptions with respect to the goethite morphology are considered in determining the site density of the surface functional groups. The results from the various model applications are not statistically significant in terms of goodness of fit. More importantly, various published assumptions with respect to the goethite morphology (i.e. the contributions of different crystal planes and their repercussions on the “overall” site densities ofmore » the various surface functional groups) do not significantly affect the final model parameters. The simultaneous fit of the chloride and nitrate data results in electrolyte binding constants, which are applicable over a wide range of electrolyte concentrations including mixtures of chloride and nitrate. Model parameters for the high surface area goethite sample are in excellent agreement with parameters that were independently obtained by another group on different goethite titration data sets.« less

PyFolding: Open-Source Graphing, Simulation, and Analysis of the Biophysical Properties of Proteins.

PubMed

Lowe, Alan R; Perez-Riba, Albert; Itzhaki, Laura S; Main, Ewan R G

2018-02-06

For many years, curve-fitting software has been heavily utilized to fit simple models to various types of biophysical data. Although such software packages are easy to use for simple functions, they are often expensive and present substantial impediments to applying more complex models or for the analysis of large data sets. One field that is reliant on such data analysis is the thermodynamics and kinetics of protein folding. Over the past decade, increasingly sophisticated analytical models have been generated, but without simple tools to enable routine analysis. Consequently, users have needed to generate their own tools or otherwise find willing collaborators. Here we present PyFolding, a free, open-source, and extensible Python framework for graphing, analysis, and simulation of the biophysical properties of proteins. To demonstrate the utility of PyFolding, we have used it to analyze and model experimental protein folding and thermodynamic data. Examples include: 1) multiphase kinetic folding fitted to linked equations, 2) global fitting of multiple data sets, and 3) analysis of repeat protein thermodynamics with Ising model variants. Moreover, we demonstrate how PyFolding is easily extensible to novel functionality beyond applications in protein folding via the addition of new models. Example scripts to perform these and other operations are supplied with the software, and we encourage users to contribute notebooks and models to create a community resource. Finally, we show that PyFolding can be used in conjunction with Jupyter notebooks as an easy way to share methods and analysis for publication and among research teams. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Effective emissivities of isothermal blackbody cavities calculated by the Monte Carlo method using the three-component bidirectional reflectance distribution function model.

PubMed

Prokhorov, Alexander

2012-05-01

This paper proposes a three-component bidirectional reflectance distribution function (3C BRDF) model consisting of diffuse, quasi-specular, and glossy components for calculation of effective emissivities of blackbody cavities and then investigates the properties of the new reflection model. The particle swarm optimization method is applied for fitting a 3C BRDF model to measured BRDFs. The model is incorporated into the Monte Carlo ray-tracing algorithm for isothermal cavities. Finally, the paper compares the results obtained using the 3C model and the conventional specular-diffuse model of reflection.

A simple prescription for simulating and characterizing gravitational arcs

NASA Astrophysics Data System (ADS)

Furlanetto, C.; Santiago, B. X.; Makler, M.; de Bom, C.; Brandt, C. H.; Neto, A. F.; Ferreira, P. C.; da Costa, L. N.; Maia, M. A. G.

2013-01-01

Simple models of gravitational arcs are crucial for simulating large samples of these objects with full control of the input parameters. These models also provide approximate and automated estimates of the shape and structure of the arcs, which are necessary for detecting and characterizing these objects on massive wide-area imaging surveys. We here present and explore the ArcEllipse, a simple prescription for creating objects with a shape similar to gravitational arcs. We also present PaintArcs, which is a code that couples this geometrical form with a brightness distribution and adds the resulting object to images. Finally, we introduce ArcFitting, which is a tool that fits ArcEllipses to images of real gravitational arcs. We validate this fitting technique using simulated arcs and apply it to CFHTLS and HST images of tangential arcs around clusters of galaxies. Our simple ArcEllipse model for the arc, associated to a Sérsic profile for the source, recovers the total signal in real images typically within 10%-30%. The ArcEllipse+Sérsic models also automatically recover visual estimates of length-to-width ratios of real arcs. Residual maps between data and model images reveal the incidence of arc substructure. They may thus be used as a diagnostic for arcs formed by the merging of multiple images. The incidence of these substructures is the main factor that prevents ArcEllipse models from accurately describing real lensed systems.

New web-based algorithm to improve rigid gas permeable contact lens fitting in keratoconus.

PubMed

Ortiz-Toquero, Sara; Rodriguez, Guadalupe; de Juan, Victoria; Martin, Raul

2017-06-01

To calculate and validate a new web-based algorithm for selecting the back optic zone radius (BOZR) of spherical gas permeable (GP) lens in keratoconus eyes. A retrospective calculation (n=35; multiple regression analysis) and a posterior prospective validation (new sample of 50 keratoconus eyes) of a new algorithm to select the BOZR of spherical KAKC design GP lenses (Conoptica) in keratoconus were conducted. BOZR calculated with the new algorithm, manufacturer guidelines and APEX software were compared with the BOZR that was finally prescribed. Number of diagnostic lenses, ordered lenses and visits to achieve optimal fitting were recorded and compared those obtained for a control group [50 healthy eyes fitted with spherical GP (BIAS design; Conoptica)]. The new algorithm highly correlated with the final BOZR fitted (r 2 =0.825, p<0.001). BOZR of the first diagnostic lens using the new algorithm demonstrated lower difference with the final BOZR prescribed (-0.01±0.12mm, p=0.65; 58% difference≤0.05mm) than with the manufacturer guidelines (+0.12±0.22mm, p<0.001; 26% difference≤0.05mm) and APEX software (-0.14±0.16mm, p=0.001; 34% difference≤0.05mm). Close numbers of diagnostic lens (1.6±0.8, 1.3±0.5; p=0.02), ordered lens (1.4±0.6, 1.1±0.3; P<0.001), and visits (3.4±0.7, 3.2±0.4; p=0.08) were required to fit keratoconus and healthy eyes, respectively. This new algorithm (free access at www.calculens.com) improves spherical KAKC GP fitting in keratoconus and can reduce the practitioner and patient chair time to achieve a final acceptable fit in keratoconus. This algorithm reduces differences between keratoconus GP fitting (KAKC design) and standard GP (BIAS design) lenses fitting in healthy eyes. Copyright © 2016 British Contact Lens Association. Published by Elsevier Ltd. All rights reserved.

Cognitive and affective influences on perceived risk of ovarian cancer.

PubMed

Peipins, Lucy A; McCarty, Frances; Hawkins, Nikki A; Rodriguez, Juan L; Scholl, Lawrence E; Leadbetter, Steven

2015-03-01

Studies suggest that both affective and cognitive processes are involved in the perception of vulnerability to cancer and that affect has an early influence in this assessment of risk. We constructed a path model based on a conceptual framework of heuristic reasoning (affect, resemblance, and availability) coupled with cognitive processes involved in developing personal models of cancer causation. From an eligible cohort of 16 700 women in a managed care organization, we randomly selected 2524 women at high, elevated, and average risk of ovarian cancer and administered a questionnaire to test our model (response rate 76.3%). Path analysis delineated the relationships between personal and cognitive characteristics (number of relatives with cancer, age, ideas about cancer causation, perceived resemblance to an affected friend or relative, and ovarian cancer knowledge) and emotional constructs (closeness to an affected relative or friend, time spent processing the cancer experience, and cancer worry) on perceived risk of ovarian cancer. Our final model fit the data well (root mean square error of approximation (RMSEA) = 0.028, comparative fit index (CFI) = 0.99, normed fit index (NFI) = 0.98). This final model (1) demonstrated the nature and direction of relationships between cognitive characteristics and perceived risk; (2) showed that time spent processing the cancer experience was associated with cancer worry; and (3) showed that cancer worry moderately influenced perceived risk. Our results highlight the important role that family cancer experience has on cancer worry and shows how cancer experience translates into personal risk perceptions. This understanding informs the discordance between medical or objective risk assessment and personal risk assessment. Published in 2014. This article is a U.S. Government work and is in the public domain in the USA. Published in 2014. This article is a U.S. Government work and is in the public domain in the USA.

Research on Process Models of Basic Arithmetic Skills, Technical Report No. 303. Psychology and Education Series - Final Report.

ERIC Educational Resources Information Center

Suppes, Patrick; And Others

This report presents a theory of eye movement that accounts for main features of the stochastic behavior of eye-fixation durations and direction of movement of saccades in the process of solving arithmetic exercises of addition and subtraction. The best-fitting distribution of fixation durations with a relatively simple theoretical justification…

Leader empowering behaviours, staff nurse empowerment and work engagement/burnout.

PubMed

Greco, Paula; Laschinger, Heather K Spence; Wong, Carol

2006-12-01

Efforts to improve nursing working conditions are critical to retaining nurses currently in the system and attracting newcomers to the profession (Laschinger et al. 2003b). The nurse leader's empowering behaviours can be pivotal in the way nurses react to their work environment. The purpose of this study was to test a model examining the relationship between nurse leaders' empowerment behaviours, perceptions of staff empowerment, areas of work life and work engagement using Kanter's theory of structural power in organizations. A cross-sectional correlational survey design tested the model in a random sample of 322 staff nurses in acute care hospitals across Ontario. Overall, staff nurses perceived their leaders' behaviours to be somewhat empowering and their work environment to be moderately empowering. Fifty-three percent reported severe levels of burnout. Leader empowering behaviour had an indirect effect on emotional exhaustion (burnout) through structural empowerment and overall fit in the six areas of work life. The final model statistics revealed a good fit (chi(2)=30.4, chi=3, chi=0.96, chi=0.95, chi=0.95). These findings suggest that the Leader's empowering behaviours can enhance person-job fit and prevent burnout. These findings have important implications in the current nursing shortage.

Factors influencing diabetes self-management in Chinese people with type 2 diabetes.

PubMed

Xu, Yin; Toobert, Deborah; Savage, Christine; Pan, Wei; Whitmer, Kyra

2008-12-01

Patients with diabetes must incorporate a complicated regimen of self-management into their daily lives (e.g., taking medication, diet, exercise). Diabetes self-management (DSM) is the cornerstone for controlling diabetes and preventing diabetic complications. The purpose of this study was to test a model describing the effects of individual and environmental factors on DSM in a sample of patients with diabetes in Beijing, China. Survey data were gathered from a convenience sample of 201 Chinese adults with type 2 diabetes during outpatient visits. Data were analyzed using structural equation modeling. Model fit indices indicated a good fit to the data. In the final model, belief in treatment effectiveness and diabetes self-efficacy were proximate factors affecting DSM. Knowledge, social support, and provider-patient communication affected self-management indirectly via beliefs and self-efficacy. The findings provide a theoretical basis to direct the development of interventions for improving DSM in Chinese individuals with diabetes. (c) 2008 Wiley Periodicals, Inc.

Teacher Support Resources, Need Satisfaction and Well-Being.

PubMed

Doménech-Betoret, Fernando; Lloret-Segura, Susana; Gómez-Artiga, Amparo

2015-03-03

Based on Job Demands-Resources Model (JD-R), this study examines the relationships among teacher support resources, psychological need satisfaction, engagement and burnout in a sample of 282 Spanish secondary school teachers. Nine teacher psychological needs were identified based on the study of Bess and on the Self-Determination Theory (SDT). Self-report questionnaires were used to measure the constructs selected for this study and their interrelationships were examined by structural equation modeling. The results reveal a good model fit to the data (NNFI = .88; CFI = .90; GFI = .90; RMSEA = .061). The analyses indicate a positive and significant effect of latent variable Psychological Need Satisfaction on engagement (β = .74, p < .05), and a negative and significant effect on burnout (β = -.78, p ≤ .05). Furthermore, the results show the mediator role played by Psychological Need Satisfaction in the relationship between teacher support resources and both engagement and burnout (additional paths did not improve the model fit: Δχ2(2) = 2.428, p = .29). Finally, practical implications of these findings are discussed.

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

PubMed

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

2014-12-01

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

Comparison of thawing and freezing dark energy parametrizations

NASA Astrophysics Data System (ADS)

Pantazis, G.; Nesseris, S.; Perivolaropoulos, L.

2016-05-01

Dark energy equation of state w (z ) parametrizations with two parameters and given monotonicity are generically either convex or concave functions. This makes them suitable for fitting either freezing or thawing quintessence models but not both simultaneously. Fitting a data set based on a freezing model with an unsuitable (concave when increasing) w (z ) parametrization [like Chevallier-Polarski-Linder (CPL)] can lead to significant misleading features like crossing of the phantom divide line, incorrect w (z =0 ), incorrect slope, etc., that are not present in the underlying cosmological model. To demonstrate this fact we generate scattered cosmological data at both the level of w (z ) and the luminosity distance DL(z ) based on either thawing or freezing quintessence models and fit them using parametrizations of convex and of concave type. We then compare statistically significant features of the best fit w (z ) with actual features of the underlying model. We thus verify that the use of unsuitable parametrizations can lead to misleading conclusions. In order to avoid these problems it is important to either use both convex and concave parametrizations and select the one with the best χ2 or use principal component analysis thus splitting the redshift range into independent bins. In the latter case, however, significant information about the slope of w (z ) at high redshifts is lost. Finally, we propose a new family of parametrizations w (z )=w0+wa(z/1 +z )n which generalizes the CPL and interpolates between thawing and freezing parametrizations as the parameter n increases to values larger than 1.

[A Model for Predicting Career Satisfaction of Nurses Experiencing Rotation].

PubMed

Shin, Sook; Yu, Mi

2017-08-01

This study aimed to present and test a structural model for describing and predicting the factors affecting subjective career satisfaction of nurses experiencing rotation and to develop human resources management strategies for promoting their career satisfaction related to rotation. In this cross-sectional study, we recruited 233 nurses by convenience sampling who had over 1 year of career experience and who had experienced rotation at least once at G university hospital. Data were collected from August to September in 2016 using self-reported questionnaires. The exogenous variables consisted of rotation perception and rotation stress. Endogenous variables consisted of career growth opportunity, work engagement, and subjective career satisfaction. A hypothetical model was tested by asymptotically distribution-free estimates, and model goodness of fit was examined using absolute fit, incremental fit measures. The final model was approved and had suitable fit. We found that subjective career satisfaction was directly affected by rotation stress (β=.20, p=.019) and work engagement (β=.58, p<.001), indirectly affected by rotation perception (β=.43, p<.001) through career growth opportunity and work engagement. However, there was no total effect of rotation stress on subjective career satisfaction (β=-.09, p=.270). Career growth opportunity directly and indirectly affected subjective career satisfaction (β=.29, p<.001; β=.28, p<.001). These variables accounted for 65% of subjective career satisfaction. The results of this study suggest that it is necessary to establish systematic and planned criteria for rotation so that nurses can grow and develop through sustained work and become satisfied with their career. © 2017 Korean Society of Nursing Science

Correlated Parameter Fit of Arrhenius Model for Thermal Denaturation of Proteins and Cells

PubMed Central

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

HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python.

PubMed

Wiecki, Thomas V; Sofer, Imri; Frank, Michael J

2013-01-01

The diffusion model is a commonly used tool to infer latent psychological processes underlying decision-making, and to link them to neural mechanisms based on response times. Although efficient open source software has been made available to quantitatively fit the model to data, current estimation methods require an abundance of response time measurements to recover meaningful parameters, and only provide point estimates of each parameter. In contrast, hierarchical Bayesian parameter estimation methods are useful for enhancing statistical power, allowing for simultaneous estimation of individual subject parameters and the group distribution that they are drawn from, while also providing measures of uncertainty in these parameters in the posterior distribution. Here, we present a novel Python-based toolbox called HDDM (hierarchical drift diffusion model), which allows fast and flexible estimation of the the drift-diffusion model and the related linear ballistic accumulator model. HDDM requires fewer data per subject/condition than non-hierarchical methods, allows for full Bayesian data analysis, and can handle outliers in the data. Finally, HDDM supports the estimation of how trial-by-trial measurements (e.g., fMRI) influence decision-making parameters. This paper will first describe the theoretical background of the drift diffusion model and Bayesian inference. We then illustrate usage of the toolbox on a real-world data set from our lab. Finally, parameter recovery studies show that HDDM beats alternative fitting methods like the χ(2)-quantile method as well as maximum likelihood estimation. The software and documentation can be downloaded at: http://ski.clps.brown.edu/hddm_docs/

Reference frame access under the effects of great earthquakes: a least squares collocation approach for non-secular post-seismic evolution

NASA Astrophysics Data System (ADS)

Gómez, D. D.; Piñón, D. A.; Smalley, R.; Bevis, M.; Cimbaro, S. R.; Lenzano, L. E.; Barón, J.

2016-03-01

The 2010, (Mw 8.8) Maule, Chile, earthquake produced large co-seismic displacements and non-secular, post-seismic deformation, within latitudes 28°S-40°S extending from the Pacific to the Atlantic oceans. Although these effects are easily resolvable by fitting geodetic extended trajectory models (ETM) to continuous GPS (CGPS) time series, the co- and post-seismic deformation cannot be determined at locations without CGPS (e.g., on passive geodetic benchmarks). To estimate the trajectories of passive geodetic benchmarks, we used CGPS time series to fit an ETM that includes the secular South American plate motion and plate boundary deformation, the co-seismic discontinuity, and the non-secular, logarithmic post-seismic transient produced by the earthquake in the Posiciones Geodésicas Argentinas 2007 (POSGAR07) reference frame (RF). We then used least squares collocation (LSC) to model both the background secular inter-seismic and the non-secular post-seismic components of the ETM at the locations without CGPS. We tested the LSC modeled trajectories using campaign and CGPS data that was not used to generate the model and found standard deviations (95 % confidence level) for position estimates for the north and east components of 3.8 and 5.5 mm, respectively, indicating that the model predicts the post-seismic deformation field very well. Finally, we added the co-seismic displacement field, estimated using an elastic finite element model. The final, trajectory model allows accessing the POSGAR07 RF using post-Maule earthquake coordinates within 5 cm for ˜ 91 % of the passive test benchmarks.

76 FR 69601 - Suitability

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-09

... Federal Contractor Employee Fitness and Reinvestigating Individuals in Positions of Public Trust, to... governing suitability, or guidance related to fitness, as the Director determines appropriate.'' Finally... results of the background investigation and fitness determination (or later changes to that determination...

Predicting Soil Organic Carbon and Total Nitrogen in the Russian Chernozem from Depth and Wireless Color Sensor Measurements

NASA Astrophysics Data System (ADS)

Mikhailova, E. A.; Stiglitz, R. Y.; Post, C. J.; Schlautman, M. A.; Sharp, J. L.; Gerard, P. D.

2017-12-01

Color sensor technologies offer opportunities for affordable and rapid assessment of soil organic carbon (SOC) and total nitrogen (TN) in the field, but the applicability of these technologies may vary by soil type. The objective of this study was to use an inexpensive color sensor to develop SOC and TN prediction models for the Russian Chernozem (Haplic Chernozem) in the Kursk region of Russia. Twenty-one dried soil samples were analyzed using a Nix Pro™ color sensor that is controlled through a mobile application and Bluetooth to collect CIEL*a*b* (darkness to lightness, green to red, and blue to yellow) color data. Eleven samples were randomly selected to be used to construct prediction models and the remaining ten samples were set aside for cross validation. The root mean squared error (RMSE) was calculated to determine each model's prediction error. The data from the eleven soil samples were used to develop the natural log of SOC (lnSOC) and TN (lnTN) prediction models using depth, L*, a*, and b* for each sample as predictor variables in regression analyses. Resulting residual plots, root mean square errors (RMSE), mean squared prediction error (MSPE) and coefficients of determination ( R 2, adjusted R 2) were used to assess model fit for each of the SOC and total N prediction models. Final models were fit using all soil samples, which included depth and color variables, for lnSOC ( R 2 = 0.987, Adj. R 2 = 0.981, RMSE = 0.003, p-value < 0.001, MSPE = 0.182) and lnTN ( R 2 = 0.980 Adj. R 2 = 0.972, RMSE = 0.004, p-value < 0.001, MSPE = 0.001). Additionally, final models were fit for all soil samples, which included only color variables, for lnSOC ( R 2 = 0.959 Adj. R 2 = 0.949, RMSE = 0.007, p-value < 0.001, MSPE = 0.536) and lnTN ( R 2 = 0.912 Adj. R 2 = 0.890, RMSE = 0.015, p-value < 0.001, MSPE = 0.001). The results suggest that soil color may be used for rapid assessment of SOC and TN in these agriculturally important soils.

Parameter Estimation and Model Selection in Computational Biology

PubMed Central

Lillacci, Gabriele; Khammash, Mustafa

2010-01-01

A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants) are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection. PMID:20221262

Simultaneous calibration of end-member thermodynamic data and solution properties with correlated uncertainties

NASA Astrophysics Data System (ADS)

Antoshechkina, P. M.; Wolf, A. S.; Hamecher, E. A.; Asimow, P. D.; Ghiorso, M. S.

2013-12-01

Community databases such as EarthChem, LEPR, and AMCSD both increase demand for quantitative petrological tools, including thermodynamic models like the MELTS family of algorithms, and are invaluable in development of such tools. The need to extend existing solid solution models to include minor components such as Cr and Na has been evident for years but as the number of components increases it becomes impossible to completely separate derivation of end-member thermodynamic data from calibration of solution properties. In Hamecher et al. (2012; 2013) we developed a calibration scheme that directly interfaces with a MySQL database based on LEPR, with volume data from AMCSD and elsewhere. Here we combine that scheme with a Bayesian approach, where independent constraints on parameter values (e.g. existence of miscibility gaps) are combined with uncertainty propagation to give a more reliable best-fit along with associated model uncertainties. We illustrate the scheme with a new model of molar volume for (Ca,Fe,Mg,Mn,Na)3(Al,Cr,Fe3+,Fe2+,Mg,Mn,Si,Ti)2Si3O12 cubic garnets. For a garnet in this chemical system, the model molar volume is obtained by adding excess volume terms to a linear combination of nine independent end-member volumes. The model calibration is broken into three main stages: (1) estimation of individual end-member thermodynamic properties; (2) calibration of standard state volumes for all available independent and dependent end members; (3) fitting of binary and mixed composition data. For each calibration step, the goodness-of-fit includes weighted residuals as well as χ2-like penalty terms representing the (not necessarily Gaussian) prior constraints on parameter values. Using the Bayesian approach, uncertainties are correctly propagated forward to subsequent steps, allowing determination of final parameter values and correlated uncertainties that account for the entire calibration process. For the aluminosilicate garnets, optimal values of the bulk modulus and its pressure derivative are obtained by fitting published compression data using the Vinet equation of state, with the Mie-Grüneisen-Debye thermal pressure formalism to model thermal expansion. End-member thermal parameters are obtained by fitting volume data while ensuring that the heat capacity is consistent with the thermodynamic database of Berman and co-workers. For other end members, data for related compositions are used where such data exist; otherwise ultrasonic data or density functional theory results are taken or, for thermal parameters, systematics in cation radii are used. In stages (2) and (3) the remaining data at ambient conditions are fit. Using this step-wise calibration scheme, most parameters are modified little by subsequent calibration steps but some, such as the standard state volume of the Ti-bearing end member, can vary within calculated uncertainties. The final model satisfies desired criteria and fits almost all the data (more than 1000 points); only excess parameters that are justified by the data are activated. The scheme can be easily extended to calibration of end-member and solution properties from experimental phase equilibria. As a first step we obtain the internally consistent standard state entropy and enthalpy of formation for knorringite and discuss differences between our results and those of Klemme and co-workers.

Using Web Search Query Data to Monitor Dengue Epidemics: A New Model for Neglected Tropical Disease Surveillance

PubMed Central

Chan, Emily H.; Sahai, Vikram; Conrad, Corrie; Brownstein, John S.

2011-01-01

Background A variety of obstacles including bureaucracy and lack of resources have interfered with timely detection and reporting of dengue cases in many endemic countries. Surveillance efforts have turned to modern data sources, such as Internet search queries, which have been shown to be effective for monitoring influenza-like illnesses. However, few have evaluated the utility of web search query data for other diseases, especially those of high morbidity and mortality or where a vaccine may not exist. In this study, we aimed to assess whether web search queries are a viable data source for the early detection and monitoring of dengue epidemics. Methodology/Principal Findings Bolivia, Brazil, India, Indonesia and Singapore were chosen for analysis based on available data and adequate search volume. For each country, a univariate linear model was then built by fitting a time series of the fraction of Google search query volume for specific dengue-related queries from that country against a time series of official dengue case counts for a time-frame within 2003–2010. The specific combination of queries used was chosen to maximize model fit. Spurious spikes in the data were also removed prior to model fitting. The final models, fit using a training subset of the data, were cross-validated against both the overall dataset and a holdout subset of the data. All models were found to fit the data quite well, with validation correlations ranging from 0.82 to 0.99. Conclusions/Significance Web search query data were found to be capable of tracking dengue activity in Bolivia, Brazil, India, Indonesia and Singapore. Whereas traditional dengue data from official sources are often not available until after some substantial delay, web search query data are available in near real-time. These data represent valuable complement to assist with traditional dengue surveillance. PMID:21647308

Investigating different approaches to develop informative priors in hierarchical Bayesian safety performance functions.

PubMed

Yu, Rongjie; Abdel-Aty, Mohamed

2013-07-01

The Bayesian inference method has been frequently adopted to develop safety performance functions. One advantage of the Bayesian inference is that prior information for the independent variables can be included in the inference procedures. However, there are few studies that discussed how to formulate informative priors for the independent variables and evaluated the effects of incorporating informative priors in developing safety performance functions. This paper addresses this deficiency by introducing four approaches of developing informative priors for the independent variables based on historical data and expert experience. Merits of these informative priors have been tested along with two types of Bayesian hierarchical models (Poisson-gamma and Poisson-lognormal models). Deviance information criterion (DIC), R-square values, and coefficients of variance for the estimations were utilized as evaluation measures to select the best model(s). Comparison across the models indicated that the Poisson-gamma model is superior with a better model fit and it is much more robust with the informative priors. Moreover, the two-stage Bayesian updating informative priors provided the best goodness-of-fit and coefficient estimation accuracies. Furthermore, informative priors for the inverse dispersion parameter have also been introduced and tested. Different types of informative priors' effects on the model estimations and goodness-of-fit have been compared and concluded. Finally, based on the results, recommendations for future research topics and study applications have been made. Copyright © 2013 Elsevier Ltd. All rights reserved.

Efficient Workflows for Curation of Heterogeneous Data Supporting Modeling of U-Nb Alloy Aging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ward, Logan Timothy; Hackenberg, Robert Errol

These are slides from a presentation summarizing a graduate research associate's summer project. The following topics are covered in these slides: data challenges in materials, aging in U-Nb Alloys, Building an Aging Model, Different Phase Trans. in U-Nb, the Challenge, Storing Materials Data, Example Data Source, Organizing Data: What is a Schema?, What does a "XML Schema" look like?, Our Data Schema: Nice and Simple, Storing Data: Materials Data Curation System (MDCS), Problem with MDCS: Slow Data Entry, Getting Literature into MDCS, Staging Data in Excel Document, Final Result: MDCS Records, Analyzing Image Data, Process for Making TTT Diagram, Bottleneckmore » Number 1: Image Analysis, Fitting a TTP Boundary, Fitting a TTP Curve: Comparable Results, How Does it Compare to Our Data?, Image Analysis Workflow, Curating Hardness Records, Hardness Data: Two Key Decisions, Before Peak Age? - Automation, Interactive Viz, Which Transformation?, Microstructure-Informed Model, Tracking the Entire Process, General Problem with Property Models, Pinyon: Toolkit for Managing Model Creation, Tracking Individual Decisions, Jupyter: Docs and Code in One File, Hardness Analysis Workflow, Workflow for Aging Models, and conclusions.« less

FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter.

PubMed

Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao

2016-07-12

In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved.

A Model for Axial Magnetic Bearings Including Eddy Currents

NASA Technical Reports Server (NTRS)

Kucera, Ladislav; Ahrens, Markus

1996-01-01

This paper presents an analytical method of modelling eddy currents inside axial bearings. The problem is solved by dividing an axial bearing into elementary geometric forms, solving the Maxwell equations for these simplified geometries, defining boundary conditions and combining the geometries. The final result is an analytical solution for the flux, from which the impedance and the force of an axial bearing can be derived. Several impedance measurements have shown that the analytical solution can fit the measured data with a precision of approximately 5%.

Analysis of Crystallization Kinetics

NASA Technical Reports Server (NTRS)

Kelton, Kenneth F.

1997-01-01

A realistic computer model for polymorphic crystallization (i.e., initial and final phases with identical compositions), which includes time-dependent nucleation and cluster-size-dependent growth rates, is developed and tested by fits to experimental data. Model calculations are used to assess the validity of two of the more common approaches for the analysis of crystallization data. The effects of particle size on transformation kinetics, important for the crystallization of many systems of limited dimension including thin films, fine powders, and nanoparticles, are examined.

A statistical method to estimate low-energy hadronic cross sections

NASA Astrophysics Data System (ADS)

Balassa, Gábor; Kovács, Péter; Wolf, György

2018-02-01

In this article we propose a model based on the Statistical Bootstrap approach to estimate the cross sections of different hadronic reactions up to a few GeV in c.m.s. energy. The method is based on the idea, when two particles collide a so-called fireball is formed, which after a short time period decays statistically into a specific final state. To calculate the probabilities we use a phase space description extended with quark combinatorial factors and the possibility of more than one fireball formation. In a few simple cases the probability of a specific final state can be calculated analytically, where we show that the model is able to reproduce the ratios of the considered cross sections. We also show that the model is able to describe proton-antiproton annihilation at rest. In the latter case we used a numerical method to calculate the more complicated final state probabilities. Additionally, we examined the formation of strange and charmed mesons as well, where we used existing data to fit the relevant model parameters.

A Unified Model for GRB Prompt Emission from Optical to Gamma-Rays; Exploring GRBs as Standard Candles

NASA Technical Reports Server (NTRS)

Guiriec, S.; Kouveliotou, C.; Hartmann, D. H.; Granot, J.; Asano, K.; Meszaros, P.; Gill, R.; Gehrels, N.; McEnery, J.

2016-01-01

The origin of prompt emission from gamma-ray bursts (GRBs) remains to be an open question. Correlated prompt optical and gamma-ray emission observed in a handful of GRBs strongly suggests a common emission region, but failure to adequately fit the broadband GRB spectrum prompted the hypothesis of different emission mechanisms for the low- and high-energy radiations. We demonstrate that our multi-component model for GRB -ray prompt emission provides an excellent fit to GRB 110205A from optical to gamma-ray energies. Our results show that the optical and highest gamma-ray emissions have the same spatial and spectral origin, which is different from the bulk of the X- and softest gamma-ray radiation. Finally, our accurate redshift estimate for GRB 110205A demonstrates promise for using GRBs as cosmological standard candles.

A random-sampling high dimensional model representation neural network for building potential energy surfaces

NASA Astrophysics Data System (ADS)

Manzhos, Sergei; Carrington, Tucker

2006-08-01

We combine the high dimensional model representation (HDMR) idea of Rabitz and co-workers [J. Phys. Chem. 110, 2474 (2006)] with neural network (NN) fits to obtain an effective means of building multidimensional potentials. We verify that it is possible to determine an accurate many-dimensional potential by doing low dimensional fits. The final potential is a sum of terms each of which depends on a subset of the coordinates. This form facilitates quantum dynamics calculations. We use NNs to represent HDMR component functions that minimize error mode term by mode term. This NN procedure makes it possible to construct high-order component functions which in turn enable us to determine a good potential. It is shown that the number of available potential points determines the order of the HDMR which should be used.

A random-sampling high dimensional model representation neural network for building potential energy surfaces.

PubMed

Manzhos, Sergei; Carrington, Tucker

2006-08-28

We combine the high dimensional model representation (HDMR) idea of Rabitz and co-workers [J. Phys. Chem. 110, 2474 (2006)] with neural network (NN) fits to obtain an effective means of building multidimensional potentials. We verify that it is possible to determine an accurate many-dimensional potential by doing low dimensional fits. The final potential is a sum of terms each of which depends on a subset of the coordinates. This form facilitates quantum dynamics calculations. We use NNs to represent HDMR component functions that minimize error mode term by mode term. This NN procedure makes it possible to construct high-order component functions which in turn enable us to determine a good potential. It is shown that the number of available potential points determines the order of the HDMR which should be used.

Experimental study of the γ p → π 0 η p reaction with the A2 setup at the Mainz Microtron

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sokhoyan, V.; Prakhov, S.; Fix, A.

2018-05-29

Here, the data available from the A2 Collaboration at MAMI were analyzed to select the γp → π 0ηp reaction on an event-by-event basis, which allows for partial-wave analyses of three-body final states to obtain more reliable results, compared to fits to measured distributions. These data provide the world’s best statistical accuracy in the energy range from threshold to E γ = 1.45 GeV, allowing a finer energy binning in the measurement of all observables needed for understanding the reaction dynamics. The results obtained for the measured observables are compared to existing models, and the impact from the new datamore » is checked by the fit with the revised Mainz model.« less

[Validity and factorial invariance of the social ecological model in explaining fruit intake in Mexican schoolchildren].

PubMed

Ochoa-Meza, Gerardo; Sierra, Juan Carlos; Pérez-Rodrigo, Carmen; Aranceta Bartrina, Javier; Esparza-Del Villar, Óscar A

2014-11-24

To test the goodness of fit of a Motivation-Ability-Opportunity model (MAO-model) to evaluate the observed variance in Mexican schoolchildren's preferences to eat fruit and daily fruit intake; also to evaluate the factorial invariance across the gender and type of population (urban and semi-urban) in which children reside. A model with seven constructs was designed from a validated questionnaire to assess preferences, cognitive abilities, attitude, modelling, perceived barriers, accessibility at school, accessibility at home, and fruit intake frequency. The instrument was administered in a representative sample of 1434 schoolchildren of 5th and 6th grade of primary school in a cross-sectional and ex post fact study conducted in 2013 in six cities of the State of Chihuahua, Mexico. The goodness of fit indexes was adequate for the MAO-model and explained 39% of the variance in preference to eat fruit. The structure of the model showed very good factor structure stability and the dimensions of the scale were equivalent in the different samples analyzed. The model analyzed with structural equation modeling showed a parsimonious model that can be used to explain the variation in fruit intake of 10 to 12 year old Mexican schoolchildren. The structure of the model was strictly invariant in the different samples analyzed and showed evidence of cross validation. Finally, implications about the modification model to fit data from scholar settings and guidelines for future research are discussed. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

NMR relaxation induced by iron oxide particles: testing theoretical models.

PubMed

Gossuin, Y; Orlando, T; Basini, M; Henrard, D; Lascialfari, A; Mattea, C; Stapf, S; Vuong, Q L

2016-04-15

Superparamagnetic iron oxide particles find their main application as contrast agents for cellular and molecular magnetic resonance imaging. The contrast they bring is due to the shortening of the transverse relaxation time T 2 of water protons. In order to understand their influence on proton relaxation, different theoretical relaxation models have been developed, each of them presenting a certain validity domain, which depends on the particle characteristics and proton dynamics. The validation of these models is crucial since they allow for predicting the ideal particle characteristics for obtaining the best contrast but also because the fitting of T 1 experimental data by the theory constitutes an interesting tool for the characterization of the nanoparticles. In this work, T 2 of suspensions of iron oxide particles in different solvents and at different temperatures, corresponding to different proton diffusion properties, were measured and were compared to the three main theoretical models (the motional averaging regime, the static dephasing regime, and the partial refocusing model) with good qualitative agreement. However, a real quantitative agreement was not observed, probably because of the complexity of these nanoparticulate systems. The Roch theory, developed in the motional averaging regime (MAR), was also successfully used to fit T 1 nuclear magnetic relaxation dispersion (NMRD) profiles, even outside the MAR validity range, and provided a good estimate of the particle size. On the other hand, the simultaneous fitting of T 1 and T 2 NMRD profiles by the theory was impossible, and this occurrence constitutes a clear limitation of the Roch model. Finally, the theory was shown to satisfactorily fit the deuterium T 1 NMRD profile of superparamagnetic particle suspensions in heavy water.

On 4-degree-of-freedom biodynamic models of seated occupants: Lumped-parameter modeling

NASA Astrophysics Data System (ADS)

Bai, Xian-Xu; Xu, Shi-Xu; Cheng, Wei; Qian, Li-Jun

2017-08-01

It is useful to develop an effective biodynamic model of seated human occupants to help understand the human vibration exposure to transportation vehicle vibrations and to help design and improve the anti-vibration devices and/or test dummies. This study proposed and demonstrated a methodology for systematically identifying the best configuration or structure of a 4-degree-of-freedom (4DOF) human vibration model and for its parameter identification. First, an equivalent simplification expression for the models was made. Second, all of the possible 23 structural configurations of the models were identified. Third, each of them was calibrated using the frequency response functions recommended in a biodynamic standard. An improved version of non-dominated sorting genetic algorithm (NSGA-II) based on Pareto optimization principle was used to determine the model parameters. Finally, a model evaluation criterion proposed in this study was used to assess the models and to identify the best one, which was based on both the goodness of curve fits and comprehensive goodness of the fits. The identified top configurations were better than those reported in the literature. This methodology may also be extended and used to develop the models with other DOFs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.

Here, new sets of parameters (“tunes”) for the underlying-event (UE) modelling of the pythia8, pythia6 and herwig++ Monte Carlo event generators are constructed using different parton distribution functions. Combined fits to CMS UE proton–proton (more » $$\\mathrm {p}\\mathrm {p}$$ ) data at $$\\sqrt{s} = 7\\,\\text {TeV} $$ and to UE proton–antiproton ( $$\\mathrm {p}\\overline{\\mathrm{p}} $$ ) data from the CDF experiment at lower $$\\sqrt{s}$$ , are used to study the UE models and constrain their parameters, providing thereby improved predictions for proton–proton collisions at 13 $$\\,\\text {TeV}$$ . In addition, it is investigated whether the values of the parameters obtained from fits to UE observables are consistent with the values determined from fitting observables sensitive to double-parton scattering processes. Finally, comparisons are presented of the UE tunes to “minimum bias” (MB) events, multijet, and Drell–Yan ( $$ \\mathrm{q} \\overline{\\mathrm{q}} \\rightarrow \\mathrm{Z}/ \\gamma ^* \\rightarrow $$ lepton-antilepton+jets) observables at 7 and 8 $$\\,\\text {TeV}$$ , as well as predictions for MB and UE observables at 13 $$\\,\\text {TeV}$$ .« less

Event generator tunes obtained from underlying event and multiparton scattering measurements

DOE PAGES

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; ...

2016-03-17

Here, new sets of parameters (“tunes”) for the underlying-event (UE) modelling of the pythia8, pythia6 and herwig++ Monte Carlo event generators are constructed using different parton distribution functions. Combined fits to CMS UE proton–proton (more » $$\\mathrm {p}\\mathrm {p}$$ ) data at $$\\sqrt{s} = 7\\,\\text {TeV} $$ and to UE proton–antiproton ( $$\\mathrm {p}\\overline{\\mathrm{p}} $$ ) data from the CDF experiment at lower $$\\sqrt{s}$$ , are used to study the UE models and constrain their parameters, providing thereby improved predictions for proton–proton collisions at 13 $$\\,\\text {TeV}$$ . In addition, it is investigated whether the values of the parameters obtained from fits to UE observables are consistent with the values determined from fitting observables sensitive to double-parton scattering processes. Finally, comparisons are presented of the UE tunes to “minimum bias” (MB) events, multijet, and Drell–Yan ( $$ \\mathrm{q} \\overline{\\mathrm{q}} \\rightarrow \\mathrm{Z}/ \\gamma ^* \\rightarrow $$ lepton-antilepton+jets) observables at 7 and 8 $$\\,\\text {TeV}$$ , as well as predictions for MB and UE observables at 13 $$\\,\\text {TeV}$$ .« less

Results from DESDM Pipeline on Data From Blanco Cosmology Survey

NASA Astrophysics Data System (ADS)

Desai, Shantanu; Mohr, J.; Armstrong, R.; Bertin, E.; Zenteno, A.; Tucker, D.; Song, J.; Ngeow, C.; Lin, H.; Bazin, G.; Liu, J.; Cosmology Survey, Blanco

2011-01-01

The Blanco Cosmology Survey (BCS) is a 60-night survey of the southern skies using the CTIO Blanco 4 m telescope, whose main goal to study cosmic acceleration using galaxy clusters. BCS has carried out observations in two 50 degree patches of the southern skies centered at 23 hr and 5 hr in griz bands. These fields were chosen to maximize overlap with the the South Pole Telescope. The data from this survey has been processed using the Dark energy Data Management System (DESDM) on Teragrid resources at NCSA and CCT. DESDM is developed to analyze data from the Dark Energy Survey, which begins around 2011 and analysis of real data provides valuable warmup exercise before the DES survey starts. We describe in detail the key steps in producing science ready catalogs from the raw data. This includes detrending, astrometric calibration, photometric calibration, co-addition with psf homogenization. The final catalogs are constructed using model-fitting photometry which includes detailed galaxy fitting models convolved with the local PSF. We illustrate how photometric redshifts of galaxy clusters are estimated using red-sequence fitting and show results from a few clusters.

COMPI Fertility Problem Stress Scales is a brief, valid and reliable tool for assessing stress in patients seeking treatment.

PubMed

Sobral, Maria P; Costa, Maria E; Schmidt, Lone; Martins, Mariana V

2017-02-01

Are the Copenhagen Multi-Centre Psychosocial Infertility research program Fertility Problem Stress Scales (COMPI-FPSS) a reliable and valid measure across gender and culture? The COMPI-FPSS is a valid and reliable measure, presenting excellent or good fit in the majority of the analyzed countries, and demonstrating full invariance across genders and partial invariance across cultures. Cross-cultural and gender validation is needed to consider a measure as standard care within fertility. The present study is the first attempting to establish comparability of fertility-related stress across genders and countries. Cross-sectional study. First, we tested the structure of the COMPI-FPSS. Then, reliability and validity (convergent and discriminant) were examined for the final model. Finally, measurement invariance both across genders and cultures was tested. Our final sample had 3923 fertility patients (1691 men and 2232 women) recruited in clinical settings from seven different countries: Denmark, China, Croatia, Germany, Greece, Hungary and Sweden. Participants had a mean age of 34 years and the majority (84%) were childless. Findings confirmed the original three-factor structure of the COMPI-FPSS, although suggesting a shortened measurement model using less items that fitted the data better than the full version model. While data from the Chinese and Croatian subsamples did not fit, all other counties presented good fit (χ 2 /df ≤ 5.4; comparative fit index ≥ 0.94; root-mean-square error of approximation ≤ 0.07; modified expected cross-validation index ≤ 0.77). In general, reliability, convergent validity, and discriminant validity were observed in all subscales from each country (composite reliability ≥ 0.63; average variance extracted ≥ 0.38; squared correlation ≥ 0.13). Full invariance was established across genders, and partial invariance was demonstrated across countries. Generalizability regarding the validation of the COMPI-FPSS cannot be made regarding infertile individuals not seeking treatment, or non-European patients. This study did not investigate predictive validity, and hence the capability of this instrument in detecting changes in fertility-specific adjustment over time and predicting the psychological impact needs to be established in future research. Besides extending knowledge on the psychometric properties of one of the most used fertility stress questionnaire, this study demonstrates both research and clinical usefulness of the COMPI-FPSS. This study was supported by European Union Funds (FEDER/COMPETE-Operational Competitiveness Program, and by national funds (FCT-Portuguese Foundation for Science and Technology) under the projects PTDC/MHC-PSC/4195/2012 and SFRH/BPD/85789/2012). There are no conflicts of interest to declare. N/A. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Modeling the growth of Listeria monocytogenes on the surface of smear- or mold-ripened cheese.

PubMed

Schvartzman, M Sol; Gonzalez-Barron, Ursula; Butler, Francis; Jordan, Kieran

2014-01-01

Surface-ripened cheeses are matured by means of manual or mechanical technologies posing a risk of cross-contamination, if any cheeses are contaminated with Listeria monocytogenes. In predictive microbiology, primary models are used to describe microbial responses, such as growth rate over time and secondary models explain how those responses change with environmental factors. In this way, primary models were used to assess the growth rate of L. monocytogenes during ripening of the cheeses and the secondary models to test how much the growth rate was affected by either the pH and/or the water activity (aw) of the cheeses. The two models combined can be used to predict outcomes. The purpose of these experiments was to test three primary (the modified Gompertz equation, the Baranyi and Roberts model, and the Logistic model) and three secondary (the Cardinal model, the Ratowski model, and the Presser model) mathematical models in order to define which combination of models would best predict the growth of L. monocytogenes on the surface of artificially contaminated surface-ripened cheeses. Growth on the surface of the cheese was assessed and modeled. The primary models were firstly fitted to the data and the effects of pH and aw on the growth rate (μmax) were incorporated and assessed one by one with the secondary models. The Logistic primary model by itself did not show a better fit of the data among the other primary models tested, but the inclusion of the Cardinal secondary model improved the final fit. The aw was not related to the growth of Listeria. This study suggests that surface-ripened cheese should be separately regulated within EU microbiological food legislation and results expressed as counts per surface area rather than per gram.

Does the choice of nucleotide substitution models matter topologically?

PubMed

Hoff, Michael; Orf, Stefan; Riehm, Benedikt; Darriba, Diego; Stamatakis, Alexandros

2016-03-24

In the context of a master level programming practical at the computer science department of the Karlsruhe Institute of Technology, we developed and make available an open-source code for testing all 203 possible nucleotide substitution models in the Maximum Likelihood (ML) setting under the common Akaike, corrected Akaike, and Bayesian information criteria. We address the question if model selection matters topologically, that is, if conducting ML inferences under the optimal, instead of a standard General Time Reversible model, yields different tree topologies. We also assess, to which degree models selected and trees inferred under the three standard criteria (AIC, AICc, BIC) differ. Finally, we assess if the definition of the sample size (#sites versus #sites × #taxa) yields different models and, as a consequence, different tree topologies. We find that, all three factors (by order of impact: nucleotide model selection, information criterion used, sample size definition) can yield topologically substantially different final tree topologies (topological difference exceeding 10 %) for approximately 5 % of the tree inferences conducted on the 39 empirical datasets used in our study. We find that, using the best-fit nucleotide substitution model may change the final ML tree topology compared to an inference under a default GTR model. The effect is less pronounced when comparing distinct information criteria. Nonetheless, in some cases we did obtain substantial topological differences.

HIA, the next step: Defining models and roles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Putters, Kim

If HIA is to be an effective instrument for optimising health interests in the policy making process it has to recognise the different contests in which policy is made and the relevance of both technical rationality and political rationality. Policy making may adopt a rational perspective in which there is a systematic and orderly progression from problem formulation to solution or a network perspective in which there are multiple interdependencies, extensive negotiation and compromise, and the steps from problem to formulation are not followed sequentially or in any particular order. Policy problems may be simple with clear causal pathways andmore » responsibilities or complex with unclear causal pathways and disputed responsibilities. Network analysis is required to show which stakeholders are involved, their support for health issues and the degree of consensus. From this analysis three models of HIA emerge. The first is the phases model which is fitted to simple problems and a rational perspective of policymaking. This model involves following structured steps. The second model is the rounds (Echternach) model that is fitted to complex problems and a network perspective of policymaking. This model is dynamic and concentrates on network solutions taking these steps in no particular order. The final model is the 'garbage can' model fitted to contexts which combine simple and complex problems. In this model HIA functions as a problem solver and signpost keeping all possible solutions and stakeholders in play and allowing solutions to emerge over time. HIA models should be the beginning rather than the conclusion of discussion the worlds of HIA and policymaking.« less

MEDIATION EFFECTS OF OVERCOMMITMENT ON EFFORT, REWARD, INSOMNIA, AND WELL-BEING AS MODERATED BY GENDER, AGE, AND JOB POSITION.

PubMed

Chao, Wang; Shuang, Li; Tao, Li; Shanfa, Yu; Junming, Dai

2017-01-01

This study aimed to detect the mediation effect of over-commitment between occupational stress, insomnia, and well-being; and the moderating role of gender, age and job position are also to be analyzed. One thousand six hundred eighteen valid samples were recruited from electronic manufacturing service industry in Hunan Province, China. All the data were collected by selfrated questionnaires after written consent. This paper introduced Effort-Reward- Insomnia-Well-being model, and it was fitted and validated through the structural equation model analysis. The results of single factor correlation analysis indicated that the coefficients between most of the items and dimensions presented statistical significance. The final fitting model had satisfactory global goodness of fit (CMIN/DF=3.99, AGFI=0.926, NNFI=0.950, IFI=0.956, RMSEA=0.043). Both of the measurement model and structural model had acceptable path loadings. Effort associated with insomnia indirectly and related to well-being directly and indirectly; reward could have either directly associated with insomnia and well-being, or indirectly related to them through over-commitment. Covariates as gender, age and position made differences on the association between occupational stress and health outcomes. Over-commitment had the ability to mediate the relationships between effort, reward, and health outcomes, and mediation effect varied from different working conditions and outcomes under different covariates.

A Multivariate Model of Stakeholder Preference for Lethal Cat Management

PubMed Central

Wald, Dara M.; Jacobson, Susan K.

