Non-linear Relationship between BOLD Activation and Amplitude of Beta Oscillations in the Supplementary Motor Area during Rhythmic Finger Tapping and Internal Timing.

PubMed

Gompf, Florian; Pflug, Anja; Laufs, Helmut; Kell, Christian A

2017-01-01

Functional imaging studies using BOLD contrasts have consistently reported activation of the supplementary motor area (SMA) both during motor and internal timing tasks. Opposing findings, however, have been shown for the modulation of beta oscillations in the SMA. While movement suppresses beta oscillations in the SMA, motor and non-motor tasks that rely on internal timing increase the amplitude of beta oscillations in the SMA. These independent observations suggest that the relationship between beta oscillations and BOLD activation is more complex than previously thought. Here we set out to investigate this rapport by examining beta oscillations in the SMA during movement with varying degrees of internal timing demands. In a simultaneous EEG-fMRI experiment, 20 healthy right-handed subjects performed an auditory-paced finger-tapping task. Internal timing was operationalized by including conditions with taps on every fourth auditory beat, which necessitates generation of a slow internal rhythm, while tapping to every auditory beat reflected simple auditory-motor synchronization. In the SMA, BOLD activity increased and power in both the low and the high beta band decreased expectedly during each condition compared to baseline. Internal timing was associated with a reduced desynchronization of low beta oscillations compared to conditions without internal timing demands. In parallel with this relative beta power increase, internal timing activated the SMA more strongly in terms of BOLD. This documents a task-dependent non-linear relationship between BOLD and beta-oscillations in the SMA. We discuss different roles of beta synchronization and desynchronization in active processing within the same cortical region.

Exact and Approximate Statistical Inference for Nonlinear Regression and the Estimating Equation Approach.

PubMed

Demidenko, Eugene

2017-09-01

The exact density distribution of the nonlinear least squares estimator in the one-parameter regression model is derived in closed form and expressed through the cumulative distribution function of the standard normal variable. Several proposals to generalize this result are discussed. The exact density is extended to the estimating equation (EE) approach and the nonlinear regression with an arbitrary number of linear parameters and one intrinsically nonlinear parameter. For a very special nonlinear regression model, the derived density coincides with the distribution of the ratio of two normally distributed random variables previously obtained by Fieller (1932), unlike other approximations previously suggested by other authors. Approximations to the density of the EE estimators are discussed in the multivariate case. Numerical complications associated with the nonlinear least squares are illustrated, such as nonexistence and/or multiple solutions, as major factors contributing to poor density approximation. The nonlinear Markov-Gauss theorem is formulated based on the near exact EE density approximation.

Coping styles in heart failure patients with depressive symptoms.

PubMed

Trivedi, Ranak B; Blumenthal, James A; O'Connor, Christopher; Adams, Kirkwood; Hinderliter, Alan; Dupree, Carla; Johnson, Kristy; Sherwood, Andrew

2009-10-01

Elevated depressive symptoms have been linked to poorer prognosis in heart failure (HF) patients. Our objective was to identify coping styles associated with depressive symptoms in HF patients. A total of 222 stable HF patients (32.75% female, 45.4% non-Hispanic black) completed multiple questionnaires. Beck Depression Inventory (BDI) assessed depressive symptoms, Life Orientation Test (LOT-R) assessed optimism, ENRICHD Social Support Inventory (ESSI) and Perceived Social Support Scale (PSSS) assessed social support, and COPE assessed coping styles. Linear regression analyses were employed to assess the association of coping styles with continuous BDI scores. Logistic regression analyses were performed using BDI scores dichotomized into BDI<10 vs. BDI> or =10, to identify coping styles accompanying clinically significant depressive symptoms. In linear regression models, higher BDI scores were associated with lower scores on the acceptance (beta=-.14), humor (beta=-.15), planning (beta=-.15), and emotional support (beta=-.14) subscales of the COPE, and higher scores on the behavioral disengagement (beta=.41), denial (beta=.33), venting (beta=.25), and mental disengagement (beta=.22) subscales. Higher PSSS and ESSI scores were associated with lower BDI scores (beta=-.32 and -.25, respectively). Higher LOT-R scores were associated with higher BDI scores (beta=.39, P<.001). In logistical regression models, BDI> or =10 was associated with greater likelihood of behavioral disengagement (OR=1.3), denial (OR=1.2), mental disengagement (OR=1.3), venting (OR=1.2), and pessimism (OR=1.2), and lower perceived social support measured by PSSS (OR=.92) and ESSI (OR=.92). Depressive symptoms in HF patients are associated with avoidant coping, lower perceived social support, and pessimism. Results raise the possibility that interventions designed to improve coping may reduce depressive symptoms.