2014-01-01

Identifying stakeholder beliefs and attitudes is critical for resolving management conflicts. Debate over outdoor cat management is often described as a conflict between two groups, environmental advocates and animal welfare advocates, but little is known about the variables predicting differences among these critical stakeholder groups. We administered a mail survey to randomly selected stakeholders representing both of these groups (n = 1,596) in Florida, where contention over the management of outdoor cats has been widespread. We used a structural equation model to evaluate stakeholder intention to support non-lethal management. The cognitive hierarchy model predicted that values influenced beliefs, which predicted general and specific attitudes, which in turn, influenced behavioral intentions. We posited that specific attitudes would mediate the effect of general attitudes, beliefs, and values on management support. Model fit statistics suggested that the final model fit the data well (CFI = 0.94, RMSEA = 0.062). The final model explained 74% of the variance in management support, and positive attitudes toward lethal management (humaneness) had the largest direct effect on management support. Specific attitudes toward lethal management and general attitudes toward outdoor cats mediated the relationship between positive (p<0.05) and negative cat-related impact beliefs (p<0.05) and support for management. These results supported the specificity hypothesis and the use of the cognitive hierarchy to assess stakeholder intention to support non-lethal cat management. Our findings suggest that stakeholders can simultaneously perceive both positive and negative beliefs about outdoor cats, which influence attitudes toward and support for non-lethal management. PMID:24736744

A multivariate model of stakeholder preference for lethal cat management.

PubMed

Wald, Dara M; Jacobson, Susan K

2014-01-01

Identifying stakeholder beliefs and attitudes is critical for resolving management conflicts. Debate over outdoor cat management is often described as a conflict between two groups, environmental advocates and animal welfare advocates, but little is known about the variables predicting differences among these critical stakeholder groups. We administered a mail survey to randomly selected stakeholders representing both of these groups (n=1,596) in Florida, where contention over the management of outdoor cats has been widespread. We used a structural equation model to evaluate stakeholder intention to support non-lethal management. The cognitive hierarchy model predicted that values influenced beliefs, which predicted general and specific attitudes, which in turn, influenced behavioral intentions. We posited that specific attitudes would mediate the effect of general attitudes, beliefs, and values on management support. Model fit statistics suggested that the final model fit the data well (CFI=0.94, RMSEA=0.062). The final model explained 74% of the variance in management support, and positive attitudes toward lethal management (humaneness) had the largest direct effect on management support. Specific attitudes toward lethal management and general attitudes toward outdoor cats mediated the relationship between positive (p<0.05) and negative cat-related impact beliefs (p<0.05) and support for management. These results supported the specificity hypothesis and the use of the cognitive hierarchy to assess stakeholder intention to support non-lethal cat management. Our findings suggest that stakeholders can simultaneously perceive both positive and negative beliefs about outdoor cats, which influence attitudes toward and support for non-lethal management.

Does vigorous exercise have a neuroprotective effect in Parkinson disease?

PubMed Central

2011-01-01

Parkinson disease (PD) is progressive, with dementia and medication-refractory motor problems common reasons for late-stage nursing-home placement. Increasing evidence suggests that ongoing vigorous exercise/physical fitness may favorably influence this progression. Parkinsonian animal models reveal exercise-related protection from dopaminergic neurotoxins, apparently mediated by brain neurotrophic factors and neuroplasticity (predicted from in vitro studies). Similarly, exercise consistently improves cognition in animals, also linked to enhanced neuroplasticity and increased neurotrophic factor expression. In these animal models, immobilization has the opposite effect. Brain-derived neurotrophic factor (BDNF) may mediate at least some of this exercise benefit. In humans, exercise increases serum BDNF, and this is known to cross the blood–brain barrier. PD risk in humans is significantly reduced by midlife exercise, documented in large prospective studies. No studies have addressed whether exercise influences dementia risk in PD, but exercised patients with PD improve cognitive scores. Among seniors in general, exercise or physical fitness has not only been associated with better cognitive scores, but midlife exercise significantly reduces the later risk of both dementia and mild cognitive impairment. Finally, numerous studies in seniors with and without dementia have reported increased cerebral gray matter volumes associated with physical fitness or exercise. These findings have several implications for PD clinicians. 1) Ongoing vigorous exercise and physical fitness should be highly encouraged. 2) PD physical therapy programs should include structured, graduated fitness instruction and guidance for deconditioned patients with PD. 3) Levodopa and other forms of dopamine replenishment therapy should be utilized to achieve the maximum capability and motivation for patients to maintain fitness. PMID:21768599

A method for simultaneous linear optics and coupling correction for storage rings with turn-by-turn beam position monitor data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xi; Huang, Xiaobiao

2016-05-13

Here, we propose a method to simultaneously correct linear optics errors and linear coupling for storage rings using turn-by-turn (TbT) beam position monitor (BPM) data. The independent component analysis (ICA) method is used to isolate the betatron normal modes from the measured TbT BPM data. The betatron amplitudes and phase advances of the projections of the normal modes on the horizontal and vertical planes are then extracted, which, combined with dispersion measurement, are used to fit the lattice model. The fitting results are used for lattice correction. Finally, the method has been successfully demonstrated on the NSLS-II storage ring.

Nucleon Axial and Electromagnetic Form Factors

NASA Astrophysics Data System (ADS)

Jang, Yong-Chull; Bhattacharya, Tanmoy; Gupta, Rajan; Lin, Huey-Wen; Yoon, Boram

2018-03-01

We present results for the isovector axial, induced pseudoscalar, electric, and magnetic form factors of the nucleon. The calculations were done using 2 + 1 + 1-flavor HISQ ensembles generated by the MILC collaboration with lattice spacings a ≈ 0.12, 0.09, 0.06 fm and pion masses Mπ ≈ 310, 220, 130 MeV. Excited-states contamination is controlled by using four-state fits to two-point correlators and by comparing two-versus three-states in three-point correlators. The Q2 behavior is analyzed using the model independent z-expansion and the dipole ansatz. Final results for the charge radii and magnetic moment are obtained using a simultaneous fit in Mπ, lattice spacing a and finite volume.

The Influence of Work-Related Fatigue, Work Conditions, and Personal Characteristics on Intent to Leave Among New Nurses.

PubMed

Liu, Yi; Wu, Li-Min; Chou, Pi-Ling; Chen, Mei-Hsin; Yang, Li-Chien; Hsu, Hsin-Tien

2016-01-01

This study aimed to (a) test the fit of the hypothesized model for new nurses' intent to leave and (b) determine the extent to which personal characteristics, work conditions, and work-related fatigue predict intent to leave among new nurses. This study was a cross-sectional survey study. A total of 162 new nurses were recruited. A hypothesized model was proposed for model testing. Structural equation modelling was used for data analysis. Work conditions only had an effect through work-related fatigue on new nurses' intent to leave. Personal characteristics did not have a significant effect on new nurses' intent to leave. The final model showed a good fit. Work-related fatigue, work conditions, and health explained 65% of the variance in new nurses' intent to leave. Work-related fatigue was a major determinant of new nurses' intent to leave. More attention should be paid to fatigue reduction strategies among new nurses. Work-related fatigue should be monitored, particularly for new nurses who work more than 10 hr per day and who have greater workloads. © 2015 Sigma Theta Tau International.

Optimization of Fit for Mass Customized Apparel Ordering Using Fit Preference and Self Measurement.

DTIC Science & Technology

2000-01-01

shorts had the highest satisfaction of fit and which short provided the optimum fit. Finally a discrepancy question form and a manual order form were...used during fit test sessions. In pilot testing manual order forms were used exclusively to record self-measurements and fit preference responses for...test participants. The website requirements were completed on site in the pilot test and manual order forms were returned to test evaluators once

A random walk model for evaluating clinical trials involving serial observations.

PubMed

Hopper, J L; Young, G P

1988-05-01

For clinical trials where the variable of interest is ordered and categorical (for example, disease severity, symptom scale), and where measurements are taken at intervals, it might be possible to achieve a greater discrimination between the efficacy of treatments by modelling each patient's progress as a stochastic process. The random walk is a simple, easily interpreted model that can be fitted by maximum likelihood using a maximization routine with inference based on standard likelihood theory. In general the model can allow for randomly censored data, incorporates measured prognostic factors, and inference is conditional on the (possibly non-random) allocation of patients. Tests of fit and of model assumptions are proposed, and application to two therapeutic trials of gastroenterological disorders are presented. The model gave measures of the rate of, and variability in, improvement for patients under different treatments. A small simulation study suggested that the model is more powerful than considering the difference between initial and final scores, even when applied to data generated by a mechanism other than the random walk model assumed in the analysis. It thus provides a useful additional statistical method for evaluating clinical trials.

Psychometric Properties of the Heart Disease Knowledge Scale: Evidence from Item and Confirmatory Factor Analyses

PubMed Central

Lim, Bee Chiu; Kueh, Yee Cheng; Arifin, Wan Nor; Ng, Kok Huan

2016-01-01

Background Heart disease knowledge is an important concept for health education, yet there is lack of evidence on proper validated instruments used to measure levels of heart disease knowledge in the Malaysian context. Methods A cross-sectional, survey design was conducted to examine the psychometric properties of the adapted English version of the Heart Disease Knowledge Questionnaire (HDKQ). Using proportionate cluster sampling, 788 undergraduate students at Universiti Sains Malaysia, Malaysia, were recruited and completed the HDKQ. Item analysis and confirmatory factor analysis (CFA) were used for the psychometric evaluation. Construct validity of the measurement model was included. Results Most of the students were Malay (48%), female (71%), and from the field of science (51%). An acceptable range was obtained with respect to both the difficulty and discrimination indices in the item analysis results. The difficulty index ranged from 0.12–0.91 and a discrimination index of ≥ 0.20 were reported for the final retained 23 items. The final CFA model showed an adequate fit to the data, yielding a 23-item, one-factor model [weighted least squares mean and variance adjusted scaled chi-square difference = 1.22, degrees of freedom = 2, P-value = 0.544, the root mean square error of approximation = 0.03 (90% confidence interval = 0.03, 0.04); close-fit P-value = > 0.950]. Conclusion Adequate psychometric values were obtained for Malaysian undergraduate university students using the 23-item, one-factor model of the adapted HDKQ. PMID:27660543

Psychometric Properties of the Heart Disease Knowledge Scale: Evidence from Item and Confirmatory Factor Analyses.

PubMed

Lim, Bee Chiu; Kueh, Yee Cheng; Arifin, Wan Nor; Ng, Kok Huan

2016-07-01

Heart disease knowledge is an important concept for health education, yet there is lack of evidence on proper validated instruments used to measure levels of heart disease knowledge in the Malaysian context. A cross-sectional, survey design was conducted to examine the psychometric properties of the adapted English version of the Heart Disease Knowledge Questionnaire (HDKQ). Using proportionate cluster sampling, 788 undergraduate students at Universiti Sains Malaysia, Malaysia, were recruited and completed the HDKQ. Item analysis and confirmatory factor analysis (CFA) were used for the psychometric evaluation. Construct validity of the measurement model was included. Most of the students were Malay (48%), female (71%), and from the field of science (51%). An acceptable range was obtained with respect to both the difficulty and discrimination indices in the item analysis results. The difficulty index ranged from 0.12-0.91 and a discrimination index of ≥ 0.20 were reported for the final retained 23 items. The final CFA model showed an adequate fit to the data, yielding a 23-item, one-factor model [weighted least squares mean and variance adjusted scaled chi-square difference = 1.22, degrees of freedom = 2, P-value = 0.544, the root mean square error of approximation = 0.03 (90% confidence interval = 0.03, 0.04); close-fit P-value = > 0.950]. Adequate psychometric values were obtained for Malaysian undergraduate university students using the 23-item, one-factor model of the adapted HDKQ.

The role of the S 3 GUT leptoquark in flavor universality and collider searches

NASA Astrophysics Data System (ADS)

Doršner, Ilja; Fajfer, Svjetlana; Faroughy, Darius A.; Košnik, Nejc

2017-10-01

We investigate the ability of the S 3 scalar leptoquark to address the recent hints of lepton universality violation in B meson decays. The S 3 leptoquark with quantum numbers (\\overline{3},3,1/3) naturally emerges in the context of an SU(5) GUT model without any conflict with the stringent limits from observed nucleon stability. Scalar leptoquark S 3 with left-handed couplings to 2nd and 3rd generations of charged leptons and down-type quarks seems well-suited to address both R K(∗) and R D(∗) . We quantify this suitability with numerical fits to a plethora of relevant flavor observables. The proposed SU(5) model calls for a second leptoquark state, i.e., \\tilde{R}_2 with quantum numbers ( 3 , 2 , 1 /6), if one is to generate gauge coupling unification and neutrino mass. We accordingly include it in our study to investigate \\tilde{R}_2 's ability to offset adverse effects of S 3 and thus improve a quality of numerical fits. A global fit of the leptoquark Yukawa couplings shows that large couplings of light S 3 to τ leptons are preferred. We furthermore identify B\\to {K}^{(\\ast )}\\overline{ν}ν as the most sensitive channel to probe the preferred region of parameter space. Large couplings of S 3 to τ leptons are finally confronted with the experimental searches for τ final states at the Large Hadron Collider. These searches comprise a study of decay products of the leptoquark pair production, as well as, and more importantly, an analysis of the high-mass ττ finalstates.

Some findings on zero-inflated and hurdle poisson models for disease mapping.

PubMed

Corpas-Burgos, Francisca; García-Donato, Gonzalo; Martinez-Beneito, Miguel A

2018-05-27

Zero excess in the study of geographically referenced mortality data sets has been the focus of considerable attention in the literature, with zero-inflation being the most common procedure to handle this lack of fit. Although hurdle models have also been used in disease mapping studies, their use is more rare. We show in this paper that models using particular treatments of zero excesses are often required for achieving appropriate fits in regular mortality studies since, otherwise, geographical units with low expected counts are oversmoothed. However, as also shown, an indiscriminate treatment of zero excess may be unnecessary and has a problematic implementation. In this regard, we find that naive zero-inflation and hurdle models, without an explicit modeling of the probabilities of zeroes, do not fix zero excesses problems well enough and are clearly unsatisfactory. Results sharply suggest the need for an explicit modeling of the probabilities that should vary across areal units. Unfortunately, these more flexible modeling strategies can easily lead to improper posterior distributions as we prove in several theoretical results. Those procedures have been repeatedly used in the disease mapping literature, and one should bear these issues in mind in order to propose valid models. We finally propose several valid modeling alternatives according to the results mentioned that are suitable for fitting zero excesses. We show that those proposals fix zero excesses problems and correct the mentioned oversmoothing of risks in low populated units depicting geographic patterns more suited to the data. Copyright © 2018 John Wiley & Sons, Ltd.

High-order shock-fitted detonation propagation in high explosives

NASA Astrophysics Data System (ADS)

Romick, Christopher M.; Aslam, Tariq D.

2017-03-01

A highly accurate numerical shock and material interface fitting scheme composed of fifth-order spatial and third- or fifth-order temporal discretizations is applied to the two-dimensional reactive Euler equations in both slab and axisymmetric geometries. High rates of convergence are not typically possible with shock-capturing methods as the Taylor series analysis breaks down in the vicinity of discontinuities. Furthermore, for typical high explosive (HE) simulations, the effects of material interfaces at the charge boundary can also cause significant computational errors. Fitting a computational boundary to both the shock front and material interface (i.e. streamline) alleviates the computational errors associated with captured shocks and thus opens up the possibility of high rates of convergence for multi-dimensional shock and detonation flows. Several verification tests, including a Sedov blast wave, a Zel'dovich-von Neumann-Döring (ZND) detonation wave, and Taylor-Maccoll supersonic flow over a cone, are utilized to demonstrate high rates of convergence to nontrivial shock and reaction flows. Comparisons to previously published shock-capturing multi-dimensional detonations in a polytropic fluid with a constant adiabatic exponent (PF-CAE) are made, demonstrating significantly lower computational error for the present shock and material interface fitting method. For an error on the order of 10 m /s, which is similar to that observed in experiments, shock-fitting offers a computational savings on the order of 1000. In addition, the behavior of the detonation phase speed is examined for several slab widths to evaluate the detonation performance of PBX 9501 while utilizing the Wescott-Stewart-Davis (WSD) model, which is commonly used in HE modeling. It is found that the thickness effect curve resulting from this equation of state and reaction model using published values is dramatically more steep than observed in recent experiments. Utilizing the present fitting strategy, in conjunction with a nonlinear optimizer, a new set of reaction rate parameters improves the correlation of the model to experimental results. Finally, this new model is tested against two dimensional slabs as a validation test.

Multi-body modeling method for rollover using MADYMO

NASA Astrophysics Data System (ADS)

Liu, Changye; Lin, Zhigui; Lv, Juncheng; Luo, Qinyue; Qin, Zhenyao; Zhang, Pu; Chen, Tao

2017-04-01

Rollovers are complex road accidents causing a big deal of fatalities. FE model for rollover study will costtoo much time due to its long duration.A new multi-body modeling method is proposed in this paper which can save a lot of time and has high-fidelity meanwhile. Following works were carried out to validate this new method. First, a small van was tested following the FMVSS 208 protocol for the validation of the proposed modeling method. Second, a MADYMO model of this small van was reconstructed. The vehicle body was divided into two main parts, the deformable upper body and the rigid lower body, modeled by different waysbased on an FE model. The specific method of modeling is offered in this paper. Finally, the trajectories of the vehicle from test and simulation were comparedand the match was very good. Acceleration of left B pillar was taken into consideration, which turned out fitting the test result well in the time of event. The final deformation status of the vehicle in test and simulation showed similar trend. This validated model provides a reliable wayfor further research in occupant injuries during rollovers.

Using Electrically-evoked Compound Action Potentials to Estimate Perceptive Levels in Experienced Adult Cochlear Implant Users.

PubMed

Joly, Charles-Alexandre; Péan, Vincent; Hermann, Ruben; Seldran, Fabien; Thai-Van, Hung; Truy, Eric

2017-10-01

The cochlear implant (CI) fitting level prediction accuracy of electrically-evoked compound action potential (ECAP) should be enhanced by the addition of demographic data in models. No accurate automated fitting of CI based on ECAP has yet been proposed. We recorded ECAP in 45 adults who had been using MED-EL CIs for more than 11 months and collected the most comfortable loudness level (MCL) used for CI fitting (prog-MCL), perception thresholds (meas-THR), and MCL (meas-MCL) measured with the stimulation used for ECAP recording. Linear mixed models taking into account cochlear site factors were computed to explain prog-MCL, meas-MCL, and meas-THR. Cochlear region and ECAP threshold were predictors of the three levels. In addition, significant predictors were the ECAP amplitude for the prog-MCL and the duration of deafness for the prog-MCL and the meas-THR. Estimations were more accurate for the meas-THR, then the meas-MCL, and finally the prog-MCL. These results show that 1) ECAP thresholds are more closely related to perception threshold than to comfort level, 2) predictions are more accurate when the inter-subject and cochlear regions variations are considered, and 3) differences between the stimulations used for ECAP recording and for CI fitting make it difficult to accurately predict the prog-MCL from the ECAP recording. Predicted prog-MCL could be used as bases for fitting but should be used with care to avoid any uncomfortable or painful stimulation.

WAIS-IV subtest covariance structure: conceptual and statistical considerations.

PubMed

Ward, L Charles; Bergman, Maria A; Hebert, Katina R

2012-06-01

D. Wechsler (2008b) reported confirmatory factor analyses (CFAs) with standardization data (ages 16-69 years) for 10 core and 5 supplemental subtests from the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV). Analyses of the 15 subtests supported 4 hypothesized oblique factors (Verbal Comprehension, Working Memory, Perceptual Reasoning, and Processing Speed) but also revealed unexplained covariance between Block Design and Visual Puzzles (Perceptual Reasoning subtests). That covariance was not included in the final models. Instead, a path was added from Working Memory to Figure Weights (Perceptual Reasoning subtest) to improve fit and achieve a desired factor pattern. The present research with the same data (N = 1,800) showed that the path from Working Memory to Figure Weights increases the association between Working Memory and Matrix Reasoning. Specifying both paths improves model fit and largely eliminates unexplained covariance between Block Design and Visual Puzzles but with the undesirable consequence that Figure Weights and Matrix Reasoning are equally determined by Perceptual Reasoning and Working Memory. An alternative 4-factor model was proposed that explained theory-implied covariance between Block Design and Visual Puzzles and between Arithmetic and Figure Weights while maintaining compatibility with WAIS-IV Index structure. The proposed model compared favorably with a 5-factor model based on Cattell-Horn-Carroll theory. The present findings emphasize that covariance model comparisons should involve considerations of conceptual coherence and theoretical adherence in addition to statistical fit. (c) 2012 APA, all rights reserved

Modeling of Phenoxy Acid Herbicide Mineralization and Growth of Microbial Degraders in 15 Soils Monitored by Quantitative Real-Time PCR of the Functional tfdA Gene

PubMed Central

Bælum, Jacob; Prestat, Emmanuel; David, Maude M.; Strobel, Bjarne W.

2012-01-01

Mineralization potentials, rates, and kinetics of the three phenoxy acid (PA) herbicides, 2,4-dichlorophenoxyacetic acid (2,4-D), 4-chloro-2-methylphenoxyacetic acid (MCPA), and 2-(4-chloro-2-methylphenoxy)propanoic acid (MCPP), were investigated and compared in 15 soils collected from five continents. The mineralization patterns were fitted by zero/linear or exponential growth forms of the three-half-order models and by logarithmic (log), first-order, or zero-order kinetic models. Prior and subsequent to the mineralization event, tfdA genes were quantified using real-time PCR to estimate the genetic potential for degrading PA in the soils. In 25 of the 45 mineralization scenarios, ∼60% mineralization was observed within 118 days. Elevated concentrations of tfdA in the range 1 × 105 to 5 × 107 gene copies g−1 of soil were observed in soils where mineralization could be described by using growth-linked kinetic models. A clear trend was observed that the mineralization rates of the three PAs occurred in the order 2,4-D > MCPA > MCPP, and a correlation was observed between rapid mineralization and soils exposed to PA previously. Finally, for 2,4-D mineralization, all seven mineralization patterns which were best fitted by the exponential model yielded a higher tfdA gene potential after mineralization had occurred than the three mineralization patterns best fitted by the Lin model. PMID:22635998

75 FR 57456 - Light-Walled Rectangular Pipe and Tube from the People's Republic of China: Final Results of the...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-21

...'') U.S. affiliated importer FitMAX Inc. (``FitMAX'') on June 2, 2010 and June 16, 2010. FitMAX... carbon- quality light-walled steel pipe and tube, of rectangular (including square) cross section, having...

Stochastic modelling of non-stationary financial assets

NASA Astrophysics Data System (ADS)

Estevens, Joana; Rocha, Paulo; Boto, João P.; Lind, Pedro G.

2017-11-01

We model non-stationary volume-price distributions with a log-normal distribution and collect the time series of its two parameters. The time series of the two parameters are shown to be stationary and Markov-like and consequently can be modelled with Langevin equations, which are derived directly from their series of values. Having the evolution equations of the log-normal parameters, we reconstruct the statistics of the first moments of volume-price distributions which fit well the empirical data. Finally, the proposed framework is general enough to study other non-stationary stochastic variables in other research fields, namely, biology, medicine, and geology.

Individual differences in processing styles: validity of the Rational-Experiential Inventory.

PubMed

Björklund, Fredrik; Bäckström, Martin

2008-10-01

In Study 1 (N= 203) the factor structure of a Swedish translation of Pacini and Epstein's Rational-Experiential Inventory (REI-40) was investigated using confirmatory factor analysis. The hypothesized model with rationality and experientiality as orthogonal factors had satisfactory fit to the data, significantly better than alternative models (with two correlated factors or a single factor). Inclusion of "ability" and "favorability" subscales for rationality and experientiality increased fit further. It was concluded that the structural validity of the REI is adequate. In Study 2 (N= 72) the REI-factors were shown to have theoretically meaningful correlations to other personality traits, indicating convergent and discriminant validity. Finally, scores on the rationality scale were negatively related to risky choice framing effects in Kahneman and Tversky's Asian disease task, indicating concurrent validity. On the basis of these findings it was concluded that the test has satisfactory psychometric properties.

An introduction to multidimensional measurement using Rasch models.

PubMed

Briggs, Derek C; Wilson, Mark

2003-01-01

The act of constructing a measure requires a number of important assumptions. Principle among these assumptions is that the construct is unidimensional. In practice there are many instances when the assumption of unidimensionality does not hold, and where the application of a multidimensional measurement model is both technically appropriate and substantively advantageous. In this paper we illustrate the usefulness of a multidimensional approach to measurement with the Multidimensional Random Coefficient Multinomial Logit (MRCML) model, an extension of the unidimensional Rasch model. An empirical example is taken from a collection of embedded assessments administered to 541 students enrolled in middle school science classes with a hands-on science curriculum. Student achievement on these assessments are multidimensional in nature, but can also be treated as consecutive unidimensional estimates, or as is most common, as a composite unidimensional estimate. Structural parameters are estimated for each model using ConQuest, and model fit is compared. Student achievement in science is also compared across models. The multidimensional approach has the best fit to the data, and provides more reliable estimates of student achievement than under the consecutive unidimensional approach. Finally, at an interpretational level, the multidimensional approach may well provide richer information to the classroom teacher about the nature of student achievement.

Efficient detection of wound-bed and peripheral skin with statistical colour models.

PubMed

Veredas, Francisco J; Mesa, Héctor; Morente, Laura

2015-04-01

A pressure ulcer is a clinical pathology of localised damage to the skin and underlying tissue caused by pressure, shear or friction. Reliable diagnosis supported by precise wound evaluation is crucial in order to success on treatment decisions. This paper presents a computer-vision approach to wound-area detection based on statistical colour models. Starting with a training set consisting of 113 real wound images, colour histogram models are created for four different tissue types. Back-projections of colour pixels on those histogram models are used, from a Bayesian perspective, to get an estimate of the posterior probability of a pixel to belong to any of those tissue classes. Performance measures obtained from contingency tables based on a gold standard of segmented images supplied by experts have been used for model selection. The resulting fitted model has been validated on a training set consisting of 322 wound images manually segmented and labelled by expert clinicians. The final fitted segmentation model shows robustness and gives high mean performance rates [(AUC: .9426 (SD .0563); accuracy: .8777 (SD .0799); F-score: 0.7389 (SD .1550); Cohen's kappa: .6585 (SD .1787)] when segmenting significant wound areas that include healing tissues.

Bayesian parameter estimation for chiral effective field theory

NASA Astrophysics Data System (ADS)

Wesolowski, Sarah; Furnstahl, Richard; Phillips, Daniel; Klco, Natalie

2016-09-01

The low-energy constants (LECs) of a chiral effective field theory (EFT) interaction in the two-body sector are fit to observable data using a Bayesian parameter estimation framework. By using Bayesian prior probability distributions (pdfs), we quantify relevant physical expectations such as LEC naturalness and include them in the parameter estimation procedure. The final result is a posterior pdf for the LECs, which can be used to propagate uncertainty resulting from the fit to data to the final observable predictions. The posterior pdf also allows an empirical test of operator redundancy and other features of the potential. We compare results of our framework with other fitting procedures, interpreting the underlying assumptions in Bayesian probabilistic language. We also compare results from fitting all partial waves of the interaction simultaneously to cross section data compared to fitting to extracted phase shifts, appropriately accounting for correlations in the data. Supported in part by the NSF and DOE.

Symmetry restored in dibosons at the LHC?

DOE PAGES

Brehmer, Johann; Hewett, JoAnne; Kopp, Joachim; ...

2015-10-28

A number of LHC resonance search channels display an excess in the invariant mass region of 1.8–2.0 TeV. Among them is a 3.4σ excess in the fully hadronic decay of a pair of Standard Model electroweak gauge bosons, in addition to potential signals in the HW and dijet final states. We perform a model-independent cross-section fit to the results of all ATLAS and CMS searches sensitive to these final states. We then interpret these results in the context of the Left-Right Symmetric Model, based on the extended gauge group SU(2) L × SU(2) R × U(1)', and show that amore » heavy right-handed gauge boson W R can naturally explain the current measurements with just a single coupling g R ~ 0.4. Thus, we discuss a possible connection to dark matter.« less

The AKARI IRC asteroid flux catalogue: updated diameters and albedos

NASA Astrophysics Data System (ADS)

Alí-Lagoa, V.; Müller, T. G.; Usui, F.; Hasegawa, S.

2018-05-01

The AKARI IRC all-sky survey provided more than twenty thousand thermal infrared observations of over five thousand asteroids. Diameters and albedos were obtained by fitting an empirically calibrated version of the standard thermal model to these data. After the publication of the flux catalogue in October 2016, our aim here is to present the AKARI IRC all-sky survey data and discuss valuable scientific applications in the field of small body physical properties studies. As an example, we update the catalogue of asteroid diameters and albedos based on AKARI using the near-Earth asteroid thermal model (NEATM). We fit the NEATM to derive asteroid diameters and, whenever possible, infrared beaming parameters. We fit groups of observations taken for the same object at different epochs of the survey separately, so we compute more than one diameter for approximately half of the catalogue. We obtained a total of 8097 diameters and albedos for 5170 asteroids, and we fitted the beaming parameter for almost two thousand of them. When it was not possible to fit the beaming parameter, we used a straight line fit to our sample's beaming parameter-versus-phase angle plot to set the default value for each fit individually instead of using a single average value. Our diameters agree with stellar-occultation-based diameters well within the accuracy expected for the model. They also match the previous AKARI-based catalogue at phase angles lower than 50°, but we find a systematic deviation at higher phase angles, at which near-Earth and Mars-crossing asteroids were observed. The AKARI IRC All-sky survey is an essential source of information about asteroids, especially the large ones, since, it provides observations at different observation geometries, rotational coverages and aspect angles. For example, by comparing in more detail a few asteroids for which dimensions were derived from occultations, we discuss how the multiple observations per object may already provide three-dimensional information about elongated objects even based on an idealised model like the NEATM. Finally, we enumerate additional expected applications for more complex models, especially in combination with other catalogues. Full Table 1 is only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/612/A85

Choice Inconsistencies among the Elderly: Evidence from Plan Choice in the Medicare Part D Program: Reply

PubMed Central

ABALUCK, JASON

2017-01-01

We explore the in- and out- of sample robustness of tests for choice inconsistencies based on parameter restrictions in parametric models, focusing on tests proposed by Ketcham, Kuminoff and Powers (KKP). We argue that their non-parametric alternatives are inherently conservative with respect to detecting mistakes. We then show that our parametric model is robust to KKP’s suggested specification checks, and that comprehensive goodness of fit measures perform better with our model than the expected utility model. Finally, we explore the robustness of our 2011 results to alternative normative assumptions highlighting the role of brand fixed effects and unobservable characteristics. PMID:29170561

Psychological model of ART adherence behaviors in persons living with HIV/AIDS in Mexico: a structural equation analysis.

PubMed

Sagarduy, José Luis Ybarra; López, Julio Alfonso Piña; Ramírez, Mónica Teresa González; Dávila, Luis Enrique Fierros

2017-09-04

The objective of this study has been to test the ability of variables of a psychological model to predict antiretroviral therapy medication adherence behavior. We have conducted a cross-sectional study among 172 persons living with HIV/AIDS (PLWHA), who completed four self-administered assessments: 1) the Psychological Variables and Adherence Behaviors Questionnaire, 2) the Stress-Related Situation Scale to assess the variable of Personality, 3) The Zung Depression Scale, and 4) the Duke-UNC Functional Social Support Questionnaire. Structural equation modeling was used to construct a model to predict medication adherence behaviors. Out of all the participants, 141 (82%) have been considered 100% adherent to antiretroviral therapy. Structural equation modeling has confirmed the direct effect that personality (decision-making and tolerance of frustration) has on motives to behave, or act accordingly, which was in turn directly related to medication adherence behaviors. In addition, these behaviors have had a direct and significant effect on viral load, as well as an indirect effect on CD4 cell count. The final model demonstrates the congruence between theory and data (x2/df. = 1.480, goodness of fit index = 0.97, adjusted goodness of fit index = 0.94, comparative fit index = 0.98, root mean square error of approximation = 0.05), accounting for 55.7% of the variance. The results of this study support our theoretical model as a conceptual framework for the prediction of medication adherence behaviors in persons living with HIV/AIDS. Implications for designing, implementing, and evaluating intervention programs based on the model are to be discussed.

Mutational Effects and Population Dynamics During Viral Adaptation Challenge Current Models

PubMed Central

Miller, Craig R.; Joyce, Paul; Wichman, Holly A.

2011-01-01

Adaptation in haploid organisms has been extensively modeled but little tested. Using a microvirid bacteriophage (ID11), we conducted serial passage adaptations at two bottleneck sizes (104 and 106), followed by fitness assays and whole-genome sequencing of 631 individual isolates. Extensive genetic variation was observed including 22 beneficial, several nearly neutral, and several deleterious mutations. In the three large bottleneck lines, up to eight different haplotypes were observed in samples of 23 genomes from the final time point. The small bottleneck lines were less diverse. The small bottleneck lines appeared to operate near the transition between isolated selective sweeps and conditions of complex dynamics (e.g., clonal interference). The large bottleneck lines exhibited extensive interference and less stochasticity, with multiple beneficial mutations establishing on a variety of backgrounds. Several leapfrog events occurred. The distribution of first-step adaptive mutations differed significantly from the distribution of second-steps, and a surprisingly large number of second-step beneficial mutations were observed on a highly fit first-step background. Furthermore, few first-step mutations appeared as second-steps and second-steps had substantially smaller selection coefficients. Collectively, the results indicate that the fitness landscape falls between the extremes of smooth and fully uncorrelated, violating the assumptions of many current mutational landscape models. PMID:21041559

Spatial uncertainty of a geoid undulation model in Guayaquil, Ecuador

NASA Astrophysics Data System (ADS)

Chicaiza, E. G.; Leiva, C. A.; Arranz, J. J.; Buenańo, X. E.

2017-06-01

Geostatistics is a discipline that deals with the statistical analysis of regionalized variables. In this case study, geostatistics is used to estimate geoid undulation in the rural area of Guayaquil town in Ecuador. The geostatistical approach was chosen because the estimation error of prediction map is getting. Open source statistical software R and mainly geoR, gstat and RGeostats libraries were used. Exploratory data analysis (EDA), trend and structural analysis were carried out. An automatic model fitting by Iterative Least Squares and other fitting procedures were employed to fit the variogram. Finally, Kriging using gravity anomaly of Bouguer as external drift and Universal Kriging were used to get a detailed map of geoid undulation. The estimation uncertainty was reached in the interval [-0.5; +0.5] m for errors and a maximum estimation standard deviation of 2 mm in relation with the method of interpolation applied. The error distribution of the geoid undulation map obtained in this study provides a better result than Earth gravitational models publicly available for the study area according the comparison with independent validation points. The main goal of this paper is to confirm the feasibility to use geoid undulations from Global Navigation Satellite Systems and leveling field measurements and geostatistical techniques methods in order to use them in high-accuracy engineering projects.

SU-D-204-05: Fitting Four NTCP Models to Treatment Outcome Data of Salivary Glands Recorded Six Months After Radiation Therapy for Head and Neck Tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mavroidis, P; Price, A; Kostich, M

Purpose: To estimate the radiobiological parameters of four popular NTCP models that describe the dose-response relations of salivary glands to the severity of patient reported dry mouth 6 months post chemo-radiotherapy. To identify the glands, which best correlate with the manifestation of those clinical endpoints. Finally, to evaluate the goodness-of-fit of the NTCP models. Methods: Forty-three patients were treated on a prospective multiinstitutional phase II study for oropharyngeal squamous cell carcinoma. All the patients received 60 Gy IMRT and they reported symptoms using the novel patient reported outcome version of the CTCAE. We derived the individual patient dosimetric data ofmore » the parotid and submandibular glands (SMG) as separate structures as well as combinations. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS), Logit and Relative Logit (RL) NTCP models were used to fit the patients data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC) and the Odds Ratio methods. Results: The AUC values were highest for the contralateral parotid for Grade ≥ 2 (0.762 for the LKB, RS, Logit and 0.753 for the RL). For the salivary glands the AUC values were: 0.725 for the LKB, RS, Logit and 0.721 for the RL. For the contralateral SMG the AUC values were: 0.721 for LKB, 0.714 for Logit and 0.712 for RS and RL. The Odds Ratio for the contralateral parotid was 5.8 (1.3–25.5) for all the four NTCP models for the radiobiological dose threshold of 21Gy. Conclusion: It was shown that all the examined NTCP models could fit the clinical data well with very similar accuracy. The contralateral parotid gland appears to correlated best with the clinical endpoints of severe/very severe dry mouth. An EQD2Gy dose of 21Gy appears to be a safe threshold to be used as a constraint in treatment planning.« less

Full-scale tank car rollover tests - survivability of top fittings and top fittings protective structures : final report.

DOT National Transportation Integrated Search

2016-05-01

Full-scale rollover crash tests were performed on three non-pressure tank carbodies to validate previous analytical work and : determine the effectiveness of two different types of protective structures in protecting the top fittings. The tests were ...

A CLOUDY/XSPEC Interface

NASA Technical Reports Server (NTRS)

Porter, R. L.; Ferland, G. J.; Kraemer, S. B.; Armentrout, B. K.; Arnaud, K. A.; Turner, T. J.

2007-01-01

We discuss new functionality of the spectral simulation code CLOUDY which allows the user to calculate grids with one or more initial parameters varied and formats the predicted spectra in the standard FITS format. These files can then be imported into the x-ray spectral analysis software XSPEC and used as theoretical models for observations. We present and verify a test case. Finally, we consider a few observations and discuss our results.

Fuzzy Performance between Surface Fitting and Energy Distribution in Turbulence Runner

PubMed Central

Liang, Zhongwei; Liu, Xiaochu; Ye, Bangyan; Brauwer, Richard Kars

2012-01-01

Because the application of surface fitting algorithms exerts a considerable fuzzy influence on the mathematical features of kinetic energy distribution, their relation mechanism in different external conditional parameters must be quantitatively analyzed. Through determining the kinetic energy value of each selected representative position coordinate point by calculating kinetic energy parameters, several typical algorithms of complicated surface fitting are applied for constructing microkinetic energy distribution surface models in the objective turbulence runner with those obtained kinetic energy values. On the base of calculating the newly proposed mathematical features, we construct fuzzy evaluation data sequence and present a new three-dimensional fuzzy quantitative evaluation method; then the value change tendencies of kinetic energy distribution surface features can be clearly quantified, and the fuzzy performance mechanism discipline between the performance results of surface fitting algorithms, the spatial features of turbulence kinetic energy distribution surface, and their respective environmental parameter conditions can be quantitatively analyzed in detail, which results in the acquirement of final conclusions concerning the inherent turbulence kinetic energy distribution performance mechanism and its mathematical relation. A further turbulence energy quantitative study can be ensured. PMID:23213287

Nine-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Final Maps and Results

NASA Technical Reports Server (NTRS)

Bennett, C. L.; Larson, D.; Weiland, J. L.; Jaorsik, N.; Hinshaw, G.; Odegard, N.; Smith, K. M.; Hill, R. S.; Gold, B.; Halpern, M;

Leadership: validation of a self-report scale.

PubMed

Dussault, Marc; Frenette, Eric; Fernet, Claude

2013-04-01

The aim of this paper was to propose and test the factor structure of a new self-report questionnaire on leadership. A sample of 373 school principals in the Province of Quebec, Canada completed the initial 46-item version of the questionnaire. In order to obtain a questionnaire of minimal length, a four-step procedure was retained. First, items analysis was performed using Classical Test Theory. Second, Rasch analysis was used to identify non-fitting or overlapping items. Third, a confirmatory factor analysis (CFA) using structural equation modelling was performed on the 21 remaining items to verify the factor structure of the scale. Results show that the model with a single third-order dimension (leadership), two second-order dimensions (transactional and transformational leadership), and one first-order dimension (laissez-faire leadership) provides a good fit to the data. Finally, invariance of factor structure was assessed with a second sample of 222 vice-principals in the Province of Quebec, Canada. This model is in agreement with the theoretical model developed by Bass (1985), upon which the questionnaire is based.

Parametric study and global sensitivity analysis for co-pyrolysis of rape straw and waste tire via variance-based decomposition.

PubMed

Xu, Li; Jiang, Yong; Qiu, Rong

2018-01-01

In present study, co-pyrolysis behavior of rape straw, waste tire and their various blends were investigated. TG-FTIR indicated that co-pyrolysis was characterized by a four-step reaction, and H 2 O, CH, OH, CO 2 and CO groups were the main products evolved during the process. Additionally, using BBD-based experimental results, best-fit multiple regression models with high R 2 -pred values (94.10% for mass loss and 95.37% for reaction heat), which correlated explanatory variables with the responses, were presented. The derived models were analyzed by ANOVA at 95% confidence interval, F-test, lack-of-fit test and residues normal probability plots implied the models described well the experimental data. Finally, the model uncertainties as well as the interactive effect of these parameters were studied, the total-, first- and second-order sensitivity indices of operating factors were proposed using Sobol' variance decomposition. To the authors' knowledge, this is the first time global parameter sensitivity analysis has been performed in (co-)pyrolysis literature. Copyright © 2017 Elsevier Ltd. All rights reserved.

Verification of ARMA identification for modelling temporal correlation of GPS observations using the toolbox ARMASA

NASA Astrophysics Data System (ADS)

Luo, Xiaoguang; Mayer, Michael; Heck, Bernhard

2010-05-01

One essential deficiency of the stochastic model used in many GNSS (Global Navigation Satellite Systems) software products consists in neglecting temporal correlation of GNSS observations. Analysing appropriately detrended time series of observation residuals resulting from GPS (Global Positioning System) data processing, the temporal correlation behaviour of GPS observations can be sufficiently described by means of so-called autoregressive moving average (ARMA) processes. Using the toolbox ARMASA which is available free of charge in MATLAB® Central (open exchange platform for the MATLAB® and SIMULINK® user community), a well-fitting time series model can be identified automatically in three steps. Firstly, AR, MA, and ARMA models are computed up to some user-specified maximum order. Subsequently, for each model type, the best-fitting model is selected using the combined (for AR processes) resp. generalised (for MA and ARMA processes) information criterion. The final model identification among the best-fitting AR, MA, and ARMA models is performed based on the minimum prediction error characterising the discrepancies between the given data and the fitted model. The ARMA coefficients are computed using Burg's maximum entropy algorithm (for AR processes), Durbin's first (for MA processes) and second (for ARMA processes) methods, respectively. This paper verifies the performance of the automated ARMA identification using the toolbox ARMASA. For this purpose, a representative data base is generated by means of ARMA simulation with respect to sample size, correlation level, and model complexity. The model error defined as a transform of the prediction error is used as measure for the deviation between the true and the estimated model. The results of the study show that the recognition rates of underlying true processes increase with increasing sample sizes and decrease with rising model complexity. Considering large sample sizes, the true underlying processes can be correctly recognised for nearly 80% of the analysed data sets. Additionally, the model errors of first-order AR resp. MA processes converge clearly more rapidly to the corresponding asymptotical values than those of high-order ARMA processes.

Modelling and kinetics studies of a corn-rape blend combustion in an oxy-fuel atmosphere.

PubMed

López, R; Fernández, C; Martínez, O; Sánchez, M E

2015-05-01

A kinetic oxy-combustion study of a previously optimized lignocellulose blend is proposed. Kinetic and diffusion control mechanism are considered. The proposed correlations fit properly with the experimental results and diffusion effects are identified as be important enough to be taken into account. Afterwards, with the results obtained in the kinetic study, a detailed consecutive and parallel kinetic scheme is proposed for modelling the oxy-combustion of the blend. A discussion of the temperature and concentration profiles are included. Variation of products final distribution is considered. Smaller particles than 0.001 m are proposed for reducing temperature and concentration profiles and obtaining a good final product distribution. CO2-char reaction is identified as one of the most important step to be optimized for obtaining the lowest final residue. In this study, char is mainly oxidised at 950 K and this situation is attributed to an optimized blending of the bioresidues. Copyright © 2015 Elsevier Ltd. All rights reserved.

Pharmacokinetic Modeling to Simulate the Concentration-Time Profiles After Dermal Application of Rivastigmine Patch.

PubMed

Nozaki, Sachiko; Yamaguchi, Masayuki; Lefèvre, Gilbert

2016-07-01

Rivastigmine is an inhibitor of acetylcholinesterases and butyrylcholinesterases for symptomatic treatment of Alzheimer disease and is available as oral and transdermal patch formulations. A dermal absorption pharmacokinetic (PK) model was developed to simulate the plasma concentration-time profile of rivastigmine to answer questions relative to the efficacy and safety risks after misuse of the patch (e.g., longer application than 24 h, multiple patches applied at the same time, and so forth). The model comprised 2 compartments which was a combination of mechanistic dermal absorption model and a basic 1-compartment model. The initial values for the model were determined based on the physicochemical characteristics of rivastigmine and PK parameters after intravenous administration. The model was fitted to the clinical PK profiles after single application of rivastigmine patch to obtain model parameters. The final model was validated by confirming that the simulated concentration-time curves and PK parameters (Cmax and area under the drug plasma concentration-time curve) conformed to the observed values and then was used to simulate the PK profiles of rivastigmine. This work demonstrated that the mechanistic dermal PK model fitted the clinical data well and was able to simulate the PK profile after patch misuse. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Using the Job Burden-Capital Model of Occupational Stress to Predict Depression and Well-Being among Electronic Manufacturing Service Employees in China

PubMed Central

Wang, Chao; Li, Shuang; Li, Tao; Yu, Shanfa; Dai, Junming; Liu, Xiaoman; Zhu, Xiaojun; Ji, Yuqing; Wang, Jin

2016-01-01

Background: This study aimed to identify the association between occupational stress and depression-well-being by proposing a comprehensive and flexible job burden-capital model with its corresponding hypotheses. Methods: For this research, 1618 valid samples were gathered from the electronic manufacturing service industry in Hunan Province, China; self-rated questionnaires were administered to participants for data collection after obtaining their written consent. The proposed model was fitted and tested through structural equation model analysis. Results: Single-factor correlation analysis results indicated that coefficients between all items and dimensions had statistical significance. The final model demonstrated satisfactory global goodness of fit (CMIN/DF = 5.37, AGFI = 0.915, NNFI = 0.945, IFI = 0.952, RMSEA = 0.052). Both the measurement and structural models showed acceptable path loadings. Job burden and capital were directly associated with depression and well-being or indirectly related to them through personality. Multi-group structural equation model analyses indicated general applicability of the proposed model to basic features of such a population. Gender, marriage and education led to differences in the relation between occupational stress and health outcomes. Conclusions: The job burden-capital model of occupational stress-depression and well-being was found to be more systematic and comprehensive than previous models. PMID:27529267

Using the Job Burden-Capital Model of Occupational Stress to Predict Depression and Well-Being among Electronic Manufacturing Service Employees in China.

PubMed

Wang, Chao; Li, Shuang; Li, Tao; Yu, Shanfa; Dai, Junming; Liu, Xiaoman; Zhu, Xiaojun; Ji, Yuqing; Wang, Jin

2016-08-12

This study aimed to identify the association between occupational stress and depression-well-being by proposing a comprehensive and flexible job burden-capital model with its corresponding hypotheses. For this research, 1618 valid samples were gathered from the electronic manufacturing service industry in Hunan Province, China; self-rated questionnaires were administered to participants for data collection after obtaining their written consent. The proposed model was fitted and tested through structural equation model analysis. Single-factor correlation analysis results indicated that coefficients between all items and dimensions had statistical significance. The final model demonstrated satisfactory global goodness of fit (CMIN/DF = 5.37, AGFI = 0.915, NNFI = 0.945, IFI = 0.952, RMSEA = 0.052). Both the measurement and structural models showed acceptable path loadings. Job burden and capital were directly associated with depression and well-being or indirectly related to them through personality. Multi-group structural equation model analyses indicated general applicability of the proposed model to basic features of such a population. Gender, marriage and education led to differences in the relation between occupational stress and health outcomes. The job burden-capital model of occupational stress-depression and well-being was found to be more systematic and comprehensive than previous models.

A sectionwise defined model for the material description of 100Cr6 in the thixotropic state

NASA Astrophysics Data System (ADS)

Behrens, B.-A.; Chugreev, A.; Hootak, M.

2018-05-01

A sectionwise defined material model has been developed for the numerical description of thixoforming processes. It consists of two sections. The first one describes the material behaviour below the solidus temperature and comprises an approach from structure mechanics, whereas the second section model describes the thixotropic behaviour above the solidus temperature based on the Ostwald-de Waele power law. The material model has been implemented in a commercial FE software Simufact Forming by means of user-defined subroutines. Numerical and experimental investigations of special upsetting tests have been designed and carried out with Armco iron-coated specimens. Finally, the model parameters were fitted by reverse engineering.

Testing a healthcare provider-patient communicative relationship quality model of pharmaceutical care in hospitals.

PubMed

Wang, Dan; Liu, Chenxi; Zhang, Zinan; Ye, Liping; Zhang, Xinping

2018-06-01

Background Patient-centeredness and participatory care is increasingly regarded as a proxy for high-quality interpersonal care. Considering the development of patient-centeredness and participatory care relationship model in pharmacist-patient domain, it is of great significance to explore the mechanism of how pharmacist and patient participative behaviors influence relationship quality and patient outcomes. Objective To validate pharmacist-patient relationship quality model in Chinese hospitals. Four tertiary hospitals in 2017. Methods The provision of pharmaceutical care was investigated. A cross-sectional questionnaire survey covering different constructs of communicative relationship quality model was conducted and the associations among pairs of the study constructs were explored. Based on the results of confirmatory factor analysis, path analysis was conducted to validate the proposed communicative relationship quality model. Main outcome measure Model fit indicators including Tucker-Lewis index (TLI), comparative fit index (CFI), root mean square error of approximation (RMSEA) and weighted root mean square residual(WRMR). Results There were 589 patients included in our study. The final path model had an excellent fit (TLI = 0.98, CFI = 0.98, RMSEA = 0.05; WRMR = 1.06). HCP participative behavior/patient-centeredness (β = 0.79, p < 0.001) and interpersonal communication (β = 0.13, p < 0.001) directly impact the communicative relationship quality. But patient participative behavior was not a predictor of either communicative relationship quality or patient satisfaction. Conclusion HCP participative behavior/patient-centeredness and interpersonal communication are positively related to relationship quality, and relationship quality is mediator between HCP participative behavior and interpersonal communication with patient satisfaction.

Testing Einstein's gravity and dark energy with growth of matter perturbations: Indications for new physics?

NASA Astrophysics Data System (ADS)

Basilakos, Spyros; Nesseris, Savvas

2016-12-01

The growth index of matter fluctuations is computed for ten distinct accelerating cosmological models and confronted by the latest growth-rate data via a two-step process. First, we implement a joint statistical analysis in order to place constraints on the free parameters of all models using solely background data. Second, using the observed growth rate of clustering from various galaxy surveys we test the performance of the current cosmological models at the perturbation level while either marginalizing over σ8 or having it as a free parameter. As a result, we find that at a statistical level, i.e., after considering the best-fit χ2 or the value of the Akaike information criterion, most models are in very good agreement with the growth-rate data and are practically indistinguishable from Λ CDM . However, when we also consider the internal consistency of the models by comparing the theoretically predicted values of (γ0,γ1), i.e., the value of the growth index γ (z ) and its derivative today, with the best-fit ones, we find that the predictions of three out of ten dark energy models are in mild tension with the best-fit ones when σ8 is marginalized over. When σ8 is free we find that most models are not only in mild tension, but also predict low values for σ8. This could be attributed to either a systematic problem with the growth-rate data or the emergence of new physics at low redshifts, with the latter possibly being related to the well-known issue of the lack of power at small scales. Finally, by utilizing mock data based on an large synoptic survey telescope-like survey we show that with future surveys and by using the growth index parametrization, it will be possible to resolve the issue of the low σ8 but also the tension between the fitted and theoretically predicted values of (γ0,γ1).

Geometric compatibility of IceCube TeV-PeV neutrino excess and its galactic dark matter origin

DOE PAGES

Bai, Yang; Lu, Ran; Salvado, Jordi

2016-01-27

Here, we perform a geometric analysis for the sky map of the IceCube TeV-PeV neutrino excess and test its compatibility with the sky map of decaying dark matter signals in our galaxy. Furthermore, we have found that a galactic decaying dark matter component in general improve the goodness of the fit of our model, although the pure isotropic hypothesis has a better fit than the pure dark matter one. Finally, we also consider several representative decaying dark matter, which can provide a good t to the observed spectrum at IceCube with a dark matter lifetime of around 12 orders ofmore » magnitude longer than the age of the universe.« less

Quantifying cancer cell receptors with paired-agent fluorescent imaging: a novel method to account for tissue optical property effects

NASA Astrophysics Data System (ADS)

Sadeghipour, Negar; Davis, Scott C.; Tichauer, Kenneth M.

2018-02-01

Dynamic fluorescence imaging approaches can be used to estimate the concentration of cell surface receptors in vivo. Kinetic models are used to generate the final estimation by taking the targeted imaging agent concentration as a function of time. However, tissue absorption and scattering properties cause the final readout signal to be on a different scale than the real fluorescent agent concentration. In paired-agent imaging approaches, simultaneous injection of a suitable control imaging agent with a targeted one can account for non-specific uptake and retention of the targeted agent. Additionally, the signal from the control agent can be a normalizing factor to correct for tissue optical property differences. In this study, the kinetic model used for paired-agent imaging analysis (i.e., simplified reference tissue model) is modified and tested in simulation and experimental data in a way that accounts for the scaling correction within the kinetic model fit to the data to ultimately extract an estimate of the targeted biomarker concentration.

Geostatistics and the representative elementary volume of gamma ray tomography attenuation in rocks cores

USGS Publications Warehouse

Vogel, J.R.; Brown, G.O.

2003-01-01

Semivariograms of samples of Culebra Dolomite have been determined at two different resolutions for gamma ray computed tomography images. By fitting models to semivariograms, small-scale and large-scale correlation lengths are determined for four samples. Different semivariogram parameters were found for adjacent cores at both resolutions. Relative elementary volume (REV) concepts are related to the stationarity of the sample. A scale disparity factor is defined and is used to determine sample size required for ergodic stationarity with a specified correlation length. This allows for comparison of geostatistical measures and representative elementary volumes. The modifiable areal unit problem is also addressed and used to determine resolution effects on correlation lengths. By changing resolution, a range of correlation lengths can be determined for the same sample. Comparison of voxel volume to the best-fit model correlation length of a single sample at different resolutions reveals a linear scaling effect. Using this relationship, the range of the point value semivariogram is determined. This is the range approached as the voxel size goes to zero. Finally, these results are compared to the regularization theory of point variables for borehole cores and are found to be a better fit for predicting the volume-averaged range.

Human mobility in space from three modes of public transportation

NASA Astrophysics Data System (ADS)

Jiang, Shixiong; Guan, Wei; Zhang, Wenyi; Chen, Xu; Yang, Liu

2017-10-01

The human mobility patterns have drew much attention from researchers for decades, considering about its importance for urban planning and traffic management. In this study, the taxi GPS trajectories, smart card transaction data of subway and bus from Beijing are utilized to model human mobility in space. The original datasets are cleaned and processed to attain the displacement of each trip according to the origin and destination locations. Then, the Akaike information criterion is adopted to screen out the best fitting distribution for each mode from candidate ones. The results indicate that displacements of taxi trips follow the exponential distribution. Besides, the exponential distribution also fits displacements of bus trips well. However, their exponents are significantly different. Displacements of subway trips show great specialties and can be well fitted by the gamma distribution. It is obvious that human mobility of each mode is different. To explore the overall human mobility, the three datasets are mixed up to form a fusion dataset according to the annual ridership proportions. Finally, the fusion displacements follow the power-law distribution with an exponential cutoff. It is innovative to combine different transportation modes to model human mobility in the city.

A BRDF statistical model applying to space target materials modeling

NASA Astrophysics Data System (ADS)

Liu, Chenghao; Li, Zhi; Xu, Can; Tian, Qichen

2017-10-01

In order to solve the problem of poor effect in modeling the large density BRDF measured data with five-parameter semi-empirical model, a refined statistical model of BRDF which is suitable for multi-class space target material modeling were proposed. The refined model improved the Torrance-Sparrow model while having the modeling advantages of five-parameter model. Compared with the existing empirical model, the model contains six simple parameters, which can approximate the roughness distribution of the material surface, can approximate the intensity of the Fresnel reflectance phenomenon and the attenuation of the reflected light's brightness with the azimuth angle changes. The model is able to achieve parameter inversion quickly with no extra loss of accuracy. The genetic algorithm was used to invert the parameters of 11 different samples in the space target commonly used materials, and the fitting errors of all materials were below 6%, which were much lower than those of five-parameter model. The effect of the refined model is verified by comparing the fitting results of the three samples at different incident zenith angles in 0° azimuth angle. Finally, the three-dimensional modeling visualizations of these samples in the upper hemisphere space was given, in which the strength of the optical scattering of different materials could be clearly shown. It proved the good describing ability of the refined model at the material characterization as well.

Dalitz plot analysis of the D+→K-π+π+ decay in the FOCUS experiment

NASA Astrophysics Data System (ADS)

Link, J. M.; Yager, P. M.; Anjos, J. C.; Bediaga, I.; Castromonte, C.; Machado, A. A.; Magnin, J.; Massafferri, A.; de Miranda, J. M.; Pepe, I. M.; Polycarpo, E.; Dos Reis, A. C.; Carrillo, S.; Casimiro, E.; Cuautle, E.; Sánchez-Hernández, A.; Uribe, C.; Vázquez, F.; Agostino, L.; Cinquini, L.; Cumalat, J. P.; Frisullo, V.; O'Reilly, B.; Segoni, I.; Stenson, K.; Butler, J. N.; Cheung, H. W. K.; Chiodini, G.; Gaines, I.; Garbincius, P. H.; Garren, L. A.; Gottschalk, E.; Kasper, P. H.; Kreymer, A. E.; Kutschke, R.; Wang, M.; Benussi, L.; Bianco, S.; Fabbri, F. L.; Zallo, A.; Reyes, M.; Cawlfield, C.; Kim, D. Y.; Rahimi, A.; Wiss, J.; Gardner, R.; Kryemadhi, A.; Chung, Y. S.; Kang, J. S.; Ko, B. R.; Kwak, J. W.; Lee, K. B.; Cho, K.; Park, H.; Alimonti, G.; Barberis, S.; Boschini, M.; Cerutti, A.; D'Angelo, P.; Dicorato, M.; Dini, P.; Edera, L.; Erba, S.; Inzani, P.; Leveraro, F.; Malvezzi, S.; Menasce, D.; Mezzadri, M.; Moroni, L.; Pedrini, D.; Pontoglio, C.; Prelz, F.; Rovere, M.; Sala, S.; Davenport, T. F.; Arena, V.; Boca, G.; Bonomi, G.; Gianini, G.; Liguori, G.; Lopes Pegna, D.; Merlo, M. M.; Pantea, D.; Ratti, S. P.; Riccardi, C.; Vitulo, P.; Göbel, C.; Otalora, J.; Hernandez, H.; Lopez, A. M.; Mendez, H.; Paris, A.; Quinones, J.; Ramirez, J. E.; Zhang, Y.; Wilson, J. R.; Handler, T.; Mitchell, R.; Engh, D.; Hosack, M.; Johns, W. E.; Luiggi, E.; Nehring, M.; Sheldon, P. D.; Vaandering, E. W.; Webster, M.; Sheaff, M.; Pennington, M. R.; Focus Collaboration

2007-09-01

Using data collected by the high-energy photoproduction experiment FOCUS at Fermilab we performed a Dalitz plot analysis of the Cabibbo favored decay D+ →K-π+π+. This study uses 53653 Dalitz-plot events with a signal fraction of ∼ 97%, and represents the highest statistics, most complete Dalitz plot analysis for this channel. Results are presented and discussed using two different formalisms. The first is a simple sum of Breit-Wigner functions with freely fitted masses and widths. It is the model traditionally adopted and serves as comparison with the already published analyses. The second uses a K-matrix approach for the dominant S-wave, in which the parameters are fixed by first fitting Kπ scattering data and continued to threshold by Chiral Perturbation Theory. We show that the Dalitz plot distribution for this decay is consistent with the assumption of two-body dominance of the final state interactions and the description of these interactions is in agreement with other data on the Kπ final state.

Modelling the distribution of chickens, ducks, and geese in China

USGS Publications Warehouse

Prosser, Diann J.; Wu, Junxi; Ellis, Erie C.; Gale, Fred; Van Boeckel, Thomas P.; Wint, William; Robinson, Tim; Xiao, Xiangming; Gilbert, Marius

2011-01-01

Global concerns over the emergence of zoonotic pandemics emphasize the need for high-resolution population distribution mapping and spatial modelling. Ongoing efforts to model disease risk in China have been hindered by a lack of available species level distribution maps for poultry. The goal of this study was to develop 1 km resolution population density models for China's chickens, ducks, and geese. We used an information theoretic approach to predict poultry densities based on statistical relationships between poultry census data and high-resolution agro-ecological predictor variables. Model predictions were validated by comparing goodness of fit measures (root mean square error and correlation coefficient) for observed and predicted values for 1/4 of the sample data which were not used for model training. Final output included mean and coefficient of variation maps for each species. We tested the quality of models produced using three predictor datasets and 4 regional stratification methods. For predictor variables, a combination of traditional predictors for livestock mapping and land use predictors produced the best goodness of fit scores. Comparison of regional stratifications indicated that for chickens and ducks, a stratification based on livestock production systems produced the best results; for geese, an agro-ecological stratification produced best results. However, for all species, each method of regional stratification produced significantly better goodness of fit scores than the global model. Here we provide descriptive methods, analytical comparisons, and model output for China's first high resolution, species level poultry distribution maps. Output will be made available to the scientific and public community for use in a wide range of applications from epidemiological studies to livestock policy and management initiatives.

Modelling the distribution of chickens, ducks, and geese in China

PubMed Central

Prosser, Diann J.; Wu, Junxi; Ellis, Erle C.; Gale, Fred; Van Boeckel, Thomas P.; Wint, William; Robinson, Tim; Xiao, Xiangming; Gilbert, Marius

2011-01-01

Global concerns over the emergence of zoonotic pandemics emphasize the need for high-resolution population distribution mapping and spatial modelling. Ongoing efforts to model disease risk in China have been hindered by a lack of available species level distribution maps for poultry. The goal of this study was to develop 1 km resolution population density models for China’s chickens, ducks, and geese. We used an information theoretic approach to predict poultry densities based on statistical relationships between poultry census data and high-resolution agro-ecological predictor variables. Model predictions were validated by comparing goodness of fit measures (root mean square error and correlation coefficient) for observed and predicted values for ¼ of the sample data which was not used for model training. Final output included mean and coefficient of variation maps for each species. We tested the quality of models produced using three predictor datasets and 4 regional stratification methods. For predictor variables, a combination of traditional predictors for livestock mapping and land use predictors produced the best goodness of fit scores. Comparison of regional stratifications indicated that for chickens and ducks, a stratification based on livestock production systems produced the best results; for geese, an agro-ecological stratification produced best results. However, for all species, each method of regional stratification produced significantly better goodness of fit scores than the global model. Here we provide descriptive methods, analytical comparisons, and model output for China’s first high resolution, species level poultry distribution maps. Output will be made available to the scientific and public community for use in a wide range of applications from epidemiological studies to livestock policy and management initiatives. PMID:21765567

77 FR 24459 - Stainless Steel Butt-Weld Pipe Fittings From Italy: Final Results of Antidumping Duty...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-24

... CR, of wrought austenitic stainless steel fittings of seamless and welded construction covered by the... DEPARTMENT OF COMMERCE International Trade Administration [A-475-828] Stainless Steel Butt-Weld... administrative review of the antidumping duty order on stainless steel butt-weld pipe fittings (SSBW pipe...

Partial polarization: a comprehensive student exercise

NASA Astrophysics Data System (ADS)

Topasna, Gregory A.; Topasna, Daniela M.

2015-10-01

We present a comprehensive student exercise in partial polarization. Students are first introduced to the concept of partial polarization using Fresnel Equations. Next, MATHCAD is used to compute and graph the reflectance for dielectrics materials. The students then design and construct a simple, easy to use collimated light source for their experiment, which is performed on an optical breadboard using optical components typically found in an optics lab above the introductory level. The students obtain reflection data that is compared with their model by a nonlinear least square fit using EXCEL. Sources of error and uncertainty are discussed and students present a final written report. In this one exercise students learn how an experiment is constructed "from the ground up". They gain practical experience on data modeling and analysis, working with optical equipment, machining and construction, and preparing a final presentation.

Handheld Synthetic Array Final Report, Part B

DTIC Science & Technology

2014-12-01

Multiple Model IMU Inertial Measurement Unit 4/154 IEEE Institute of Electrical and Electronics Engineers KF Kalman Filter KL Kullback - Leibler LAMBDA...important metric in information theory is the input–output mutual information (MI) that is used as an indicator of how much coded information can be...tracking using best- fitting Gaussian distributions,” Proc. Int. Conf. Inform . Fusion, pp. 1–8, 2005. [liv] L. Svensson, “On the Bayesian Cramér-Rao

Flexible work in call centres: Working hours, work-life conflict & health.

PubMed

Bohle, Philip; Willaby, Harold; Quinlan, Michael; McNamara, Maria

2011-01-01

Call-centre workers encounter major psychosocial pressures, including high work intensity and undesirable working hours. Little is known, however, about whether these pressures vary with employment status and how they affect work-life conflict and health. Questionnaire data were collected from 179 telephone operators in Sydney, Australia, of whom 124 (69.3%) were female and 54 (30.2%) were male. Ninety-three (52%) were permanent full-time workers, 37 (20.7%) were permanent part-time, and 49 (27.4%) were casual employees. Hypothesised structural relationships between employment status, working hours and work organisation, work-life conflict and health were tested using partial least squares modelling in PLS (Chin, 1998). The final model demonstrated satisfactory fit. It supported important elements of the hypothesised structure, although four of the proposed paths failed to reach significance and the fit was enhanced by adding a path. The final model indicated that casual workers reported more variable working hours which were relatively weakly associated with greater dissatisfaction with hours. The interaction of schedule control and variability of hours also predicted dissatisfaction with hours. Conversely, permanent workers reported greater work intensity, which was associated with both lower work schedule control and greater work-life conflict. Greater work-life conflict was associated with more fatigue and psychological symptoms. Labour market factors and the undesirability of longer hours in a stressful, high-intensity work environment appear to have contributed to the results. Copyright © 2010 Elsevier Ltd and The Ergonomics Society. All rights reserved.

One-dimensional analysis of the rate of plasma-assisted sputter deposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palmero, A.; Rudolph, H.; Habraken, F. H. P. M.

2007-04-15

In this article a recently developed model [A. Palmero, H. Rudolph, and F. H. P. M. Habraken, Appl. Phys. Lett. 89, 211501 (2006)] is applied to analyze the transport of sputtered material from the cathode toward the growing film when using a plasma-assisted sputtering deposition technique. The argon pressure dependence of the deposition rate of aluminum, silicon, vanadium, chromium, germanium, tantalum, and tungsten under several different experimental conditions has been analyzed by fitting experimental results from the literature to the above-mentioned theory. Good fits are obtained. Three quantities are deduced from the fit: the temperature of the cathode and ofmore » the growing film, and the value of the effective cross section for thermalization due to elastic scattering of a sputtered particle on background gas atoms. The values derived from the fits for the growing film and cathode temperature are very similar to those experimentally determined and reported in the literature. The effective cross sections have been found to be approximately the corresponding geometrical cross section divided by the average number of collisions required for the thermalization, implying that the real and effective thermalization lengths have a similar value. Finally, the values of the throw distance appearing in the Keller-Simmons model, as well as its dependence on the deposition conditions have been understood invoking the values of the cathode and film temperature, as well as of the value of the effective cross section. The analysis shows the overall validity of this model for the transport of sputtered particles in sputter deposition.« less

Virtual plate pre-bending for the long bone fracture based on axis pre-alignment.

PubMed

Liu, Bin; Luo, Xinjian; Huang, Rui; Wan, Chao; Zhang, Bingbing; Hu, Weihua; Yue, Zongge

2014-06-01

In this paper, a modeling and visualizing system for assisting surgeons in correctly registering for the closed fracture reduction surgery is presented. By using this system, the geometric parameters of the target fixation plate before the long bone fracture operation can be obtained. The main processing scheme consists of following steps: firstly (image data process), utilize the Curvelet transform to denoise the CT images of fracture part and then reconstruct the 3D models of the broken bones. Secondly (pre-alignment), extract the axial lines of the broken bones and spatially align them. Then drive the broken bone models to be pre-aligned. Thirdly (mesh segmentation), a method based on vertex normal feature is utilized to obtain the broken bone cross-sections mesh models. Fourthly (fine registration), the ICP (Iterative Closest Point) algorithm is used to register the cross-sections and the broken bone models are driven to achieve the fine registration posture. Lastly (plate fitting), an accurate NURBS surface fitting method is used to construct the virtual plate. The experiment proved that the obtained models of the pre-bended plates were closely bonded to the surface of the registered long bone models. Finally, the lengths, angles and other interested geometric parameters can be measured on the plate models. Copyright © 2014 Elsevier Ltd. All rights reserved.

Psychometrics of the preschooler physical activity parenting practices instrument among a Latino sample.

PubMed

O'Connor, Teresia M; Cerin, Ester; Hughes, Sheryl O; Robles, Jessica; Thompson, Deborah I; Mendoza, Jason A; Baranowski, Tom; Lee, Rebecca E

2014-01-15

Latino preschoolers (3-5 year old children) have among the highest rates of obesity. Low levels of physical activity (PA) are a risk factor for obesity. Characterizing what Latino parents do to encourage or discourage their preschooler to be physically active can help inform interventions to increase their PA. The objective was therefore to develop and assess the psychometrics of a new instrument: the Preschooler Physical Activity Parenting Practices (PPAPP) among a Latino sample, to assess parenting practices used to encourage or discourage PA among preschool-aged children. Cross-sectional study of 240 Latino parents who reported the frequency of using PA parenting practices. 95% of respondents were mothers; 42% had more than a high school education. Child mean age was 4.5 (±0.9) years (52% male). Test-retest reliability was assessed in 20%, 2 weeks later. We assessed the fit of a priori models using Confirmatory factor analyses (CFA). In a separate sub-sample (35%), preschool-aged children wore accelerometers to assess associations with their PA and PPAPP subscales. The a-priori models showed poor fit to the data. A modified factor structure for encouraging PPAPP had one multiple-item scale: engagement (15 items), and two single-items (have outdoor toys; not enroll in sport-reverse coded). The final factor structure for discouraging PPAPP had 4 subscales: promote inactive transport (3 items), promote screen time (3 items), psychological control (4 items) and restricting for safety (4 items). Test-retest reliability (ICC) for the two scales ranged from 0.56-0.85. Cronbach's alphas ranged from 0.5-0.9. Several sub-factors correlated in the expected direction with children's objectively measured PA. The final models for encouraging and discouraging PPAPP had moderate to good fit, with moderate to excellent test-retest reliabilities. The PPAPP should be further evaluated to better assess its associations with children's PA and offers a new tool for measuring PPAPP among Latino families with preschool-aged children.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nersisyan, Henrik; Cid, Adrian Fernandez; Amendola, Luca, E-mail: h.nersisyan@thphys.uni-heidelberg.de, E-mail: fernandez@thphys.uni-heidelberg.de, E-mail: l.amendola@thphys.uni-heidelberg.de

In this work, we extend previous analyses of the structure formation in the f (□{sup −1} R ) model of nonlocal gravity proposed by Deser and Woodard (DW), which reproduces the background expansion of ΛCDM with no need of a cosmological constant nor of any dimensional constant beside Newton's one. A previous analysis based on redshift-space distortions (RSD) data concluded that the model was ruled out. In this work we revisit the issue and find that, when recast in a localized model, the DW model is not ruled out and actually gives a better fit to RSD data than ΛCDM.more » In fact, the DW model presents a suppressed growth of matter perturbations with respect to ΛCDM and a slightly lower value of σ{sub 8}, as favored by observations. We also produce analytical approximations of the two modified gravity functions, i.e. the anisotropic stress η and the relative change of Newton's constant Y , and of f σ{sub 8}( z ) as a function of redshift. Finally, we also show how much the fit depends on initial conditions when these are generalized with respect to a standard matter-dominated era.« less

Design Considerations for Heavily-Doped Cryogenic Schottky Diode Varactor Multipliers

NASA Technical Reports Server (NTRS)

Schlecht, E.; Maiwald, F.; Chattopadhyay, G.; Martin, S.; Mehdi, I.

2001-01-01

Diode modeling for Schottky varactor frequency multipliers above 500 GHz is presented with special emphasis placed on simple models and fitted equations for rapid circuit design. Temperature- and doping-dependent mobility, resistivity, and avalanche current multiplication and breakdown are presented. Next is a discussion of static junction current, including the effects of tunneling as well as thermionic emission. These results have been compared to detailed measurements made down to 80 K on diodes fabricated at JPL, followed by a discussion of the effect on multiplier efficiency. Finally, a simple model of current saturation in the undepleted active layer suitable for inclusion in harmonic balance simulators is derived.

FY09 Final Report for LDRD Project: Understanding Viral Quasispecies Evolution through Computation and Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, C

2009-11-12

In FY09 they will (1) complete the implementation, verification, calibration, and sensitivity and scalability analysis of the in-cell virus replication model; (2) complete the design of the cell culture (cell-to-cell infection) model; (3) continue the research, design, and development of their bioinformatics tools: the Web-based structure-alignment-based sequence variability tool and the functional annotation of the genome database; (4) collaborate with the University of California at San Francisco on areas of common interest; and (5) submit journal articles that describe the in-cell model with simulations and the bioinformatics approaches to evaluation of genome variability and fitness.

[Research and application of computer-aided technology in restoration of maxillary defect].

PubMed

Cheng, Xiaosheng; Liao, Wenhe; Hu, Qingang; Wang, Qian; Dai, Ning

2008-08-01

This paper presents a new method of designing restoration model of maxillectomy defect through Computer aided technology. Firstly, 3D maxillectomy triangle mesh model is constructed from Helical CT data. Secondly, the triangle mesh model is transformed into initial computer-aided design (CAD) model of maxillectomy through reverse engineering software. Thirdly, the 3D virtual restoration model of maxillary defect is obtained after designing and adjusting the initial CAD model through CAD software according to the patient's practical condition. Therefore, the 3D virtual restoration can be fitted very well with the broken part of maxilla. The exported design data can be manufactured using rapid prototyping technology and foundry technology. Finally, the result proved that this method is effective and feasible.

A design of experiments approach to validation sampling for logistic regression modeling with error-prone medical records.

PubMed

Ouyang, Liwen; Apley, Daniel W; Mehrotra, Sanjay

2016-04-01

Electronic medical record (EMR) databases offer significant potential for developing clinical hypotheses and identifying disease risk associations by fitting statistical models that capture the relationship between a binary response variable and a set of predictor variables that represent clinical, phenotypical, and demographic data for the patient. However, EMR response data may be error prone for a variety of reasons. Performing a manual chart review to validate data accuracy is time consuming, which limits the number of chart reviews in a large database. The authors' objective is to develop a new design-of-experiments-based systematic chart validation and review (DSCVR) approach that is more powerful than the random validation sampling used in existing approaches. The DSCVR approach judiciously and efficiently selects the cases to validate (i.e., validate whether the response values are correct for those cases) for maximum information content, based only on their predictor variable values. The final predictive model will be fit using only the validation sample, ignoring the remainder of the unvalidated and unreliable error-prone data. A Fisher information based D-optimality criterion is used, and an algorithm for optimizing it is developed. The authors' method is tested in a simulation comparison that is based on a sudden cardiac arrest case study with 23 041 patients' records. This DSCVR approach, using the Fisher information based D-optimality criterion, results in a fitted model with much better predictive performance, as measured by the receiver operating characteristic curve and the accuracy in predicting whether a patient will experience the event, than a model fitted using a random validation sample. The simulation comparisons demonstrate that this DSCVR approach can produce predictive models that are significantly better than those produced from random validation sampling, especially when the event rate is low. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Parameter Estimation as a Problem in Statistical Thermodynamics.

PubMed

Earle, Keith A; Schneider, David J

2011-03-14

In this work, we explore the connections between parameter fitting and statistical thermodynamics using the maxent principle of Jaynes as a starting point. In particular, we show how signal averaging may be described by a suitable one particle partition function, modified for the case of a variable number of particles. These modifications lead to an entropy that is extensive in the number of measurements in the average. Systematic error may be interpreted as a departure from ideal gas behavior. In addition, we show how to combine measurements from different experiments in an unbiased way in order to maximize the entropy of simultaneous parameter fitting. We suggest that fit parameters may be interpreted as generalized coordinates and the forces conjugate to them may be derived from the system partition function. From this perspective, the parameter fitting problem may be interpreted as a process where the system (spectrum) does work against internal stresses (non-optimum model parameters) to achieve a state of minimum free energy/maximum entropy. Finally, we show how the distribution function allows us to define a geometry on parameter space, building on previous work[1, 2]. This geometry has implications for error estimation and we outline a program for incorporating these geometrical insights into an automated parameter fitting algorithm.

Parenting quality: Confirmation of a higher-order latent construct with mothers of Head Start children

PubMed Central

Hubbs-Tait, Laura; Page, Melanie C.; Huey, Erron L.; Starost, Huei-Juang; Culp, Anne McDonald; Culp, Rex E.; Harper, M. Elizabeth

2009-01-01

We proposed a higher order latent construct of parenting young children, parenting quality. This higher-order latent construct comprises five component constructs: demographic protection, psychological distress, psychosocial maturity, moral and cognitive reflectivity, and parenting attitudes and beliefs. We evaluated this model with data provided by 199 mothers of 4-year-old children enrolled in Head Start. The model was confirmed with only one adjustment suggested by modification indices. Final RMSEA was .05, CFI .96, and NNFI .94, indicating good model fit. Results were interpreted as emphasizing the interdependence of psychological and environmental demands on parenting. Implications of the model for teachers, early interventionists, and public policy are discussed. PMID:19629192

Psychological model of ART adherence behaviors in persons living with HIV/AIDS in Mexico: a structural equation analysis

PubMed Central

Sagarduy, José Luis Ybarra; López, Julio Alfonso Piña; Ramírez, Mónica Teresa González; Dávila, Luis Enrique Fierros

2017-01-01

ABSTRACT OBJECTIVE The objective of this study has been to test the ability of variables of a psychological model to predict antiretroviral therapy medication adherence behavior. METHODS We have conducted a cross-sectional study among 172 persons living with HIV/AIDS (PLWHA), who completed four self-administered assessments: 1) the Psychological Variables and Adherence Behaviors Questionnaire, 2) the Stress-Related Situation Scale to assess the variable of Personality, 3) The Zung Depression Scale, and 4) the Duke-UNC Functional Social Support Questionnaire. Structural equation modeling was used to construct a model to predict medication adherence behaviors. RESULTS Out of all the participants, 141 (82%) have been considered 100% adherent to antiretroviral therapy. Structural equation modeling has confirmed the direct effect that personality (decision-making and tolerance of frustration) has on motives to behave, or act accordingly, which was in turn directly related to medication adherence behaviors. In addition, these behaviors have had a direct and significant effect on viral load, as well as an indirect effect on CD4 cell count. The final model demonstrates the congruence between theory and data (x 2/df. = 1.480, goodness of fit index = 0.97, adjusted goodness of fit index = 0.94, comparative fit index = 0.98, root mean square error of approximation = 0.05), accounting for 55.7% of the variance. CONCLUSIONS The results of this study support our theoretical model as a conceptual framework for the prediction of medication adherence behaviors in persons living with HIV/AIDS. Implications for designing, implementing, and evaluating intervention programs based on the model are to be discussed. PMID:28876412

Studies of cluster X-ray sources, energy spectra for the Perseus, Virgo, and Coma clusters

NASA Technical Reports Server (NTRS)

Kellogg, E.; Baldwin, J. R.; Koch, D.

1975-01-01

Final Uhuru X-ray differential-energy spectra are presented for the Perseus, Virgo, and Coma clusters. Power-law and isothermal bremsstrahlung model spectra with low-energy cutoffs are given, and the energy-dependent Gaunt factor is calculated for the bremsstrahlung. The spectra, which are best fits to the Uhuru data between 2 and 10 keV, are compared with previous observations of these sources in the energy range from 0.1 to 100 keV. The problem of parameter estimation is discussed, error bars with 68% confidence are given for the independently determined slope and cutoff parameters, and the 68% confidence limits are plotted for the fitted spectral functions. The data for Perseus above 20 keV marginally favor the bremsstrahlung fit, those for Virgo between 0.25 and 1.0 keV clearly favor that curve, and those for Coma indicate a low-energy turnover or cutoff. Implications of such a cutoff are briefly discussed.

Dynamics of Tumor Heterogeneity Derived from Clonal Karyotypic Evolution.

PubMed

Laughney, Ashley M; Elizalde, Sergi; Genovese, Giulio; Bakhoum, Samuel F

2015-08-04

Numerical chromosomal instability is a ubiquitous feature of human neoplasms. Due to experimental limitations, fundamental characteristics of karyotypic changes in cancer are poorly understood. Using an experimentally inspired stochastic model, based on the potency and chromosomal distribution of oncogenes and tumor suppressor genes, we show that cancer cells have evolved to exist within a narrow range of chromosome missegregation rates that optimizes phenotypic heterogeneity and clonal survival. Departure from this range reduces clonal fitness and limits subclonal diversity. Mapping of the aneuploid fitness landscape reveals a highly favorable, commonly observed, near-triploid state onto which evolving diploid- and tetraploid-derived populations spontaneously converge, albeit at a much lower fitness cost for the latter. Finally, by analyzing 1,368 chromosomal translocation events in five human cancers, we find that karyotypic evolution also shapes chromosomal translocation patterns by selecting for more oncogenic derivative chromosomes. Thus, chromosomal instability can generate the heterogeneity required for Darwinian tumor evolution. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

New database for improving virtual system “body-dress”

NASA Astrophysics Data System (ADS)

Yan, J. Q.; Zhang, S. C.; Kuzmichev, V. E.; Adolphe, D. C.

2017-10-01

The aim of this exploration is to develop a new database of solid algorithms and relations between the dress fit and the fabric mechanical properties, the pattern block construction for improving the reality of virtual system “body-dress”. In virtual simulation, the system “body-clothing” sometimes shown distinct results with reality, especially when important changes in pattern block and fabrics were involved. In this research, to enhance the simulation process, diverse fit parameters were proposed: bottom height of dress, angle of front center contours, air volume and its distribution between dress and dummy. Measurements were done and optimized by ruler, camera, 3D body scanner image processing software and 3D modeling software. In the meantime, pattern block indexes were measured and fabric properties were tested by KES. Finally, the correlation and linear regression equations between indexes of fabric properties, pattern blocks and fit parameters were investigated. In this manner, new database could be extended in programming modules of virtual design for more realistic results.

[Application of numerical convolution in in vivo/in vitro correlation research].

PubMed

Yue, Peng

2009-01-01

This paper introduced the conception and principle of in vivo/in vitro correlation (IVIVC) and convolution/deconvolution methods, and elucidated in details the convolution strategy and method for calculating the in vivo absorption performance of the pharmaceutics according to the their pharmacokinetic data in Excel, then put the results forward to IVIVC research. Firstly, the pharmacokinetic data ware fitted by mathematical software to make up the lost points. Secondly, the parameters of the optimal fitted input function were defined by trail-and-error method according to the convolution principle in Excel under the hypothesis that all the input functions fit the Weibull functions. Finally, the IVIVC between in vivo input function and the in vitro dissolution was studied. In the examples, not only the application of this method was demonstrated in details but also its simplicity and effectiveness were proved by comparing with the compartment model method and deconvolution method. It showed to be a powerful tool for IVIVC research.

The adventure of carbon stars. Observations and modeling of a set of C-rich AGB stars

NASA Astrophysics Data System (ADS)

Rau, G.; Hron, J.; Paladini, C.; Aringer, B.; Eriksson, K.; Marigo, P.; Nowotny, W.; Grellmann, R.

2017-04-01

Context. Modeling stellar atmospheres is a complex and intriguing task in modern astronomy. A systematic comparison of models with multi-technique observations is the only efficient way to constrain the models. Aims: We intend to perform self-consistent modeling of the atmospheres of six carbon-rich AGB stars (R Lep, R Vol, Y Pav, AQ Sgr, U Hya, and X TrA) with the aim of enlarging the knowledge of the dynamic processes occurring in their atmospheres. Methods: We used VLTI/MIDI interferometric observations, in combination with spectro-photometric data, and compared them with self-consistent, dynamic model atmospheres. Results: We found that the models can reproduce spectral energy distribution (SED) data well at wavelengths longer than 1 μm, and the interferometric observations between 8 μm and 10 μm. Discrepancies observed at wavelengths shorter than 1 μm in the SED, and longer than 10 μm in the visibilities, could be due to a combination of data- and model-related effects. The models best fitting the Miras are significantly extended, and have a prominent shell-like structure. On the contrary, the models best fitting the non-Miras are more compact, showing lower average mass loss. The mass loss is of episodic or multi-periodic nature but causes the visual amplitudes to be notably larger than the observed ones. A number of stellar parameters were derived from the model fitting: TRoss, LRoss, M, C/O, and Ṁ. Our findings agree well with literature values within the uncertainties. TRoss, and LRoss are also in good agreement with the temperature derived from the angular diameter T(θ(V-K)) and the bolometric luminosity from the SED fitting Lbol, except for AQ Sgr. The possible reasons are discussed in the text. Finally, θRoss and θ(V-K) agree with one another better for the Miras than for the non-Miras targets, which is probably connected to the episodic nature of the latter models. We also located the stars in the H-R diagram, comparing them with evolutionary tracks. We found that the main derived properties (L, Teff, C/O ratios and stellar masses) from the model fitting are in good agreement with TP-AGB evolutionary calculations for carbon stars carried out with the COLIBRI code. Based on observations made with ESO telescopes at La Silla Paranal Observatory under program IDs: 090.D-0410, 086.D-899, 187.D-0924, 081.D-0021, 086.D-0899.

The Benchmark Ultracool Subdwarf HD 114762B: A Test of Low-metallicity Atmospheric and Evolutionary Models

NASA Astrophysics Data System (ADS)

Bowler, Brendan P.; Liu, Michael C.; Cushing, Michael C.

2009-12-01

We present a near-infrared spectroscopic study of HD 114762B, the latest-type metal-poor companion discovered to date and the only ultracool subdwarf with a known metallicity, inferred from the primary star to be [Fe/H] = -0.7. We obtained a medium-resolution (R ~ 3800) Keck/OSIRIS 1.18-1.40 μm spectrum and a low-resolution (R ~ 150) Infrared Telescope Facility/SpeX 0.8-2.4 μm spectrum of HD 114762B to test atmospheric and evolutionary models for the first time in this mass-metallicity regime. HD 114762B exhibits spectral features common to both late-type dwarfs and subdwarfs, and we assign it a spectral type of d/sdM9 ± 1. We use a Monte Carlo technique to fit PHOENIX/GAIA synthetic spectra to the observations, accounting for the coarsely gridded nature of the models. Fits to the entire OSIRIS J-band and to the metal-sensitive J-band atomic absorption features (Fe I, K I, and Al I lines) yield model parameters that are most consistent with the metallicity of the primary star and the high surface gravity expected of old late-type objects. The effective temperatures and radii inferred from the model atmosphere fitting broadly agree with those predicted by the evolutionary models of Chabrier & Baraffe, and the model color-absolute magnitude relations accurately predict the metallicity of HD 114762B. We conclude that current low-mass, mildly metal-poor atmospheric and evolutionary models are mutually consistent for spectral fits to medium-resolution J-band spectra of HD 114762B, but are inconsistent for fits to low-resolution near-infrared spectra of mild subdwarfs. Finally, we develop a technique for estimating distances to ultracool subdwarfs based on a single near-infrared spectrum. We show that this "spectroscopic parallax" method enables distance estimates accurate to lsim10% of parallactic distances for ultracool subdwarfs near the hydrogen burning minimum mass. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

Integrating local pastoral knowledge, participatory mapping, and species distribution modeling for risk assessment of invasive rubber vine (Cryptostegia grandiflora) in Ethiopia’s Afar region

USGS Publications Warehouse

Luizza, Matthew; Wakie, Tewodros; Evangelista, Paul; Jarnevich, Catherine S.

2016-01-01

The threats posed by invasive plants span ecosystems and economies worldwide. Local knowledge of biological invasions has proven beneficial for invasive species research, but to date no work has integrated this knowledge with species distribution modeling for invasion risk assessments. In this study, we integrated pastoral knowledge with Maxent modeling to assess the suitable habitat and potential impacts of invasive Cryptostegia grandiflora Robx. Ex R.Br. (rubber vine) in Ethiopia’s Afar region. We conducted focus groups with seven villages across the Amibara and Awash-Fentale districts. Pastoral knowledge revealed the growing threat of rubber vine, which to date has received limited attention in Ethiopia, and whose presence in Afar was previously unknown to our team. Rubber vine occurrence points were collected in the field with pastoralists and processed in Maxent with MODIS-derived vegetation indices, topographic data, and anthropogenic variables. We tested model fit using a jackknife procedure and validated the final model with an independent occurrence data set collected through participatory mapping activities with pastoralists. A Multivariate Environmental Similarity Surface analysis revealed areas with novel environmental conditions for future targeted surveys. Model performance was evaluated using area under the receiver-operating characteristic curve (AUC) and showed good fit across the jackknife models (average AUC = 0.80) and the final model (test AUC = 0.96). Our results reveal the growing threat rubber vine poses to Afar, with suitable habitat extending downstream of its current known location in the middle Awash River basin. Local pastoral knowledge provided important context for its rapid expansion due to acute changes in seasonality and habitat alteration, in addition to threats posed to numerous endemic tree species that provide critical provisioning ecosystem services. This work demonstrates the utility of integrating local ecological knowledge with species distribution modeling for early detection and targeted surveying of recently established invasive species.

Application of 2-D travel-time inversion of seismic refraction data to the mid-continent rift beneath Lake Superior

USGS Publications Warehouse

Lutter, William J.; Tréhu, Anne M.; Nowack, Robert L.

1993-01-01

The inversion technique of Nowack and Lutter (1988a) and Lutter et al. (1990) has been applied to first arrival seismic refraction data collected along Line A of the 1986 Lake Superior GLIMPCE experiment, permitting comparison of the inversion image with an independently derived forward model (Trehu et al., 1991; Shay and Trehu, in press). For this study, the inversion method was expanded to allow variable grid spacing for the bicubic spline parameterization of velocity. The variable grid spacing improved model delineation and data fit by permitting model parameters to be clustered at features of interest. Over 800 first-arrival travel-times were fit with a final RMS error of 0.045 s. The inversion model images a low velocity central graben and smaller flanking half-grabens of the Midcontinent Rift, and higher velocity regions (+0.5 to +0.75 km/s) associated with the Isle Royale and Keweenaw faults, which bound the central graben. Although the forward modeling interpretation gives finer details associated with the near surface expression of the two faults because of the inclusion of secondary reflections and refractions that were not included in the inversion, the inversion model reproduces the primary features of the forward model.

Model for macroevolutionary dynamics.

PubMed

Maruvka, Yosef E; Shnerb, Nadav M; Kessler, David A; Ricklefs, Robert E

2013-07-02

The highly skewed distribution of species among genera, although challenging to macroevolutionists, provides an opportunity to understand the dynamics of diversification, including species formation, extinction, and morphological evolution. Early models were based on either the work by Yule [Yule GU (1925) Philos Trans R Soc Lond B Biol Sci 213:21-87], which neglects extinction, or a simple birth-death (speciation-extinction) process. Here, we extend the more recent development of a generic, neutral speciation-extinction (of species)-origination (of genera; SEO) model for macroevolutionary dynamics of taxon diversification. Simulations show that deviations from the homogeneity assumptions in the model can be detected in species-per-genus distributions. The SEO model fits observed species-per-genus distributions well for class-to-kingdom-sized taxonomic groups. The model's predictions for the appearance times (the time of the first existing species) of the taxonomic groups also approximately match estimates based on molecular inference and fossil records. Unlike estimates based on analyses of phylogenetic reconstruction, fitted extinction rates for large clades are close to speciation rates, consistent with high rates of species turnover and the relatively slow change in diversity observed in the fossil record. Finally, the SEO model generally supports the consistency of generic boundaries based on morphological differences between species and provides a comparator for rates of lineage splitting and morphological evolution.

Novel Virtual User Models of Mild Cognitive Impairment for Simulating Dementia

PubMed Central

Segkouli, Sofia; Tzovaras, Dimitrios; Tsakiris, Thanos; Tsolaki, Magda; Karagiannidis, Charalampos

2015-01-01

Virtual user modeling research has attempted to address critical issues of human-computer interaction (HCI) such as usability and utility through a large number of analytic, usability-oriented approaches as cognitive models in order to provide users with experiences fitting to their specific needs. However, there is demand for more specific modules embodied in cognitive architecture that will detect abnormal cognitive decline across new synthetic task environments. Also, accessibility evaluation of graphical user interfaces (GUIs) requires considerable effort for enhancing ICT products accessibility for older adults. The main aim of this study is to develop and test virtual user models (VUM) simulating mild cognitive impairment (MCI) through novel specific modules, embodied at cognitive models and defined by estimations of cognitive parameters. Well-established MCI detection tests assessed users' cognition, elaborated their ability to perform multitasks, and monitored the performance of infotainment related tasks to provide more accurate simulation results on existing conceptual frameworks and enhanced predictive validity in interfaces' design supported by increased tasks' complexity to capture a more detailed profile of users' capabilities and limitations. The final outcome is a more robust cognitive prediction model, accurately fitted to human data to be used for more reliable interfaces' evaluation through simulation on the basis of virtual models of MCI users. PMID:26339282

Proton exchange membrane fuel cell model for aging predictions: Simulated equivalent active surface area loss and comparisons with durability tests

NASA Astrophysics Data System (ADS)

Robin, C.; Gérard, M.; Quinaud, M.; d'Arbigny, J.; Bultel, Y.

2016-09-01

The prediction of Proton Exchange Membrane Fuel Cell (PEMFC) lifetime is one of the major challenges to optimize both material properties and dynamic control of the fuel cell system. In this study, by a multiscale modeling approach, a mechanistic catalyst dissolution model is coupled to a dynamic PEMFC cell model to predict the performance loss of the PEMFC. Results are compared to two 2000-h experimental aging tests. More precisely, an original approach is introduced to estimate the loss of an equivalent active surface area during an aging test. Indeed, when the computed Electrochemical Catalyst Surface Area profile is fitted on the experimental measures from Cyclic Voltammetry, the computed performance loss of the PEMFC is underestimated. To be able to predict the performance loss measured by polarization curves during the aging test, an equivalent active surface area is obtained by a model inversion. This methodology enables to successfully find back the experimental cell voltage decay during time. The model parameters are fitted from the polarization curves so that they include the global degradation. Moreover, the model captures the aging heterogeneities along the surface of the cell observed experimentally. Finally, a second 2000-h durability test in dynamic operating conditions validates the approach.

The Population Tracking Model: A Simple, Scalable Statistical Model for Neural Population Data

PubMed Central

O'Donnell, Cian; alves, J. Tiago Gonç; Whiteley, Nick; Portera-Cailliau, Carlos; Sejnowski, Terrence J.

2017-01-01

Our understanding of neural population coding has been limited by a lack of analysis methods to characterize spiking data from large populations. The biggest challenge comes from the fact that the number of possible network activity patterns scales exponentially with the number of neurons recorded (∼2Neurons). Here we introduce a new statistical method for characterizing neural population activity that requires semi-independent fitting of only as many parameters as the square of the number of neurons, requiring drastically smaller data sets and minimal computation time. The model works by matching the population rate (the number of neurons synchronously active) and the probability that each individual neuron fires given the population rate. We found that this model can accurately fit synthetic data from up to 1000 neurons. We also found that the model could rapidly decode visual stimuli from neural population data from macaque primary visual cortex about 65 ms after stimulus onset. Finally, we used the model to estimate the entropy of neural population activity in developing mouse somatosensory cortex and, surprisingly, found that it first increases, and then decreases during development. This statistical model opens new options for interrogating neural population data and can bolster the use of modern large-scale in vivo Ca2+ and voltage imaging tools. PMID:27870612

Study of Water Absorption in Raffia vinifera Fibres from Bandjoun, Cameroon

PubMed Central

Sikame Tagne, N. R.; Njeugna, E.; Fogue, M.; Drean, J.-Y.; Nzeukou, A.; Fokwa, D.

2014-01-01

The study is focused on the water diffusion phenomenon through the Raffia vinifera fibre from the stem. The knowledge on the behavior of those fibres in presence of liquid during the realization of biocomposite, is necessary. The parameters like percentage of water gain at the point of saturation, modelling of the kinetic of water absorption, and the effective diffusion coefficient were the main objectives. Along a stem of raffia, twelve zones of sampling were defined. From Fick's 2nd law of diffusion, a new model was proposed and evaluated compared to four other models at a constant temperature of 23°C. From the proposed model, the effective diffusion coefficient was deduced. The percentage of water gain was in the range of 303–662%. The proposed model fitted better to the experimental data. The estimated diffusion coefficient was evaluated during the initial phase and at the final phase. In any cross section located along the stem of Raffia vinifera, it was found that the effective diffusion coefficient increases from the periphery to the centre during the initial and final phases. PMID:24592199

Theoretical investigation of microstructure evolution and deformation of zirconium under neutron irradiation

DOE PAGES

Barashev, A. V.; Golubov, S. I.; Stoller, R. E.