Computation of nonlinear least squares estimator and maximum likelihood using principles in matrix calculus

NASA Astrophysics Data System (ADS)

Mahaboob, B.; Venkateswarlu, B.; Sankar, J. Ravi; Balasiddamuni, P.

2017-11-01

This paper uses matrix calculus techniques to obtain Nonlinear Least Squares Estimator (NLSE), Maximum Likelihood Estimator (MLE) and Linear Pseudo model for nonlinear regression model. David Pollard and Peter Radchenko [1] explained analytic techniques to compute the NLSE. However the present research paper introduces an innovative method to compute the NLSE using principles in multivariate calculus. This study is concerned with very new optimization techniques used to compute MLE and NLSE. Anh [2] derived NLSE and MLE of a heteroscedatistic regression model. Lemcoff [3] discussed a procedure to get linear pseudo model for nonlinear regression model. In this research article a new technique is developed to get the linear pseudo model for nonlinear regression model using multivariate calculus. The linear pseudo model of Edmond Malinvaud [4] has been explained in a very different way in this paper. David Pollard et.al used empirical process techniques to study the asymptotic of the LSE (Least-squares estimation) for the fitting of nonlinear regression function in 2006. In Jae Myung [13] provided a go conceptual for Maximum likelihood estimation in his work “Tutorial on maximum likelihood estimation

Non-linear Relationship between BOLD Activation and Amplitude of Beta Oscillations in the Supplementary Motor Area during Rhythmic Finger Tapping and Internal Timing

PubMed Central

Gompf, Florian; Pflug, Anja; Laufs, Helmut; Kell, Christian A.

2017-01-01

Functional imaging studies using BOLD contrasts have consistently reported activation of the supplementary motor area (SMA) both during motor and internal timing tasks. Opposing findings, however, have been shown for the modulation of beta oscillations in the SMA. While movement suppresses beta oscillations in the SMA, motor and non-motor tasks that rely on internal timing increase the amplitude of beta oscillations in the SMA. These independent observations suggest that the relationship between beta oscillations and BOLD activation is more complex than previously thought. Here we set out to investigate this rapport by examining beta oscillations in the SMA during movement with varying degrees of internal timing demands. In a simultaneous EEG-fMRI experiment, 20 healthy right-handed subjects performed an auditory-paced finger-tapping task. Internal timing was operationalized by including conditions with taps on every fourth auditory beat, which necessitates generation of a slow internal rhythm, while tapping to every auditory beat reflected simple auditory-motor synchronization. In the SMA, BOLD activity increased and power in both the low and the high beta band decreased expectedly during each condition compared to baseline. Internal timing was associated with a reduced desynchronization of low beta oscillations compared to conditions without internal timing demands. In parallel with this relative beta power increase, internal timing activated the SMA more strongly in terms of BOLD. This documents a task-dependent non-linear relationship between BOLD and beta-oscillations in the SMA. We discuss different roles of beta synchronization and desynchronization in active processing within the same cortical region. PMID:29249950

High beta effects and nonlinear evolution of the TAE instability

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

Spong, D.A.

1992-12-31

The toroidal Alfven eigenmode has recently been observed experimentally on DIII-D and TFTR when neutral beams are injected near the Alfven velocity. This instability is also of concern for future high {beta} D-T devices where fusion by-product alpha populations will generally be super-Alfvenic. We have developed a gyrofluid model (with Landau closure) of the TAE mode which can include most of the relevant damping mechanisms (continuum damping, ion and electron damping, ion FLR and collisional trapped electron damping) as well as reproducing analytically predicted undamped growth rates relatively accurately. An important consideration in predicting future unstable TAE regimes is themore » effect of finite beta in the background plasma. Due to the Shafranov shift and distortion of the flux surfaces, the location of the stable TAE root and the continuum will shift with increasing {beta}. The net effect of this is to generally enhance continuum damping and stabilize the TAF instability. Also, as the pressure gradient drive from the background becomes increasingly important, coupling between TAE and background driven modes can alter the TAE mode. A further application of our gyrofluid model which will be discussed is the nonlinear evolution of the TAE instability. Gyrofluid models offer a convenient reduced description which is more amenable to computational nonlinear modeling than full kinetic particle models. Our results demonstrate the rise and crash phases of TAE activity similar to experimental observations. The saturation is caused by generation of m=0 n=0 components through nonlinear beatings of the n > 1 modes; these cause modifications to the original equilibrium profiles in such a direction as to decrease the instability drive. This is the gyrofluid analog of direct particle losses. The peak magnetic fluctuation level increases with increasing energetic species beta, resulting in non-resonant stochastization of magnetic field lines.« less