2015-06-01

We studied the radiation growth of zirconium using a reaction–diffusion model which takes into account intra-cascade clustering of self-interstitial atoms and one-dimensional diffusion of interstitial clusters. The observed dose dependence of strain rates is accounted for by accumulation of sessile dislocation loops during irradiation. Moreover, the computational model developed and fitted to available experimental data is applied to study deformation of Zr single crystals under irradiation up to hundred dpa. Finally, the effect of cold work and the reasons for negative prismatic strains and co-existence of vacancy and interstitial loops are elucidated.

Advancing Consumer Product Composition and Chemical ...

EPA Pesticide Factsheets

This presentation describes EPA efforts to collect, model, and measure publically available consumer product data for use in exposure assessment. The development of the ORD Chemicals and Products database will be described, as will machine-learning based models for predicting chemical function. Finally, the talk describes new mass spectrometry-based methods for measuring chemicals in formulation and articles. This presentation is an invited talk to the ICCA-LRI workshop "Fit-For-Purpose Exposure Assessments For Risk-Based Decision Making". The talk will share EPA efforts to characterize the components of consumer products for use in exposure assessment with the international exposure science community.

Reports of investigations on: Derivation of an infinite-dilution activity coefficient model and application to two-component vapor/liquid equilibria data: Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roper, V.P.; Kobayashi, R.

1988-02-01

Infinite-dilution fugacity coefficients were obtained for the system fluorene/phenanthrene at thirteen temperatures by fitting total pressure across the entire mole fraction range by a computer routine. A thermodynamically consistent routine, that allowed for both positive and negative pressure deviations from the ideal values, was used to correlate data over the full mole fraction range from 0 to 1. The four-suffix Margules activity coefficient model without modification essentially served this purpose since total pressures and total pressure derivatives with respect to mole fraction were negligible compared to pressure measurement precision. The water/ethanol system and binary systems comprised of aniline, chlorobenzene, acetonitrilemore » and other polar compounds were fit for total pressure across the entire mole fraction range for binary Vapor-Liquid-Equilbria (VLE) using the rigorous, thermodynamically consistent Gibbs-Duhem Relation derived by Ibl and Dodge. Data correlation was performed using a computer least squares procedure. Infinite-dilution fugacity coefficients were obtained using a modified Margules activity coefficient model.« less

Uncertainty Analysis in 3D Equilibrium Reconstruction

DOE PAGES

Cianciosa, Mark R.; Hanson, James D.; Maurer, David A.

2018-02-21

Reconstruction is an inverse process where a parameter space is searched to locate a set of parameters with the highest probability of describing experimental observations. Due to systematic errors and uncertainty in experimental measurements, this optimal set of parameters will contain some associated uncertainty. This uncertainty in the optimal parameters leads to uncertainty in models derived using those parameters. V3FIT is a three-dimensional (3D) equilibrium reconstruction code that propagates uncertainty from the input signals, to the reconstructed parameters, and to the final model. Here in this paper, we describe the methods used to propagate uncertainty in V3FIT. Using the resultsmore » of whole shot 3D equilibrium reconstruction of the Compact Toroidal Hybrid, this propagated uncertainty is validated against the random variation in the resulting parameters. Two different model parameterizations demonstrate how the uncertainty propagation can indicate the quality of a reconstruction. As a proxy for random sampling, the whole shot reconstruction results in a time interval that will be used to validate the propagated uncertainty from a single time slice.« less

Uncertainty Analysis in 3D Equilibrium Reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cianciosa, Mark R.; Hanson, James D.; Maurer, David A.

Reconstruction is an inverse process where a parameter space is searched to locate a set of parameters with the highest probability of describing experimental observations. Due to systematic errors and uncertainty in experimental measurements, this optimal set of parameters will contain some associated uncertainty. This uncertainty in the optimal parameters leads to uncertainty in models derived using those parameters. V3FIT is a three-dimensional (3D) equilibrium reconstruction code that propagates uncertainty from the input signals, to the reconstructed parameters, and to the final model. Here in this paper, we describe the methods used to propagate uncertainty in V3FIT. Using the resultsmore » of whole shot 3D equilibrium reconstruction of the Compact Toroidal Hybrid, this propagated uncertainty is validated against the random variation in the resulting parameters. Two different model parameterizations demonstrate how the uncertainty propagation can indicate the quality of a reconstruction. As a proxy for random sampling, the whole shot reconstruction results in a time interval that will be used to validate the propagated uncertainty from a single time slice.« less

Life's attractors : understanding developmental systems through reverse engineering and in silico evolution.

PubMed

Jaeger, Johannes; Crombach, Anton

2012-01-01

We propose an approach to evolutionary systems biology which is based on reverse engineering of gene regulatory networks and in silico evolutionary simulations. We infer regulatory parameters for gene networks by fitting computational models to quantitative expression data. This allows us to characterize the regulatory structure and dynamical repertoire of evolving gene regulatory networks with a reasonable amount of experimental and computational effort. We use the resulting network models to identify those regulatory interactions that are conserved, and those that have diverged between different species. Moreover, we use the models obtained by data fitting as starting points for simulations of evolutionary transitions between species. These simulations enable us to investigate whether such transitions are random, or whether they show stereotypical series of regulatory changes which depend on the structure and dynamical repertoire of an evolving network. Finally, we present a case study-the gap gene network in dipterans (flies, midges, and mosquitoes)-to illustrate the practical application of the proposed methodology, and to highlight the kind of biological insights that can be gained by this approach.

An autoregressive integrated moving average model for short-term prediction of hepatitis C virus seropositivity among male volunteer blood donors in Karachi, Pakistan

PubMed Central

Akhtar, Saeed; Rozi, Shafquat

2009-01-01

AIM: To identify the stochastic autoregressive integrated moving average (ARIMA) model for short term forecasting of hepatitis C virus (HCV) seropositivity among volunteer blood donors in Karachi, Pakistan. METHODS: Ninety-six months (1998-2005) data on HCV seropositive cases (1000-1 × month-1) among male volunteer blood donors tested at four major blood banks in Karachi, Pakistan were subjected to ARIMA modeling. Subsequently, a fitted ARIMA model was used to forecast HCV seropositive donors for 91-96 mo to contrast with observed series of the same months. To assess the forecast accuracy, the mean absolute error rate (%) between the observed and predicted HCV seroprevalence was calculated. Finally, a fitted ARIMA model was used for short-term forecasts beyond the observed series. RESULTS: The goodness-of-fit test of the optimum ARIMA (2,1,7) model showed non-significant autocorrelations in the residuals of the model. The forecasts by ARIMA for 91-96 mo closely followed the pattern of observed series for the same months, with mean monthly absolute forecast errors (%) over 6 mo of 6.5%. The short-term forecasts beyond the observed series adequately captured the pattern in the data and showed increasing tendency of HCV seropositivity with a mean ± SD HCV seroprevalence (1000-1 × month-1) of 24.3 ± 1.4 over the forecast interval. CONCLUSION: To curtail HCV spread, public health authorities need to educate communities and health care providers about HCV transmission routes based on known HCV epidemiology in Pakistan and its neighboring countries. Future research may focus on factors associated with hyperendemic levels of HCV infection. PMID:19340903

Developing and establishing the validity and reliability of the perceptions toward Aviation Safety Action Program (ASAP) and Line Operations Safety Audit (LOSA) questionnaires

NASA Astrophysics Data System (ADS)

Steckel, Richard J.

Aviation Safety Action Program (ASAP) and Line Operations Safety Audits (LOSA) are voluntary safety reporting programs developed by the Federal Aviation Administration (FAA) to assist air carriers in discovering and fixing threats, errors and undesired aircraft states during normal flights that could result in a serious or fatal accident. These programs depend on voluntary participation of and reporting by air carrier pilots to be successful. The purpose of the study was to develop and validate a measurement scale to measure U.S. air carrier pilots' perceived benefits and/or barriers to participating in ASAP and LOSA programs. Data from these surveys could be used to make changes to or correct pilot misperceptions of these programs to improve participation and the flow of data. ASAP and LOSA a priori models were developed based on previous research in aviation and healthcare. Sixty thousand ASAP and LOSA paper surveys were sent to 60,000 current U.S. air carrier pilots selected at random from an FAA database of pilot certificates. Two thousand usable ASAP and 1,970 usable LOSA surveys were returned and analyzed using Confirmatory Factor Analysis. Analysis of the data using confirmatory actor analysis and model generation resulted in a five factor ASAP model (Ease of use, Value, Improve, Trust and Risk) and a five factor LOSA model (Value, Improve, Program Trust, Risk and Management Trust). ASAP and LOSA data were not normally distributed, so bootstrapping was used. While both final models exhibited acceptable fit with approximate fit indices, the exact fit hypothesis and the Bollen-Stine p value indicated possible model mis-specification for both ASAP and LOSA models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guiriec, S.; Kouveliotou, C.; Hartmann, D. H.

The origin of prompt emission from gamma-ray bursts (GRBs) remains to be an open question. Correlated prompt optical and γ -ray emission observed in a handful of GRBs strongly suggests a common emission region, but failure to adequately fit the broadband GRB spectrum prompted the hypothesis of different emission mechanisms for the low- and high-energy radiations. We demonstrate that our multi-component model for GRB γ -ray prompt emission provides an excellent fit to GRB 110205A from optical to γ -ray energies. Our results show that the optical and highest γ -ray emissions have the same spatial and spectral origin, whichmore » is different from the bulk of the X- and softest γ -ray radiation. Finally, our accurate redshift estimate for GRB 110205A demonstrates promise for using GRBs as cosmological standard candles.« less

Gamma-ray burst: evolution of the fireball and afterglow

NASA Astrophysics Data System (ADS)

Huang, W. G.; Yang, P. B.; Lu, Y.

2001-02-01

After the main part of a GRB, its fireball continuously expands. With the hydrodynamic equations for the postburst fireball, the authors study the distribution of electrons which changes with time. The equations are solved numerically and the relations of the flux density of Optical afterglow in R band as well as the X-ray afterglow with time have been obtained. The results fit the observations quite well. Finally the shortcomings of the fireball + blast model are discussed.

A novel method for improving the accuracy of coordinate transformation in multiple measurement systems

NASA Astrophysics Data System (ADS)

Liu, W. L.; Li, Y. W.

2017-09-01

Large-scale dimensional metrology usually requires a combination of multiple measurement systems, such as laser tracking, total station, laser scanning, coordinate measuring arm and video photogrammetry, etc. Often, the results from different measurement systems must be combined to provide useful results. The coordinate transformation is used to unify coordinate frames in combination; however, coordinate transformation uncertainties directly affect the accuracy of the final measurement results. In this paper, a novel method is proposed for improving the accuracy of coordinate transformation, combining the advantages of the best-fit least-square and radial basis function (RBF) neural networks. First of all, the configuration of coordinate transformation is introduced and a transformation matrix containing seven variables is obtained. Second, the 3D uncertainty of the transformation model and the residual error variable vector are established based on the best-fit least-square. Finally, in order to optimize the uncertainty of the developed seven-variable transformation model, we used the RBF neural network to identify the uncertainty of the dynamic, and unstructured, owing to its great ability to approximate any nonlinear function to the designed accuracy. Intensive experimental studies were conducted to check the validity of the theoretical results. The results show that the mean error of coordinate transformation decreased from 0.078 mm to 0.054 mm after using this method in contrast with the GUM method.

Physiological effects of diet mixing on consumer fitness: a meta-analysis.

PubMed

Lefcheck, Jonathan S; Whalen, Matthew A; Davenport, Theresa M; Stone, Joshua P; Duffy, J Emmett

2013-03-01

The degree of dietary generalism among consumers has important consequences for population, community, and ecosystem processes, yet the effects on consumer fitness of mixing food types have not been examined comprehensively. We conducted a meta-analysis of 161 peer-reviewed studies reporting 493 experimental manipulations of prey diversity to test whether diet mixing enhances consumer fitness based on the intrinsic nutritional quality of foods and consumer physiology. Averaged across studies, mixed diets conferred significantly higher fitness than the average of single-species diets, but not the best single prey species. More than half of individual experiments, however, showed maximal growth and reproduction on mixed diets, consistent with the predicted benefits of a balanced diet. Mixed diets including chemically defended prey were no better than the average prey type, opposing the prediction that a diverse diet dilutes toxins. Finally, mixed-model analysis showed that the effect of diet mixing was stronger for herbivores than for higher trophic levels. The generally weak evidence for the nutritional benefits of diet mixing in these primarily laboratory experiments suggests that diet generalism is not strongly favored by the inherent physiological benefits of mixing food types, but is more likely driven by ecological and environmental influences on consumer foraging.

The lytic transglycosylase MltB connects membrane homeostasis and in vivo fitness of Acinetobacter baumannii.

PubMed

Crépin, Sébastien; Ottosen, Elizabeth N; Peters, Katharina; Smith, Sara N; Himpsl, Stephanie D; Vollmer, Waldemar; Mobley, Harry L T

2018-06-08

Acinetobacter baumannii has emerged as a leading nosocomial pathogen, infecting a wide range of anatomic sites including the respiratory tract and the bloodstream. In addition to being multi-drug resistant, little is known about the molecular basis of A. baumannii pathogenesis. To better understand A. baumannii virulence, a combination of a transposon-sequencing (TraDIS) screen and the neutropenic mouse model of bacteremia was used to identify the full set of fitness genes required during bloodstream infection. The lytic transglycosylase MltB was identified as a critical fitness factor. MltB cleaves the MurNAc-GlcNAc bond of peptidoglycan, which leads to cell wall remodeling. Here we show that MltB is part of a complex network connecting resistance to stresses, membrane homeostasis, biogenesis of pili and in vivo fitness. Indeed, inactivation of mltB not only impaired resistance to serum complement, cationic antimicrobial peptides and oxygen species, but also altered the cell envelope integrity, activated the envelope stress response, drastically reduced the number of pili at the cell surface and finally, significantly decreased colonization of both the bloodstream and the respiratory tract. This article is protected by copyright. All rights reserved. © 2018 John Wiley & Sons Ltd.

Links between Natural Variation in the Microbiome and Host Fitness in Wild Mammals.

PubMed

Suzuki, Taichi A

2017-10-01

Recent studies in model organisms have shown that compositional variation in the microbiome can affect a variety of host phenotypes including those related to digestion, development, immunity, and behavior. Natural variation in the microbiome within and between natural populations and species may also affect host phenotypes and thus fitness in the wild. Here, I review recent evidence that compositional variation in the microbiome may affect host phenotypes and fitness in wild mammals. Studies over the last decade indicate that natural variation in the mammalian microbiome may be important in the assistance of energy uptake from different diet types, detoxification of plant secondary compounds, protection from pathogens, chemical communication, and behavior. I discuss the importance of combining both field observations and manipulative experiments in a single system to fully characterize the functions and fitness effects of the microbiome. Finally, I discuss the evolutionary consequences of mammal-microbiome associations by proposing a framework to test how natural selection on hosts is mediated by the microbiome. © The Author 2017. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

The 1.5 Ms Observing Campaign on IRAS 13224-3809: X-ray Spectral Analysis I.

NASA Astrophysics Data System (ADS)

Jiang, J.; Parker, M. L.; Fabian, A. C.; Alston, W. N.; Buisson, D. J. K.; Cackett, E. M.; Chiang, C.-Y.; Dauser, T.; Gallo, L. C.; García, J. A.; Harrison, F. A.; Lohfink, A. M.; De Marco, B.; Kara, E.; Miller, J. M.; Miniutti, G.; Pinto, C.; Walton, D. J.; Wilkins, D. R.

2018-03-01

We present a detailed spectral analysis of the recent 1.5 Ms XMM-Newton observing campaign on the narrow line Seyfert 1 galaxy IRAS 13224-3809, taken simultaneously with 500 ks of NuSTAR data. The X-ray lightcurve shows three flux peaks, registering at about 100 times the minimum flux seen during the campaign, and rapid variability with a time scale of kiloseconds. The spectra are well fit with a primary powerlaw continuum, two relativistic-blurred reflection components from the inner accretion disk with very high iron abundance, and a simple blackbody-shaped model for the remaining soft excess. The spectral variability is dominated by the power law continuum from a corona region within a few gravitational radii from the black hole. Additionally, blueshifted Ne X, Mg XII, Si XIV and S XVI absorption lines are identified in the stacked low-flux spectrum, confirming the presence of a highly ionized outflow with velocity up to v = 0.263 and 0.229 c. We fit the absorption features with xstar models and find a relatively constant velocity outflow through the whole observation. Finally, we replace the bbody and supersolar abundance reflection models by fitting the soft excess successfully with the extended reflection model relxillD, which allows for higher densities than the standard relxill model. This returns a disk electron density ne > 1018.7 cm-3 and lowers the iron abundance from Z_Fe=24^{+3}_{-4}Z_⊙ with ne ≡ 1015 cm-3 to Z_Fe=6.6^{+0.8}_{-2.1}Z_⊙.

Anomalous diffusion and dynamics of fluorescence recovery after photobleaching in the random-comb model

NASA Astrophysics Data System (ADS)

Yuste, S. B.; Abad, E.; Baumgaertner, A.

2016-07-01

We address the problem of diffusion on a comb whose teeth display varying lengths. Specifically, the length ℓ of each tooth is drawn from a probability distribution displaying power law behavior at large ℓ ,P (ℓ ) ˜ℓ-(1 +α ) (α >0 ). To start with, we focus on the computation of the anomalous diffusion coefficient for the subdiffusive motion along the backbone. This quantity is subsequently used as an input to compute concentration recovery curves mimicking fluorescence recovery after photobleaching experiments in comblike geometries such as spiny dendrites. Our method is based on the mean-field description provided by the well-tested continuous time random-walk approach for the random-comb model, and the obtained analytical result for the diffusion coefficient is confirmed by numerical simulations of a random walk with finite steps in time and space along the backbone and the teeth. We subsequently incorporate retardation effects arising from binding-unbinding kinetics into our model and obtain a scaling law characterizing the corresponding change in the diffusion coefficient. Finally, we show that recovery curves obtained with the help of the analytical expression for the anomalous diffusion coefficient cannot be fitted perfectly by a model based on scaled Brownian motion, i.e., a standard diffusion equation with a time-dependent diffusion coefficient. However, differences between the exact curves and such fits are small, thereby providing justification for the practical use of models relying on scaled Brownian motion as a fitting procedure for recovery curves arising from particle diffusion in comblike systems.

The use of random forests in modelling short-term air pollution effects based on traffic and meteorological conditions: A case study in Wrocław.

PubMed

Kamińska, Joanna A

2018-07-01

Random forests, an advanced data mining method, are used here to model the regression relationships between concentrations of the pollutants NO 2 , NO x and PM 2.5 , and nine variables describing meteorological conditions, temporal conditions and traffic flow. The study was based on hourly values of wind speed, wind direction, temperature, air pressure and relative humidity, temporal variables, and finally traffic flow, in the two years 2015 and 2016. An air quality measurement station was selected on a main road, located a short distance (40 m) from a large intersection equipped with a traffic flow measurement system. Nine different time subsets were defined, based among other things on the climatic conditions in Wrocław. An analysis was made of the fit of models created for those subsets, and of the importance of the predictors. Both the fit and the importance of particular predictors were found to be dependent on season. The best fit was obtained for models created for the six-month warm season (April-September) and for the summer season (June-August). The most important explanatory variable in the models of concentrations of nitrogen oxides was traffic flow, while in the case of PM 2.5 the most important were meteorological conditions, in particular temperature, wind speed and wind direction. Temporal variables (except for month in the case of PM 2.5 ) were found to have no significant effect on the concentrations of the studied pollutants. Copyright © 2018 Elsevier Ltd. All rights reserved.

The 1.5 Ms observing campaign on IRAS 13224-3809 - I. X-ray spectral analysis

NASA Astrophysics Data System (ADS)

Jiang, J.; Parker, M. L.; Fabian, A. C.; Alston, W. N.; Buisson, D. J. K.; Cackett, E. M.; Chiang, C.-Y.; Dauser, T.; Gallo, L. C.; García, J. A.; Harrison, F. A.; Lohfink, A. M.; De Marco, B.; Kara, E.; Miller, J. M.; Miniutti, G.; Pinto, C.; Walton, D. J.; Wilkins, D. R.

2018-07-01

We present a detailed spectral analysis of the recent 1.5 Ms XMM-Newton observing campaign on the narrow-line Seyfert 1 galaxy IRAS 13224-3809, taken simultaneously with 500 ks of NuSTAR data. The X-ray light curve shows three flux peaks, registering at about 100 times the minimum flux seen during the campaign, and rapid variability with a time-scale of kiloseconds. The spectra are well fit with a primary power-law continuum, two relativistic-blurred reflection components from the inner accretion disc with very high iron abundance, and a simple blackbody-shaped model for the remaining soft excess. The spectral variability is dominated by the power-law continuum from a corona region within a few gravitational radii from the black hole. Additionally, blueshifted Ne X, Mg XII, Si XIV, and S XVI absorption lines are identified in the stacked low-flux spectrum, confirming the presence of a highly ionized outflow with velocity up to v = 0.267 and 0.225 c. We fit the absorption features with xstar models and find a relatively constant velocity outflow through the whole observation. Finally, we replace the bbody and supersolar abundance reflection models by fitting the soft excess successfully with the extended reflection model relxillD, which allows for higher densities than the standard relxill model. This returns a disc electron density ne > 1018.7 cm-3 and lowers the iron abundance from Z_Fe = 24^{+3}_{-4} Z_{⊙} with ne ≡ 1015 cm-3 to Z_Fe = 6.6^{+0.8}_{-2.1} Z_{⊙}.

Factors that contribute to the body image concern of female college students.

PubMed

Silva, Wanderson Roberto; Dias, Juliana Chioda Ribeiro; Maroco, João; Campos, Juliana Alvares Duarte Bonini

2015-01-01

To estimate the contribution of sociodemographic and labor variables and body mass index to body image concern. In order to estimate body image concern, the Body Shape Questionnaire (BSQ) and the Weight Concerns Scale (WCS) were applied. A confirmatory factor analysis of scales was carried out. The reason χ2 by degree of freedom ratio (χ2/df ), Comparative Fit Index (CFI), Normed Fit Index (NFI), and root mean square error of approximation (RMSEA) were used. Convergent validity was assessed through the average variance extracted and composed reliability and the internal consistency through standardized Cronbach's alpha coefficient (α). A structural model was developed, and the body image concern was the second-order main construct. The model appropriation was evaluated based on the goodness-of-fit indices. The z test was used to estimate the significance of trajectories (β) using a 5% significance level. Totally, 595 female college students participated in the study, with a mean age of 20.42 ± 2.44 years. The entire model, with the inclusion of all independent variables, showed unsatisfactory adjustment and was refined. The final model presented a satisfactory adjustment (χ2/df = 5.75; CFI = 0.87; NFI = 0.85; RMSEA = 0.09) with inclusion of medication use because of studies (β = 0.08; p = 0.04), academic performance (β = 0.09; p = 0.02), economic class (β = 0.08; p = 0.03), and body mass index (β = 0.44; p < 0.001). This model explained 22% of body image concern. Medication use due to studies, academic performance, economic class and body mass index significantly contribute to body image concern.

Exploring relations among mindfulness facets and various meditation practices: Do they work in different ways?

PubMed

Cebolla, Ausiàs; Campos, Daniel; Galiana, Laura; Oliver, Amparo; Tomás, Jose Manuel; Feliu-Soler, Albert; Soler, Joaquim; García-Campayo, Javier; Demarzo, Marcelo; Baños, Rosa María

2017-03-01

Several meditation practices are associated with mindfulness-based interventions but little is known about their specific effects on the development of different mindfulness facets. This study aimed to assess the relations among different practice variables, types of meditation, and mindfulness facets. The final sample was composed of 185 participants who completed an on-line survey, including information on the frequency and duration of each meditation practice, lifetime practice, and the Five Facet Mindfulness Questionnaire. A Multiple Indicators Multiple Causes structural model was specified, estimated, and tested. Results showed that the Model's overall fit was adequate: χ 2 (1045)=1542.800 (p<0.001), CFI=0.902, RMSEA=0.042. Results revealed that mindfulness facets were uniquely related to the different variables and types of meditation. Our findings showed the importance of specific practices in promoting mindfulness, compared to compassion and informal practices, and they pointed out which one fits each mindfulness facet better. Copyright © 2017 Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hormain, Laureline; Monnerville, Maurice, E-mail: maurice.monnerville@univ-lille1.fr; Toubin, Céline

The chlorine/water interface is of crucial importance in the context of atmospheric chemistry. Modeling the structure and dynamics at this interface requires an accurate description of the interaction potential energy surfaces. We propose here an analytical intermolecular potential that reproduces the interaction between the Cl{sub 2} molecule and a water molecule. Our functional form is fitted to a set of high level ab initio data using the coupled-cluster single double (triple)/aug-cc-p-VTZ level of electronic structure theory for the Cl{sub 2} − H{sub 2}O complex. The potential fitted to reproduce the three minima structures of 1:1 complex is validated by themore » comparison of ab initio results of Cl{sub 2} interacting with an increasing number of water molecules. Finally, the model potential is used to study the physisorption of Cl{sub 2} on a perfectly ordered hexagonal ice slab. The calculated adsorption energy, in the range 0.27 eV, shows a good agreement with previous experimental results.« less

Autonomous celestial navigation based on Earth ultraviolet radiance and fast gradient statistic feature extraction

NASA Astrophysics Data System (ADS)

Lu, Shan; Zhang, Hanmo

2016-01-01

To meet the requirement of autonomous orbit determination, this paper proposes a fast curve fitting method based on earth ultraviolet features to obtain accurate earth vector direction, in order to achieve the high precision autonomous navigation. Firstly, combining the stable characters of earth ultraviolet radiance and the use of transmission model software of atmospheric radiation, the paper simulates earth ultraviolet radiation model on different time and chooses the proper observation band. Then the fast improved edge extracting method combined Sobel operator and local binary pattern (LBP) is utilized, which can both eliminate noises efficiently and extract earth ultraviolet limb features accurately. And earth's centroid locations on simulated images are estimated via the least square fitting method using part of the limb edges. Taken advantage of the estimated earth vector direction and earth distance, Extended Kalman Filter (EKF) is applied to realize the autonomous navigation finally. Experiment results indicate the proposed method can achieve a sub-pixel earth centroid location estimation and extremely enhance autonomous celestial navigation precision.

Transmission-clearance trade-offs indicate that dengue virulence evolution depends on epidemiological context.

PubMed

Ben-Shachar, Rotem; Koelle, Katia

2018-06-15

An extensive body of theory addresses the topic of pathogen virulence evolution, yet few studies have empirically demonstrated the presence of fitness trade-offs that would select for intermediate virulence. Here we show the presence of transmission-clearance trade-offs in dengue virus using viremia measurements. By fitting a within-host model to these data, we further find that the interaction between dengue and the host immune response can account for the observed trade-offs. Finally, we consider dengue virulence evolution when selection acts on the virus's production rate. By combining within-host model simulations with empirical findings on how host viral load affects human-to-mosquito transmission success, we show that the virus's transmission potential is maximized at production rates associated with intermediate virulence and that the optimal production rate critically depends on dengue's epidemiological context. These results indicate that long-term changes in dengue's global distribution impact the invasion and spread of virulent dengue virus genotypes.

Correlations between Physical Fitness Tests and Performance of Military Tasks: A Systematic Review and Meta-Analyses

DTIC Science & Technology

2014-06-30

U.S. Army Public Health Command Correlations between Physical Fitness Tests and Performance of Military Tasks: A Systematic Review and Meta...30 JUN 2014 2. REPORT TYPE Final 3. DATES COVERE D 4. TITLE AN D SUBTITLE Correlations between Physical Fitness Tests and Performance of... Physical Fitness Test (APFT) and ensure a future test is associated with Soldiers’ performance of common physical job requirements, the USAPHC applied

Improving the efficiency of the cardiac catheterization laboratories through understanding the stochastic behavior of the scheduled procedures.

PubMed

Stepaniak, Pieter S; Soliman Hamad, Mohamed A; Dekker, Lukas R C; Koolen, Jacques J

2014-01-01

In this study, we sought to analyze the stochastic behavior of Catherization Laboratories (Cath Labs) procedures in our institution. Statistical models may help to improve estimated case durations to support management in the cost-effective use of expensive surgical resources. We retrospectively analyzed all the procedures performed in the Cath Labs in 2012. The duration of procedures is strictly positive (larger than zero) and has mostly a large minimum duration. Because of the strictly positive character of the Cath Lab procedures, a fit of a lognormal model may be desirable. Having a minimum duration requires an estimate of the threshold (shift) parameter of the lognormal model. Therefore, the 3-parameter lognormal model is interesting. To avoid heterogeneous groups of observations, we tested every group-cardiologist-procedure combination for the normal, 2- and 3-parameter lognormal distribution. The total number of elective and emergency procedures performed was 6,393 (8,186 h). The final analysis included 6,135 procedures (7,779 h). Electrophysiology (intervention) procedures fit the 3-parameter lognormal model 86.1% (80.1%). Using Friedman test statistics, we conclude that the 3-parameter lognormal model is superior to the 2-parameter lognormal model. Furthermore, the 2-parameter lognormal is superior to the normal model. Cath Lab procedures are well-modelled by lognormal models. This information helps to improve and to refine Cath Lab schedules and hence their efficient use.

Racial and Cultural Factors Affecting the Mental Health of Asian Americans

PubMed Central

Miller, Matthew J.; Yang, Minji; Farrell, Jerome A.; Lin, Li-Ling

2011-01-01

In this study, we employed structural equation modeling to test the degree to which racism-related stress, acculturative stress, and bicultural self-efficacy were predictive of mental health in a predominantly community-based sample of 367 Asian American adults. We also tested whether bicultural self-efficacy moderated the relationship between acculturative stress and mental health. Finally, we examined whether generational status moderated the impact of racial and cultural predictors of mental health by testing our model across immigrant and U.S.-born samples. Results indicated that our hypothesized structural model represented a good fit to the total sample data. While racism-related stress, acculturative stress, and bicultural self-efficacy were significant predictors of mental health in the total sample analyses, our generational analyses revealed a differential predictive pattern across generational status. Finally, we found that the buffering effect of bicultural self-efficacy on the relationship between acculturative stress and mental health was significant for U.S.-born individuals only. Implications for research and service delivery are explored. PMID:21977934

A simplified model for equilibrium and transient swelling of thermo-responsive gels.

PubMed

Drozdov, A D; deClaville Christiansen, J

2017-11-01

A simplified model is developed for the elastic response of thermo-responsive gels subjected to swelling under an arbitrary deformation with finite strains. The constitutive equations involve five adjustable parameters that are determined by fitting observations in equilibrium water uptake tests and T-jump transient tests on thin gel disks. Two scenarios for water release under heating are revealed by means of numerical simulation. When the final temperature in a T-jump test is below the volume-phase transition temperature, deswelling is characterized by smooth distribution of water molecules and small tensile stresses. When the final temperature exceeds the critical temperature, a gel disk is split into three regions (central part with a high concentration of water molecules and two domains near the boundaries with low water content) separated by sharp interfaces, whose propagation is accompanied by development of large (comparable with the elastic modulus) tensile stresses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computer-aided implant design for the restoration of cranial defects.

PubMed

Chen, Xiaojun; Xu, Lu; Li, Xing; Egger, Jan

2017-06-23

Patient-specific cranial implants are important and necessary in the surgery of cranial defect restoration. However, traditional methods of manual design of cranial implants are complicated and time-consuming. Our purpose is to develop a novel software named EasyCrania to design the cranial implants conveniently and efficiently. The process can be divided into five steps, which are mirroring model, clipping surface, surface fitting, the generation of the initial implant and the generation of the final implant. The main concept of our method is to use the geometry information of the mirrored model as the base to generate the final implant. The comparative studies demonstrated that the EasyCrania can improve the efficiency of cranial implant design significantly. And, the intra- and inter-rater reliability of the software were stable, which were 87.07 ± 1.6% and 87.73 ± 1.4% respectively.

77 FR 28447 - Electronic On-Board Recorders for Hours-of-Service Compliance; Removal of Final Rule Vacated by...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-14

... reviews, requiring such carriers to use EOBRs for a 2-year period; (3) altered the Agency's safety fitness standard to take into account issuance of a remedial directive when determining a carrier's fitness; and (4... conditions: * * * * * PART 385--SAFETY FITNESS PROCEDURES 0 3. The authority citation for part 385 continues...

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 cost.

Testing the Quality Health Outcomes Model Applied to Infection Prevention in Hospitals.

PubMed

Gilmartin, Heather M; Sousa, Karen H

2016-01-01

To test the Quality Health Outcomes Model to investigate the relationship between health care-associated infection (HAI) prevention interventions, organizational context, and HAI outcomes using structural equation modeling. Variables for adherence to the central line bundle, organizational context, and central line-associated bloodstream infections (CLABSIs) were selected for this secondary data analysis from 614 US hospitals that participated in the Prevention of Nosocomial Infection and Cost-effectiveness-Refined study. One half of the dataset was used for exploration of the concepts, the second half for confirmation of the measurement models and testing of the structural model. The final model resulted in a good fit to the data (χ (1215) = 1906.86, P < .00; comparative fit index = 0.94; root mean square of error of approximation = 0.04). A significant relationship was noted between adherence to the central line bundle interventions and organizational context (β = 0.23, P < .01), whereas the relationship between context and CLABSIs was not significant (β = -0.20, P = .78). This study supports a relationship between greater adherence to HAI interventions and higher levels of organizational context and highlights the complexity of measuring organizational context. Given the importance of preventing HAIs, ongoing research is needed to reveal the exact aspects of context that influence interventions and outcomes.

A clinical data validated mathematical model of prostate cancer growth under intermittent androgen suppression therapy

NASA Astrophysics Data System (ADS)

Portz, Travis; Kuang, Yang; Nagy, John D.

2012-03-01

Prostate cancer is commonly treated by a form of hormone therapy called androgen suppression. This form of treatment, while successful at reducing the cancer cell population, adversely affects quality of life and typically leads to a recurrence of the cancer in an androgen-independent form. Intermittent androgen suppression aims to alleviate some of these adverse affects by cycling the patient on and off treatment. Clinical studies have suggested that intermittent therapy is capable of maintaining androgen dependence over multiple treatment cycles while increasing quality of life during off-treatment periods. This paper presents a mathematical model of prostate cancer to study the dynamics of androgen suppression therapy and the production of prostate-specific antigen (PSA), a clinical marker for prostate cancer. Preliminary models were based on the assumption of an androgen-independent (AI) cell population with constant net growth rate. These models gave poor accuracy when fitting clinical data during simulation. The final model presented hypothesizes an AI population with increased sensitivity to low levels of androgen. It also hypothesizes that PSA production is heavily dependent on androgen. The high level of accuracy in fitting clinical data with this model appears to confirm these hypotheses, which are also consistent with biological evidence.

The relationship between physical fitness and academic achievement among adolescent in South Korea.

PubMed

Han, Gun-Soo

2018-04-01

[Purpose] The purpose of this study was to identify the relationship between physical fitness level and academic achievement in middle school students. [Subjects and Methods] A total of 236 students aged 13-15 from three middle schools in D city, South Korea, were selected using a random sampling method. Academic achievement was measured by students' 2014 fall-semester final exam scores and the level of physical fitness was determined according to the PAPS (Physical Activity Promotion System) score administrated by the Korean Ministry of Education. A Pearson correlation test with SPSS 20.0 was employed. [Results] The Pearson correlation test revealed a significant correlation between physical fitness and academic achievement. Specifically, students with higher levels of physical fitness tend to have higher academic performance. In addition, final exam scores of core subjects (e.g., English, mathematics, and science) were significantly related to the PAPS score. [Conclusion] Results of this study can be used to develop more effective physical education curricula. In addition, the data can also be applied to recreation and sport programs for other populations (e.g., children and adult) as well as existing national physical fitness data in various countries.

Level-Specific Evaluation of Model Fit in Multilevel Structural Equation Modeling

ERIC Educational Resources Information Center

Ryu, Ehri; West, Stephen G.

2009-01-01

In multilevel structural equation modeling, the "standard" approach to evaluating the goodness of model fit has a potential limitation in detecting the lack of fit at the higher level. Level-specific model fit evaluation can address this limitation and is more informative in locating the source of lack of model fit. We proposed level-specific test…

Proposal for a candidate core-set of fitness and strength tests for patients with childhood or adult idiopathic inflammatory myopathies

PubMed Central

van der Stap, Djamilla K.D.; Rider, Lisa G.; Alexanderson, Helene; Huber, Adam M.; Gualano, Bruno; Gordon, Patrick; van der Net, Janjaap; Mathiesen, Pernille; Johnson, Liam G.; Ernste, Floranne C.; Feldman, Brian M.; Houghton, Kristin M.; Singh-Grewal, Davinder; Kutzbach, Abraham Garcia; Munters, Li Alemo; Takken, Tim

2015-01-01

OBJECTIVES Currently there are no evidence-based recommendations regarding which fitness and strength tests to use for patients with childhood or adult idiopathic inflammatory myopathies (IIM). This hinders clinicians and researchers in choosing the appropriate fitness- or muscle strength-related outcome measures for these patients. Through a Delphi survey, we aimed to identify a candidate core-set of fitness and strength tests for children and adults with IIM. METHODS Fifteen experts participated in a Delphi survey that consisted of five stages to achieve a consensus. Using an extensive search of published literature and through the expertise of the experts, a candidate core-set based on expert opinion and clinimetric properties was developed. Members of the International Myositis Assessment and Clinical Studies Group (IMACS) were invited to review this candidate core-set during the final stage, which led to a final candidate core-set. RESULTS A core-set of fitness- and strength-related outcome measures was identified for children and adults with IIM. For both children and adults, different tests were identified and selected for maximal aerobic fitness, submaximal aerobic fitness, anaerobic fitness, muscle strength tests and muscle function tests. CONCLUSIONS The core-set of fitness and strength-related outcome measures provided by this expert consensus process will assist practitioners and researchers in deciding which tests to use in IIM patients. This will improve the uniformity of fitness and strength tests across studies, thereby facilitating the comparison of study results and therapeutic exercise program outcomes among patients with IIM. PMID:26568594

Vectorlike fermions and Higgs effective field theory revisited

DOE PAGES

Chen, Chien-Yi; Dawson, S.; Furlan, Elisabetta

2017-07-10

Heavy vectorlike quarks (VLQs) appear in many models of beyond the Standard Model physics. Direct experimental searches require these new quarks to be heavy, ≳ 800 – 1000 GeV . Here, we perform a global fit of the parameters of simple VLQ models in minimal representations of S U ( 2 ) L to precision data and Higgs rates. One interesting connection between anomalous Z bmore » $$\\bar{b}$$ interactions and Higgs physics in VLQ models is discussed. Finally, we present our analysis in an effective field theory (EFT) framework and show that the parameters of VLQ models are already highly constrained. Exact and approximate analytical formulas for the S and T parameters in the VLQ models we consider are available in the Supplemental Material as Mathematica files.« less

Estimating the Effect of Competition on Trait Evolution Using Maximum Likelihood Inference.

PubMed

Drury, Jonathan; Clavel, Julien; Manceau, Marc; Morlon, Hélène

2016-07-01

Many classical ecological and evolutionary theoretical frameworks posit that competition between species is an important selective force. For example, in adaptive radiations, resource competition between evolving lineages plays a role in driving phenotypic diversification and exploration of novel ecological space. Nevertheless, current models of trait evolution fit to phylogenies and comparative data sets are not designed to incorporate the effect of competition. The most advanced models in this direction are diversity-dependent models where evolutionary rates depend on lineage diversity. However, these models still treat changes in traits in one branch as independent of the value of traits on other branches, thus ignoring the effect of species similarity on trait evolution. Here, we consider a model where the evolutionary dynamics of traits involved in interspecific interactions are influenced by species similarity in trait values and where we can specify which lineages are in sympatry. We develop a maximum likelihood based approach to fit this model to combined phylogenetic and phenotypic data. Using simulations, we demonstrate that the approach accurately estimates the simulated parameter values across a broad range of parameter space. Additionally, we develop tools for specifying the biogeographic context in which trait evolution occurs. In order to compare models, we also apply these biogeographic methods to specify which lineages interact sympatrically for two diversity-dependent models. Finally, we fit these various models to morphological data from a classical adaptive radiation (Greater Antillean Anolis lizards). We show that models that account for competition and geography perform better than other models. The matching competition model is an important new tool for studying the influence of interspecific interactions, in particular competition, on phenotypic evolution. More generally, it constitutes a step toward a better integration of interspecific interactions in many ecological and evolutionary processes. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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),…

A spatial characterization of the Sagittarius dwarf galaxy tidal tails

DOE Office of Scientific and Technical Information (OSTI.GOV)

Newby, Matthew; Cole, Nathan; Newberg, Heidi Jo

2013-06-01

We measure the spatial density of F turnoff stars in the Sagittarius dwarf tidal stream, from Sloan Digital Sky Survey data, using statistical photometric parallax. We find a set of continuous, consistent parameters that describe the leading Sgr stream's position, direction, and width for 15 stripes in the north Galactic cap, and three stripes in the south Galactic cap. We produce a catalog of stars that has the density characteristics of the dominant leading Sgr tidal stream that can be compared with simulations. We find that the width of the leading (north) tidal tail is consistent with recent triaxial andmore » axisymmetric halo model simulations. The density along the stream is roughly consistent with common disruption models in the north, but possibly not in the south. We explore the possibility that one or more of the dominant Sgr streams has been misidentified, and that one or more of the ''bifurcated'' pieces is the real Sgr tidal tail, but we do not reach definite conclusions. If two dwarf progenitors are assumed, fits to the planes of the dominant and ''bifurcated'' tidal tails favor an association of the Sgr dwarf spheroidal galaxy with the dominant southern stream and the ''bifurcated'' stream in the north. In the north Galactic cap, the best fit Hernquist density profile for the smooth component of the stellar halo is oblate, with a flattening parameter q = 0.53, and a scale length of r {sub 0} = 6.73. The southern data for both the tidal debris and the smooth component of the stellar halo do not match the model fits to the north, although the stellar halo is still overwhelmingly oblate. Finally, we verify that we can reproduce the parameter fits on the asynchronous MilkyWay@home volunteer computing platform.« less

Evolution with Stochastic Fitness and Stochastic Migration

PubMed Central

Rice, Sean H.; Papadopoulos, Anthony

2009-01-01

Background Migration between local populations plays an important role in evolution - influencing local adaptation, speciation, extinction, and the maintenance of genetic variation. Like other evolutionary mechanisms, migration is a stochastic process, involving both random and deterministic elements. Many models of evolution have incorporated migration, but these have all been based on simplifying assumptions, such as low migration rate, weak selection, or large population size. We thus have no truly general and exact mathematical description of evolution that incorporates migration. Methodology/Principal Findings We derive an exact equation for directional evolution, essentially a stochastic Price equation with migration, that encompasses all processes, both deterministic and stochastic, contributing to directional change in an open population. Using this result, we show that increasing the variance in migration rates reduces the impact of migration relative to selection. This means that models that treat migration as a single parameter tend to be biassed - overestimating the relative impact of immigration. We further show that selection and migration interact in complex ways, one result being that a strategy for which fitness is negatively correlated with migration rates (high fitness when migration is low) will tend to increase in frequency, even if it has lower mean fitness than do other strategies. Finally, we derive an equation for the effective migration rate, which allows some of the complex stochastic processes that we identify to be incorporated into models with a single migration parameter. Conclusions/Significance As has previously been shown with selection, the role of migration in evolution is determined by the entire distributions of immigration and emigration rates, not just by the mean values. The interactions of stochastic migration with stochastic selection produce evolutionary processes that are invisible to deterministic evolutionary theory. PMID:19816580

Physical fitness, injuries, and team performance in soccer.

PubMed

Arnason, Arni; Sigurdsson, Stefan B; Gudmundsson, Arni; Holme, Ingar; Engebretsen, Lars; Bahr, Roald

2004-02-01

To investigate the relationship between physical fitness and team success in soccer, and to test for differences in physical fitness between different player positions. Participants were 306 male soccer players from 17 teams in the two highest divisions in Iceland. Just before the start of the 1999 soccer season, the following variables were tested: height and weight, body composition, flexibility, leg extension power, jump height, and peak O2 uptake. Injuries and player participation in matches and training were recorded through the 4-month competitive season. Team average physical fitness was compared with team success (final league standing) using a linear regression model. Physical fitness was also compared between players in different playing positions. A significant relationship was found between team average jump height (countermovement jump and standing jump) and team success (P = 0.009 and P = 0.012, respectively). The same trend was also found for leg extension power (P = 0.097), body composition (% body fat, P = 0.07), and the total number of injury days per team (P = 0.09). Goalkeepers demonstrated different fitness characteristics from outfield players. They were taller and heavier, more flexible in hip extension and knee flexion, and had higher leg extension power and a lower peak O2 uptake. However, only minor differences were observed between defenders, midfield players, and attackers. Coaches and medical support teams should pay more attention to jump and power training, as well as preventive measures and adequate rehabilitation of previous injuries to increase team success.

Quantifying the Role of Population Subdivision in Evolution on Rugged Fitness Landscapes

PubMed Central

Bitbol, Anne-Florence; Schwab, David J.

2014-01-01

Natural selection drives populations towards higher fitness, but crossing fitness valleys or plateaus may facilitate progress up a rugged fitness landscape involving epistasis. We investigate quantitatively the effect of subdividing an asexual population on the time it takes to cross a fitness valley or plateau. We focus on a generic and minimal model that includes only population subdivision into equivalent demes connected by global migration, and does not require significant size changes of the demes, environmental heterogeneity or specific geographic structure. We determine the optimal speedup of valley or plateau crossing that can be gained by subdivision, if the process is driven by the deme that crosses fastest. We show that isolated demes have to be in the sequential fixation regime for subdivision to significantly accelerate crossing. Using Markov chain theory, we obtain analytical expressions for the conditions under which optimal speedup is achieved: valley or plateau crossing by the subdivided population is then as fast as that of its fastest deme. We verify our analytical predictions through stochastic simulations. We demonstrate that subdivision can substantially accelerate the crossing of fitness valleys and plateaus in a wide range of parameters extending beyond the optimal window. We study the effect of varying the degree of subdivision of a population, and investigate the trade-off between the magnitude of the optimal speedup and the width of the parameter range over which it occurs. Our results, obtained for fitness valleys and plateaus, also hold for weakly beneficial intermediate mutations. Finally, we extend our work to the case of a population connected by migration to one or several smaller islands. Our results demonstrate that subdivision with migration alone can significantly accelerate the crossing of fitness valleys and plateaus, and shed light onto the quantitative conditions necessary for this to occur. PMID:25122220

Data mining of audiology patient records: factors influencing the choice of hearing aid type

PubMed Central

2012-01-01

Background This paper describes the analysis of a database of over 180,000 patient records, collected from over 23,000 patients, by the hearing aid clinic at James Cook University Hospital in Middlesbrough, UK. These records consist of audiograms (graphs of the faintest sounds audible to the patient at six different pitches), categorical data (such as age, gender, diagnosis and hearing aid type) and brief free text notes made by the technicians. This data is mined to determine which factors contribute to the decision to fit a BTE (worn behind the ear) hearing aid as opposed to an ITE (worn in the ear) hearing aid. Methods From PCA (principal component analysis) four main audiogram types are determined, and are related to the type of hearing aid chosen. The effects of age, gender, diagnosis, masker, mould and individual audiogram frequencies are combined into a single model by means of logistic regression. Some significant keywords are also discovered in the free text fields by using the chi-squared (χ2) test, which can also be used in the model. The final model can act a decision support tool to help decide whether an individual patient should be offered a BTE or an ITE hearing aid. Results The final model was tested using 5-fold cross validation, and was able to replicate the decisions of audiologists whether to fit an ITE or a BTE hearing aid with precision in the range 0.79 to 0.87. Conclusions A decision support system was produced to predict the type of hearing aid which should be prescribed, with an explanation facility explaining how that decision was arrived at. This system should prove useful in providing a "second opinion" for audiologists. PMID:22595091

Quantification of soil water retention parameters using multi-section TDR-waveform analysis

NASA Astrophysics Data System (ADS)

Baviskar, S. M.; Heimovaara, T. J.

2017-06-01

Soil water retention parameters are important for describing flow in variably saturated soils. TDR is one of the standard methods used for determining water content in soil samples. In this study, we present an approach to estimate water retention parameters of a sample which is initially saturated and subjected to an incremental decrease in boundary head causing it to drain in a multi-step fashion. TDR waveforms are measured along the height of the sample at assumed different hydrostatic conditions at daily interval. The cumulative discharge outflow drained from the sample is also recorded. The saturated water content is obtained using volumetric analysis after the final step involved in multi-step drainage. The equation obtained by coupling the unsaturated parametric function and the apparent dielectric permittivity is fitted to a TDR wave propagation forward model. The unsaturated parametric function is used to spatially interpolate the water contents along TDR probe. The cumulative discharge outflow data is fitted with cumulative discharge estimated using the unsaturated parametric function. The weight of water inside the sample estimated at the first and final boundary head in multi-step drainage is fitted with the corresponding weights calculated using unsaturated parametric function. A Bayesian optimization scheme is used to obtain optimized water retention parameters for these different objective functions. This approach can be used for samples with long heights and is especially suitable for characterizing sands with a uniform particle size distribution at low capillary heads.

Modelling and observations of molecules in discs around young stars

NASA Astrophysics Data System (ADS)

Ilee, John David

2013-04-01

This thesis contains a study of molecules within circumstellar discs around young stars. Firstly, the chemistry of a disc around a young, Class 0 protostar is modelled. Such discs are thought to be massive, and thus experience gravitational instabilities, which produce spiral density waves. These affect the chemistry in three ways; by desorbing molecules from dust grains, by providing extra energy for new reactions to take place, and by mixing the internal structure of the disc to provide a rich chemistry near the midplane. Secondly, high resolution near-infrared spectra of 20 massive young stellar objects are presented. The objects display CO first overtone bandhead emission, which is excited in the conditions expected within circumstellar discs. The emission is modelled using a simple analytic model of a Keplerian disc, and good fits are found to all spectra. On average, the discs correspond to being geometrically thin, spread across a wide range of inclinations. The discs are located within the dust sublimation radius, providing strong evidence that the CO emission originates in small gaseous discs, supporting the scenario in which massive stars form via disc accretion. Finally, medium resolution near-infrared spectra of 5 Herbig Ae/Be stars are presented. The spectra cover both CO bandhead and Br gamma emission. Accretion rates are derived from the measuring the Br gamma emission and through modelling the CO emission, however these accretion rates are found to be inconsistent. High resolution archival data of one of the targets is presented, and it is shown that this CO disc model is unable to fit the high resolution data. Therefore, it is concluded that to properly fit CO spectra, high resolution data are needed, and that previously published information determined from low resolution spectra should be treated with caution.

The Type Ia Supernova Color-Magnitude Relation and Host Galaxy Dust: A Simple Hierarchical Bayesian Model

NASA Astrophysics Data System (ADS)

Mandel, Kaisey S.; Scolnic, Daniel M.; Shariff, Hikmatali; Foley, Ryan J.; Kirshner, Robert P.

2017-06-01

Conventional Type Ia supernova (SN Ia) cosmology analyses currently use a simplistic linear regression of magnitude versus color and light curve shape, which does not model intrinsic SN Ia variations and host galaxy dust as physically distinct effects, resulting in low color-magnitude slopes. We construct a probabilistic generative model for the dusty distribution of extinguished absolute magnitudes and apparent colors as the convolution of an intrinsic SN Ia color-magnitude distribution and a host galaxy dust reddening-extinction distribution. If the intrinsic color-magnitude (M B versus B - V) slope {β }{int} differs from the host galaxy dust law R B , this convolution results in a specific curve of mean extinguished absolute magnitude versus apparent color. The derivative of this curve smoothly transitions from {β }{int} in the blue tail to R B in the red tail of the apparent color distribution. The conventional linear fit approximates this effective curve near the average apparent color, resulting in an apparent slope {β }{app} between {β }{int} and R B . We incorporate these effects into a hierarchical Bayesian statistical model for SN Ia light curve measurements, and analyze a data set of SALT2 optical light curve fits of 248 nearby SNe Ia at z< 0.10. The conventional linear fit gives {β }{app}≈ 3. Our model finds {β }{int}=2.3+/- 0.3 and a distinct dust law of {R}B=3.8+/- 0.3, consistent with the average for Milky Way dust, while correcting a systematic distance bias of ˜0.10 mag in the tails of the apparent color distribution. Finally, we extend our model to examine the SN Ia luminosity-host mass dependence in terms of intrinsic and dust components.

Size-density scaling in protists and the links between consumer-resource interaction parameters.

PubMed

DeLong, John P; Vasseur, David A

2012-11-01

Recent work indicates that the interaction between body-size-dependent demographic processes can generate macroecological patterns such as the scaling of population density with body size. In this study, we evaluate this possibility for grazing protists and also test whether demographic parameters in these models are correlated after controlling for body size. We compiled data on the body-size dependence of consumer-resource interactions and population density for heterotrophic protists grazing algae in laboratory studies. We then used nested dynamic models to predict both the height and slope of the scaling relationship between population density and body size for these protists. We also controlled for consumer size and assessed links between model parameters. Finally, we used the models and the parameter estimates to assess the individual- and population-level dependence of resource use on body-size and prey-size selection. The predicted size-density scaling for all models matched closely to the observed scaling, and the simplest model was sufficient to predict the pattern. Variation around the mean size-density scaling relationship may be generated by variation in prey productivity and area of capture, but residuals are relatively insensitive to variation in prey size selection. After controlling for body size, many consumer-resource interaction parameters were correlated, and a positive correlation between residual prey size selection and conversion efficiency neutralizes the apparent fitness advantage of taking large prey. Our results indicate that widespread community-level patterns can be explained with simple population models that apply consistently across a range of sizes. They also indicate that the parameter space governing the dynamics and the steady states in these systems is structured such that some parts of the parameter space are unlikely to represent real systems. Finally, predator-prey size ratios represent a kind of conundrum, because they are widely observed but apparently have little influence on population size and fitness, at least at this level of organization. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

The influence of prototype testing in three-dimensional aortic models on fenestrated endograft design.

PubMed

Taher, Fadi; Falkensammer, Juergen; McCarte, Jamie; Strassegger, Johann; Uhlmann, Miriam; Schuch, Philipp; Assadian, Afshin

2017-06-01

The fenestrated Anaconda endograft (Vascutek/Terumo, Inchinnan, UK) is intended for the treatment of abdominal aortic aneurysms with an insufficient infrarenal landing zone. The endografts are custom-made with use of high-resolution, 1-mm-slice computed tomography angiography images. For every case, a nonsterile prototype and a three-dimensional (3D) model of the patient's aorta are constructed to allow the engineers as well as the physician to test-implant the device and to review the fit of the graft. The aim of this investigation was to assess the impact of 3D model construction and prototype testing on the design of the final sterile endograft. A prospectively held database on fenestrated endovascular aortic repair patients treated at a single institution was completed with data from the Vascutek engineers' prototype test results as well as the product request forms. Changes to endograft design based on prototype testing were assessed and are reported for all procedures. Between April 1, 2013, and August 18, 2015, 60 fenestrated Anaconda devices were implanted. Through prototype testing, engineers were able to identify and report potential risks to technical success related to use of the custom device for the respective patient. Theoretical concerns about endograft fit in the rigid model were expressed in 51 cases (85.0%), and the engineers suggested potential changes to the design of 21 grafts (35.0%). Thirteen cases (21.7%) were eventually modified after the surgeon's testing of the prototype. A second prototype was ordered in three cases (5.0%) because of extensive changes to endograft design, such as inclusion of an additional fenestration. Technical success rates were comparable for grafts that showed a perfect fit from the beginning and cases in which prototype testing resulted in a modification of graft design. Planning and construction of fenestrated endografts for complex aortic anatomies where exact fit and positioning of the graft are paramount to allow cannulation of the aortic branches are challenging. In the current series, approximately one in five endografts was modified after prototype testing in an aortic model. Eventually, success rates were comparable between the groups of patients with a good primary prototype fit and those in which the endograft design was altered. Prototype testing in 3D aortic models is a valuable tool to test the fit of a custom-made endograft before implantation. This may help avoid potentially debilitating adverse events associated with misaligned fenestrations and unconnected aortic branches. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Relaxation Dynamics of a Granular Pile on a Vertically Vibrating Plate

NASA Astrophysics Data System (ADS)

Tsuji, Daisuke; Otsuki, Michio; Katsuragi, Hiroaki

2018-03-01

Nonlinear relaxation dynamics of a vertically vibrated granular pile is experimentally studied. In the experiment, the flux and slope on the relaxing pile are measured by using a high-speed laser profiler. The relation of these quantities can be modeled by the nonlinear transport law assuming the uniform vibrofluidization of an entire pile. The fitting parameter in this model is only the relaxation efficiency, which characterizes the energy conversion rate from vertical vibration into horizontal transport. We demonstrate that this value is a constant independent of experimental conditions. The actual relaxation is successfully reproduced by the continuity equation with the proposed model. Finally, its specific applicability toward an astrophysical phenomenon is shown.

Neutrino catalyzed diphoton excess

DOE PAGES

Chao, Wei

2016-08-16

In this paper we explain the 750 GeV diphoton resonance observed at the run-2 LHC as a scalar singlet S, that plays a key role in generating tiny but nonzero Majorana neutrino masses. The model contains four electroweak singlets: two leptoquarks, a singly charged scalar and a neutral scalar S. Majorana neutrino masses might be generated at the two-loop level as S gets nonzero vacuum expectation value. S can be produced at the LHC through the gluon fusion and decays into diphoton with charged scalars running in the loop. The model fits perfectly with a narrow width of the resonance.more » Finally, constraints on the model are investigated, which shows a negligible mixing between the resonance and the standard model Higgs boson.« less

A Bayesian hierarchical latent trait model for estimating rater bias and reliability in large-scale performance assessment

PubMed Central

2018-01-01

We propose a novel approach to modelling rater effects in scoring-based assessment. The approach is based on a Bayesian hierarchical model and simulations from the posterior distribution. We apply it to large-scale essay assessment data over a period of 5 years. Empirical results suggest that the model provides a good fit for both the total scores and when applied to individual rubrics. We estimate the median impact of rater effects on the final grade to be ± 2 points on a 50 point scale, while 10% of essays would receive a score at least ± 5 different from their actual quality. Most of the impact is due to rater unreliability, not rater bias. PMID:29614129

Participation in fitness-related activities of an incentive-based health promotion program and hospital costs: a retrospective longitudinal study.

PubMed

Patel, Deepak; Lambert, Estelle V; da Silva, Roseanne; Greyling, Mike; Kolbe-Alexander, Tracy; Noach, Adam; Conradie, Jaco; Nossel, Craig; Borresen, Jill; Gaziano, Thomas

2011-01-01

A retrospective, longitudinal study examined changes in participation in fitness-related activities and hospital claims over 5 years amongst members of an incentivized health promotion program offered by a private health insurer. A 3-year retrospective observational analysis measuring gym visits and participation in documented fitness-related activities, probability of hospital admission, and associated costs of admission. A South African private health plan, Discovery Health and the Vitality health promotion program. 304,054 adult members of the Discovery medical plan, 192,467 of whom registered for the health promotion program and 111,587 members who were not on the program. Members were incentivised for fitness-related activities on the basis of the frequency of gym visits. Changes in electronically documented gym visits and registered participation in fitness-related activities over 3 years and measures of association between changes in participation (years 1-3) and subsequent probability and costs of hospital admission (years 4-5). Hospital admissions and associated costs are based on claims extracted from the health insurer database. The probability of a claim modeled by using linear logistic regression and costs of claims examined by using general linear models. Propensity scores were estimated and included age, gender, registration for chronic disease benefits, plan type, and the presence of a claim during the transition period, and these were used as covariates in the final model. There was a significant decrease in the prevalence of inactive members (76% to 68%) over 5 years. Members who remained highly active (years 1-3) had a lower probability (p < .05) of hospital admission in years 4 to 5 (20.7%) compared with those who remained inactive (22.2%). The odds of admission were 13% lower for two additional gym visits per week (odds ratio, .87; 95% confidence interval [CI], .801-.949). We observed an increase in fitness-related activities over time amongst members of this incentive-based health promotion program, which was associated with a lower probability of hospital admission and lower hospital costs in the subsequent 2 years. Copyright © 2011 by American Journal of Health Promotion, Inc.

Development of dark disk model of positron anomaly origin

NASA Astrophysics Data System (ADS)

Belotsky, K. M.; Kirillov, A. A.; Solovyov, M. L.

Dark disk model could be a remedy for dark matter (DM) explanation of positron anomaly (PA) in cosmic rays (CR). The main difficulty in PA explanation relates to cosmic gamma-radiation which is inevitably produced in DM annihilation or decay leading to tension with respective observation data. Introduction of “active” (producing CR) DM component concentrating in galactic disk alleviates this tension. Earlier, we considered 2-lepton modes, with branching ratios being chosen to fit in the best way all the observation data. Here we considered, in the framework of the same dark disk model, two cases: 2-body final state annihilation and 4-body one, and in each case a quark mode is added to the leptonic ones. It is shown that 4-body mode case is a little better than 2-body one from viewpoint of quality of observation data description at the fixed all other parameters (of CR propagation, background, disk height). The values of DM particle mass around 350GeV and 500GeV are more favorable for 2- and 4-body modes, respectively. Higher values would improve description of data on positrons only but accounting for data on gamma-radiation prevents it because of unwanted more abundant high-energy gamma production. Inclusion of the quark modes improves a little fitting data in both 4- and 2-body mode cases, contrary to naive expectations. In fact, quark mode has a bigger gammas yield than that of most gamma-productive leptonic mode — tau, but they are softer due to bigger final state hadron multiplicity.

Measurements and Quasi-Quantum Modeling of the Steric Asymmetry and Parity Propensities in State-to-State Rotationally Inelastic Scattering of NO ( 2Π 1/2) with D 2

DOE PAGES

Taatjes, Craig A.; Gijsbertsen, Arjan; de Lange, Marc J. L.; ...

2007-06-02

In this paper, relative integrated cross sections are measured for spin-orbit-conserving, rotationally inelastic scattering of NO ( 2Π 1/2), hexapole-selected in the upper Λ-doublet level of the ground rotational state (j = 0.5), in collisions with D 2 at a nominal energy of 551 cm -1. The final state of the NO molecule is detected by laser-induced fluorescence (LIF). The state-selected NO molecule is oriented with either the N end or the O end toward the incoming D 2 molecule by application of a static electric field E in the scattering region. This field is directed parallel or antiparallel tomore » the relative velocity vector v. Comparison of signals taken for the different applied field directions gives the experimental steric asymmetry SA, defined by SA = (σ v↑↓E - σ v↑↑E)/(σ v↑↓E + σ v↑↑E), which is equal to within a factor of -1 to the molecular steric effect, S i→f ≡ (σ D2→NO - σ D2→ON)/(σ D2→NO + σ D2→ON). The dependence of the integral inelastic cross section on the incoming Λ-doublet component is also measured as a function of the final rotational (j final) and Λ-doublet (ε final) state. The measured steric asymmetries are similar to those previously observed for NO-He scattering. Spin-orbit manifold-conserving collisions exhibit a larger propensity for parity conservation than their NO-He counterparts. The results are interpreted in the context of the recently developed quasi-quantum treatment (QQT) of rotationally inelastic scattering. The QQT predictions can be inverted to obtain a fitted hard-shell potential that reproduces the experimental steric asymmetry; this fitted potential gives an empirical estimate of the anisotropy of the repulsive interaction between NO and D 2. Finally, QQT computation of the differential cross section using this simple model potential shows reasonable agreement with the measured differential cross sections.« less

KNGEOID14: A national hybrid geoid model in Korea

NASA Astrophysics Data System (ADS)

Kang, S.; Sung, Y. M.; KIM, H.; Kim, Y. S.

2016-12-01

This study describes in brief the construction of a national hybrid geoid model in Korea, KNGEOID14, which can be used as an accurate vertical datum in/around Korea. The hybrid geoid model should be determined by fitting the gravimetric geoid to the geometric geoid undulations from GNSS/Leveling data which were presented the local vertical level. For developing the gravimetric geoid model, we determined all frequency parts (long, middle and short-frequency) of gravimetric geoid using all available data with optimal remove-restore technique based on EGM2008 reference surface. In remove-restore technique, the EGM2008 model to degree 360, RTM reduction method were used for calculating the long, middle and short-frequency part of gravimetric geoid, respectively. A number of gravity data compiled for modeling the middle-frequency part, residual geoid, containing 8,866 points gravity data on land and ocean areas. And, the DEM data gridded by 100m×100m were used for short-frequency part, is the topographic effect on the geoid generated by RTM method. The accuracy of gravimetric geoid model were evaluated by comparison with GNSS/Leveling data was about -0.362m ± 0.055m. Finally, we developed the national hybrid geoid model in Korea, KNGEOID14, corrected to gravimetric geoid with the correction term by fitting the about 1,200 GNSS/Leveling data on Korean bench marks. The correction term is modeled using the difference between GNSS/Leveling derived geoidal heights and gravimetric geoidal heights. The stochastic model used in the calculation of correction term is the LSC technique based on second-order Markov covariance function. The post-fit error (mean and std. dev.) of the KNGEOID14 model was evaluated as 0.001m ± 0.033m. Concerning the result of this study, the accurate orthometric height at any points in Korea will be easily and precisely calculated by combining the geoidal height from KNGEOID14 and ellipsoidal height from GPS observation technique.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thappily, Praveen, E-mail: pravvmon@gmail.com, E-mail: shiiuvenus@gmail.com; Shiju, K., E-mail: pravvmon@gmail.com, E-mail: shiiuvenus@gmail.com

Green synthesis of silver nanoparticles was achieved by simple visible light irradiation using aloe barbadensis leaf extract as reducing agent. UV-Vis spectroscopic analysis was used for confirmation of the successful formation of nanoparticles. Investigated the effect of light irradiation time on the light absorption of the nanoparticles. It is observed that upto 25 minutes of light irradiation, the absorption is linearly increasing with time and after that it becomes saturated. Finally, theoretically fitted the time-absorption graph and modeled a relation between them with the help of simulation software.

jsc2012e224533

NASA Image and Video Library

2012-10-18

Expedition 33/34 Flight Engineer Kevin Ford of NASA (left), Soyuz Commander Oleg Novitskiy (center) and Flight Engineer Evgeny Tarelkin (right) pose for pictures in front of a model of Sputnik 1, the world’s first artificial satellite, in the Korolev Museum at the Baikonur Cosmodrome in Kazakhstan October 18, 2012. The trio completed a final “fit check” dress rehearsal, preparing for launch October 23 in their Soyuz TMA-06M spacecraft from the Cosmodrome for a five-month mission on the International Space Station. NASA/Victor Zelentsov

Bio-Inspired Flexible Cellular Actuating Systems

DTIC Science & Technology

2013-11-21

spline . 4) Finally, the control law does not require that a, b, or M be known for the purpose of regulation. We only need to know bounds on a and M to...would have to be modeled as plates rather than beams. Although several MAV wings do have aspect ratios smaller than 3 (such as the one built by the... spline fitting. Such an array of sensors is light and cheap enough to implement in a practical setting, and more so compared with a distributed actuation

Inferring Microbial Fitness Landscapes

DTIC Science & Technology

2016-02-25

infer from data the determinants of microbial evolution with sufficient resolution that we can quantify 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND...Distribution Unlimited UU UU UU UU 25-02-2016 1-Oct-2012 30-Sep-2015 Final Report: Inferring Microbial Fitness Landscapes The views, opinions and/or findings...Triangle Park, NC 27709-2211 evolution, fitness landscapes, epistasis, microbial populations REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT

A biopsychosocial model of body image concerns and disordered eating in early adolescent girls.

PubMed

Rodgers, Rachel F; Paxton, Susan J; McLean, Siân A

2014-05-01

Body image and eating concerns are prevalent among early adolescent girls, and associated with biological, psychological and sociocultural risk factors. To date, explorations of biopsychosocial models of body image concerns and disordered eating in early adolescent girls are lacking. A sample of 488 early adolescent girls, mean age = 12.35 years (SD = 0.53), completed a questionnaire assessing depressive symptoms, self-esteem, body mass index (BMI), sociocultural appearance pressures, thin-ideal internalization, appearance comparison, body image concerns and disordered eating. Structural equation modelling was conducted to test a hypothetical model in which internalization and comparison were mediators of the effect of both negative affect and sociocultural influences on body image concerns and disordered eating. In addition, the model proposed that BMI would impact body image concerns. Although the initial model was a poor fit to the data, the fit was improved after the addition of a direct pathway between negative affect and bulimic symptoms. The final model explained a large to moderate proportion of the variance in body image and eating concerns. This study supports the role of negative affect in biopsychosocial models of the development of body image concerns and disordered eating in early adolescent girls. Interventions including strategies to address negative affect as well as sociocultural appearance pressures may help decrease the risk for body image concerns and disordered eating among this age group.

[Model of multiple seasonal autoregressive integrated moving average model and its application in prediction of the hand-foot-mouth disease incidence in Changsha].

PubMed

Tan, Ting; Chen, Lizhang; Liu, Fuqiang

2014-11-01

To establish multiple seasonal autoregressive integrated moving average model (ARIMA) according to the hand-foot-mouth disease incidence in Changsha, and to explore the feasibility of the multiple seasonal ARIMA in predicting the hand-foot-mouth disease incidence. EVIEWS 6.0 was used to establish multiple seasonal ARIMA according to the hand-foot- mouth disease incidence from May 2008 to August 2013 in Changsha, and the data of the hand- foot-mouth disease incidence from September 2013 to February 2014 were served as the examined samples of the multiple seasonal ARIMA, then the errors were compared between the forecasted incidence and the real value. Finally, the incidence of hand-foot-mouth disease from March 2014 to August 2014 was predicted by the model. After the data sequence was handled by smooth sequence, model identification and model diagnosis, the multiple seasonal ARIMA (1, 0, 1)×(0, 1, 1)12 was established. The R2 value of the model fitting degree was 0.81, the root mean square prediction error was 8.29 and the mean absolute error was 5.83. The multiple seasonal ARIMA is a good prediction model, and the fitting degree is good. It can provide reference for the prevention and control work in hand-foot-mouth disease.

Measurement of spin correlations in t-tbar production using the matrix element method in the muon+jets final state in pp collisions at √(s) = 8 TeV

DOE PAGES

Khachatryan, Vardan

2016-05-06

The consistency of the spin correlation strength in top quark pair production with the standard model (SM) prediction is tested in the muon+jets final state. The events are selected from pp collisions, collected by the CMS detector, at a centre-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 19.7 fb -1. We then compare the data with the expectation for the spin correlation predicted by the SM and with the expectation of no correlation. Furthermore, by using a template fit method, the fraction of events that show SM spin correlations is measured to be 0.72 ±0.08 (stat) +0.15more » -0.13 (syst), representing the most precise measurement of this quantity in the lepton+jets final state to date.« less

Measurement of spin correlations in t t ‾ production using the matrix element method in the muon+jets final state in pp collisions at √{ s} = 8 TeV

NASA Astrophysics Data System (ADS)

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Knünz, V.; König, A.; Krammer, M.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Lauwers, J.; Luyckx, S.; Rougny, R.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; De Bruyn, I.; Deroover, K.; Heracleous, N.; Keaveney, J.; Lowette, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Van Parijs, I.; Barria, P.; Brun, H.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Fasanella, G.; Favart, L.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Léonard, A.; Maerschalk, T.; Marinov, A.; Perniè, L.; Randle-conde, A.; Reis, T.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Yonamine, R.; Zenoni, F.; Zhang, F.; Beernaert, K.; Benucci, L.; Cimmino, A.; Crucy, S.; Dobur, D.; Fagot, A.; Garcia, G.; Gul, M.; Mccartin, J.; Ocampo Rios, A. A.; Poyraz, D.; Ryckbosch, D.; Salva, S.; Sigamani, M.; Strobbe, N.; Tytgat, M.; Van Driessche, W.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; Ceard, L.; Da Silveira, G. G.; Delaere, C.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Mertens, A.; Nuttens, C.; Perrini, L.; Pin, A.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Beliy, N.; Hammad, G. H.; Aldá Júnior, W. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Hamer, M.; Hensel, C.; Mora Herrera, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; De Souza Santos, A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Cheng, T.; Du, R.; Jiang, C. H.; Plestina, R.; Romeo, F.; Shaheen, S. M.; Tao, J.; Wang, C.; Wang, Z.; Zhang, H.; Asawatangtrakuldee, C.; Ban, Y.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Zou, W.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Kadija, K.; Luetic, J.; Micanovic, S.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Bodlak, M.; Finger, M.; Finger, M.; El Sawy, M.; El-khateeb, E.; Elkafrawy, T.; Mohamed, A.; Salama, E.; Calpas, B.; Kadastik, M.; Murumaa, M.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Zghiche, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Dahms, T.; Davignon, O.; Filipovic, N.; Florent, A.; Granier de Cassagnac, R.; Lisniak, S.; Mastrolorenzo, L.; Miné, P.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Goetzmann, C.; Le Bihan, A.-C.; Merlin, J. A.; Skovpen, K.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Bouvier, E.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Ruiz Alvarez, J. D.; Sabes, D.; Sgandurra, L.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Toriashvili, T.; Lomidze, D.; Autermann, C.; Beranek, S.; Edelhoff, M.; Feld, L.; Heister, A.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Schael, S.; Schulte, J. F.; Verlage, T.; Weber, H.; Wittmer, B.; Zhukov, V.; Ata, M.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Klingebiel, D.; Knutzen, S.; Kreuzer, P.; Merschmeyer, M.; Meyer, A.; Millet, P.; Olschewski, M.; Padeken, K.; Papacz, P.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Künsken, A.; Lingemann, J.; Nehrkorn, A.; Nowack, A.; Nugent, I. M.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Asin, I.; Bartosik, N.; Behnke, O.; Behrens, U.; Bell, A. J.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Choudhury, S.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Dooling, S.; Dorland, T.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Flucke, G.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Gunnellini, P.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Katsas, P.; Kieseler, J.; Kleinwort, C.; Korol, I.; Lange, W.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Mankel, R.; Marfin, I.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Nayak, A.; Ntomari, E.; Perrey, H.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Roland, B.; Sahin, M. Ö.; Saxena, P.; Schoerner-Sadenius, T.; Schröder, M.; Seitz, C.; Spannagel, S.; Trippkewitz, K. D.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Erfle, J.; Garutti, E.; Goebel, K.; Gonzalez, D.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. S.; Junkes, A.; Klanner, R.; Kogler, R.; Lapsien, T.; Lenz, T.; Marchesini, I.; Marconi, D.; Meyer, M.; Nowatschin, D.; Ott, J.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Pietsch, N.; Poehlsen, J.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Schwandt, J.; Seidel, M.; Sola, V.; Stadie, H.; Steinbrück, G.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Vormwald, B.; Akbiyik, M.; Barth, C.; Baus, C.; Berger, J.; Böser, C.; Butz, E.; Chwalek, T.; Colombo, F.; De Boer, W.; Descroix, A.; Dierlamm, A.; Fink, S.; Frensch, F.; Giffels, M.; Gilbert, A.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Katkov, I.; Kornmayer, A.; Lobelle Pardo, P.; Maier, B.; Mildner, H.; Mozer, M. U.; Müller, T.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Röcker, S.; Roscher, F.; Simonis, H. J.; Stober, F. M.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weber, M.; Weiler, T.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Psallidas, A.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Loukas, N.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Bencze, G.; Hajdu, C.; Hazi, A.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Molnar, J.; Szillasi, Z.; Bartók, M.; Makovec, A.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Mal, P.; Mandal, K.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Gupta, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Mehta, A.; Mittal, M.; Singh, J. B.; Walia, G.; Kumar, Ashok; Bhardwaj, A.; Choudhary, B. C.; Garg, R. B.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Nishu, N.; Ranjan, K.; Sharma, R.; Sharma, V.; Bhattacharya, S.; Chatterjee, K.; Dey, S.; Dutta, S.; Jain, Sa.; Majumdar, N.; Modak, A.; Mondal, K.; Mukherjee, S.; Mukhopadhyay, S.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Abdulsalam, A.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Banerjee, S.; Bhowmik, S.; Chatterjee, R. M.; Dewanjee, R. K.; Dugad, S.; Ganguly, S.; Ghosh, S.; Guchait, M.; Gurtu, A.; Kole, G.; Kumar, S.; Mahakud, B.; Maity, M.; Majumder, G.; Mazumdar, K.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sarkar, T.; Sudhakar, K.; Sur, N.; Sutar, B.; Wickramage, N.; Chauhan, S.; Dube, S.; Sharma, S.; Bakhshiansohi, H.; Behnamian, H.; Etesami, S. M.; Fahim, A.; Goldouzian, R.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Caputo, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Travaglini, R.; Cappello, G.; Chiorboli, M.; Costa, S.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Gonzi, S.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Tropiano, A.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Lo Vetere, M.; Monge, M. R.; Robutti, E.; Tosi, S.; Brianza, L.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Gerosa, R.; Ghezzi, A.; Govoni, P.; Malvezzi, S.; Manzoni, R. A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Ragazzi, S.; Redaelli, N.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; Di Guida, S.; Esposito, M.; Fabozzi, F.; Iorio, A. O. M.; Lanza, G.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Branca, A.; Carlin, R.; Checchia, P.; Dall'Osso, M.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Kanishchev, K.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pegoraro, M.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Tosi, M.; Zanetti, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Biasini, M.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Spiezia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Broccolo, G.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fedi, G.; Foà, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Serban, A. T.; Spagnolo, P.; Squillacioti, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; D'imperio, G.; Del Re, D.; Diemoz, M.; Gelli, S.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Traczyk, P.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bellan, R.; Biino, C.; Cartiglia, N.; Costa, M.; Covarelli, R.; Degano, A.; Dellacasa, G.; Demaria, N.; Finco, L.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Musich, M.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. 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P., III; Majumder, D.; Malek, M.; Murray, M.; Sanders, S.; Stringer, R.; Wang, Q.; Ivanov, A.; Kaadze, K.; Khalil, S.; Makouski, M.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Lange, D.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Gomez, J. A.; Hadley, N. J.; Jabeen, S.; Kellogg, R. G.; Kolberg, T.; Kunkle, J.; Lu, Y.; Mignerey, A. C.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Baty, A.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; Demiragli, Z.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Marini, A. C.; Mcginn, C.; Mironov, C.; Niu, X.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Sumorok, K.; Varma, M.; Velicanu, D.; Veverka, J.; Wang, J.; Wang, T. W.; Wyslouch, B.; Yang, M.; Zhukova, V.; Dahmes, B.; Evans, A.; Finkel, A.; Gude, A.; Hansen, P.; Kalafut, S.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Meier, F.; Monroy, J.; Ratnikov, F.; Siado, J. E.; Snow, G. R.; Alyari, M.; Dolen, J.; George, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Kaisen, J.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wang, R.-J.; Wood, D.; Zhang, J.; Hahn, K. A.; Kubik, A.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Trovato, M.; Velasco, M.; Brinkerhoff, A.; Dev, N.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Lynch, S.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Pearson, T.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hart, A.; Hill, C.; Hughes, R.; Ji, W.; Kotov, K.; Ling, T. Y.; Liu, B.; Luo, W.; Puigh, D.; Rodenburg, M.; Winer, B. L.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Palmer, C.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Malik, S.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Sun, J.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Redjimi, R.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Harel, A.; Hindrichs, O.; Khukhunaishvili, A.; Petrillo, G.; Verzetti, M.; Demortier, L.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Lath, A.; Nash, K.; Panwalkar, S.; Park, M.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Foerster, M.; Riley, G.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Krutelyov, V.; Mueller, R.; Osipenkov, I.; Pakhotin, Y.; Patel, R.; Perloff, A.; Rose, A.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Undleeb, S.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Ni, H.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Sun, X.; Wang, Y.; Wolfe, E.; Wood, J.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Christian, A.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Gomber, B.; Grothe, M.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ruggles, T.; Sarangi, T.; Savin, A.; Sharma, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.; CMS Collaboration

2016-07-01

The consistency of the spin correlation strength in top quark pair production with the standard model (SM) prediction is tested in the muon+jets final state. The events are selected from pp collisions, collected by the CMS detector, at a centre-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 19.7 fb-1. The data are compared with the expectation for the spin correlation predicted by the SM and with the expectation of no correlation. Using a template fit method, the fraction of events that show SM spin correlations is measured to be 0.72 ± 0.08(stat)0.13+0.15 (syst), representing the most precise measurement of this quantity in the muon+jets final state to date.

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

PubMed

Sherer, Eric A; Sale, Mark E; Pollock, Bruce G; Belani, Chandra P; Egorin, Merrill J; Ivy, Percy S; Lieberman, Jeffrey A; Manuck, Stephen B; Marder, Stephen R; Muldoon, Matthew F; Scher, Howard I; Solit, David B; Bies, Robert R

2012-08-01

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data.

Several Well-observed Asteroidal Occultations in 2010

NASA Astrophysics Data System (ADS)

Timerson, Brad; Durech, J.; Abramson, H.; Brooks, J.; Caton, D.; Clark, D.; Conard, S.; Cooke, B.; Dunham, D. W.; Dunham, J.; Edberg, S.; Ellington, C.; Faircloth, J.; Herchak, S.; Iverson, E.; Jones, R.; Lucas, G.; Lyzenga, G.; Maley, P.; Martinez, L.; Menke, J.; Mroz, G.; Nolan, P.; Peterson, R.; Preston, S.; Rattley, G.; Ray, J.; Scheck, A.; Stamm, J.; Stanton, R.; Suggs, R.; Tatum, R.; Thomas, W.

2011-10-01

During 2010 IOTA observers in North America reported about 190 positive observations for 106 asteroid occultation events. For several asteroids, this included observations with multiple chords. For two events, an inversion model was available. An occultation by 16 Psyche on 2010 August 21 yielded a best-fit ellipse of 235.4 x 230.4 km. On 2010 December 24, an occultation by 93 Minerva produced a best-fit ellipse of 179.4 x 133.4 km. An occultation by 96 Aegle on 2010 October 29 yielded a best-fit ellipse of 124.9 x 88.0 km. An occultation by 105 Artemis on 2010 June 24 showed a best-fit ellipse of 125.0 x 92.0 km. An occultation by 375 Ursula on 2010 December 4 produced a best-fit ellipse of 125.0 km x 135.0 km. Of note are two events not summarized in this article. On 2010 August 31, an occultation by 695 Bella yielded a new double star. That event will be summarized in the JDSO. Finally, on 2010 April 6, an occultation of zeta Ophiuchi by 824 Anastasia was observed by 65 observers at 69 locations. Unfortunately a large shift in the path yielded only 4 chords. Results of that event, and all the events mentioned here, can be found on the North American Asteroidal Occultation Results web page.

Measurement of the $$ \\mathrm{t}\\overline{\\mathrm{t}} $$ production cross section in the all-jet final state in pp collisions at $$ \\sqrt{s}=7 $$ TeV

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.

A measurement is presented of themore » $$t\\bar{t}$$ cross section $$(\\sigma_{t\\bar{t}})$$ in proton-proton collisions at a centre-of-mass energy of 7 TeV, in the all-jet final state that contains at least six jets, two of which are tagged as likely originating from b quarks. The data correspond to an integrated luminosity of 3.54 inverse femtobarns, collected with the CMS detector at the LHC. The cross section is determined through an unbinned maximum likelihood fit of contributions from background and t t-bar signal to the reconstructed mass spectrum of t t-bar candidates in the data, in which events are subjected to a kinematic fit assuming a $$t\\bar{t} \\to W^+ b W^- \\bar{b} \\to 6$$ jets hypothesis. The measurement yields $$\\sigma_{t\\bar{t}} = 139 \\pm 10 (stat.) \\pm 26 (syst.) \\pm 3 (lum.)$$ pb, a result consistent with those obtained in other $$t\\bar{t}$$ decay channels, as well as with predictions of the standard model.« less

On the streaming model for redshift-space distortions

NASA Astrophysics Data System (ADS)

Kuruvilla, Joseph; Porciani, Cristiano

2018-06-01

The streaming model describes the mapping between real and redshift space for 2-point clustering statistics. Its key element is the probability density function (PDF) of line-of-sight pairwise peculiar velocities. Following a kinetic-theory approach, we derive the fundamental equations of the streaming model for ordered and unordered pairs. In the first case, we recover the classic equation while we demonstrate that modifications are necessary for unordered pairs. We then discuss several statistical properties of the pairwise velocities for DM particles and haloes by using a suite of high-resolution N-body simulations. We test the often used Gaussian ansatz for the PDF of pairwise velocities and discuss its limitations. Finally, we introduce a mixture of Gaussians which is known in statistics as the generalised hyperbolic distribution and show that it provides an accurate fit to the PDF. Once inserted in the streaming equation, the fit yields an excellent description of redshift-space correlations at all scales that vastly outperforms the Gaussian and exponential approximations. Using a principal-component analysis, we reduce the complexity of our model for large redshift-space separations. Our results increase the robustness of studies of anisotropic galaxy clustering and are useful for extending them towards smaller scales in order to test theories of gravity and interacting dark-energy models.

Anxiety, Depression and Hopelessness in Adolescents: A Structural Equation Model

PubMed Central

Cunningham, Shaylyn; Gunn, Thelma; Alladin, Assen; Cawthorpe, David

2008-01-01

Objective This study tested a structural model, examining the relationship between a latent variable termed demoralization and measured variables (anxiety, depression and hopelessness) in a community sample of Canadian youth. Methods The combined sample consisted of data collected from four independent studies from 2001 to 2005. Nine hundred and seventy one (n=971) participants were high school students (grades 10–12) from three geographic locations: Calgary, Saskatchewan and Lethbridge. Participants completed the Beck Anxiety Inventory (BAI), Beck Depression Inventory-Revised (BDI-II), Beck Hopelessness Scale (BHS), and demographic survey. Structural equation modeling was used for statistical analysis. Results The analysis revealed that the final model, including depression, anxiety and hopelessness and one latent variable demoralization, fit the data (chi-square value, X2 (2) = 7.25, p< .001, goodness of fit indices (CFI=0.99, NFI=0.98) and standardized error (0.05). Overall, the findings suggest that close relationships exist among depression, anxiety, hopelessness and demoralization that is stable across demographic variables. Further, the model explains the relationship between sub-clinical anxiety, depression and hopelessness. Conclusion These findings contribute to a theoretical framework, which has implications for educational and clinical intervention. The present findings will help guide further preventative research on examining demoralization as a precursor to sub-clinical anxiety and depression. PMID:18769644

Desire thinking: what is it and what drives it?

PubMed

Caselli, Gabriele; Spada, Marcantonio M

2015-05-01

The aim of this study was to provide an overview of the construct of desire thinking and test a metacognitive model of desire thinking and craving, based on the work of Spada, Caselli and Wells (2012; 2013), which aims to explain the perseveration of desire thinking. We conducted two studies involving four clinical samples (total N = 493) and a community sample (N = 494) presenting with different addictive behaviors. The relationships among variables were examined by testing the fit of path models within each sample. In the model presented it was proposed that positive metacognitions about desire thinking are associated with, in turn, imaginal prefiguration and verbal perseveration, marking the activation of desire thinking. Verbal perseveration is then associated to negative metacognitions about desire thinking and craving denoting the pathological escalation of desire thinking. Finally, a direct association between positive metacognitions about desire thinking and negative metacognitions about desire thinking would mark those occasions where target-achieving behaviour runs as an automatized schemata without the experience of craving. Results indicated a good model fit in the clinical sample and a variation in the model structure in the community sample. These findings provide further support for the application of metacognitive theory to desire thinking and craving in addictive behaviors. Copyright © 2014 Elsevier Ltd. All rights reserved.

Interactive planning of miniplates

NASA Astrophysics Data System (ADS)

Gall, Markus; Reinbacher, Knut; Wallner, Jürgen; Stanzel, Jan; Chen, Xiaojun; Schwenzer-Zimmerer, Katja; Schmalstieg, Dieter; Egger, Jan

2017-03-01

In this contribution, a novel method for computer aided surgery planning of facial defects by using models of purchasable MedArtis Modus 2.0 miniplates is proposed. Implants of this kind, which belong to the osteosynthetic material, are commonly used for treating defects in the facial area. By placing them perpendicular on the defect, the miniplates are fixed on the healthy bone, bent with respect to the surface, to stabilize the defective area. Our software is able to fit a selection of the most common implant models to the surgeon's desired position in a 3D computer model. The fitting respects the local surface curvature and adjusts direction and position in any desired way. Conventional methods use Computed Tomography (CT) scans to generate STereoLithic (STL) models serving as bending template for the implants or use a bending tool during the surgery for readjusting the implant several times. Both approaches lead to undesirable expenses in time. With our visual planning tool, surgeons are able to pre-plan the final implant within just a few minutes. The resulting model can be stored in STL format, which is the commonly used format for 3D printing. With this technology, surgeons are able to print the implant just in time or use it for generating a bending tool, both leading to an exactly bent miniplate.

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…

An Applied Framework for Incorporating Multiple Sources of Uncertainty in Fisheries Stock Assessments.

PubMed

Scott, Finlay; Jardim, Ernesto; Millar, Colin P; Cerviño, Santiago

2016-01-01

Estimating fish stock status is very challenging given the many sources and high levels of uncertainty surrounding the biological processes (e.g. natural variability in the demographic rates), model selection (e.g. choosing growth or stock assessment models) and parameter estimation. Incorporating multiple sources of uncertainty in a stock assessment allows advice to better account for the risks associated with proposed management options, promoting decisions that are more robust to such uncertainty. However, a typical assessment only reports the model fit and variance of estimated parameters, thereby underreporting the overall uncertainty. Additionally, although multiple candidate models may be considered, only one is selected as the 'best' result, effectively rejecting the plausible assumptions behind the other models. We present an applied framework to integrate multiple sources of uncertainty in the stock assessment process. The first step is the generation and conditioning of a suite of stock assessment models that contain different assumptions about the stock and the fishery. The second step is the estimation of parameters, including fitting of the stock assessment models. The final step integrates across all of the results to reconcile the multi-model outcome. The framework is flexible enough to be tailored to particular stocks and fisheries and can draw on information from multiple sources to implement a broad variety of assumptions, making it applicable to stocks with varying levels of data availability The Iberian hake stock in International Council for the Exploration of the Sea (ICES) Divisions VIIIc and IXa is used to demonstrate the framework, starting from length-based stock and indices data. Process and model uncertainty are considered through the growth, natural mortality, fishing mortality, survey catchability and stock-recruitment relationship. Estimation uncertainty is included as part of the fitting process. Simple model averaging is used to integrate across the results and produce a single assessment that considers the multiple sources of uncertainty.

Mechanical modeling for magnetorheological elastomer isolators based on constitutive equations and electromagnetic analysis

NASA Astrophysics Data System (ADS)

Wang, Qi; Dong, Xufeng; Li, Luyu; Ou, Jinping

2018-06-01

As constitutive models are too complicated and existing mechanical models lack universality, these models are beyond satisfaction for magnetorheological elastomer (MRE) devices. In this article, a novel universal method is proposed to build concise mechanical models. Constitutive model and electromagnetic analysis were applied in this method to ensure universality, while a series of derivations and simplifications were carried out to obtain a concise formulation. To illustrate the proposed modeling method, a conical MRE isolator was introduced. Its basic mechanical equations were built based on equilibrium, deformation compatibility, constitutive equations and electromagnetic analysis. An iteration model and a highly efficient differential equation editor based model were then derived to solve the basic mechanical equations. The final simplified mechanical equations were obtained by re-fitting the simulations with a novel optimal algorithm. In the end, verification test of the isolator has proved the accuracy of the derived mechanical model and the modeling method.

Indirect genetic effect model using feeding behaviour traits to define the degree of interaction between mates: an implementation in pigs growth rate.

PubMed

Ragab, M; Piles, M; Quintanilla, R; Sánchez, J P

2018-06-06

An alternative implementation of the animal model including indirect genetic effect (IGE) is presented considering pair-mate-specific interaction degrees to improve the performance of the model. Data consisted of average daily gain (ADG) records from 663 pigs kept in groups of 10 to 14 mates during the fattening period. Three types of models were used to fit ADG data: (i) animal model (AM); (ii) AM with classical IGE (AM-IGE); and (iii) AM fitting IGE with a specific degree of interaction between each pair of mates (AM-IGEi). Several feeding behavior phenotypes were used to define the pair-mate-specific degree of interaction in AM-IGEi: feeding rate (g/min), feeding frequency (min/day), the time between consecutive visits to the feeder (min/day), occupation time (min/day) and an index considering all these variables. All models included systematic effects batch, initial age (covariate), final age (covariate), number of pigs per pen (covariate), plus the random effect of the pen. Estimated posterior mean (posterior SD) of heritability was 0.47 (0.15) using AM. Including social genetic effects in the model, total heritable variance expressed as a proportion of total phenotypic variance (T 2) was 0.54 (0.29) using AM-IGE, whereas it ranged from 0.51 to 0.55 (0.12 to 0.14) with AM-IGEi, depending on the behavior trait used to define social interactions. These results confirm the contribution of IGEs to the total heritable variation of ADG. Moreover, important differences between models were observed in EBV rankings. The percentage of coincidence of top 10% animals between AM and AM-IGEi ranged from 0.44 to 0.89 and from 0.41to 0.68 between AM-IGE and AM-IGEi. Based on the goodness of fit and predictive ability, social models are preferred for the genetic evaluation of ADG. Among models including IGEs, when the pair-specific degree of interaction was defined using feeding behavior phenotypes we obtained an increase in the accuracy of genetic parameters estimates, the better goodness of fit and higher predictive ability. We conclude that feeding behavior variables can be used to measure the interaction between pen mates and to improve the performance of models including IGEs.

Disk Emission from Magnetohydrodynamic Simulations of Spinning Black Holes

NASA Technical Reports Server (NTRS)

Schnittman, Jeremy D.; Krolik, Julian H.; Noble, Scott C.

2016-01-01

We present the results of a new series of global, three-dimensional, relativistic magnetohydrodynamic (MHD) simulations of thin accretion disks around spinning black holes. The disks have aspect ratios of H/R approx. 0.05 and spin parameters of a/M = 0, 0.5, 0.9, and 0.99. Using the ray-tracing code Pandurata, we generate broadband thermal spectra and polarization signatures from the MHD simulations. We find that the simulated spectra can be well fit with a simple, universal emissivity profile that better reproduces the behavior of the emission from the inner disk, compared to traditional analyses carried out using a Novikov-Thorne thin disk model. Finally, we show how spectropolarization observations can be used to convincingly break the spin-inclination degeneracy well known to the continuum-fitting method of measuring black hole spin.

The PROMIS fatigue item bank has good measurement properties in patients with fibromyalgia and severe fatigue.

PubMed

Yost, Kathleen J; Waller, Niels G; Lee, Minji K; Vincent, Ann

2017-06-01

Efficient management of fibromyalgia (FM) requires precise measurement of FM-specific symptoms. Our objective was to assess the measurement properties of the Patient-Reported Outcome Measurement Information System (PROMIS) fatigue item bank (FIB) in people with FM. We applied classical psychometric and item response theory methods to cross-sectional PROMIS-FIB data from two samples. Data on the clinical FM sample were obtained at a tertiary medical center. Data for the U.S. general population sample were obtained from the PROMIS network. The full 95-item bank was administered to both samples. We investigated dimensionality of the item bank in both samples by separately fitting a bifactor model with two group factors; experience and impact. We assessed measurement invariance between samples, and we explored an alternate factor structure with the normative sample and subsequently confirmed that structure in the clinical sample. Finally, we assessed whether reporting FM subdomain scores added value over reporting a single total score. The item bank was dominated by a general fatigue factor. The fit of the initial bifactor model and evidence of measurement invariance indicated that the same constructs were measured across the samples. An alternative bifactor model with three group factors demonstrated slightly improved fit. Subdomain scores add value over a total score. We demonstrated that the PROMIS-FIB is appropriate for measuring fatigue in clinical samples of FM patients. The construct can be presented by a single score; however, subdomain scores for the three group factors identified in the alternative model may also be reported.

Development of a Polarizable Force Field For Proteins via Ab Initio Quantum Chemistry: First Generation Model and Gas Phase Tests

PubMed Central

KAMINSKI, GEORGE A.; STERN, HARRY A.; BERNE, B. J.; FRIESNER, RICHARD A.; CAO, YIXIANG X.; MURPHY, ROBERT B.; ZHOU, RUHONG; HALGREN, THOMAS A.

2014-01-01

We present results of developing a methodology suitable for producing molecular mechanics force fields with explicit treatment of electrostatic polarization for proteins and other molecular system of biological interest. The technique allows simulation of realistic-size systems. Employing high-level ab initio data as a target for fitting allows us to avoid the problem of the lack of detailed experimental data. Using the fast and reliable quantum mechanical methods supplies robust fitting data for the resulting parameter sets. As a result, gas-phase many-body effects for dipeptides are captured within the average RMSD of 0.22 kcal/mol from their ab initio values, and conformational energies for the di- and tetrapeptides are reproduced within the average RMSD of 0.43 kcal/mol from their quantum mechanical counterparts. The latter is achieved in part because of application of a novel torsional fitting technique recently developed in our group, which has already been used to greatly improve accuracy of the peptide conformational equilibrium prediction with the OPLS-AA force field.1 Finally, we have employed the newly developed first-generation model in computing gas-phase conformations of real proteins, as well as in molecular dynamics studies of the systems. The results show that, although the overall accuracy is no better than what can be achieved with a fixed-charges model, the methodology produces robust results, permits reasonably low computational cost, and avoids other computational problems typical for polarizable force fields. It can be considered as a solid basis for building a more accurate and complete second-generation model. PMID:12395421

Non-Targeted Effects and the Dose Response for Heavy Ion Tumorigenesis

NASA Technical Reports Server (NTRS)

Chappelli, Lori J.; Cucinotta, Francis A.

2010-01-01

BACKGROUND: There is no human epidemiology data available to estimate the heavy ion cancer risks experienced by astronauts in space. Studies of tumor induction in mice are a necessary step to estimate risks to astronauts. Previous experimental data can be better utilized to model dose response for heavy ion tumorigenesis and plan future low dose studies. DOSE RESPONSE MODELS: The Harderian Gland data of Alpen et al.[1-3] was re-analyzed [4] using non-linear least square regression. The data set measured the induction of Harderian gland tumors in mice by high-energy protons, helium, neon, iron, niobium and lanthanum with LET s ranging from 0.4 to 950 keV/micron. We were able to strengthen the individual ion models by combining data for all ions into a model that relates both radiation dose and LET for the ion to tumor prevalence. We compared models based on Targeted Effects (TE) to one motivated by Non-targeted Effects (NTE) that included a bystander term that increased tumor induction at low doses non-linearly. When comparing fitted models to the experimental data, we considered the adjusted R2, the Akaike Information Criteria (AIC), and the Bayesian Information Criteria (BIC) to test for Goodness of fit.In the adjusted R2test, the model with the highest R2values provides a better fit to the available data. In the AIC and BIC tests, the model with the smaller values of the summary value provides the better fit. The non-linear NTE models fit the combined data better than the TE models that are linear at low doses. We evaluated the differences in the relative biological effectiveness (RBE) and found the NTE model provides a higher RBE at low dose compared to the TE model. POWER ANALYSIS: The final NTE model estimates were used to simulate example data to consider the design of new experiments to detect NTE at low dose for validation. Power and sample sizes were calculated for a variety of radiation qualities including some not considered in the Harderian Gland data set and with different background tumor incidences. We considered different experimental designs with varying number of doses and varying low doses dependant on the LET of the radiation. The optimal design to detect a NTE for an individual ion had 4 doses equally spaced below a maximal dose where bending due to cell sterilization was < 2%. For example at 100 keV/micron we would irradiate at 0.03 Gy, 0.065 Gy, 0.13 Gy, and 0.26 Gy and require 850 mice including a control dose for a sensitivity to detect NTE with 80% power. Sample sizes could be improved by combining ions similar to the methods used with the Harderian Gland data.

Relative risk for HIV in India - An estimate using conditional auto-regressive models with Bayesian approach.

PubMed

Kandhasamy, Chandrasekaran; Ghosh, Kaushik

2017-02-01

Indian states are currently classified into HIV-risk categories based on the observed prevalence counts, percentage of infected attendees in antenatal clinics, and percentage of infected high-risk individuals. This method, however, does not account for the spatial dependence among the states nor does it provide any measure of statistical uncertainty. We provide an alternative model-based approach to address these issues. Our method uses Poisson log-normal models having various conditional autoregressive structures with neighborhood-based and distance-based weight matrices and incorporates all available covariate information. We use R and WinBugs software to fit these models to the 2011 HIV data. Based on the Deviance Information Criterion, the convolution model using distance-based weight matrix and covariate information on female sex workers, literacy rate and intravenous drug users is found to have the best fit. The relative risk of HIV for the various states is estimated using the best model and the states are then classified into the risk categories based on these estimated values. An HIV risk map of India is constructed based on these results. The choice of the final model suggests that an HIV control strategy which focuses on the female sex workers, intravenous drug users and literacy rate would be most effective. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

MIMO system identification using frequency response data

NASA Technical Reports Server (NTRS)

Medina, Enrique A.; Irwin, R. D.; Mitchell, Jerrel R.; Bukley, Angelia P.

1992-01-01

A solution to the problem of obtaining a multi-input, multi-output statespace model of a system from its individual input/output frequency responses is presented. The Residue Identification Algorithm (RID) identifies the system poles from a transfer function model of the determinant of the frequency response data matrix. Next, the residue matrices of the modes are computed guaranteeing that each input/output frequency response is fitted in the least squares sense. Finally, a realization of the system is computed. Results of the application of RID to experimental frequency responses of a large space structure ground test facility are presented and compared to those obtained via the Eigensystem Realization Algorithm.

Developing a Dynamic Pharmacophore Model for HIV-1 Integrase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlson, Heather A.; Masukawa, Keven M.; Rubins, Kathleen

2000-05-11

We present the first receptor-based pharmacophore model for HIV-1 integrase. The development of ''dynamic'' pharmacophore models is a new method that accounts for the inherent flexibility of the active site and aims to reduce the entropic penalties associated with binding a ligand. Furthermore, this new drug discovery method overcomes the limitation of an incomplete crystal structure of the target protein. A molecular dynamics (MD) simulation describes the flexibility of the uncomplexed protein. Many conformational models of the protein are saved from the MD simulations and used in a series of multi-unit search for interacting conformers (MUSIC) simulations. MUSIC is amore » multiple-copy minimization method, available in the BOSS program; it is used to determine binding regions for probe molecules containing functional groups that complement the active site. All protein conformations from the MD are overlaid, and conserved binding regions for the probe molecules are identified. Those conserved binding regions define the dynamic pharmacophore model. Here, the dynamic model is compared to known inhibitors of the integrase as well as a three-point, ligand-based pharmacophore model from the literature. Also, a ''static'' pharmacophore model was determined in the standard fashion, using a single crystal structure. Inhibitors thought to bind in the active site of HIV-1 integrase fit the dynamic model but not the static model. Finally, we have identified a set of compounds from the Available Chemicals Directory that fit the dynamic pharmacophore model, and experimental testing of the compounds has confirmed several new inhibitors.« less

Validation of the internalization of the Model Minority Myth Measure (IM-4) and its link to academic performance and psychological adjustment among Asian American adolescents.

PubMed

Yoo, Hyung Chol; Miller, Matthew J; Yip, Pansy

2015-04-01

There is limited research examining psychological correlates of a uniquely racialized experience of the model minority stereotype faced by Asian Americans. The present study examined the factor structure and fit of the only published measure of the internalization of the model minority myth, the Internalization of the Model Minority Myth Measure (IM-4; Yoo et al., 2010), with a sample of 155 Asian American high school adolescents. We also examined the link between internalization of the model minority myth types (i.e., myth associated with achievement and myth associated with unrestricted mobility) and psychological adjustment (i.e., affective distress, somatic distress, performance difficulty, academic expectations stress), and the potential moderating effect of academic performance (cumulative grade point average). Results suggested the 2-factor model of the IM-4 had an acceptable fit to the data and supported the factor structure using confirmatory factor analyses. Internalizing the model minority myth of achievement related positively to academic expectations stress; however, internalizing the model minority myth of unrestricted mobility related negatively to academic expectations stress, both controlling for gender and academic performance. Finally, academic performance moderated the model minority myth associated with unrestricted mobility and affective distress link and the model minority myth associated with achievement and performance difficulty link. These findings highlight the complex ways in which the model minority myth relates to psychological outcomes. (c) 2015 APA, all rights reserved).

Model fit evaluation in multilevel structural equation models

PubMed Central

Ryu, Ehri

2014-01-01

Assessing goodness of model fit is one of the key questions in structural equation modeling (SEM). Goodness of fit is the extent to which the hypothesized model reproduces the multivariate structure underlying the set of variables. During the earlier development of multilevel structural equation models, the “standard” approach was to evaluate the goodness of fit for the entire model across all levels simultaneously. The model fit statistics produced by the standard approach have a potential problem in detecting lack of fit in the higher-level model for which the effective sample size is much smaller. Also when the standard approach results in poor model fit, it is not clear at which level the model does not fit well. This article reviews two alternative approaches that have been proposed to overcome the limitations of the standard approach. One is a two-step procedure which first produces estimates of saturated covariance matrices at each level and then performs single-level analysis at each level with the estimated covariance matrices as input (Yuan and Bentler, 2007). The other level-specific approach utilizes partially saturated models to obtain test statistics and fit indices for each level separately (Ryu and West, 2009). Simulation studies (e.g., Yuan and Bentler, 2007; Ryu and West, 2009) have consistently shown that both alternative approaches performed well in detecting lack of fit at any level, whereas the standard approach failed to detect lack of fit at the higher level. It is recommended that the alternative approaches are used to assess the model fit in multilevel structural equation model. Advantages and disadvantages of the two alternative approaches are discussed. The alternative approaches are demonstrated in an empirical example. PMID:24550882

Improved fabrication of electrolytic capacitors

NASA Technical Reports Server (NTRS)

Gamari, F. J.; Moresi, J. L.

1975-01-01

After processing parts for assembly, insulative cup is fitted to bottom of can, then electrolytic solution consisting of white sulfuric acid gel is inserted into can. Pellet is put in can and is fitted tightly into cup. Finally, bead weld is formed between can and header plug.

Physical activity, self-efficacy and self-esteem in breast cancer survivors: a panel model.

PubMed

Awick, Elizabeth A; Phillips, Siobhan M; Lloyd, Gillian R; McAuley, Edward

2017-10-01

Physical activity (PA) has been consistently associated with improved self-esteem in breast cancer survivors. However, this relationship is poorly understood. The purpose of this study was to examine whether changes in PA and self-efficacy influenced changes in self-esteem in breast cancer survivors across 6 months. Increases in PA were hypothesized to result in increases in self-efficacy, which were hypothesized to influence increases in physical self-worth (PSW) and global self-esteem. Breast cancer survivors (n = 370; M age  = 56.04) wore accelerometers to measure PA and completed measures of self-efficacy (e.g., exercise and barriers self-efficacy), PSW, and global self-esteem at baseline and 6 months. The hypothesized model provided a good fit to the data (χ 2  = 67.56, df = 26, p < 0.001; comparative fit index (CFI) = 0.98; standardized root mean residual = 0.05). Women with higher activity at baseline reported significantly higher levels of barrier (β = 0.29) and exercise (β = 0.23) self-efficacy. In turn, more efficacious women reported significantly higher PSW (β = 0.26, 0.16). Finally, higher PSW was significantly associated with greater global self-esteem (β = 0.47). Relationships were similar among changes in model constructs over 6 months. After controlling for covariates, the hypothesized model provided an excellent fit to the data (χ 2  = 59.93, df = 33, p = 0.003; comparative fit index = 0.99; standardized root mean residual = 0.03). Our findings provide support for the role played by PA and self-efficacy in positive self-esteem, a key component of well-being. Highlighting successful PA mastery experiences is likely to enhance self-efficacy and improve self-esteem in this population. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

On the Early-Time Excess Emission in Hydrogen-Poor Superluminous Supernovae

NASA Technical Reports Server (NTRS)

Vreeswijk, Paul M.; Leloudas, Giorgos; Gal-Yam, Avishay; De Cia, Annalisa; Perley, Daniel A.; Quimby, Robert M.; Waldman, Roni; Sullivan, Mark; Yan, Lin; Ofek, Eran O.;

On The Early-Time Excess Emission In Hydrogen-Poor Superluminous Supernovae

DOE PAGES

Vreeswijk, Paul M.; Leloudas, Giorgos; Gal-Yam, Avishay; ...

2017-01-18

Here, we present the light curves of the hydrogen-poor superluminous supernovae (SLSNe I) PTF 12dam and iPTF 13dcc, discovered by the (intermediate) Palomar Transient Factory. Both show excess emission at early times and a slowly declining light curve at late times. The early bump in PTF 12dam is very similar in duration (~10 days) and brightness relative to the main peak (2-3 mag fainter) compared to that observed in other SLSNe I. In contrast, the long-duration ( > 30 days) early excess emission in iPTF 13dcc, whose brightness competes with that of the main peak, appears to be of amore » different nature. We construct bolometric light curves for both targets, and fit a variety of light-curve models to both the early bump and main peak in an attempt to understand the nature of these explosions. Even though the slope of the late-time decline in the light curves of both SLSNe is suggestively close to that expected from the radioactive decay of 56Ni and 56Co, the amount of nickel required to power the full light curves is too large considering the estimated ejecta mass. The magnetar model including an increasing escape fraction provides a reasonable description of the PTF 12dam observations. However, neither the basic nor the double-peaked magnetar model is capable of reproducing the light curve of iPTF 13dcc. A model combining a shock breakout in an extended envelope with late-time magnetar energy injection provides a reasonable fit to the iPTF 13dcc observations. Finally, we find that the light curves of both PTF 12dam and iPTF 13dcc can be adequately fit with the model involving interaction with the circumstellar medium.« less

ON THE EARLY-TIME EXCESS EMISSION IN HYDROGEN-POOR SUPERLUMINOUS SUPERNOVAE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vreeswijk, Paul M.; Leloudas, Giorgos; Gal-Yam, Avishay

2017-01-20

We present the light curves of the hydrogen-poor superluminous supernovae (SLSNe I) PTF 12dam and iPTF 13dcc, discovered by the (intermediate) Palomar Transient Factory. Both show excess emission at early times and a slowly declining light curve at late times. The early bump in PTF 12dam is very similar in duration (∼10 days) and brightness relative to the main peak (2–3 mag fainter) compared to that observed in other SLSNe I. In contrast, the long-duration (>30 days) early excess emission in iPTF 13dcc, whose brightness competes with that of the main peak, appears to be of a different nature. Wemore » construct bolometric light curves for both targets, and fit a variety of light-curve models to both the early bump and main peak in an attempt to understand the nature of these explosions. Even though the slope of the late-time decline in the light curves of both SLSNe is suggestively close to that expected from the radioactive decay of {sup 56}Ni and {sup 56}Co, the amount of nickel required to power the full light curves is too large considering the estimated ejecta mass. The magnetar model including an increasing escape fraction provides a reasonable description of the PTF 12dam observations. However, neither the basic nor the double-peaked magnetar model is capable of reproducing the light curve of iPTF 13dcc. A model combining a shock breakout in an extended envelope with late-time magnetar energy injection provides a reasonable fit to the iPTF 13dcc observations. Finally, we find that the light curves of both PTF 12dam and iPTF 13dcc can be adequately fit with the model involving interaction with the circumstellar medium.« less

Accurate and noninvasive embryos screening during in vitro fertilization (IVF) assisted by Raman analysis of embryos culture medium Accurate and noninvasive embryos screening during IVF

NASA Astrophysics Data System (ADS)

Shen, A. G.; Peng, J.; Zhao, Q. H.; Su, L.; Wang, X. H.; Hu, J. M.; Yang, J.

2012-04-01

In combination with morphological evaluation tests, we employ Raman spectroscopy to select higher potential reproductive embryos during in vitro fertilization (IVF) based on chemical composition of embryos culture medium. In this study, 57 Raman spectra are acquired from both higher and lower quality embryos culture medium (ECM) from 10 patients which have been preliminarily confirmed by clinical assay. Data are fit by using a linear combination model of least squares method in which 12 basis spectra represent the chemical features of ECM. The final fitting coefficients provide insight into the chemical compositions of culture medium samples and are subsequently used as criterion to evaluate the quality of embryos. The relative fitting coefficients ratios of sodium pyruvate/albumin and phenylalanine/albumin seem act as key roles in the embryo screening, attaining 85.7% accuracy in comparison with clinical pregnancy. The good results demonstrate that Raman spectroscopy therefore is an important candidate for an accurate and noninvasive screening of higher quality embryos, which potentially decrease the time-consuming clinical trials during IVF.

Turbulent and directed plasma motions in solar flares

NASA Technical Reports Server (NTRS)

Fludra, A.; Bentley, R. D.; Lemen, J. R.; Jakimiec, J.; Sylwester, J.

1989-01-01

An improved method for fitting asymmetric soft X-ray line profiles from solar flares is presented. A two-component model is used where one component represents the total emission from directed upflow plasma and the other the emission from the plasma at rest. Unlike previous methods, the width of the moving component is independent from that of the stationary component. Time variations of flare plasma characteristics (i.e., temperature, emission measure of moving and stationary plasma, upflow and turbulent velocities) are derived from the Ca XIX and Fe XXV spectra recorded by the Bent Crystal Spectrometer on the Solar Maximum Mission. The fitting technique provides a statistical estimation for the uncertainties in the fitting parameters. The relationship between the directed and turbulent motions has been studied, and a correlation of the random and directed motions has been found in some flares with intensive plasma upflows. Mean temperatures of the upflowing and stationary plasmas are compared for the first time from ratios of calcium to iron X-ray line intensities. Finally, evidence for turbulent motions and the possibility of plasma upflow late into the decay phase is presented and discussed.

Fit Assessment of N95 Filtering-Facepiece Respirators in the U.S. Centers for Disease Control and Prevention Strategic National Stockpile.

PubMed

Bergman, Michael; Zhuang, Ziqing; Brochu, Elizabeth; Palmiero, Andrew

National Institute for Occupational Safety and Health (NIOSH)-approved N95 filtering-facepiece respirators (FFR) are currently stockpiled by the U.S. Centers for Disease Control and Prevention (CDC) for emergency deployment to healthcare facilities in the event of a widespread emergency such as an influenza pandemic. This study assessed the fit of N95 FFRs purchased for the CDC Strategic National Stockpile. The study addresses the question of whether the fit achieved by specific respirator sizes relates to facial size categories as defined by two NIOSH fit test panels. Fit test data were analyzed from 229 test subjects who performed a nine-donning fit test on seven N95 FFR models using a quantitative fit test protocol. An initial respirator model selection process was used to determine if the subject could achieve an adequate fit on a particular model; subjects then tested the adequately fitting model for the nine-donning fit test. Only data for models which provided an adequate initial fit (through the model selection process) for a subject were analyzed for this study. For the nine-donning fit test, six of the seven respirator models accommodated the fit of subjects (as indicated by geometric mean fit factor > 100) for not only the intended NIOSH bivariate and PCA panel sizes corresponding to the respirator size, but also for other panel sizes which were tested for each model. The model which showed poor performance may not be accurately represented because only two subjects passed the initial selection criteria to use this model. Findings are supportive of the current selection of facial dimensions for the new NIOSH panels. The various FFR models selected for the CDC Strategic National Stockpile provide a range of sizing options to fit a variety of facial sizes.

Fit Assessment of N95 Filtering-Facepiece Respirators in the U.S. Centers for Disease Control and Prevention Strategic National Stockpile

PubMed Central

Bergman, Michael; Zhuang, Ziqing; Brochu, Elizabeth; Palmiero, Andrew

2016-01-01

National Institute for Occupational Safety and Health (NIOSH)-approved N95 filtering-facepiece respirators (FFR) are currently stockpiled by the U.S. Centers for Disease Control and Prevention (CDC) for emergency deployment to healthcare facilities in the event of a widespread emergency such as an influenza pandemic. This study assessed the fit of N95 FFRs purchased for the CDC Strategic National Stockpile. The study addresses the question of whether the fit achieved by specific respirator sizes relates to facial size categories as defined by two NIOSH fit test panels. Fit test data were analyzed from 229 test subjects who performed a nine-donning fit test on seven N95 FFR models using a quantitative fit test protocol. An initial respirator model selection process was used to determine if the subject could achieve an adequate fit on a particular model; subjects then tested the adequately fitting model for the nine-donning fit test. Only data for models which provided an adequate initial fit (through the model selection process) for a subject were analyzed for this study. For the nine-donning fit test, six of the seven respirator models accommodated the fit of subjects (as indicated by geometric mean fit factor > 100) for not only the intended NIOSH bivariate and PCA panel sizes corresponding to the respirator size, but also for other panel sizes which were tested for each model. The model which showed poor performance may not be accurately represented because only two subjects passed the initial selection criteria to use this model. Findings are supportive of the current selection of facial dimensions for the new NIOSH panels. The various FFR models selected for the CDC Strategic National Stockpile provide a range of sizing options to fit a variety of facial sizes. PMID:26877587

An individual-based model of zebrafish population dynamics accounting for energy dynamics.

PubMed

Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R R

2015-01-01

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level.

An Individual-Based Model of Zebrafish Population Dynamics Accounting for Energy Dynamics

PubMed Central

Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R. R.

2015-01-01

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level. PMID:25938409

Instructional Model and Thinking Skill in Chemistry Class

NASA Astrophysics Data System (ADS)

Langkudi, H. H.

2018-02-01

Chemistry course are considered a difficult lesson for students as evidenced by low learning outcomes on daily tests, mid-semester tests as well as final semester tests. This research intended to investigate the effect of instructional model, thinking skill and the interaction of these variables on students’ achievement in chemistry. Experimental method was applying used 2 x 2 factorial design. The results showed that the use of instructional model with thinking skill influences student’s learning outcomes, so that the chemistry teacher is recommended to pay attention to the learning model, and adjusted to the student’s skill thinking on the chemistry material being taught. The conclusion of this research is that discovery model is suitable for students who have formal thinking skill and conventional model is fit for the students that have concrete thinking skill.

Simplified models for Higgs physics: singlet scalar and vector-like quark phenomenology

DOE PAGES

Dolan, Matthew J.; Hewett, J. L.; Krämer, M.; ...

2016-07-08

Simplified models provide a useful tool to conduct the search and exploration of physics beyond the Standard Model in a model-independent fashion. In this study, we consider the complementarity of indirect searches for new physics in Higgs couplings and distributions with direct searches for new particles, using a simplified model which includes a new singlet scalar resonance and vector-like fermions that can mix with the SM top-quark. We fit this model to the combined ATLAS and CMS 125 GeV Higgs production and coupling measurements and other precision electroweak constraints, and explore in detail the effects of the new matter contentmore » upon Higgs production and kinematics. Finally, we highlight some novel features and decay modes of the top partner phenomenology, and discuss prospects for Run II.« less

Characterization of small-to-medium head-and-face dimensions for developing respirator fit test panels and evaluating fit of filtering facepiece respirators with different faceseal design

PubMed Central

Lin, Yi-Chun

2017-01-01

A respirator fit test panel (RFTP) with facial size distribution representative of intended users is essential to the evaluation of respirator fit for new models of respirators. In this study an anthropometric survey was conducted among youths representing respirator users in mid-Taiwan to characterize head-and-face dimensions key to RFTPs for application to small-to-medium facial features. The participants were fit-tested for three N95 masks of different facepiece design and the results compared to facial size distribution specified in the RFTPs of bivariate and principal component analysis design developed in this study to realize the influence of facial characteristics to respirator fit in relation to facepiece design. Nineteen dimensions were measured for 206 participants. In fit testing the qualitative fit test (QLFT) procedures prescribed by the U.S. Occupational Safety and Health Administration were adopted. As the results show, the bizygomatic breadth of the male and female participants were 90.1 and 90.8% of their counterparts reported for the U.S. youths (P < 0.001), respectively. Compared to the bivariate distribution, the PCA design better accommodated variation in facial contours among different respirator user groups or populations, with the RFTPs reported in this study and from literature consistently covering over 92% of the participants. Overall, the facial fit of filtering facepieces increased with increasing facial dimensions. The total percentages of the tests wherein the final maneuver being completed was “Moving head up-and-down”, “Talking” or “Bending over” in bivariate and PCA RFTPs were 13.3–61.9% and 22.9–52.8%, respectively. The respirators with a three-panel flat fold structured in the facepiece provided greater fit, particularly when the users moved heads. When the facial size distribution in a bivariate RFTP did not sufficiently represent petite facial size, the fit testing was inclined to overestimate the general fit, thus for small-to-medium facial dimensions a distinct RFTP should be considered. PMID:29176833

Characterization of small-to-medium head-and-face dimensions for developing respirator fit test panels and evaluating fit of filtering facepiece respirators with different faceseal design.

PubMed

Lin, Yi-Chun; Chen, Chen-Peng

2017-01-01

A respirator fit test panel (RFTP) with facial size distribution representative of intended users is essential to the evaluation of respirator fit for new models of respirators. In this study an anthropometric survey was conducted among youths representing respirator users in mid-Taiwan to characterize head-and-face dimensions key to RFTPs for application to small-to-medium facial features. The participants were fit-tested for three N95 masks of different facepiece design and the results compared to facial size distribution specified in the RFTPs of bivariate and principal component analysis design developed in this study to realize the influence of facial characteristics to respirator fit in relation to facepiece design. Nineteen dimensions were measured for 206 participants. In fit testing the qualitative fit test (QLFT) procedures prescribed by the U.S. Occupational Safety and Health Administration were adopted. As the results show, the bizygomatic breadth of the male and female participants were 90.1 and 90.8% of their counterparts reported for the U.S. youths (P < 0.001), respectively. Compared to the bivariate distribution, the PCA design better accommodated variation in facial contours among different respirator user groups or populations, with the RFTPs reported in this study and from literature consistently covering over 92% of the participants. Overall, the facial fit of filtering facepieces increased with increasing facial dimensions. The total percentages of the tests wherein the final maneuver being completed was "Moving head up-and-down", "Talking" or "Bending over" in bivariate and PCA RFTPs were 13.3-61.9% and 22.9-52.8%, respectively. The respirators with a three-panel flat fold structured in the facepiece provided greater fit, particularly when the users moved heads. When the facial size distribution in a bivariate RFTP did not sufficiently represent petite facial size, the fit testing was inclined to overestimate the general fit, thus for small-to-medium facial dimensions a distinct RFTP should be considered.

Sintering of viscous droplets under surface tension

NASA Astrophysics Data System (ADS)

Wadsworth, Fabian B.; Vasseur, Jérémie; Llewellin, Edward W.; Schauroth, Jenny; Dobson, Katherine J.; Scheu, Bettina; Dingwell, Donald B.

2016-04-01

We conduct experiments to investigate the sintering of high-viscosity liquid droplets. Free-standing cylinders of spherical glass beads are heated above their glass transition temperature, causing them to densify under surface tension. We determine the evolving volume of the bead pack at high spatial and temporal resolution. We use these data to test a range of existing models. We extend the models to account for the time-dependent droplet viscosity that results from non-isothermal conditions, and to account for non-zero final porosity. We also present a method to account for the initial distribution of radii of the pores interstitial to the liquid spheres, which allows the models to be used with no fitting parameters. We find a good agreement between the models and the data for times less than the capillary relaxation timescale. For longer times, we find an increasing discrepancy between the data and the model as the Darcy outgassing time-scale approaches the sintering timescale. We conclude that the decreasing permeability of the sintering system inhibits late-stage densification. Finally, we determine the residual, trapped gas volume fraction at equilibrium using X-ray computed tomography and compare this with theoretical values for the critical gas volume fraction in systems of overlapping spheres.

Idle minds are the devil's tools? Coping, depressed mood and divergent thinking in older adults.

PubMed

Mélendez, Juan Carlos; Alfonso-Benlliure, Vicente; Mayordomo, Teresa

2017-10-20

The main aim was to test a causal relations model of the problem-focused and emotion-focused coping styles, depressed mood, and divergent thinking (DT) in older adults. It was hypothesized that both forms of coping would have a significant effect on predicting depressed mood, and that problem-focused coping and depressed mood would have a significant effect on DT. Participants were 135 subjects with ages ranging between 55 and 84 years old, who took part in a personal interview and filled out several questionnaires. The statistical analysis included structural equations models (SEM). The initial model led to a final model endorsed by the goodness of fit, composite reliability, and discriminant validity indexes. This model confirms a direct relationship between the two types of coping strategies and depressed mood (with the opposite sign), but not between rational coping and DT. Finally, depressed mood was also confirmed as a mediator variable between coping and DT. The type of coping is a clear predictor of mood in older adults. Advanced age decline is not necessarily translated into inefficacy in everyday problem solving especially in those who, through proble-focused coping, avoid depressed moods and maintain good levels of DT.

SU-F-T-104: Determining the NTCP Parameters of Pharyngeal Constrictors and Proximal Esophagus for Radiation Induced Swallowing Problems Recorded Six Months After Radiation Therapy for Head and Neck Tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mavroidis, P; Price, A; Kostich, M

Purpose: To estimate the radiobiological parameters of four NTCP models that describe the dose-response relations of pharyngeal constrictors and proximal esophagus regarding the severity of patient reported swallowing problems 6 months post chemo-radiotherapy. To identify the section/structure that best correlates with the manifestation of the clinical endpoints. Finally, to compare the goodness-of-fit of those models. Methods: Forty-three patients were treated on a prospective multi-institutional phase II study for oropharyngeal squamous cell carcinoma. All the patients received 60 Gy IMRT and they reported symptoms using the novel patient reported outcome version of the CTCAE. We derived the individual patient dosimetric datamore » of superior, medium and inferior sections of pharyngeal constrictors (SPC, MPC and IPC), superior and inferior sections of esophagus (SES and IES) as separate structures as well as combinations. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS), Logit and Relative Logit (RL) NTCP models were used to fit the patient data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC) and the Odds Ratio methods. Results: The AUC values were highest for the SPC for Grade ≥ 2 (0.719 for the RS and RL models, and 0.716 for LKB and Logit). For Grade ≥ 1, the respective values were 0.699 for RS, LKB and Logit and 0.676 for RL. For MPC the AUC values varied between 0.463–0.477, for IPC between 0.396–0.458, for SES between 0.556–0.613 and for IES between 0.410–0.519. The Odds Ratio for the SPC was 15.6 (1.7–146.4) for RS, LKB and Logit for NTCP of 55%. Conclusion: All the examined NTCP models could fit the clinical data with similar accuracy. The SPC appear to correlate best with the clinical endpoints of swallowing problems. A prospective study could establish the use of NTCP values of SPC as a constraint in treatment planning.« less

Simulation Study on Fit Indexes in CFA Based on Data with Slightly Distorted Simple Structure

ERIC Educational Resources Information Center

Beauducel, Andre; Wittmann, Werner W.

2005-01-01

Fit indexes were compared with respect to a specific type of model misspecification. Simple structure was violated with some secondary loadings that were present in the true models that were not specified in the estimated models. The c2 test, Comparative Fit Index, Goodness-of-Fit Index, Incremental Fit Index, Nonnormed Fit Index, root mean…

In situ repair of a failed compression fitting

DOEpatents

Wolbert, R.R.; Jandrasits, W.G.

1985-08-05

A method and apparatus for the in situ repair of a failed compression fitting is provided. Initially, a portion of a guide tube is inserted coaxially in the bore of the compression fitting and locked therein. A close fit dethreading device is then coaxially mounted on the guide tube to cut the threads from the fitting. Thereafter, the dethreading device and guide tube are removed and a new fitting is inserted onto the dethreaded fitting with the body of the new fitting overlaying the dethreaded portion. Finally, the main body of the new fitting is welded to the main body of the old fitting whereby a new threaded portion of the replacement fitting is precisely coaxial with the old threaded portion. If needed, a bushing is located on the dethreaded portion which is sized to fit snugly between the dethreaded portion and the new fitting. Preferably, the dethreading device includes a cutting tool which is moved incrementally in a radial direction whereby the threads are cut from the threaded portion of the failed fitting in increments.

Validation of the Spanish version of the Amsterdam Preoperative Anxiety and Information Scale (APAIS).

PubMed

Vergara-Romero, Manuel; Morales-Asencio, José Miguel; Morales-Fernández, Angelines; Canca-Sanchez, Jose Carlos; Rivas-Ruiz, Francisco; Reinaldo-Lapuerta, Jose Antonio

2017-06-07

Preoperative anxiety is a frequent and challenging problem with deleterious effects on the development of surgical procedures and postoperative outcomes. To prevent and treat preoperative anxiety effectively, the level of anxiety of patients needs to be assessed through valid and reliable measuring instruments. One such measurement tool is the Amsterdam Preoperative Anxiety and Information Scale (APAIS), of which a Spanish version has not been validated yet. To perform a Spanish cultural adaptation and empirical validation of the APAIS for assessing preoperative anxiety in the Spanish population. A two-step forward/back translation of the APAIS scale was performed to ensure a reliable Spanish cultural adaptation. The final Spanish version of the APAIS questionnaire was administered to 529 patients between the ages of 18 to 70 undergoing elective surgery at hospitals of the Agencia Sanitaria Costa del Sol (Spain). Cronbach's alpha, homogeneity index, intra-class correlation coefficient, and confirmatory factor analysis were calculated to assess internal consistency and criteria and construct validity. Confirmatory factor analysis showed that a one-factor model was better fitted than a two-factor model, with good fitting patterns (root mean square error of approximation: 0.05, normed-fit index: 0.99, goodness-of-fit statistic: 0.99). The questionnaire showed high internal consistency (Cronbach's alpha: 0.84) and a good correlation with the Goldberg Anxiety Scale (CCI: 0.62 (95% CI: 0.55 to 0.68). The Spanish version of the APAIS is a valid and reliable preoperative anxiety measurement tool and shows psychometric properties similar to those obtained by similar previous studies.

Prony series spectra of structural relaxation in N-BK7 for finite element modeling.

PubMed

Koontz, Erick; Blouin, Vincent; Wachtel, Peter; Musgraves, J David; Richardson, Kathleen

2012-12-20

Structural relaxation behavior of N-BK7 glass was characterized at temperatures 20 °C above and below T(12) for this glass, using a thermo mechanical analyzer (TMA). T(12) is a characteristic temperature corresponding to a viscosity of 10(12) Pa·s. The glass was subject to quick temperature down-jumps preceded and followed by long isothermal holds. The exponential-like decay of the sample height was recorded and fitted using a unique Prony series method. The result of his method was a plot of the fit parameters revealing the presence of four distinct peaks or distributions of relaxation times. The number of relaxation times decreased as final test temperature was increased. The relaxation times did not shift significantly with changing temperature; however, the Prony weight terms varied essentially linearly with temperature. It was also found that the structural relaxation behavior of the glass trended toward single exponential behavior at temperatures above the testing range. The result of the analysis was a temperature-dependent Prony series model that can be used in finite element modeling of glass behavior in processes such as precision glass molding (PGM).

The Role of Oxygen in Avascular Tumor Growth

PubMed Central

Grimes, David Robert; Kannan, Pavitra; McIntyre, Alan; Kavanagh, Anthony; Siddiky, Abul; Wigfield, Simon; Harris, Adrian; Partridge, Mike

2016-01-01

The oxygen status of a tumor has significant clinical implications for treatment prognosis, with well-oxygenated subvolumes responding markedly better to radiotherapy than poorly supplied regions. Oxygen is essential for tumor growth, yet estimation of local oxygen distribution can be difficult to ascertain in situ, due to chaotic patterns of vasculature. It is possible to avoid this confounding influence by using avascular tumor models, such as tumor spheroids, a much better approximation of realistic tumor dynamics than monolayers, where oxygen supply can be described by diffusion alone. Similar to in situ tumours, spheroids exhibit an approximately sigmoidal growth curve, often approximated and fitted by logistic and Gompertzian sigmoid functions. These describe the basic rate of growth well, but do not offer an explicitly mechanistic explanation. This work examines the oxygen dynamics of spheroids and demonstrates that this growth can be derived mechanistically with cellular doubling time and oxygen consumption rate (OCR) being key parameters. The model is fitted to growth curves for a range of cell lines and derived values of OCR are validated using clinical measurement. Finally, we illustrate how changes in OCR due to gemcitabine treatment can be directly inferred using this model. PMID:27088720

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.…

Effect of Solar Wind Drag on the Determination of the Properties of Coronal Mass Ejections from Heliospheric Images

NASA Astrophysics Data System (ADS)

Lugaz, N.; Kintner, P.

2013-07-01

The Fixed-Φ (FΦ) and Harmonic Mean (HM) fitting methods are two methods to determine the "average" direction and velocity of coronal mass ejections (CMEs) from time-elongation tracks produced by Heliospheric Imagers (HIs), such as the HIs onboard the STEREO spacecraft. Both methods assume a constant velocity in their descriptions of the time-elongation profiles of CMEs, which are used to fit the observed time-elongation data. Here, we analyze the effect of aerodynamic drag on CMEs propagating through interplanetary space, and how this drag affects the result of the FΦ and HM fitting methods. A simple drag model is used to analytically construct time-elongation profiles which are then fitted with the two methods. It is found that higher angles and velocities give rise to greater error in both methods, reaching errors in the direction of propagation of up to 15∘ and 30∘ for the FΦ and HM fitting methods, respectively. This is due to the physical accelerations of the CMEs being interpreted as geometrical accelerations by the fitting methods. Because of the geometrical definition of the HM fitting method, it is more affected by the acceleration than the FΦ fitting method. Overall, we find that both techniques overestimate the initial (and final) velocity and direction for fast CMEs propagating beyond 90∘ from the Sun-spacecraft line, meaning that arrival times at 1 AU would be predicted early (by up to 12 hours). We also find that the direction and arrival time of a wide and decelerating CME can be better reproduced by the FΦ due to the cancelation of two errors: neglecting the CME width and neglecting the CME deceleration. Overall, the inaccuracies of the two fitting methods are expected to play an important role in the prediction of CME hit and arrival times as we head towards solar maximum and the STEREO spacecraft further move behind the Sun.

Psychometrics of the preschooler physical activity parenting practices instrument among a Latino sample

PubMed Central

2014-01-01

Background Latino preschoolers (3-5 year old children) have among the highest rates of obesity. Low levels of physical activity (PA) are a risk factor for obesity. Characterizing what Latino parents do to encourage or discourage their preschooler to be physically active can help inform interventions to increase their PA. The objective was therefore to develop and assess the psychometrics of a new instrument: the Preschooler Physical Activity Parenting Practices (PPAPP) among a Latino sample, to assess parenting practices used to encourage or discourage PA among preschool-aged children. Methods Cross-sectional study of 240 Latino parents who reported the frequency of using PA parenting practices. 95% of respondents were mothers; 42% had more than a high school education. Child mean age was 4.5 (±0.9) years (52% male). Test-retest reliability was assessed in 20%, 2 weeks later. We assessed the fit of a priori models using Confirmatory factor analyses (CFA). In a separate sub-sample (35%), preschool-aged children wore accelerometers to assess associations with their PA and PPAPP subscales. Results The a-priori models showed poor fit to the data. A modified factor structure for encouraging PPAPP had one multiple-item scale: engagement (15 items), and two single-items (have outdoor toys; not enroll in sport-reverse coded). The final factor structure for discouraging PPAPP had 4 subscales: promote inactive transport (3 items), promote screen time (3 items), psychological control (4 items) and restricting for safety (4 items). Test-retest reliability (ICC) for the two scales ranged from 0.56-0.85. Cronbach’s alphas ranged from 0.5-0.9. Several sub-factors correlated in the expected direction with children’s objectively measured PA. Conclusion The final models for encouraging and discouraging PPAPP had moderate to good fit, with moderate to excellent test-retest reliabilities. The PPAPP should be further evaluated to better assess its associations with children’s PA and offers a new tool for measuring PPAPP among Latino families with preschool-aged children. PMID:24428935

Exact solution for the time evolution of network rewiring models

NASA Astrophysics Data System (ADS)

Evans, T. S.; Plato, A. D. K.

2007-05-01

We consider the rewiring of a bipartite graph using a mixture of random and preferential attachment. The full mean-field equations for the degree distribution and its generating function are given. The exact solution of these equations for all finite parameter values at any time is found in terms of standard functions. It is demonstrated that these solutions are an excellent fit to numerical simulations of the model. We discuss the relationship between our model and several others in the literature, including examples of urn, backgammon, and balls-in-boxes models, the Watts and Strogatz rewiring problem, and some models of zero range processes. Our model is also equivalent to those used in various applications including cultural transmission, family name and gene frequencies, glasses, and wealth distributions. Finally some Voter models and an example of a minority game also show features described by our model.

On the Structure of a Best Possible Crossover Selection Strategy in Genetic Algorithms

NASA Astrophysics Data System (ADS)

Lässig, Jörg; Hoffmann, Karl Heinz

The paper considers the problem of selecting individuals in the current population in genetic algorithms for crossover to find a solution with high fitness for a given optimization problem. Many different schemes have been described in the literature as possible strategies for this task but so far comparisons have been predominantly empirical. It is shown that if one wishes to maximize any linear function of the final state probabilities, e.g. the fitness of the best individual in the final population of the algorithm, then a best probability distribution for selecting an individual in each generation is a rectangular distribution over the individuals sorted in descending sequence by their fitness values. This means uniform probabilities have to be assigned to a group of the best individuals of the population but probabilities equal to zero to individuals with lower fitness, assuming that the probability distribution to choose individuals from the current population can be chosen independently for each iteration and each individual. This result is then generalized also to typical practically applied performance measures, such as maximizing the expected fitness value of the best individual seen in any generation.

Statistical alignment: computational properties, homology testing and goodness-of-fit.

PubMed

Hein, J; Wiuf, C; Knudsen, B; Møller, M B; Wibling, G

2000-09-08

The model of insertions and deletions in biological sequences, first formulated by Thorne, Kishino, and Felsenstein in 1991 (the TKF91 model), provides a basis for performing alignment within a statistical framework. Here we investigate this model.Firstly, we show how to accelerate the statistical alignment algorithms several orders of magnitude. The main innovations are to confine likelihood calculations to a band close to the similarity based alignment, to get good initial guesses of the evolutionary parameters and to apply an efficient numerical optimisation algorithm for finding the maximum likelihood estimate. In addition, the recursions originally presented by Thorne, Kishino and Felsenstein can be simplified. Two proteins, about 1500 amino acids long, can be analysed with this method in less than five seconds on a fast desktop computer, which makes this method practical for actual data analysis.Secondly, we propose a new homology test based on this model, where homology means that an ancestor to a sequence pair can be found finitely far back in time. This test has statistical advantages relative to the traditional shuffle test for proteins.Finally, we describe a goodness-of-fit test, that allows testing the proposed insertion-deletion (indel) process inherent to this model and find that real sequences (here globins) probably experience indels longer than one, contrary to what is assumed by the model. Copyright 2000 Academic Press.

The factor structure of posttraumatic stress disorder: a literature update, critique of methodology, and agenda for future research.

PubMed

Elhai, Jon D; Palmieri, Patrick A

2011-08-01

We present an update of recent literature (since 2007) exploring the factor structure of posttraumatic stress disorder (PTSD) symptom measures. Research supporting a four-factor emotional numbing model and a four-factor dysphoria model is presented, with these models fitting better than all other models examined. Variables accounting for factor structure differences are reviewed, including PTSD query instructions, type of PTSD measure, extent of trauma exposure, ethnicity, and timing of administration. Methodological and statistical limitations with recent studies are presented. Finally, a research agenda and recommendations are offered to push this research area forward, including suggestions to validate PTSD’s factors against external measures of psychopathology, test moderators of factor structure, and examine heterogeneity of symptom presentations based on factor structure examination.

Cardiorespiratory fitness does not alter plasma pentraxin 3 and cortisol reactivity to acute psychological stress and exercise.

PubMed

Huang, Chun-Jung; Webb, Heather E; Beasley, Kathleen N; McAlpine, David A; Tangsilsat, Supatchara E; Acevedo, Edmund O

2014-03-01

Pentraxin 3 (PTX3) has been recently identified as a biomarker of vascular inflammation in predicting cardiovascular events. The purpose of this study was to examine the effect of cardiorespiratory fitness on plasma PTX3 and cortisol responses to stress, utilizing a dual-stress model. Fourteen male subjects were classified into high-fit (HF) and low-fit (LF) groups and completed 2 counterbalanced experimental conditions. The exercise-alone condition (EAC) consisted of cycling at 60% maximal oxygen uptake for 37 min, while the dual-stress condition (DSC) included 20 min of a mental stress while cycling for 37 min. Plasma PTX3 revealed significant increases over time with a significant elevation at 37 min in both HF and LF groups in response to EAC and DSC. No difference in plasma PTX3 levels was observed between EAC and DSC. In addition, plasma cortisol revealed a significant condition by time interaction with greater levels during DSC at 37 min, whereas cardiorespiratory fitness level did not reveal different plasma cortisol responses in either the EAC or DSC. Aerobic exercise induces plasma PTX3 release, while additional acute mental stress, in a dual-stress condition, does not exacerbate or further modulate the PTX3 response. Furthermore, cardiorespiratory fitness may not affect the stress reactivity of plasma PTX3 to physical and combined physical and psychological stressors. Finally, the exacerbated cortisol responses to combined stress may provide the potential link to biological pathways that explain changes in physiological homeostasis that may be associated with an increase in the risk of cardiovascular disease.

Marginal Accuracy and Internal Fit of Dental Copings Fabricated by Modern Additive and Subtractive Digital Technologies.

PubMed

Nelson, Neha; K S, Jyothi; Sunny, Kiran

2017-03-01

The margins of copings for crowns and retainers of fixed partial dentures affect the progress of microleakage and dental caries. Failures occur due to altered fit which is also influenced by the method of fabrication. An in-vitro study was conducted to determine among the cast base metal, copy milled zirconia, computer aided designing computer aided machining/manufacturing zirconia and direct metal laser sintered copings which showed best marginal accuracy and internal fit. Forty extracted maxillary premolars were mounted on an acrylic model and reduced occlusally using a milling machine up to a final tooth height of 4 mm from the cementoenamel junction. Axial reduction was accomplished on a surveyor and a chamfer finish line was given. The impressions and dies were made for fabrication of copings which were luted on the prepared teeth under standardized loading, embedded in self-cure acrylic resin, sectioned and observed using scanning electron microscope for internal gap and marginal accuracy. The copings fabricated using direct metal laser sintering technique exhibited best marginal accuracy and internal fit. Comparison of mean between the four groups by ANOVA and post-hoc Tukey HSD tests showed a statistically significant difference between all the groups (p⟨0.05). It was concluded that the copings fabricated using direct metal laser sintering technique exhibited best marginal accuracy and internal fit. Additive digital technologies such as direct metal laser sintering could be cost-effective for the clinician, minimize failures related to fit and increase longevity of teeth and prostheses. Copyright© 2017 Dennis Barber Ltd.

A comparison of methods of fitting several models to nutritional response data.

PubMed

Vedenov, D; Pesti, G M

2008-02-01

A variety of models have been proposed to fit nutritional input-output response data. The models are typically nonlinear; therefore, fitting the models usually requires sophisticated statistical software and training to use it. An alternative tool for fitting nutritional response models was developed by using widely available and easier-to-use Microsoft Excel software. The tool, implemented as an Excel workbook (NRM.xls), allows simultaneous fitting and side-by-side comparisons of several popular models. This study compared the results produced by the tool we developed and PROC NLIN of SAS. The models compared were the broken line (ascending linear and quadratic segments), saturation kinetics, 4-parameter logistics, sigmoidal, and exponential models. The NRM.xls workbook provided results nearly identical to those of PROC NLIN. Furthermore, the workbook successfully fit several models that failed to converge in PROC NLIN. Two data sets were used as examples to compare fits by the different models. The results suggest that no particular nonlinear model is necessarily best for all nutritional response data.

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…

In situ repair of a failed compression fitting

DOEpatents

Wolbert, Ronald R.; Jandrasits, Walter G.

1986-01-01

A method and apparatus for the in situ repair of a failed compression fitg is provided. Initially, a portion of a guide tube is inserted coaxially in the bore of the compression fitting and locked therein. A close fit dethreading device is then coaxially mounted on the guide tube to cut the threads from the fitting. Thereafter, the dethreading device and guide tube are removed and a new fitting is inserted onto the dethreaded fitting with the body of the new fitting overlaying the dethreaded portion. Finally, the main body of the new fitting is welded to the main body of the old fitting whereby a new threaded portion of the replacement fitting is precisely coaxial with the old threaded portion. If needed, a bushing is located on the dethreaded portion which is sized to fit snugly between the dethreaded portion and the new fitting. Preferably, the dethreading device includes a cutting tool which is moved incrementally in a radial direction whereby the threads are cut from the threaded portion of the failed fitting in increments.

Improving large-scale groundwater models by considering fossil gradients

NASA Astrophysics Data System (ADS)

Schulz, Stephan; Walther, Marc; Michelsen, Nils; Rausch, Randolf; Dirks, Heiko; Al-Saud, Mohammed; Merz, Ralf; Kolditz, Olaf; Schüth, Christoph

2017-05-01

Due to limited availability of surface water, many arid to semi-arid countries rely on their groundwater resources. Despite the quasi-absence of present day replenishment, some of these groundwater bodies contain large amounts of water, which was recharged during pluvial periods of the Late Pleistocene to Early Holocene. These mostly fossil, non-renewable resources require different management schemes compared to those which are usually applied in renewable systems. Fossil groundwater is a finite resource and its withdrawal implies mining of aquifer storage reserves. Although they receive almost no recharge, some of them show notable hydraulic gradients and a flow towards their discharge areas, even without pumping. As a result, these systems have more discharge than recharge and hence are not in steady state, which makes their modelling, in particular the calibration, very challenging. In this study, we introduce a new calibration approach, composed of four steps: (i) estimating the fossil discharge component, (ii) determining the origin of fossil discharge, (iii) fitting the hydraulic conductivity with a pseudo steady-state model, and (iv) fitting the storage capacity with a transient model by reconstructing head drawdown induced by pumping activities. Finally, we test the relevance of our approach and evaluated the effect of considering or ignoring fossil gradients on aquifer parameterization for the Upper Mega Aquifer (UMA) on the Arabian Peninsula.

Modeling protein conformational changes by iterative fitting of distance constraints using reoriented normal modes.

PubMed

Zheng, Wenjun; Brooks, Bernard R

2006-06-15

Recently we have developed a normal-modes-based algorithm that predicts the direction of protein conformational changes given the initial state crystal structure together with a small number of pairwise distance constraints for the end state. Here we significantly extend this method to accurately model both the direction and amplitude of protein conformational changes. The new protocol implements a multisteps search in the conformational space that is driven by iteratively minimizing the error of fitting the given distance constraints and simultaneously enforcing the restraint of low elastic energy. At each step, an incremental structural displacement is computed as a linear combination of the lowest 10 normal modes derived from an elastic network model, whose eigenvectors are reorientated to correct for the distortions caused by the structural displacements in the previous steps. We test this method on a list of 16 pairs of protein structures for which relatively large conformational changes are observed (root mean square deviation >3 angstroms), using up to 10 pairwise distance constraints selected by a fluctuation analysis of the initial state structures. This method has achieved a near-optimal performance in almost all cases, and in many cases the final structural models lie within root mean square deviation of 1 approximately 2 angstroms from the native end state structures.

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

PubMed

Slater, Graham J; Harmon, Luke J; Wegmann, Daniel; Joyce, Paul; Revell, Liam J; Alfaro, Michael E

2012-03-01

In recent years, a suite of methods has been developed to fit multiple rate models to phylogenetic comparative data. However, most methods have limited utility at broad phylogenetic scales because they typically require complete sampling of both the tree and the associated phenotypic data. Here, we develop and implement a new, tree-based method called MECCA (Modeling Evolution of Continuous Characters using ABC) that uses a hybrid likelihood/approximate Bayesian computation (ABC)-Markov-Chain Monte Carlo approach to simultaneously infer rates of diversification and trait evolution from incompletely sampled phylogenies and trait data. We demonstrate via simulation that MECCA has considerable power to choose among single versus multiple evolutionary rate models, and thus can be used to test hypotheses about changes in the rate of trait evolution across an incomplete tree of life. We finally apply MECCA to an empirical example of body size evolution in carnivores, and show that there is no evidence for an elevated rate of body size evolution in the pinnipeds relative to terrestrial carnivores. ABC approaches can provide a useful alternative set of tools for future macroevolutionary studies where likelihood-dependent approaches are lacking. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Nonlinear dynamic analysis and optimal trajectory planning of a high-speed macro-micro manipulator

NASA Astrophysics Data System (ADS)

Yang, Yi-ling; Wei, Yan-ding; Lou, Jun-qiang; Fu, Lei; Zhao, Xiao-wei

2017-09-01

This paper reports the nonlinear dynamic modeling and the optimal trajectory planning for a flexure-based macro-micro manipulator, which is dedicated to the large-scale and high-speed tasks. In particular, a macro- micro manipulator composed of a servo motor, a rigid arm and a compliant microgripper is focused. Moreover, both flexure hinges and flexible beams are considered. By combining the pseudorigid-body-model method, the assumed mode method and the Lagrange equation, the overall dynamic model is derived. Then, the rigid-flexible-coupling characteristics are analyzed by numerical simulations. After that, the microscopic scale vibration excited by the large-scale motion is reduced through the trajectory planning approach. Especially, a fitness function regards the comprehensive excitation torque of the compliant microgripper is proposed. The reference curve and the interpolation curve using the quintic polynomial trajectories are adopted. Afterwards, an improved genetic algorithm is used to identify the optimal trajectory by minimizing the fitness function. Finally, the numerical simulations and experiments validate the feasibility and the effectiveness of the established dynamic model and the trajectory planning approach. The amplitude of the residual vibration reduces approximately 54.9%, and the settling time decreases 57.1%. Therefore, the operation efficiency and manipulation stability are significantly improved.

Population Pharmacokinetics of Topiramate in Japanese Pediatric and Adult Patients With Epilepsy Using Routinely Monitored Data.

PubMed

Takeuchi, Masato; Yano, Ikuko; Ito, Satoko; Sugimoto, Mitsuhiro; Yamamoto, Shota; Yonezawa, Atsushi; Ikeda, Akio; Matsubara, Kazuo

2017-04-01

Topiramate is a second-generation antiepileptic drug used as monotherapy and adjunctive therapy in adults and children with partial seizures. A population pharmacokinetic (PPK) analysis was performed to improve the topiramate dosage adjustment for individualized treatment. Patients whose steady-state serum concentration of topiramate was routinely monitored at Kyoto University Hospital from April 2012 to March 2013 were included in the model-building data. A nonlinear mixed effects modeling program was used to evaluate the influence of covariates on topiramate pharmacokinetics. The obtained PPK model was evaluated by internal model validations, including goodness-of-fit plots and prediction-corrected visual predictive checks, and was externally confirmed using the validation data from January 2015 to December 2015. A total of 177 steady-state serum concentrations from 93 patients were used for the model-building analysis. The patients' age ranged from 2 to 68 years, and body weight ranged from 8.6 to 105 kg. The median serum concentration of topiramate was 1.7 mcg/mL, and half of the patients received carbamazepine coadministration. Based on a one-compartment model with first order absorption and elimination, the apparent volume of distribution was 105 L/70 kg, and the apparent clearance was allometrically related to the body weight as 2.25 L·h·70 kg without carbamazepine or phenytoin. Combination treatment with carbamazepine or phenytoin increased the apparent clearance to 3.51 L·h·70 kg. Goodness-of-fit plots, prediction-corrected visual predictive check, and external validation using the validation data from 43 patients confirmed an appropriateness of the final model. Simulations based on the final model showed that dosage adjustments allometrically scaling to body weight can equalize the serum concentrations in children of various ages and adults. The PPK model, using the power scaling of body weight, effectively elucidated the topiramate serum concentration profile ranging from pediatric to adult patients. Dosage adjustments based on body weight and concomitant antiepileptic drug help obtain the dosage of topiramate necessary to reach an effective concentration in each individual.

78 FR 78699 - Airworthiness Directives; Bell Helicopter Textron Canada Limited Helicopters

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-27

... Administration (FAA), DOT. ACTION: Final rule. SUMMARY: We are adopting a new airworthiness directive (AD) for...-4 helicopters with a certain tailboom upper left attachment fitting (fitting). This AD requires..., West Building Ground Floor, Room W12-140, 1200 New Jersey Avenue SE., Washington, DC 20590. FOR FURTHER...

78 FR 41280 - Airworthiness Directives; Airbus Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-10

... Transportation (DOT). ACTION: Final rule. SUMMARY: We are adopting a new airworthiness directive (AD) for certain... left-hand and right-hand sides of the continuity fittings at the front windshield lower framing on a... cracking on the left- hand and right-hand sides of the windshield central lower node continuity fittings...

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

PubMed Central

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

2015-01-01

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

Is the Bifactor Model a Better Model or Is It Just Better at Modeling Implausible Responses? Application of Iteratively Reweighted Least Squares to the Rosenberg Self-Esteem Scale.

PubMed

Reise, Steven P; Kim, Dale S; Mansolf, Maxwell; Widaman, Keith F

2016-01-01

Although the structure of the Rosenberg Self-Esteem Scale (RSES) has been exhaustively evaluated, questions regarding dimensionality and direction of wording effects continue to be debated. To shed new light on these issues, we ask (a) for what percentage of individuals is a unidimensional model adequate, (b) what additional percentage of individuals can be modeled with multidimensional specifications, and (c) what percentage of individuals respond so inconsistently that they cannot be well modeled? To estimate these percentages, we applied iteratively reweighted least squares (IRLS) to examine the structure of the RSES in a large, publicly available data set. A distance measure, d s , reflecting a distance between a response pattern and an estimated model, was used for case weighting. We found that a bifactor model provided the best overall model fit, with one general factor and two wording-related group factors. However, on the basis of d r  values, a distance measure based on individual residuals, we concluded that approximately 86% of cases were adequately modeled through a unidimensional structure, and only an additional 3% required a bifactor model. Roughly 11% of cases were judged as "unmodelable" due to their significant residuals in all models considered. Finally, analysis of d s revealed that some, but not all, of the superior fit of the bifactor model is owed to that model's ability to better accommodate implausible and possibly invalid response patterns, and not necessarily because it better accounts for the effects of direction of wording.

Temporal and Spectral Characteristics of X-Ray Bright Pleiads

NASA Astrophysics Data System (ADS)

Caillault, J.-P.; Gagne, M.; Yglesias, J.; Hartmann, L.; Prosser, C.; Stauffer, J.

1993-05-01

ROSAT PSPC observations of the Pleiades have allowed us to analyze the spectral and temporal characteristics of the X-ray sources within the cluster. Of the ~ 300 sources detected within the images, ~ 20-30 of them seem to be variable at the 99% confidence level (chi (2) -test). Numerous flares have also been found, the light curves of which we display. In addition, we have fit two-temperature Raymond-Smith thermal plasma models to the spectra of the ~ 6 brightest sources and examined whether these sources behave in accordance with coronal loop models. We also demonstrate that the two-temperature fit changes during a flare. We have constructed composite spectra for both shallow and deep convective zone stars in order to see whether there is a systematic change of spectral characteristics from spectral type F to M. Finally, in an attempt to discern possible evolutionary effects, we compare our results with those from the older Hyades cluster (Stern et al. 1993). This research was supported by NASA Grants NAG5-1608 to UGA and NAG5-1849 & NAGW-2698 to the CfA.

Competing opinion diffusion on social networks.

PubMed

Hu, Haibo

2017-11-01

Opinion competition is a common phenomenon in real life, such as with opinions on controversial issues or political candidates; however, modelling this competition remains largely unexplored. To bridge this gap, we propose a model of competing opinion diffusion on social networks taking into account degree-dependent fitness or persuasiveness. We study the combined influence of social networks, individual fitnesses and attributes, as well as mass media on people's opinions, and find that both social networks and mass media act as amplifiers in opinion diffusion, the amplifying effect of which can be quantitatively characterized. We analytically obtain the probability that each opinion will ultimately pervade the whole society when there are no committed people in networks, and the final proportion of each opinion at the steady state when there are committed people in networks. The results of numerical simulations show good agreement with those obtained through an analytical approach. This study provides insight into the collective influence of individual attributes, local social networks and global media on opinion diffusion, and contributes to a comprehensive understanding of competing diffusion behaviours in the real world.

Competing opinion diffusion on social networks

PubMed Central

2017-01-01

Opinion competition is a common phenomenon in real life, such as with opinions on controversial issues or political candidates; however, modelling this competition remains largely unexplored. To bridge this gap, we propose a model of competing opinion diffusion on social networks taking into account degree-dependent fitness or persuasiveness. We study the combined influence of social networks, individual fitnesses and attributes, as well as mass media on people’s opinions, and find that both social networks and mass media act as amplifiers in opinion diffusion, the amplifying effect of which can be quantitatively characterized. We analytically obtain the probability that each opinion will ultimately pervade the whole society when there are no committed people in networks, and the final proportion of each opinion at the steady state when there are committed people in networks. The results of numerical simulations show good agreement with those obtained through an analytical approach. This study provides insight into the collective influence of individual attributes, local social networks and global media on opinion diffusion, and contributes to a comprehensive understanding of competing diffusion behaviours in the real world. PMID:29291101

Using framework-based synthesis for conducting reviews of qualitative studies.

PubMed

Dixon-Woods, Mary

2011-04-14

Framework analysis is a technique used for data analysis in primary qualitative research. Recent years have seen its being adapted to conduct syntheses of qualitative studies. Framework-based synthesis shows considerable promise in addressing applied policy questions. An innovation in the approach, known as 'best fit' framework synthesis, has been published in BMC Medical Research Methodology this month. It involves reviewers in choosing a conceptual model likely to be suitable for the question of the review, and using it as the basis of their initial coding framework. This framework is then modified in response to the evidence reported in the studies in the reviews, so that the final product is a revised framework that may include both modified factors and new factors that were not anticipated in the original model. 'Best fit' framework-based synthesis may be especially suitable in addressing urgent policy questions where the need for a more fully developed synthesis is balanced by the need for a quick answer. Please see related article: http://www.biomedcentral.com/1471-2288/11/29.

Gap Gene Regulatory Dynamics Evolve along a Genotype Network

PubMed Central

Crombach, Anton; Wotton, Karl R.; Jiménez-Guri, Eva; Jaeger, Johannes

2016-01-01

Developmental gene networks implement the dynamic regulatory mechanisms that pattern and shape the organism. Over evolutionary time, the wiring of these networks changes, yet the patterning outcome is often preserved, a phenomenon known as “system drift.” System drift is illustrated by the gap gene network—involved in segmental patterning—in dipteran insects. In the classic model organism Drosophila melanogaster and the nonmodel scuttle fly Megaselia abdita, early activation and placement of gap gene expression domains show significant quantitative differences, yet the final patterning output of the system is essentially identical in both species. In this detailed modeling analysis of system drift, we use gene circuits which are fit to quantitative gap gene expression data in M. abdita and compare them with an equivalent set of models from D. melanogaster. The results of this comparative analysis show precisely how compensatory regulatory mechanisms achieve equivalent final patterns in both species. We discuss the larger implications of the work in terms of “genotype networks” and the ways in which the structure of regulatory networks can influence patterns of evolutionary change (evolvability). PMID:26796549

Confirmatory factor analysis of the Malay version comprehensive feeding practices questionnaire tested among mothers of primary school children in Malaysia.

PubMed

Shohaimi, Shamarina; Wei, Wong Yoke; Shariff, Zalilah Mohd

2014-01-01

Comprehensive feeding practices questionnaire (CFPQ) is an instrument specifically developed to evaluate parental feeding practices. It has been confirmed among children in America and applied to populations in France, Norway, and New Zealand. In order to extend the application of CFPQ, we conducted a factor structure validation of the translated version of CFPQ (CFPQ-M) using confirmatory factor analysis among mothers of primary school children (N = 397) in Malaysia. Several items were modified for cultural adaptation. Of 49 items, 39 items with loading factors >0.40 were retained in the final model. The confirmatory factor analysis revealed that the final model (twelve-factor model with 39 items and 2 error covariances) displayed the best fit for our sample (Chi-square = 1147; df = 634; P < 0.05; CFI = 0.900; RMSEA = 0.045; SRMR = 0.0058). The instrument with some modifications was confirmed among mothers of school children in Malaysia. The present study extends the usability of the CFPQ and enables researchers and parents to better understand the relationships between parental feeding practices and related problems such as childhood obesity.

Fact Sheet About the Hazardous Waste Generator Improvements Final Rule

EPA Pesticide Factsheets

October 28, 2016, EPA finalized a rule that revises the hazardous waste generator regulations by making them easier to understand and providing greater flexibility in how hazardous waste is managed to better fit today's business operations.

Amplitude analysis of resonant production in three pions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jackura, Andrew; Mikhasenko, Mikhail; Szczepaniak, Adam

2016-11-29

We present some results on the analysis of three pion resonances. The analyses are motivated by the recent release of the largest data set on diffractively produced three pions by the COMPASS collaboration. We construct reaction amplitudes that satisfy fundamentalmore » $S$-matrix principles, which allows the use of models that have physical constraints to be used in fitting data. The models are motivated by the isobar model that satisfy unitarity constraints. The model consist of a Deck production amplitude with which final state interactions are constrained by unitarity. We employ the isobar model where two of the pions form a quasi-stable particle. The analysis is performed in the high-energy, single Regge limit. We specifically discuss the examples of the three pion $$J^{PC}=2^{-+}$$ resonance in the $$\\rho\\pi$$ and $$f_2\\pi$$ channels.« less

Accurate in situ measurement of complex refractive index and particle size in intralipid emulsions

NASA Astrophysics Data System (ADS)

Dong, Miao L.; Goyal, Kashika G.; Worth, Bradley W.; Makkar, Sorab S.; Calhoun, William R.; Bali, Lalit M.; Bali, Samir

2013-08-01

A first accurate measurement of the complex refractive index in an intralipid emulsion is demonstrated, and thereby the average scatterer particle size using standard Mie scattering calculations is extracted. Our method is based on measurement and modeling of the reflectance of a divergent laser beam from the sample surface. In the absence of any definitive reference data for the complex refractive index or particle size in highly turbid intralipid emulsions, we base our claim of accuracy on the fact that our work offers several critically important advantages over previously reported attempts. First, our measurements are in situ in the sense that they do not require any sample dilution, thus eliminating dilution errors. Second, our theoretical model does not employ any fitting parameters other than the two quantities we seek to determine, i.e., the real and imaginary parts of the refractive index, thus eliminating ambiguities arising from multiple extraneous fitting parameters. Third, we fit the entire reflectance-versus-incident-angle data curve instead of focusing on only the critical angle region, which is just a small subset of the data. Finally, despite our use of highly scattering opaque samples, our experiment uniquely satisfies a key assumption behind the Mie scattering formalism, namely, no multiple scattering occurs. Further proof of our method's validity is given by the fact that our measured particle size finds good agreement with the value obtained by dynamic light scattering.

Accurate in situ measurement of complex refractive index and particle size in intralipid emulsions.

PubMed

Dong, Miao L; Goyal, Kashika G; Worth, Bradley W; Makkar, Sorab S; Calhoun, William R; Bali, Lalit M; Bali, Samir

2013-08-01

A first accurate measurement of the complex refractive index in an intralipid emulsion is demonstrated, and thereby the average scatterer particle size using standard Mie scattering calculations is extracted. Our method is based on measurement and modeling of the reflectance of a divergent laser beam from the sample surface. In the absence of any definitive reference data for the complex refractive index or particle size in highly turbid intralipid emulsions, we base our claim of accuracy on the fact that our work offers several critically important advantages over previously reported attempts. First, our measurements are in situ in the sense that they do not require any sample dilution, thus eliminating dilution errors. Second, our theoretical model does not employ any fitting parameters other than the two quantities we seek to determine, i.e., the real and imaginary parts of the refractive index, thus eliminating ambiguities arising from multiple extraneous fitting parameters. Third, we fit the entire reflectance-versus-incident-angle data curve instead of focusing on only the critical angle region, which is just a small subset of the data. Finally, despite our use of highly scattering opaque samples, our experiment uniquely satisfies a key assumption behind the Mie scattering formalism, namely, no multiple scattering occurs. Further proof of our method's validity is given by the fact that our measured particle size finds good agreement with the value obtained by dynamic light scattering.

Curve fitting of the corporate recovery rates: the comparison of Beta distribution estimation and kernel density estimation.

PubMed

Chen, Rongda; Wang, Ze

2013-01-01

Recovery rate is essential to the estimation of the portfolio's loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody's. However, it has a fatal defect that it can't fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody's new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management.

Curve Fitting of the Corporate Recovery Rates: The Comparison of Beta Distribution Estimation and Kernel Density Estimation

PubMed Central

Chen, Rongda; Wang, Ze

2013-01-01

Recovery rate is essential to the estimation of the portfolio’s loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody’s. However, it has a fatal defect that it can’t fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody’s new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management. PMID:23874558

High-intensity interval training in patients with coronary heart disease: Prescription models and perspectives.

PubMed

Ribeiro, Paula A B; Boidin, Maxime; Juneau, Martin; Nigam, Anil; Gayda, Mathieu

2017-01-01

Recently, high-intensity interval training (HIIT) has emerged as an alternative and/or complementary exercise modality to continuous aerobic exercise training (CAET) in CHD patients. However, the literature contains descriptions of many HIIT protocols with different stage durations, nature of recovery and intensities. In this review, we discuss the most recent forms of validated HIIT protocols in patients with coronary heart disease (CHD) and how to prescribe and use them during short- and long-term (phase II and III) cardiac rehabilitation programs. We also compare the superior and/or equivalent short- and long-term effects of HIIT versus CAET on aerobic fitness, cardiovascular function, and quality of life; their efficiency, safety, and tolerance; and exercise adherence. Short interval HIIT was found beneficial for CHD patients with lower aerobic fitness and would ideally be used in initiation and improvement stages. Medium and/or long interval HIIT protocols may be beneficial for CHD patients with higher aerobic fitness, and would be ideally used in the improvement and maintenance stages because of their high physiological stimulus. Finally, we propose progressive individualized models of HIIT programs (phase II to III) for patients with CHD and how to ideally use them according to the clinical status of patients and phase of the cardiac rehabilitation program. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Identification of Biokinetic Models Using the Concept of Extents.

PubMed

Mašić, Alma; Srinivasan, Sriniketh; Billeter, Julien; Bonvin, Dominique; Villez, Kris

2017-07-05

The development of a wide array of process technologies to enable the shift from conventional biological wastewater treatment processes to resource recovery systems is matched by an increasing demand for predictive capabilities. Mathematical models are excellent tools to meet this demand. However, obtaining reliable and fit-for-purpose models remains a cumbersome task due to the inherent complexity of biological wastewater treatment processes. In this work, we present a first study in the context of environmental biotechnology that adopts and explores the use of extents as a way to simplify and streamline the dynamic process modeling task. In addition, the extent-based modeling strategy is enhanced by optimal accounting for nonlinear algebraic equilibria and nonlinear measurement equations. Finally, a thorough discussion of our results explains the benefits of extent-based modeling and its potential to turn environmental process modeling into a highly automated task.

Statistical mapping of count survey data

USGS Publications Warehouse

Royle, J. Andrew; Link, W.A.; Sauer, J.R.; Scott, J. Michael; Heglund, Patricia J.; Morrison, Michael L.; Haufler, Jonathan B.; Wall, William A.

2002-01-01

We apply a Poisson mixed model to the problem of mapping (or predicting) bird relative abundance from counts collected from the North American Breeding Bird Survey (BBS). The model expresses the logarithm of the Poisson mean as a sum of a fixed term (which may depend on habitat variables) and a random effect which accounts for remaining unexplained variation. The random effect is assumed to be spatially correlated, thus providing a more general model than the traditional Poisson regression approach. Consequently, the model is capable of improved prediction when data are autocorrelated. Moreover, formulation of the mapping problem in terms of a statistical model facilitates a wide variety of inference problems which are cumbersome or even impossible using standard methods of mapping. For example, assessment of prediction uncertainty, including the formal comparison of predictions at different locations, or through time, using the model-based prediction variance is straightforward under the Poisson model (not so with many nominally model-free methods). Also, ecologists may generally be interested in quantifying the response of a species to particular habitat covariates or other landscape attributes. Proper accounting for the uncertainty in these estimated effects is crucially dependent on specification of a meaningful statistical model. Finally, the model may be used to aid in sampling design, by modifying the existing sampling plan in a manner which minimizes some variance-based criterion. Model fitting under this model is carried out using a simulation technique known as Markov Chain Monte Carlo. Application of the model is illustrated using Mourning Dove (Zenaida macroura) counts from Pennsylvania BBS routes. We produce both a model-based map depicting relative abundance, and the corresponding map of prediction uncertainty. We briefly address the issue of spatial sampling design under this model. Finally, we close with some discussion of mapping in relation to habitat structure. Although our models were fit in the absence of habitat information, the resulting predictions show a strong inverse relation with a map of forest cover in the state, as expected. Consequently, the results suggest that the correlated random effect in the model is broadly representing ecological variation, and that BBS data may be generally useful for studying bird-habitat relationships, even in the presence of observer errors and other widely recognized deficiencies of the BBS.

Intelligent diagnosis and prescription for a customized physical fitness and healthcare system.

PubMed

Huang, Chung-Chi; Liu, Hsiao-Man; Huang, Chung-Lin

2015-01-01

With the advent of the era of global high-tech industry and commerce and its associated sedentary lifestyle, opportunities for physical activity are reduced. People's physical fitness and health is deteriorating. Therefore, it is necessary to develop a system that can enhance people's physical fitness and health. However, it is difficult for general physical fitness and healthcare systems to meet individualized needs. The main purpose of this research is to develop a method of intelligent diagnosis and prescription for a customized physical fitness and healthcare system. The proposed system records all processes of the physical fitness and healthcare system via a wireless sensor network and the results of the diagnosis and prescription will be generated by fuzzy logic inference. It will improve individualized physical fitness and healthcare. Finally, we demonstrate the advantages of intelligent diagnosis and prescription for a customized physical fitness and healthcare system.

Is the Bifactor Model a Better Model or is it Just Better at Modeling Implausible Responses? Application of Iteratively Reweighted Least Squares to the Rosenberg Self-Esteem Scale

PubMed Central

Reise, Steven P.; Kim, Dale S.; Mansolf, Maxwell; Widaman, Keith F.

2017-01-01

Although the structure of the Rosenberg Self-Esteem Scale (RSES; Rosenberg, 1965) has been exhaustively evaluated, questions regarding dimensionality and direction of wording effects continue to be debated. To shed new light on these issues, we ask: (1) for what percentage of individuals is a unidimensional model adequate, (2) what additional percentage of individuals can be modeled with multidimensional specifications, and (3) what percentage of individuals respond so inconsistently that they cannot be well modeled? To estimate these percentages, we applied iteratively reweighted least squares (IRLS; Yuan & Bentler, 2000) to examine the structure of the RSES in a large, publicly available dataset. A distance measure, ds, reflecting a distance between a response pattern and an estimated model, was used for case weighting. We found that a bifactor model provided the best overall model fit, with one general factor and two wording-related group factors. But, based on dr values, a distance measure based on individual residuals, we concluded that approximately 86% of cases were adequately modeled through a unidimensional structure, and only an additional 3% required a bifactor model. Roughly 11% of cases were judged as “unmodelable” due to their significant residuals in all models considered. Finally, analysis of ds revealed that some, but not all, of the superior fit of the bifactor model is owed to that model’s ability to better accommodate implausible and possibly invalid response patterns, and not necessarily because it better accounts for the effects of direction of wording. PMID:27834509

Resolving the problem of galaxy clustering on small scales: any new physics needed?

NASA Astrophysics Data System (ADS)

Kang, X.

2014-02-01

Galaxy clustering sets strong constraints on the physics governing galaxy formation and evolution. However, most current models fail to reproduce the clustering of low-mass galaxies on small scales (r < 1 Mpc h-1). In this paper, we study the galaxy clusterings predicted from a few semi-analytical models. We first compare two Munich versions, Guo et al. and De Lucia & Blaizot. The Guo11 model well reproduces the galaxy stellar mass function, but overpredicts the clustering of low-mass galaxies on small scales. The DLB07 model provides a better fit to the clustering on small scales, but overpredicts the stellar mass function. These seem to be puzzling. The clustering on small scales is dominated by galaxies in the same dark matter halo, and there is slightly more fraction of satellite galaxies residing in massive haloes in the Guo11 model, which is the dominant contribution to the clustering discrepancy between the two models. However, both models still overpredict the clustering at 0.1 < r < 10 Mpc h-1 for low-mass galaxies. This is because both models overpredict the number of satellites by 30 per cent in massive haloes than the data. We show that the Guo11 model could be slightly modified to simultaneously fit the stellar mass function and clusterings, but that cannot be easily achieved in the DLB07 model. The better agreement of DLB07 model with the data actually comes as a coincidence as it predicts too many low-mass central galaxies which are less clustered and thus brings down the total clustering. Finally, we show the predictions from the semi-analytical models of Kang et al. We find that this model can simultaneously fit the stellar mass function and galaxy clustering if the supernova feedback in satellite galaxies is stronger. We conclude that semi-analytical models are now able to solve the small-scales clustering problem, without invoking of any other new physics or changing the dark matter properties, such as the recent favoured warm dark matter.

Diagnostic uncertainty, guilt, mood, and disability in back pain.

PubMed

Serbic, Danijela; Pincus, Tamar; Fife-Schaw, Chris; Dawson, Helen

2016-01-01

In the majority of patients a definitive cause for low back pain (LBP) cannot be established, and many patients report feeling uncertain about their diagnosis, accompanied by guilt. The relationship between diagnostic uncertainty, guilt, mood, and disability is currently unknown. This study tested 3 theoretical models to explore possible pathways between these factors. In Model 1, diagnostic uncertainty was hypothesized to correlate with pain-related guilt, which in turn would positively correlate with depression, anxiety and disability. Two alternative models were tested: (a) a path from depression and anxiety to guilt, from guilt to diagnostic uncertainty, and finally to disability; (b) a model in which depression and anxiety, and independently, diagnostic uncertainty, were associated with guilt, which in turn was associated with disability. Structural equation modeling was employed on data from 413 participants with chronic LBP. All 3 models showed a reasonable-to-good fit with the data, with the 2 alternative models providing marginally better fit indices. Guilt, and especially social guilt, was associated with disability in all 3 models. Diagnostic uncertainty was associated with guilt, but only moderately. Low mood was also associated with guilt. Two newly defined factors, pain related guilt and diagnostic uncertainty, appear to be linked to disability and mood in people with LBP. The causal path of these links cannot be established in this cross sectional study. However, pain-related guilt especially appears to be important, and future research should examine whether interventions directly targeting guilt improve outcomes. (c) 2015 APA, all rights reserved).

Modelling and forecasting 3D-hypocentre seismicity in the Kanto region

NASA Astrophysics Data System (ADS)

Guo, Yicun; Zhuang, Jiancang; Hirata, Naoshi

2018-04-01

This study analyses the seismicity in the Kanto region by fitting the 2D-epicentre and 3D-hypocentre ETAS models to the JMA catalogue for events above magnitude M4.0. In the 3D ETAS model, the focal depth is assumed to follow the beta distribution. Compared with results from the 2D-epicentre ETAS model, the 3D ETAS model greatly improves the data fitting. In addition, the stochastic reconstruction method is used when validating the results of the 3D ETAS model, with results indicating that the shallow events are more productive and their aftershocks decay slightly faster in the time and epicentre dimensions. We also study the changes of seismicity patterns before and after the 2011 Tohoku earthquake. The direct aftershocks of events from the post-Tohoku period are more diffusive in time and epicentre but more concentrated in depth. The seismicity rate increases significantly following the Tohoku earthquake, especially along the interface of the subducting Pacific plate. The curve of cumulative background probabilities for events above M4.0 implies that the background rate decays back to the pre-Tohoku level in about 5 years after the Tohoku earthquake. However, the occurrence rates of smaller events (from M2.0 to M4.0) indicate that the adjustments of local stress field continue at finer scales. Finally, we verify that the 3D model can reproduce the focal depths better than the 2D model and improve the forecasting performance.

Optimally analyzing and implementing of bolt fittings in steel structure based on ANSYS

NASA Astrophysics Data System (ADS)

Han, Na; Song, Shuangyang; Cui, Yan; Wu, Yongchun

2018-03-01

ANSYS simulation software for its excellent performance become outstanding one in Computer-aided Engineering (CAE) family, it is committed to the innovation of engineering simulation to help users to shorten the design process. First, a typical procedure to implement CAE was design. The framework of structural numerical analysis on ANSYS Technology was proposed. Then, A optimally analyzing and implementing of bolt fittings in beam-column join of steel structure was implemented by ANSYS, which was display the cloud chart of XY-shear stress, the cloud chart of YZ-shear stress and the cloud chart of Y component of stress. Finally, ANSYS software simulating results was compared with the measured results by the experiment. The result of ANSYS simulating and analyzing is reliable, efficient and optical. In above process, a structural performance's numerical simulating and analyzing model were explored for engineering enterprises' practice.

A comparative study of the adsorption equilibrium of progesterone by a carbon black and a commercial activated carbon

NASA Astrophysics Data System (ADS)

Valenzuela-Calahorro, Cristóbal; Navarrete-Guijosa, Antonio; Stitou, Mostafa; Cuerda-Correa, Eduardo M.

2007-04-01

In this paper the adsorption process of a natural steroid hormone (progesterone) by a carbon black and a commercial activated carbon has been studied. The corresponding equilibrium isotherms have been analyzed according to a previously proposed model which establishes a kinetic law satisfactorily fitting the C versus t isotherms. The analysis of the experimental data points out the existence of two well-defined sections in the equilibrium isotherms. A general equation including these two processes has been proposed, the global adsorption process being fitted to such equation. From the values of the kinetic equilibrium constant so obtained, values of standard average adsorption enthalpy ( ΔH°) and entropy ( ΔS°) have been calculated. Finally, information related to variations of differential adsorption enthalpy ( ΔH) and entropy ( ΔS) with the surface coverage fraction ( θ) was obtained by using the corresponding Clausius-Clapeyron equations.

Application of separable parameter space techniques to multi-tracer PET compartment modeling.

PubMed

Zhang, Jeff L; Michael Morey, A; Kadrmas, Dan J

2016-02-07

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg-Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models.

Application of separable parameter space techniques to multi-tracer PET compartment modeling

NASA Astrophysics Data System (ADS)

Zhang, Jeff L.; Morey, A. Michael; Kadrmas, Dan J.

2016-02-01

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg-Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models.

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

PubMed

Chernyshenko, O S; Stark, S; Chan, K Y; Drasgow, F; Williams, B

2001-10-01

The present study compared the fit of several IRT models to two personality assessment instruments. Data from 13,059 individuals responding to the US-English version of the Fifth Edition of the Sixteen Personality Factor Questionnaire (16PF) and 1,770 individuals responding to Goldberg's 50 item Big Five Personality measure were analyzed. Various issues pertaining to the fit of the IRT models to personality data were considered. We examined two of the most popular parametric models designed for dichotomously scored items (i.e., the two- and three-parameter logistic models) and a parametric model for polytomous items (Samejima's graded response model). Also examined were Levine's nonparametric maximum likelihood formula scoring models for dichotomous and polytomous data, which were previously found to provide good fits to several cognitive ability tests (Drasgow, Levine, Tsien, Williams, & Mead, 1995). The two- and three-parameter logistic models fit some scales reasonably well but not others; the graded response model generally did not fit well. The nonparametric formula scoring models provided the best fit of the models considered. Several implications of these findings for personality measurement and personnel selection were described.

Comparative evaluation of a new lactation curve model for pasture-based Holstein-Friesian dairy cows.

PubMed

Adediran, S A; Ratkowsky, D A; Donaghy, D J; Malau-Aduli, A E O

2012-09-01

Fourteen lactation models were fitted to average and individual cow lactation data from pasture-based dairy systems in the Australian states of Victoria and Tasmania. The models included a new "log-quadratic" model, and a major objective was to evaluate and compare the performance of this model with the other models. Nine empirical and 5 mechanistic models were first fitted to average test-day milk yield of Holstein-Friesian dairy cows using the nonlinear procedure in SAS. Two additional semiparametric models were fitted using a linear model in ASReml. To investigate the influence of days to first test-day and the number of test-days, 5 of the best-fitting models were then fitted to individual cow lactation data. Model goodness of fit was evaluated using criteria such as the residual mean square, the distribution of residuals, the correlation between actual and predicted values, and the Wald-Wolfowitz runs test. Goodness of fit was similar in all but one of the models in terms of fitting average lactation but they differed in their ability to predict individual lactations. In particular, the widely used incomplete gamma model most displayed this failing. The new log-quadratic model was robust in fitting average and individual lactations, and was less affected by sampled data and more parsimonious in having only 3 parameters, each of which lends itself to biological interpretation. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Measurements of WW and WZ Production in W+jets Final States in pp̄ Collisions

DOE PAGES

Abazov, V. M.; Abbott, B.; Acharya, B. S.; ...

2012-05-02

We study WW and WZ production with lνqq (l=e,μ) final states using data collected by the D0 detector at the Fermilab Tevatron Collider corresponding to 4.3 fb⁻¹ of integrated luminosity from pp̄ collisions at √s=1.96 TeV. Assuming the ratio between the production cross sections σ(WW) and σ(WZ) as predicted by the standard model, we measure the total WV (V=W,Z) cross section to be σ(WV)=19.6 +3.2 -3.0 pb and reject the background-only hypothesis at a level of 7.9 standard deviations. We also use b-jet discrimination to separate the WZ component from the dominant WW component. Simultaneously fitting WW and WZ contributions,more » we measure σ(WW)=15.9 +3.7-3.2 pb and σ(WZ)=3.3 +4.1 -3.3 pb, which is consistent with the standard model predictions.« less

Unsteady Aerodynamic Force Sensing from Strain Data

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi

2017-01-01

A simple approach for computing unsteady aerodynamic forces from simulated measured strain data is proposed in this study. First, the deflection and slope of the structure are computed from the unsteady strain using the two-step approach. Velocities and accelerations of the structure are computed using the autoregressive moving average model, on-line parameter estimator, low-pass filter, and a least-squares curve fitting method together with analytical derivatives with respect to time. Finally, aerodynamic forces over the wing are computed using modal aerodynamic influence coefficient matrices, a rational function approximation, and a time-marching algorithm.

Environmental restraints and life strategies: a habitat templet matrix.

PubMed

Holm, E

1988-02-01

Four basic environmental restraints on life are deduced from the requirements of life's inherent order laws. Possible life strategies to contend with these restraints are listed. The various combinations of the restraints are subsequently investigated, and appropriate combinations of life strategies are fitted. This model is finally tested against insect case histories in various environments, and is demonstrated to explain some combinations of characteristics of insects in ecosystems not covered by the r-K or r-K-A continua. The role of heterochrony in achieving appropriate life strategies is briefly discussed.

Physical frailty and fitness of older driver

PubMed Central

Lenardt, Maria Helena; Binotto, Maria Angelica; Kolb Carneiro, Nathalia Hammerschmidt; Lourenço, Tânia Maria

2017-01-01

Abstract Aim: to analyze the association between physical frailty and the results of fitness capacity exams for driving vehicles among elder Brazilians. Methods: this is a cross sectional study, performed in traffic medicine clinics of the city of Curitiba (Brazil). The data was collected through the physical frailty tests, the use of a structured questionnaire, and searches on the records of the Brazilian National Register of Qualified Drivers.To analyze the information, the authors used descriptive statistics and non-parametrical tests. Results: One hundred seventy two elderly people, of whom 56.4% pre-fragile and 43.6% non-fragile. 25.0% were considered fit for driving, 68.6% were considered fit, but with some restrictions, and 6.4% were placed as temporarily unfit for driving. There was no association between frailty condition and the final results for driving fitness (p= 0.8934). Physical frailty was significantly associated to the restrictions observed for those who were fit under restrictions (p= 0.0313), according to the weekly amount of kilometers traveled (p= 0.0222), and to car accidents occurred after the age of 60 (p= 0.0165). Conclusion: Physical frailty was significantly associated to the restrictions related to driving, reason to which makes important to manage frailty over this group of drivers. However, no association observed between physical frailty and the final result for driving vehicles. PMID:29021637

Refining and validating a conceptual model of Clinical Nurse Leader integrated care delivery.

PubMed

Bender, Miriam; Williams, Marjory; Su, Wei; Hites, Lisle

2017-02-01

To empirically validate a conceptual model of Clinical Nurse Leader integrated care delivery. There is limited evidence of frontline care delivery models that consistently achieve quality patient outcomes. Clinical Nurse Leader integrated care delivery is a promising nursing model with a growing record of success. However, theoretical clarity is necessary to generate causal evidence of effectiveness. Sequential mixed methods. A preliminary Clinical Nurse Leader practice model was refined and survey items developed to correspond with model domains, using focus groups and a Delphi process with a multi-professional expert panel. The survey was administered in 2015 to clinicians and administrators involved in Clinical Nurse Leader initiatives. Confirmatory factor analysis and structural equation modelling were used to validate the measurement and model structure. Final sample n = 518. The model incorporates 13 components organized into five conceptual domains: 'Readiness for Clinical Nurse Leader integrated care delivery'; 'Structuring Clinical Nurse Leader integrated care delivery'; 'Clinical Nurse Leader Practice: Continuous Clinical Leadership'; 'Outcomes of Clinical Nurse Leader integrated care delivery'; and 'Value'. Sample data had good fit with specified model and two-level measurement structure. All hypothesized pathways were significant, with strong coefficients suggesting good fit between theorized and observed path relationships. The validated model articulates an explanatory pathway of Clinical Nurse Leader integrated care delivery, including Clinical Nurse Leader practices that result in improved care dynamics and patient outcomes. The validated model provides a basis for testing in practice to generate evidence that can be deployed across the healthcare spectrum. © 2016 John Wiley & Sons Ltd.

A point cloud modeling method based on geometric constraints mixing the robust least squares method

NASA Astrophysics Data System (ADS)

Yue, JIanping; Pan, Yi; Yue, Shun; Liu, Dapeng; Liu, Bin; Huang, Nan

2016-10-01

The appearance of 3D laser scanning technology has provided a new method for the acquisition of spatial 3D information. It has been widely used in the field of Surveying and Mapping Engineering with the characteristics of automatic and high precision. 3D laser scanning data processing process mainly includes the external laser data acquisition, the internal industry laser data splicing, the late 3D modeling and data integration system. For the point cloud modeling, domestic and foreign researchers have done a lot of research. Surface reconstruction technology mainly include the point shape, the triangle model, the triangle Bezier surface model, the rectangular surface model and so on, and the neural network and the Alfa shape are also used in the curved surface reconstruction. But in these methods, it is often focused on single surface fitting, automatic or manual block fitting, which ignores the model's integrity. It leads to a serious problems in the model after stitching, that is, the surfaces fitting separately is often not satisfied with the well-known geometric constraints, such as parallel, vertical, a fixed angle, or a fixed distance. However, the research on the special modeling theory such as the dimension constraint and the position constraint is not used widely. One of the traditional modeling methods adding geometric constraints is a method combing the penalty function method and the Levenberg-Marquardt algorithm (L-M algorithm), whose stability is pretty good. But in the research process, it is found that the method is greatly influenced by the initial value. In this paper, we propose an improved method of point cloud model taking into account the geometric constraint. We first apply robust least-squares to enhance the initial value's accuracy, and then use penalty function method to transform constrained optimization problems into unconstrained optimization problems, and finally solve the problems using the L-M algorithm. The experimental results show that the internal accuracy is improved, and it is shown that the improved method for point clouds modeling proposed by this paper outperforms the traditional point clouds modeling methods.

X-ray peak broadening analysis of AA 6061{sub 100-x} - x wt.% Al{sub 2}O{sub 3} nanocomposite prepared by mechanical alloying

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sivasankaran, S., E-mail: sivasankarangs1979@gmail.com; Sivaprasad, K., E-mail: ksp@nitt.edu; Narayanasamy, R., E-mail: narayan@nitt.edu

2011-07-15

Nanocrystalline AA 6061 alloy reinforced with alumina (0, 4, 8, and 12 wt.%) in amorphized state composite powder was synthesized by mechanical alloying and consolidated by conventional powder metallurgy route. The as-milled and as-sintered (573 K and 673 K) nanocomposites were characterized by X-ray diffraction (XRD) and transmission electron microscopy (TEM). The peaks corresponding to fine alumina was not observed by XRD patterns due to amorphization. Using high-resolution transmission electron microscope, it is confirmed that the presence of amorphized alumina observed in Al lattice fringes. The crystallite size, lattice strain, deformation stress, and strain energy density of AA 6061 matrixmore » were determined precisely from the first five most intensive reflection of XRD using simple Williamson-Hall models; uniform deformation model, uniform stress deformation model, and uniform energy density deformation model. Among the developed models, uniform energy density deformation model was observed to be the best fit and realistic model for mechanically alloyed powders. This model evidenced the more anisotropic nature of the ball milled powders. The XRD peaks of as-milled powder samples demonstrated a considerable broadening with percentage of reinforcement due to grain refinement and lattice distortions during same milling time (40 h). The as-sintered (673 K) unreinforced AA 6061 matrix crystallite size from well fitted uniform energy density deformation model was 98 nm. The as-milled and as-sintered (673 K) nanocrystallite matrix sizes for 12 wt.% Al{sub 2}O{sub 3} well fitted by uniform energy density deformation model were 38 nm and 77 nm respectively, which indicate that the fine Al{sub 2}O{sub 3} pinned the matrix grain boundary and prevented the grain growth during sintering. Finally, the lattice parameter of Al matrix in as-milled and as-sintered conditions was also investigated in this paper. Research highlights: {yields} Integral breadth methods using various Williamson-Hall models were investigated for line profile analysis. {yields} Uniform energy density deformation model is observed to the best realistic model. {yields} The present analysis is used for understanding the stress and the strain present in the nanocomposites.« less

The VMC survey - XXIII. Model fitting of light and radial velocity curves of Small Magellanic Cloud classical Cepheids

NASA Astrophysics Data System (ADS)

Marconi, M.; Molinaro, R.; Ripepi, V.; Cioni, M.-R. L.; Clementini, G.; Moretti, M. I.; Ragosta, F.; de Grijs, R.; Groenewegen, M. A. T.; Ivanov, V. D.

2017-04-01

We present the results of the χ2 minimization model fitting technique applied to optical and near-infrared photometric and radial velocity data for a sample of nine fundamental and three first overtone classical Cepheids in the Small Magellanic Cloud (SMC). The near-infrared photometry (JK filters) was obtained by the European Southern Observatory (ESO) public survey 'VISTA near-infrared Y, J, Ks survey of the Magellanic Clouds system' (VMC). For each pulsator, isoperiodic model sequences have been computed by adopting a non-linear convective hydrodynamical code in order to reproduce the multifilter light and (when available) radial velocity curve amplitudes and morphological details. The inferred individual distances provide an intrinsic mean value for the SMC distance modulus of 19.01 mag and a standard deviation of 0.08 mag, in agreement with the literature. Moreover, the intrinsic masses and luminosities of the best-fitting model show that all these pulsators are brighter than the canonical evolutionary mass-luminosity relation (MLR), suggesting a significant efficiency of core overshooting and/or mass-loss. Assuming that the inferred deviation from the canonical MLR is only due to mass-loss, we derive the expected distribution of percentage mass-loss as a function of both the pulsation period and the canonical stellar mass. Finally, a good agreement is found between the predicted mean radii and current period-radius (PR) relations in the SMC available in the literature. The results of this investigation support the predictive capabilities of the adopted theoretical scenario and pave the way for the application to other extensive data bases at various chemical compositions, including the VMC Large Magellanic Cloud pulsators and Galactic Cepheids with Gaia parallaxes.

Testing comparison models of DASS-12 and its reliability among adolescents in Malaysia.

PubMed

Osman, Zubaidah Jamil; Mukhtar, Firdaus; Hashim, Hairul Anuar; Abdul Latiff, Latiffah; Mohd Sidik, Sherina; Awang, Hamidin; Ibrahim, Normala; Abdul Rahman, Hejar; Ismail, Siti Irma Fadhilah; Ibrahim, Faisal; Tajik, Esra; Othman, Norlijah

2014-10-01

The 21-item Depression, Anxiety and Stress Scale (DASS-21) is frequently used in non-clinical research to measure mental health factors among adults. However, previous studies have concluded that the 21 items are not stable for utilization among the adolescent population. Thus, the aims of this study are to examine the structure of the factors and to report on the reliability of the refined version of the DASS that consists of 12 items. A total of 2850 students (aged 13 to 17 years old) from three major ethnic in Malaysia completed the DASS-21. The study was conducted at 10 randomly selected secondary schools in the northern state of Peninsular Malaysia. The study population comprised secondary school students (Forms 1, 2 and 4) from the selected schools. Based on the results of the EFA stage, 12 items were included in a final CFA to test the fit of the model. Using maximum likelihood procedures to estimate the model, the selected fit indices indicated a close model fit (χ(2)=132.94, df=57, p=.000; CFI=.96; RMR=.02; RMSEA=.04). Moreover, significant loadings of all the unstandardized regression weights implied an acceptable convergent validity. Besides the convergent validity of the item, a discriminant validity of the subscales was also evident from the moderate latent factor inter-correlations, which ranged from .62 to .75. The subscale reliability was further estimated using Cronbach's alpha and the adequate reliability of the subscales was obtained (Total=76; Depression=.68; Anxiety=.53; Stress=.52). The new version of the 12-item DASS for adolescents in Malaysia (DASS-12) is reliable and has a stable factor structure, and thus it is a useful instrument for distinguishing between depression, anxiety and stress. Copyright © 2014 Elsevier Inc. All rights reserved.

Landslide susceptibility mapping using decision-tree based CHi-squared automatic interaction detection (CHAID) and Logistic regression (LR) integration

NASA Astrophysics Data System (ADS)

Althuwaynee, Omar F.; Pradhan, Biswajeet; Ahmad, Noordin

2014-06-01

This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies.

PSR J0007+7303 In The CTA1 Supernova Remnant: New Gamma-Ray Results From Two Years Of Fermi Large Area Telescope Observations

DOE PAGES

Abdo, A. A.; Wood, K. S.; DeCesar, M. E.; ...

2011-12-22

One of the main results of the Fermi Gamma-Ray Space Telescope is the discovery of γ-ray selected pulsars. The high magnetic field pulsar, PSR J0007+7303 in CTA1, was the first ever to be discovered through its γ-ray pulsations. Based on analysis of 2 years of LAT survey data, we report on the discovery of γ-ray emission in the off-pulse phase interval at the ~ 6σ level. The flux from this emission in the energy range E ≥ 100 MeV is F100 = (1.73±0.40)×10 -8 photons cm -2 s -1 and is best fitted by a power law with a photonmore » index of Γ = 2.54±0.14. The pulsed -ray flux in the same energy range is F100 = (3.95±0.07)×10 -7 photons cm -2 s -1 and is best fitted by an exponentially-cutoff power-law spectrum with a photon index of Γ = 1.41 ± 0.23 and a cutoff energy Ec = 4.04 ± 0.20 GeV. We find no flux variability neither at the 2009 May glitch nor in the long term behavior. We model the γ-ray light curve with two high-altitude emission models, the outer gap and slot gap, and find that the model that best fits the data depends strongly on the assumed origin of the off-pulse emission. Both models favor a large angle between the magnetic axis and observer line of sight, consistent with the nondetection of radio emission being a geometrical effect. Finally we discuss how the LAT results bear on the understanding of the cooling of this neutron star.« less

Optimal moment determination in POME-copula based hydrometeorological dependence modelling

NASA Astrophysics Data System (ADS)

Liu, Dengfeng; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Chen, Yuanfang; Chen, Xi

2017-07-01

Copula has been commonly applied in multivariate modelling in various fields where marginal distribution inference is a key element. To develop a flexible, unbiased mathematical inference framework in hydrometeorological multivariate applications, the principle of maximum entropy (POME) is being increasingly coupled with copula. However, in previous POME-based studies, determination of optimal moment constraints has generally not been considered. The main contribution of this study is the determination of optimal moments for POME for developing a coupled optimal moment-POME-copula framework to model hydrometeorological multivariate events. In this framework, margins (marginals, or marginal distributions) are derived with the use of POME, subject to optimal moment constraints. Then, various candidate copulas are constructed according to the derived margins, and finally the most probable one is determined, based on goodness-of-fit statistics. This optimal moment-POME-copula framework is applied to model the dependence patterns of three types of hydrometeorological events: (i) single-site streamflow-water level; (ii) multi-site streamflow; and (iii) multi-site precipitation, with data collected from Yichang and Hankou in the Yangtze River basin, China. Results indicate that the optimal-moment POME is more accurate in margin fitting and the corresponding copulas reflect a good statistical performance in correlation simulation. Also, the derived copulas, capturing more patterns which traditional correlation coefficients cannot reflect, provide an efficient way in other applied scenarios concerning hydrometeorological multivariate modelling.

Jupiter's Magnetodisc in the Juno Era and Implications for the Aurora

NASA Astrophysics Data System (ADS)

Vogt, M. F.; Spalsbury, L.; Connerney, J. E. P.

2017-12-01

The magnetic field in Jupiter's middle and outer magnetosphere is highly radially stretched by the presence of an azimuthally directed current sheet or magnetodisc. Magnetic field measurements from the Voyager, Pioneer, and Galileo spacecraft have been used to construct models of this current sheet, but these observations were limited to latitudes near the jovigraphic equator. High-latitude measurements, such as those recently collected by the Juno spacecraft in its polar orbit of Jupiter, are needed to more fully constrain our understanding of the magnetodisc structure and its effects on the coupling between the ionosphere and middle and outer magnetosphere. Here we will present Juno magnetic field observations from Jupiter's middle magnetosphere and will fit these data to current sheet models, including the Connerney et al. (1981) and Khurana (1997) models, to study the structure of the magnetodisc. We will examine how well the observations are fit by the available current sheet models and discuss any model modifications that are necessary to accurately represent the magnetic field measurements at high latitudes. We will also discuss temporal changes in the magnetodisc between successive Juno orbits ( 53 days) and on longer time scales by comparing Juno data to data from the Voyager, Pioneer, and Galileo spacecraft. Finally, we will consider the implications of our findings for other magnetospheric and auroral processes, particularly the magnetic mapping between the ionosphere and middle and outer magnetosphere.

Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach

PubMed Central

Senior, Alistair M.; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J.

2016-01-01

Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments. PMID:26858671

Cumulative burden of lifetime adversities: Trauma and mental health in low-SES African Americans and Latino/as.

PubMed

Myers, Hector F; Wyatt, Gail E; Ullman, Jodie B; Loeb, Tamra B; Chin, Dorothy; Prause, Nicole; Zhang, Muyu; Williams, John K; Slavich, George M; Liu, Honghu

2015-05-01

This study examined the utility of a lifetime cumulative adversities and trauma model in predicting the severity of mental health symptoms of depression, anxiety, and posttraumatic stress disorder. We also tested whether ethnicity and gender moderate the effects of this stress exposure construct on mental health using multigroup structural equation modeling. A sample of 500 low-socioeconomic status African American and Latino men and women with histories of adversities and trauma were recruited and assessed with a standard battery of self-report measures of stress and mental health. Multiple-group structural equation models indicated good overall model fit. As hypothesized, experiences of discrimination, childhood family adversities, childhood sexual abuse, other childhood trauma, and chronic stresses all loaded on the latent cumulative burden of adversities and trauma construct (CBAT). The CBAT stress exposure index in turn predicted the mental health status latent variable. Although there were several significant univariate ethnic and gender differences, and ethnic and gender differences were observed on several paths, there were no significant ethnic differences in the final model fit of the data. These findings highlight the deleterious consequences of cumulative stress and trauma for mental health and underscore a need to assess these constructs in selecting appropriate clinical interventions for reducing mental health disparities and improving human health. (c) 2015 APA, all rights reserved).

An assessment of the construct distinctiveness of stress arousal and burnout.

PubMed

Smith, Kenneth J; Davy, Jeanette A; Everly, George S

2006-10-01

This study examined the construct and discriminant validity of stress arousal and burnout as measured on the Stress Arousal Scale and the multidimensional role-specific version of the Maslach Burnout Inventory, respectively. The analyses utilized data from 148 individuals randomly selected from a database of 563 respondents to a larger study. The sample responded to a survey sent to members of the American Institute of Certified Public Accountants (AICPA). Sample size used in this study fell within Loehlin's 1992 prescription that for confirmatory factor analysis with two to four factors, a minimum of 100 to 200 cases should be collected. Forty-six respondents indicated that they were partners, principals, or sole practitioners in accounting firms, and 103 indicated that they were staff members (juniors, seniors, or managers). Latent variables were first constructed for the stress arousal and burnout factors. Confirmatory factor analysis was then conducted on the scale data to assess whether the factors would load on their respective underlying theoretical constructs. Finally, a nested model constraining stress arousal and burnout to load on one underlying construct was tested against the hypothesized two-factor model. The results indicated good model fit for the two-factor model and a significant loss of fit for the one-factor model, thus providing strong support for the conceptualization of stress arousal and burnout as distinct constructs.

Combining shock barometry with numerical modeling: Insights into complex crater formation—The example of the Siljan impact structure (Sweden)

NASA Astrophysics Data System (ADS)

Holm-Alwmark, Sanna; Rae, Auriol S. P.; Ferrière, Ludovic; Alwmark, Carl; Collins, Gareth S.

2017-12-01

Siljan, central Sweden, is the largest known impact structure in Europe. It was formed at about 380 Ma, in the late Devonian period. The structure has been heavily eroded to a level originally located underneath the crater floor, and to date, important questions about the original size and morphology of Siljan remain unanswered. Here we present the results of a shock barometry study of quartz-bearing surface and drill core samples combined with numerical modeling using iSALE. The investigated 13 bedrock granitoid samples show that the recorded shock pressure decreases with increasing depth from 15 to 20 GPa near the (present) surface, to 10-15 GPa at 600 m depth. A best-fit model that is consistent with observational constraints relating to the present size of the structure, the location of the downfaulted sediments, and the observed surface and vertical shock barometry profiles is presented. The best-fit model results in a final crater (rim-to-rim) diameter of 65 km. According to our simulations, the original Siljan impact structure would have been a peak-ring crater. Siljan was formed in a mixed target of Paleozoic sedimentary rocks overlaying crystalline basement. Our modeling suggests that, at the time of impact, the sedimentary sequence was approximately 3 km thick. Since then, there has been around 4 km of erosion of the structure.

Development and control of a magnetorheological haptic device for robot assisted surgery.

PubMed

Shokrollahi, Elnaz; Goldenberg, Andrew A; Drake, James M; Eastwood, Kyle W; Kang, Matthew

2017-07-01

A prototype magnetorheological (MR) fluid-based actuator has been designed for tele-robotic surgical applications. This device is capable of generating forces up to 47 N, with input currents ranging from 0 to 1.5 A. We begin by outlining the physical design of the device, and then discuss a novel nonlinear model of the device's behavior. The model was developed using the Hammerstein-Wiener (H-W) nonlinear black-box technique and is intended to accurately capture the hysteresis behavior of the MR-fluid. Several experiments were conducted on the device to collect estimation and validation datasets to construct the model and assess its performance. Different estimating functions were used to construct the model, and their effectiveness is assessed based on goodness-of-fit and final-prediction-error measurements. A sigmoid network was found to have a goodness-of-fit of 95%. The model estimate was then used to tune a PID controller. Two control schemes were proposed to eliminate the hysteresis behavior present in the MR fluid device. One method uses a traditional force feedback control loop and the other is based on measuring the magnetic field using a Hall-effect sensor embedded within the device. The Hall-effect sensor scheme was found to be superior in terms of cost, simplicity and real-time control performance compared to the force control strategy.

Research on an innovative design model

NASA Astrophysics Data System (ADS)

Fu, Y.; Fang, H.

2018-03-01

The design methods of furniture are different from east to west; it has been the hotspot of the scholars. However, in terms of the theory of modern design innovation, neither the early creation theory, the modern design theory, nor the widely applied TRIZ theory can fully fit the modern furniture design innovation, so it is urgent to study the modern furniture design theory. This paper is based on the idea of TRIZ theory, using lots of literatures as data, and uses the method of statistical stratification to analyze and sort out the research of modern sitting equipment, and finally put forward the modern furniture design model, which provides new ideas and perspectives for the modern design of Chinese furniture.

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.

Curve fitting methods for solar radiation data modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karim, Samsul Ariffin Abdul, E-mail: samsul-ariffin@petronas.com.my, E-mail: balbir@petronas.com.my; Singh, Balbir Singh Mahinder, E-mail: samsul-ariffin@petronas.com.my, E-mail: balbir@petronas.com.my

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 withmore » two terms) gives better results as compare with the other fitting methods.« less

Modeling coding-sequence evolution within the context of residue solvent accessibility.

PubMed

Scherrer, Michael P; Meyer, Austin G; Wilke, Claus O

2012-09-12

Protein structure mediates site-specific patterns of sequence divergence. In particular, residues in the core of a protein (solvent-inaccessible residues) tend to be more evolutionarily conserved than residues on the surface (solvent-accessible residues). Here, we present a model of sequence evolution that explicitly accounts for the relative solvent accessibility of each residue in a protein. Our model is a variant of the Goldman-Yang 1994 (GY94) model in which all model parameters can be functions of the relative solvent accessibility (RSA) of a residue. We apply this model to a data set comprised of nearly 600 yeast genes, and find that an evolutionary-rate ratio ω that varies linearly with RSA provides a better model fit than an RSA-independent ω or an ω that is estimated separately in individual RSA bins. We further show that the branch length t and the transition-transverion ratio κ also vary with RSA. The RSA-dependent GY94 model performs better than an RSA-dependent Muse-Gaut 1994 (MG94) model in which the synonymous and non-synonymous rates individually are linear functions of RSA. Finally, protein core size affects the slope of the linear relationship between ω and RSA, and gene expression level affects both the intercept and the slope. Structure-aware models of sequence evolution provide a significantly better fit than traditional models that neglect structure. The linear relationship between ω and RSA implies that genes are better characterized by their ω slope and intercept than by just their mean ω.

The European Southern Observatory-MIDAS table file system

NASA Technical Reports Server (NTRS)

Peron, M.; Grosbol, P.

1992-01-01

The new and substantially upgraded version of the Table File System in MIDAS is presented as a scientific database system. MIDAS applications for performing database operations on tables are discussed, for instance, the exchange of the data to and from the TFS, the selection of objects, the uncertainty joins across tables, and the graphical representation of data. This upgraded version of the TFS is a full implementation of the binary table extension of the FITS format; in addition, it also supports arrays of strings. Different storage strategies for optimal access of very large data sets are implemented and are addressed in detail. As a simple relational database, the TFS may be used for the management of personal data files. This opens the way to intelligent pipeline processing of large amounts of data. One of the key features of the Table File System is to provide also an extensive set of tools for the analysis of the final results of a reduction process. Column operations using standard and special mathematical functions as well as statistical distributions can be carried out; commands for linear regression and model fitting using nonlinear least square methods and user-defined functions are available. Finally, statistical tests of hypothesis and multivariate methods can also operate on tables.

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

PubMed

Clark, D Angus; Bowles, Ryan P

2018-04-23

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

77 FR 37793 - Airworthiness Directives; the Boeing Company Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-25

... proposed to require installing new structural members in and new tie rod(s) and attach fittings on the left.... ACTION: Final rule. SUMMARY: We are adopting a new airworthiness directive (AD) for certain the Boeing... forward load. This AD requires installing new structural members, tie rod(s), and attach fittings on the...

Fitting of hearing aids with different technical parameters to a patient with dead regions

NASA Astrophysics Data System (ADS)

Hojan-Jezierska, Dorota; Skrodzka, Ewa

2009-01-01

The purpose of the study was to determine an optimal hearing aid fitting procedure for a patient with well diagnosed high-frequency ‘dead regions’ in both cochleas. The patient reported non-symmetrical hearing problems of sensorineural origin. For binaural amplification two similar independent hearing aids were used as well as a pair of dependent devices with an ear-to-ear function. Two fitting methods were used: DSLi/o and NAL-NL1, and four different strategies of fitting were tested: the initial fitting based on the DSLi/o or NAL-NL1 method with necessary loudness corrections, the second fitting taking into account all the available functions of hearing instruments, the third fitting (based on the second one) but with significantly reduced amplification well above one octave of frequency inside dead region, and the final fitting with significantly reduced gain slightly below one octave inside dead regions. The results of hearing aids fitting were assessed using an APHAB procedure.

3D craniofacial registration using thin-plate spline transform and cylindrical surface projection

PubMed Central

Chen, Yucong; Deng, Qingqiong; Duan, Fuqing

2017-01-01

Craniofacial registration is used to establish the point-to-point correspondence in a unified coordinate system among human craniofacial models. It is the foundation of craniofacial reconstruction and other craniofacial statistical analysis research. In this paper, a non-rigid 3D craniofacial registration method using thin-plate spline transform and cylindrical surface projection is proposed. First, the gradient descent optimization is utilized to improve a cylindrical surface fitting (CSF) for the reference craniofacial model. Second, the thin-plate spline transform (TPST) is applied to deform a target craniofacial model to the reference model. Finally, the cylindrical surface projection (CSP) is used to derive the point correspondence between the reference and deformed target models. To accelerate the procedure, the iterative closest point ICP algorithm is used to obtain a rough correspondence, which can provide a possible intersection area of the CSP. Finally, the inverse TPST is used to map the obtained corresponding points from the deformed target craniofacial model to the original model, and it can be realized directly by the correspondence between the original target model and the deformed target model. Three types of registration, namely, reflexive, involutive and transitive registration, are carried out to verify the effectiveness of the proposed craniofacial registration algorithm. Comparison with the methods in the literature shows that the proposed method is more accurate. PMID:28982117

3D craniofacial registration using thin-plate spline transform and cylindrical surface projection.

PubMed

Chen, Yucong; Zhao, Junli; Deng, Qingqiong; Duan, Fuqing

2017-01-01

Craniofacial registration is used to establish the point-to-point correspondence in a unified coordinate system among human craniofacial models. It is the foundation of craniofacial reconstruction and other craniofacial statistical analysis research. In this paper, a non-rigid 3D craniofacial registration method using thin-plate spline transform and cylindrical surface projection is proposed. First, the gradient descent optimization is utilized to improve a cylindrical surface fitting (CSF) for the reference craniofacial model. Second, the thin-plate spline transform (TPST) is applied to deform a target craniofacial model to the reference model. Finally, the cylindrical surface projection (CSP) is used to derive the point correspondence between the reference and deformed target models. To accelerate the procedure, the iterative closest point ICP algorithm is used to obtain a rough correspondence, which can provide a possible intersection area of the CSP. Finally, the inverse TPST is used to map the obtained corresponding points from the deformed target craniofacial model to the original model, and it can be realized directly by the correspondence between the original target model and the deformed target model. Three types of registration, namely, reflexive, involutive and transitive registration, are carried out to verify the effectiveness of the proposed craniofacial registration algorithm. Comparison with the methods in the literature shows that the proposed method is more accurate.

An Update of the Bodeker Scientific Vertically Resolved, Global, Gap-Free Ozone Database

NASA Astrophysics Data System (ADS)

Kremser, S.; Bodeker, G. E.; Lewis, J.; Hassler, B.

2016-12-01

High vertical resolution ozone measurements from multiple satellite-based instruments have been merged with measurements from the global ozonesonde network to calculate monthly mean ozone values in 5º latitude zones. Ozone number densities and ozone mixing ratios are provided on 70 altitude levels (1 to 70 km) and on 70 pressure levels spaced approximately 1 km apart (878.4 hPa to 0.046 hPa). These data are sparse and do not cover the entire globe or altitude range. To provide a gap-free database, a least squares regression model is fitted to these data and then evaluated globally. By applying a single fit at each level, and using the approach of allowing the regression fits to change only slightly from one level to the next, the regression is less sensitive to measurement anomalies at individual stations or to individual satellite-based instruments. Particular attention is paid to ensuring that the low ozone abundances in the polar regions are captured. This presentation reports on updates to an earlier version of the vertically resolved ozone database, including the incorporation of new ozone measurements and new techniques for combining the data. Compared to previous versions of the database, particular attention is paid to avoiding spatial and temporal sampling biases and tracing uncertainties through to the final product. This updated database, developed within the New Zealand Deep South National Science Challenge, is suitable for assessing ozone fields from chemistry-climate model simulations or for providing the ozone boundary conditions for global climate model simulations that do not treat stratospheric chemistry interactively.

Measuring everyday functional competence using the Rasch assessment of everyday activity limitations (REAL) item bank.

PubMed

Oude Voshaar, Martijn A H; Ten Klooster, Peter M; Vonkeman, Harald E; van de Laar, Mart A F J

2017-11-01

Traditional patient-reported physical function instruments often poorly differentiate patients with mild-to-moderate disability. We describe the development and psychometric evaluation of a generic item bank for measuring everyday activity limitations in outpatient populations. Seventy-two items generated from patient interviews and mapped to the International Classification of Functioning, Disability and Health (ICF) domestic life chapter were administered to 1128 adults representative of the Dutch population. The partial credit model was fitted to the item responses and evaluated with respect to its assumptions, model fit, and differential item functioning (DIF). Measurement performance of a computerized adaptive testing (CAT) algorithm was compared with the SF-36 physical functioning scale (PF-10). A final bank of 41 items was developed. All items demonstrated acceptable fit to the partial credit model and measurement invariance across age, sex, and educational level. Five- and ten-item CAT simulations were shown to have high measurement precision, which exceeded that of SF-36 physical functioning scale across the physical function continuum. Floor effects were absent for a 10-item empirical CAT simulation, and ceiling effects were low (13.5%) compared with SF-36 physical functioning (38.1%). CAT also discriminated better than SF-36 physical functioning between age groups, number of chronic conditions, and respondents with or without rheumatic conditions. The Rasch assessment of everyday activity limitations (REAL) item bank will hopefully prove a useful instrument for assessing everyday activity limitations. T-scores obtained using derived measures can be used to benchmark physical function outcomes against the general Dutch adult population.

What Is Fitness Training? Definitions and Implications: A Systematic Review Article

PubMed Central

PAOLI, Antonio; BIANCO, Antonino

2015-01-01

Background: This review based upon studies searched from the major scientific libraries has the objective of clarifying what is fitness training in modern days, the implications that it has on health in both youth and elderly and finally discuss fitness training practical implications. Methods: The PRISMA statement was partially adopted and a number of 92 items were selected, according to the inclusion criteria. Results were discussed in 4 main sections: 1. Children and adolescents fitness levels; 2. Fitness training in the elderly; 3. Pathology prevention through fitness training; 4. Training through Fitness activities. Results: This review pointed out the fact that nowadays there is a large variety of fitness activities available within gyms and fitness centers. Even though they significantly differ with each other, the common aim they have is the wellbeing of the people through the improvement of the physical fitness components and the psychological balance. Conclusion: Fitness instructors’ recommendations should be followed in gym context and should be contingent upon an individual’s objectives, physical capacity, physical characteristics and experience. PMID:26284201

The associations between physical fitness and cardiometabolic risk and body-size phenotypes in perimenopausal women.

PubMed

Gregorio-Arenas, E; Ruiz-Cabello, P; Camiletti-Moirón, D; Moratalla-Cecilia, N; Aranda, P; López-Jurado, M; Llopis, J; Aparicio, V A

2016-10-01

To study the association between physical fitness and body-size phenotypes, and to test which aspects of physical fitness show the greatest independent association with cardiometabolic risk in perimenopausal women. This cross-sectional study involved 228 women aged 53±5years from southern Spain. Physical fitness was assessed by means of the Senior Fitness Test Battery (additionally including handgrip strength and timed up-and-go tests). Anthropometry, resting heart rate, blood pressure and plasma markers of lipid, glycaemic and inflammatory status were measured by standard procedures. The harmonized definition of the 'metabolically healthy but obese' (MHO) phenotype was employed to classify individuals. The overall prevalence of the MHO phenotype was 13% but was 43% among the obese women. Apart from traditional markers, metabolically healthy non-obese women had lower levels of C-reactive protein than women with the other phenotypes (p<0.001), and levels of glycosylated haemoglobin were lower in MHO women than in metabolically abnormal non-obese women (overall p=0.004). Most of the components of physical fitness differed with body-size phenotypes. The 6-min walk and the back-scratch tests presented the most robust differences (both p<0.001). Moreover, the women's performance on the back-scratch (β=0.32; p<0.001) and the 6-min walk (β=0.22; p=0.003) tests was independently associated with the clustered cardiometabolic risk. The back-scratch test explained 10% of the variability (step 1, p<0.001), and the final model, which also included the 6-min walk test (step 2, p=0.003), explained 14% of the variability. Low upper-body flexibility was the most important fitness indicator of cardiometabolic risk in perimenopausal women, but cardiorespiratory fitness also played an important role. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Application of separable parameter space techniques to multi-tracer PET compartment modeling

PubMed Central

Zhang, Jeff L; Morey, A Michael; Kadrmas, Dan J

2016-01-01

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg–Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models. PMID:26788888

On the Complexity of Item Response Theory Models.

PubMed

Bonifay, Wes; Cai, Li

2017-01-01

Complexity in item response theory (IRT) has traditionally been quantified by simply counting the number of freely estimated parameters in the model. However, complexity is also contingent upon the functional form of the model. We examined four popular IRT models-exploratory factor analytic, bifactor, DINA, and DINO-with different functional forms but the same number of free parameters. In comparison, a simpler (unidimensional 3PL) model was specified such that it had 1 more parameter than the previous models. All models were then evaluated according to the minimum description length principle. Specifically, each model was fit to 1,000 data sets that were randomly and uniformly sampled from the complete data space and then assessed using global and item-level fit and diagnostic measures. The findings revealed that the factor analytic and bifactor models possess a strong tendency to fit any possible data. The unidimensional 3PL model displayed minimal fitting propensity, despite the fact that it included an additional free parameter. The DINA and DINO models did not demonstrate a proclivity to fit any possible data, but they did fit well to distinct data patterns. Applied researchers and psychometricians should therefore consider functional form-and not goodness-of-fit alone-when selecting an IRT model.

Advantages of estimating parameters of photosynthesis model by fitting A-Ci curves at multiple subsaturating light intensities

NASA Astrophysics Data System (ADS)

Fu, W.; Gu, L.; Hoffman, F. M.

2013-12-01

The photosynthesis model of Farquhar, von Caemmerer & Berry (1980) is an important tool for predicting the response of plants to climate change. So far, the critical parameters required by the model have been obtained from the leaf-level measurements of gas exchange, namely the net assimilation of CO2 against intercellular CO2 concentration (A-Ci) curves, made at saturating light conditions. With such measurements, most points are likely in the Rubisco-limited state for which the model is structurally overparameterized (the model is also overparameterized in the TPU-limited state). In order to reliably estimate photosynthetic parameters, there must be sufficient number of points in the RuBP regeneration-limited state, which has no structural over-parameterization. To improve the accuracy of A-Ci data analysis, we investigate the potential of using multiple A-Ci curves at subsaturating light intensities to generate some important parameter estimates more accurately. Using subsaturating light intensities allow more RuBp regeneration-limited points to be obtained. In this study, simulated examples are used to demonstrate how this method can eliminate the errors of conventional A-Ci curve fitting methods. Some fitted parameters like the photocompensation point and day respiration impose a significant limitation on modeling leaf CO2 exchange. The multiple A-Ci curves fitting can also improve over the so-called Laisk (1977) method, which was shown by some recent publication to produce incorrect estimates of photocompensation point and day respiration. We also test the approach with actual measurements, along with suggested measurement conditions to constrain measured A-Ci points to maximize the occurrence of RuBP regeneration-limited photosynthesis. Finally, we use our measured gas exchange datasets to quantify the magnitude of resistance of chloroplast and cell wall-plasmalemma and explore the effect of variable mesophyll conductance. The variable mesophyll conductance takes into account the influence of CO2 from mitochondria, comparing to the commonly used constant value of mesophyll conductance. We show that after considering this effect the other parameters of the photosynthesis model can be re-estimated. Our results indicate that variable mesophyll conductance has most effect on the estimation of the parameter of the maximum electron transport rate (Jmax), but has a negligible impact on the estimated day respiration (Rd) and photocompensation point (<2%).

Models for Predicting the Biomass of Cunninghamialanceolata Trees and Stands in Southeastern China

PubMed Central

Saeed, Sajjad

2017-01-01

Using existing equations to estimate the biomass of a single tree or a forest stand still involves large uncertainties. In this study, we developed individual-tree biomass models for Chinese Fir (Cunninghamia lanceolata.) stands in Fujian Province, southeast China, by using 74 previously established models that have been most commonly used to estimate tree biomass. We selected the best fit models and modified them. The results showed that the published model ln(B(Biomass)) = a + b * ln(D) + c * (ln(H))2 + d * (ln(H))3 + e * ln(WD) had the best fit for estimating the tree biomass of Chinese Fir stands. Furthermore, we observed that variables D(diameter at breast height), H (height), and WD(wood density)were significantly correlated with the total tree biomass estimation model. As a result, a natural logarithm structure gave the best estimates for the tree biomass structure. Finally, when a multi-step improvement on tree biomass model was performed, the tree biomass model with Tree volume(TV), WD and biomass wood density conversion factor (BECF),achieved the highest simulation accuracy, expressed as ln(TB) = −0.0703 + 0.9780 * ln(TV) + 0.0213 * ln(WD) + 1.0166 * ln(BECF). Therefore, when TV, WD and BECF were combined with tree biomass volume coefficient bi for Chinese Fir, the stand biomass (SB)model included both volume(SV) and coefficient bi variables of the stand as follows: bi = Exp(−0.0703+0.9780*ln(TV)+0.0213 * ln(WD)+1.0166*ln(BECF)). The stand biomass model is SB = SV/TV * bi. PMID:28095512

Models for Predicting the Biomass of Cunninghamialanceolata Trees and Stands in Southeastern China.

PubMed

Guangyi, Mei; Yujun, Sun; Saeed, Sajjad

2017-01-01

Using existing equations to estimate the biomass of a single tree or a forest stand still involves large uncertainties. In this study, we developed individual-tree biomass models for Chinese Fir (Cunninghamia lanceolata.) stands in Fujian Province, southeast China, by using 74 previously established models that have been most commonly used to estimate tree biomass. We selected the best fit models and modified them. The results showed that the published model ln(B(Biomass)) = a + b * ln(D) + c * (ln(H))2 + d * (ln(H))3 + e * ln(WD) had the best fit for estimating the tree biomass of Chinese Fir stands. Furthermore, we observed that variables D(diameter at breast height), H (height), and WD(wood density)were significantly correlated with the total tree biomass estimation model. As a result, a natural logarithm structure gave the best estimates for the tree biomass structure. Finally, when a multi-step improvement on tree biomass model was performed, the tree biomass model with Tree volume(TV), WD and biomass wood density conversion factor (BECF),achieved the highest simulation accuracy, expressed as ln(TB) = -0.0703 + 0.9780 * ln(TV) + 0.0213 * ln(WD) + 1.0166 * ln(BECF). Therefore, when TV, WD and BECF were combined with tree biomass volume coefficient bi for Chinese Fir, the stand biomass (SB)model included both volume(SV) and coefficient bi variables of the stand as follows: bi = Exp(-0.0703+0.9780*ln(TV)+0.0213 * ln(WD)+1.0166*ln(BECF)). The stand biomass model is SB = SV/TV * bi.

Testing goodness of fit in regression: a general approach for specified alternatives.

PubMed

Solari, Aldo; le Cessie, Saskia; Goeman, Jelle J

2012-12-10

When fitting generalized linear models or the Cox proportional hazards model, it is important to have tools to test for lack of fit. Because lack of fit comes in all shapes and sizes, distinguishing among different types of lack of fit is of practical importance. We argue that an adequate diagnosis of lack of fit requires a specified alternative model. Such specification identifies the type of lack of fit the test is directed against so that if we reject the null hypothesis, we know the direction of the departure from the model. The goodness-of-fit approach of this paper allows to treat different types of lack of fit within a unified general framework and to consider many existing tests as special cases. Connections with penalized likelihood and random effects are discussed, and the application of the proposed approach is illustrated with medical examples. Tailored functions for goodness-of-fit testing have been implemented in the R package global test. Copyright © 2012 John Wiley & Sons, Ltd.

Soft-sensing model of temperature for aluminum reduction cell on improved twin support vector regression

NASA Astrophysics Data System (ADS)

Li, Tao

2018-06-01

The complexity of aluminum electrolysis process leads the temperature for aluminum reduction cells hard to measure directly. However, temperature is the control center of aluminum production. To solve this problem, combining some aluminum plant's practice data, this paper presents a Soft-sensing model of temperature for aluminum electrolysis process on Improved Twin Support Vector Regression (ITSVR). ITSVR eliminates the slow learning speed of Support Vector Regression (SVR) and the over-fit risk of Twin Support Vector Regression (TSVR) by introducing a regularization term into the objective function of TSVR, which ensures the structural risk minimization principle and lower computational complexity. Finally, the model with some other parameters as auxiliary variable, predicts the temperature by ITSVR. The simulation result shows Soft-sensing model based on ITSVR has short time-consuming and better generalization.

Modelling the atomic structure of Al92U8 metallic glass.

PubMed

Michalik, S; Bednarcik, J; Jóvári, P; Honkimäki, V; Webb, A; Franz, H; Fazakas, E; Varga, L K

2010-10-13

The local atomic structure of the glassy Al(92)U(8) alloy was modelled by the reverse Monte Carlo (RMC) method, fitting x-ray diffraction (XRD) and extended x-ray absorption fine structure (EXAFS) signals. The final structural model was analysed by means of partial pair correlation functions, coordination number distributions and Voronoi tessellation. In our study we found that the most probable atomic separations between Al-Al and U-Al pairs in the glassy Al(92)U(8) alloy are 2.7 Å and 3.1 Å with coordination numbers 11.7 and 17.1, respectively. The Voronoi analysis did not support evidence of the existence of well-defined building blocks directly embedded in the amorphous matrix. The dense-random-packing model seems to be adequate for describing the connection between solvent and solute atoms.

Immersion freezing of water and aqueous ammonium sulfate droplets initiated by humic-like substances as a function of water activity

DOE PAGES

Rigg, Y. J.; Alpert, P. A.; Knopf, Daniel A.

2013-07-12

Immersion freezing of water and aqueous (NH 4) 2SO 4 droplets containing leonardite (LEO) and Pahokee peat (PP) serving as surrogates for humic-like substances (HULIS) has been investigated. Organic aerosol containing HULIS are ubiquitous in the atmosphere; however, their potential for ice cloud formation is uncertain. Immersion freezing has been studied for temperatures as low as 215K and solution water activity, aw, from 0.85 to 1.0. The freezing temperatures of water and aqueous solution droplets containing LEO and PP are 5–15 K warmer than homogeneous ice nucleation temperatures. Heterogeneous freezing temperatures can be represented by a horizontal shift of themore » ice melting curve as a function of solution aw by Δ aw = 0.2703 and 0.2466, respectively. Corresponding heterogeneous ice nucleation rate coefficients, Jhet, are (9.6 ± 2.5) × 10 4 and (5.4 ± 1.4) × 10 4 cm -2 s -1 for LEO and PP containing droplets, respectively, and remain constant along freezing curves characterized by Δ aw. Consequently predictions of freezing temperatures and kinetics can be made without knowledge of the solute type when relative humidity and ice nuclei (IN) surface areas are known. The acquired ice nucleation data are applied to evaluate different approaches to fit and reproduce experimentally derived frozen fractions. In addition, we apply a basic formulation of classical nucleation theory (α( T)-model) to calculate contact angles and frozen fractions. Contact angles calculated for each ice nucleus as a function of temperature, α( T)-model, reproduce exactly experimentally derived frozen fractions without involving free-fit parameters. However, assigning the IN a single contact angle for the entire population (single-α model) is not suited to represent the frozen fractions. Application of α-PDF, active sites, and deterministic model approaches to measured frozen fractions yield similar good representations. Furthermore, when using a single parameterization of α-PDF or active sites distribution to fit all individual aw immersion freezing data simultaneously, frozen fraction curves are not reproduced. This implies that these fitting formulations cannot be applied to immersion freezing of aqueous solutions, and suggests that derived fit parameters do not represent independent particle properties. Thus, from fitting frozen fractions only, the underlying ice nucleation mechanism and nature of the ice nucleating sites cannot be inferred. In contrast to using fitted functions obtained to represent experimental conditions only, we suggest to use experimentally derived Jhet as a function of temperature and aw that can be applied to conditions outside of those probed in laboratory. Finally, this is because Jhet(T) is independent of time and IN surface areas in contrast to the fit parameters obtained by representation of experimentally derived frozen fractions.« less

A global goodness-of-fit statistic for Cox regression models.

PubMed

Parzen, M; Lipsitz, S R

1999-06-01

In this paper, a global goodness-of-fit test statistic for a Cox regression model, which has an approximate chi-squared distribution when the model has been correctly specified, is proposed. Our goodness-of-fit statistic is global and has power to detect if interactions or higher order powers of covariates in the model are needed. The proposed statistic is similar to the Hosmer and Lemeshow (1980, Communications in Statistics A10, 1043-1069) goodness-of-fit statistic for binary data as well as Schoenfeld's (1980, Biometrika 67, 145-153) statistic for the Cox model. The methods are illustrated using data from a Mayo Clinic trial in primary billiary cirrhosis of the liver (Fleming and Harrington, 1991, Counting Processes and Survival Analysis), in which the outcome is the time until liver transplantation or death. The are 17 possible covariates. Two Cox proportional hazards models are fit to the data, and the proposed goodness-of-fit statistic is applied to the fitted models.

Nutritional Status of Rural Older Adults Is Linked to Physical and Emotional Health.

PubMed

Jung, Seung Eun; Bishop, Alex J; Kim, Minjung; Hermann, Janice; Kim, Giyeon; Lawrence, Jeannine

2017-06-01

Although nutritional status is influenced by multidimensional aspects encompassing physical and emotional well-being, there is limited research on this complex relationship. The purpose of this study was to examine the interplay between indicators of physical health (perceived health status and self-care capacity) and emotional well-being (depressive affect and loneliness) on rural older adults' nutritional status. The cross-sectional study was conducted from June 1, 2007, to June 1, 2008. A total of 171 community-dwelling older adults, aged 65 years and older, residing within nonmetro rural communities in the United States participated in this study. Participants completed validated instruments measuring self-care capacity, perceived health status, loneliness, depressive affect, and nutritional status. Structural equation modeling was employed to investigate the complex interplay of physical and emotional health status with nutritional status among rural older adults. The χ 2 test, comparative fit index, root mean square error of approximation, and standardized root mean square residual were used to assess model fit. The χ 2 test and the other model fit indexes showed the hypothesized structural equation model provided a good fit to the data (χ 2 (2)=2.15; P=0.34; comparative fit index=1.00; root mean square error of approximation=0.02; and standardized root mean square residual=0.03). Self-care capacity was significantly related with depressive affect (γ=-0.11; P=0.03), whereas self-care capacity was not significantly related with loneliness. Perceived health status had a significant negative relationship with both loneliness (γ=-0.16; P=0.03) and depressive affect (γ=-0.22; P=0.03). Although loneliness showed no significant direct relationship with nutritional status, it showed a significant direct relationship with depressive affect (β=.4; P<0.01). Finally, the results demonstrated that depressive affect had a significant negative relationship with nutritional status (β=-.30; P<0.01). The results indicated physical health and emotional indicators have significant multidimensional associations with nutritional status among rural older adults. The present study provides insights into the importance of addressing both physical and emotional well-being together to reduce potential effects of poor emotional well-being on nutritional status, particularly among rural older adults with impaired physical health and self-care capacity. Copyright © 2017 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Assessing normative cut points through differential item functioning analysis: an example from the adaptation of the Middlesex Elderly Assessment of Mental State (MEAMS) for use as a cognitive screening test in Turkey.

PubMed

Tennant, Alan; Küçükdeveci, Ayse A; Kutlay, Sehim; Elhan, Atilla H

2006-03-23

The Middlesex Elderly Assessment of Mental State (MEAMS) was developed as a screening test to detect cognitive impairment in the elderly. It includes 12 subtests, each having a 'pass score'. A series of tasks were undertaken to adapt the measure for use in the adult population in Turkey and to determine the validity of existing cut points for passing subtests, given the wide range of educational level in the Turkish population. This study focuses on identifying and validating the scoring system of the MEAMS for Turkish adult population. After the translation procedure, 350 normal subjects and 158 acquired brain injury patients were assessed by the Turkish version of MEAMS. Initially, appropriate pass scores for the normal population were determined through ANOVA post-hoc tests according to age, gender and education. Rasch analysis was then used to test the internal construct validity of the scale and the validity of the cut points for pass scores on the pooled data by using Differential Item Functioning (DIF) analysis within the framework of the Rasch model. Data with the initially modified pass scores were analyzed. DIF was found for certain subtests by age and education, but not for gender. Following this, pass scores were further adjusted and data re-fitted to the model. All subtests were found to fit the Rasch model (mean item fit 0.184, SD 0.319; person fit -0.224, SD 0.557) and DIF was then found to be absent. Thus the final pass scores for all subtests were determined. The MEAMS offers a valid assessment of cognitive state for the adult Turkish population, and the revised cut points accommodate for age and education. Further studies are required to ascertain the validity in different diagnostic groups.

The effect of different screw-tightening techniques on the strain generated on an internal-connection implant superstructure. Part 2: Models created with a splinted impression technique.

PubMed

Choi, Jung-Han

2011-01-01

This study aimed to evaluate the effect of different screw-tightening sequences, torques, and methods on the strains generated on an internal-connection implant (Astra Tech) superstructure with good fit. An edentulous mandibular master model and a metal framework directly connected to four parallel implants with a passive fit to each other were fabricated. Six stone casts were made from a dental stone master model by a splinted impression technique to represent a well-fitting situation with the metal framework. Strains generated by four screw-tightening sequences (1-2-3-4, 4-3-2-1, 2-4-3-1, and 2-3-1-4), two torques (10 and 20 Ncm), and two methods (one-step and two-step) were evaluated. In the two-step method, screws were tightened to the initial torque (10 Ncm) in a predetermined screw-tightening sequence and then to the final torque (20 Ncm) in the same sequence. Strains were recorded twice by three strain gauges attached to the framework (superior face midway between abutments). Deformation data were analyzed using multiple analysis of variance at a .05 level of statistical significance. In all stone casts, strains were produced by connection of the superstructure, regardless of screw-tightening sequence, torque, and method. No statistically significant differences in superstructure strains were found based on screw-tightening sequences (range, -409.8 to -413.8 μm/m), torques (-409.7 and -399.1 μm/m), or methods (-399.1 and -410.3 μm/m). Within the limitations of this in vitro study, screw-tightening sequence, torque, and method were not critical factors for the strain generated on a well-fitting internal-connection implant superstructure by the splinted impression technique. Further studies are needed to evaluate the effect of screw-tightening techniques on the preload stress in various different clinical situations.

Mild angle early onset idiopathic scoliosis children avoid progression under FITS method (Functional Individual Therapy of Scoliosis).

PubMed

Białek, Marianna

2015-05-01

Physiotherapy for stabilization of idiopathic scoliosis angle in growing children remains controversial. Notably, little data on effectiveness of physiotherapy in children with Early Onset Idiopathic Scoliosis (EOIS) has been published.The aim of this study was to check results of FITS physiotherapy in a group of children with EOIS.The charts of the patients archived in a prospectively collected database were retrospectively reviewed. The inclusion criteria were:diagnosis of EOIS based on spine radiography, age below 10 years, both girls and boys, Cobb angle between 118 and 308, Risser zero, FITS therapy, no other treatment (bracing), and a follow-up at least 2 years from the initiation of the treatment. The criterion for curve progression were as follows: the Cobb angle increase of 68 or more, for curve stabilization; the Cobb angle was 58 comparing to the initial radiograph,for curve correction; and the Cobb angle decrease of 68 or more at the final follow-up radiograph.There were 41 children with EOIS, 36 girls and 5 boys, mean age 7.71.3 years (range 4 to 9 years) who started FITS therapy. The curve pattern was single thoracic (5 children), single thoracolumbar (22 children) or double thoracic/thoracolumbar (14 children), totally 55 structural curvatures. The minimum follow-up was 2 years after initiation of the FITS treatment, maximum was 16 years, mean 4.8 years). At follow-up the mean age was 12.53.4 years. Out of 41 children, 10 passed pubertal growth spurt at the final follow-up and 31 were still immature and continued FITS therapy. Out of 41 children, 27 improved, 13 were stable, and one progressed. Out of 55 structural curves, 32 improved, 22 were stable and one progressed. For the 55 structural curves, the Cobb angle significantly decreased from 18.085.48 at first assessment to 12.586.38 at last evaluation,p<0.0001, paired t-test. The angle of trunk rotation decreased significantly from 4.782.98 to 3.282.58 at last evaluation, p<0.0001,paired t-test.FITS physiotherapy was effective in preventing curve progression in children with EOIS. Final postpubertal follow-up data is needed.

Earthquake simulator tests and associated study of an 1/6-scale nine-story RC model

NASA Astrophysics Data System (ADS)

Sun, Jingjiang; Wang, Tao; Qi, Hu

2007-09-01

Earthquake simulator tests of a 1/6-scale nine-story reinforced concrete frame-wall model are described in the paper. The test results and associated numerical simulation are summarized and discussed. Based on the test data, a relationship between maximum inter-story drift and damage state is established. Equations of variation of structural characteristics (natural frequency and equivalent stiffness) with overall drifts are derived by data fitting, which can be used to estimate structural damage state if structural characteristics can be measured. A comparison of the analytical and experimental results show that both the commonly used equivalent beam and fiber element models can simulate the nonlinear seismic response of structures very well. Finally, conclusions associated with seismic design and damage evaluation of RC structures are presented.

Effective field theory in the harmonic oscillator basis

DOE PAGES

Binder, S.; Ekström, Jan A.; Hagen, Gaute; ...

2016-04-25

In this paper, we develop interactions from chiral effective field theory (EFT) that are tailored to the harmonic oscillator basis. As a consequence, ultraviolet convergence with respect to the model space is implemented by construction and infrared convergence can be achieved by enlarging the model space for the kinetic energy. In oscillator EFT, matrix elements of EFTs formulated for continuous momenta are evaluated at the discrete momenta that stem from the diagonalization of the kinetic energy in the finite oscillator space. By fitting to realistic phase shifts and deuteron data we construct an effective interaction from chiral EFT at next-to-leadingmore » order. Finally, many-body coupled-cluster calculations of nuclei up to 132Sn converge fast for the ground-state energies and radii in feasible model spaces.« less

PyPWA: A partial-wave/amplitude analysis software framework

NASA Astrophysics Data System (ADS)

Salgado, Carlos

2016-05-01

The PyPWA project aims to develop a software framework for Partial Wave and Amplitude Analysis of data; providing the user with software tools to identify resonances from multi-particle final states in photoproduction. Most of the code is written in Python. The software is divided into two main branches: one general-shell where amplitude's parameters (or any parametric model) are to be estimated from the data. This branch also includes software to produce simulated data-sets using the fitted amplitudes. A second branch contains a specific realization of the isobar model (with room to include Deck-type and other isobar model extensions) to perform PWA with an interface into the computer resources at Jefferson Lab. We are currently implementing parallelism and vectorization using the Intel's Xeon Phi family of coprocessors.

Pion exchange at high energies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, L.M.

1980-07-01

The state of Regge pion exchange calculations for high-energy reactions is reviewed. Experimental evidence is summarized to show that (i) the pion trajectory has a slope similar to that of other trajectories; (ii) the pion exchange contribution can dominate contributions of higher trajectories up to quite a large energy; (iii) many two-body cross sections with large pion contributions can be fit only by models which allow for kinematical conspiracy at t=0. The theory of kinematic conspiracy is reviewed for two-body amplitudes, and calculations of the conspiring pion--Pomeron cut discussed. The author then summarizes recent work on pion exchange in Reggeizedmore » Deck models for multiparticle final states, with emphasis on the predictions of various models (with and without resonances) for phases of the partial wave amplitudes.« less

Wind Tunnel Strain-Gage Balance Calibration Data Analysis Using a Weighted Least Squares Approach

NASA Technical Reports Server (NTRS)

Ulbrich, N.; Volden, T.

2017-01-01

A new approach is presented that uses a weighted least squares fit to analyze wind tunnel strain-gage balance calibration data. The weighted least squares fit is specifically designed to increase the influence of single-component loadings during the regression analysis. The weighted least squares fit also reduces the impact of calibration load schedule asymmetries on the predicted primary sensitivities of the balance gages. A weighting factor between zero and one is assigned to each calibration data point that depends on a simple count of its intentionally loaded load components or gages. The greater the number of a data point's intentionally loaded load components or gages is, the smaller its weighting factor becomes. The proposed approach is applicable to both the Iterative and Non-Iterative Methods that are used for the analysis of strain-gage balance calibration data in the aerospace testing community. The Iterative Method uses a reasonable estimate of the tare corrected load set as input for the determination of the weighting factors. The Non-Iterative Method, on the other hand, uses gage output differences relative to the natural zeros as input for the determination of the weighting factors. Machine calibration data of a six-component force balance is used to illustrate benefits of the proposed weighted least squares fit. In addition, a detailed derivation of the PRESS residuals associated with a weighted least squares fit is given in the appendices of the paper as this information could not be found in the literature. These PRESS residuals may be needed to evaluate the predictive capabilities of the final regression models that result from a weighted least squares fit of the balance calibration data.

Relationships between attitudes toward and achievement in science for rural middle school students: Patterns across gender

NASA Astrophysics Data System (ADS)

Mattern, Nancy Page Garland

Four causal models describing the relationships between attitudes and achievement have been proposed in the literature. The cross-effects, or reciprocal effects, model highlights the effects of prior attitudes on later achievement (over and above the effect of previous achievement) and of prior achievement on later attitudes (above the effect of previous attitudes). In the achievement predominant model, the effect of prior achievement on later attitudes is emphasized, controlling for the effect of previous attitudes. The effect of prior attitudes on later achievement, controlling for the effect of previous achievement, is emphasized in the attitudes predominant model. In the no cross-effects model there are no significant cross paths from prior attitudes to later achievement or from prior achievement to later attitudes. To determine the best-fitting model for rural seventh and eighth grade science girls and boys, the causal relationships over time between attitudes toward science and achievement in science were examined by gender using structural equation modeling. Data were collected in two waves, over one school year. A baseline measurement model was estimated in simultaneous two-group solutions and was a good fit to the data. Next, the four structural models were estimated and model fits compared. The three models nested within the structural cross-effects model showed significant decay of fit when compared to the fit of the cross-effects model. The cross-effects model was the best fit overall for middle school girls and boys. The cross-effects model was then tested for invariance across gender. There was significant decay of fit when model form, factor path loadings, and structural paths were constrained to be equal for girls and boys. Two structural paths, the path from prior achievement to later attitudes, and the path from prior attitudes to later attitudes, were the sources of gender non-invariance. Separate models were estimated for girls and boys, and the fits of nested models were compared. The no cross-effects model was the best-fitting model for rural middle school girls. The new no attitudes-path model was the best-fitting model for boys. Implications of these findings for teaching middle school students were discussed.

Delivering good service: personal resources, job satisfaction and nurses' 'customer' (patient) orientation.

PubMed

Gountas, Sandra; Gountas, John; Soutar, Geoffrey; Mavondo, Felix

2014-07-01

To explore the complex relationships between nurses' personal resources, job satisfaction and 'customer' (patient) orientation. Previous research has shown that nursing is highly intensive, emotionally charged work, which affects nurses' job performance and their customer orientation as well as patient or 'customer' satisfaction. This study contributes to the literature by examining how nurses' personal resources relate to their personal satisfaction and customer orientation and the relationships between them. Specifically, this study explores the effects of two facets of emotional labour (deep acting and surface acting), empathic concern, self-efficacy and emotional exhaustion on personal job satisfaction and customer orientation. We also test the moderating effects of inauthenticity and emotional contagion. A quantitative survey. Data were collected through a self-completion questionnaire administered to a sample of 159 Australian nurses, in a public teaching hospital, in 2010. The data were analysed using Partial Least Square analysis. Partial Least Square analysis indicates that the final model is a good fit to the data (Goodness of Fit = 0.51). Deep acting and surface acting have different effects (positive and negative) on job satisfaction and 'customer' orientation, self-efficacy has a positive effect on both and emotional exhaustion has a positive effect on customer orientation and a negative effect on job satisfaction. The moderating effects of emotional contagion and empathic concern, in the final model, are discussed. Understanding the complex interactions between personal resources, job satisfaction and customer orientation helps to increase service providers' (nurses in this study) personal satisfaction and 'customer' orientation particularly in difficult contexts. © 2013 John Wiley & Sons Ltd.