High beta effects and nonlinear evolution of the TAE instability

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

Spong, D.A.

1992-01-01

The toroidal Alfven eigenmode has recently been observed experimentally on DIII-D and TFTR when neutral beams are injected near the Alfven velocity. This instability is also of concern for future high [beta] D-T devices where fusion by-product alpha populations will generally be super-Alfvenic. We have developed a gyrofluid model (with Landau closure) of the TAE mode which can include most of the relevant damping mechanisms (continuum damping, ion and electron damping, ion FLR and collisional trapped electron damping) as well as reproducing analytically predicted undamped growth rates relatively accurately. An important consideration in predicting future unstable TAE regimes is themore » effect of finite beta in the background plasma. Due to the Shafranov shift and distortion of the flux surfaces, the location of the stable TAE root and the continuum will shift with increasing [beta]. The net effect of this is to generally enhance continuum damping and stabilize the TAF instability. Also, as the pressure gradient drive from the background becomes increasingly important, coupling between TAE and background driven modes can alter the TAE mode. A further application of our gyrofluid model which will be discussed is the nonlinear evolution of the TAE instability. Gyrofluid models offer a convenient reduced description which is more amenable to computational nonlinear modeling than full kinetic particle models. Our results demonstrate the rise and crash phases of TAE activity similar to experimental observations. The saturation is caused by generation of m=0 n=0 components through nonlinear beatings of the n > 1 modes; these cause modifications to the original equilibrium profiles in such a direction as to decrease the instability drive. This is the gyrofluid analog of direct particle losses. The peak magnetic fluctuation level increases with increasing energetic species beta, resulting in non-resonant stochastization of magnetic field lines.« less

Nonlinear evolution of magnetic flux ropes. I - Low-beta limit

NASA Technical Reports Server (NTRS)

Osherovich, V. A.; Farrugia, C. J.; Burlaga, L. F.

1993-01-01

We study the nonlinear self-similar evolution of a cylindrical magnetic flux tube with two components of the magnetic field, axial and azimuthal. We restrict ourselves to the case of a plasma of low beta. Introducing a special class of configurations we call 'separable fields', we reduce the problem to an ordinary differential equation. Two cases are to be distinguished: (1) when the total field minimizes on the symmetry axis, the magnetic configuration inexorably collapses, and (2) when, on the other hand, the total field maximizes on the symmetry axis, the magnetic configuration behaves analogously to a nonlinear oscillator. Here we focus on the latter case. The effective potential of the motion contains two terms: a strong repulsive term and a weak restoring term associated with the pinch. We solve the nonlinear differential equation of motion numerically and find that the period of oscillations grows exponentially with the energy of the oscillator. Our treatment emphasizes the role of the force-free configuration as the lowest potential energy state about which the system oscillates.

Dependence of Microelastic-plastic Nonlinearity of Martensitic Stainless Steel on Fatigue Damage Accumulation

NASA Technical Reports Server (NTRS)

Cantrell, John H.

2006-01-01

Self-organized substructural arrangements of dislocations formed in wavy slip metals during cyclic stress-induced fatigue produce substantial changes in the material microelastic-plastic nonlinearity, a quantitative measure of which is the nonlinearity parameter Beta extracted from acoustic harmonic generation measurements. The contributions to Beta from the substructural evolution of dislocations and crack growth for fatigued martensitic 410Cb stainless steel are calculated from the Cantrell model as a function of percent full fatigue life to fracture. A wave interaction factor f(sub WI) is introduced into the model to account experimentally for the relative volume of material fatigue damage included in the volume of material swept out by an interrogating acoustic wave. For cyclic stress-controlled loading at 551 MPa and f(sub WI) = 0.013 the model predicts a monotonic increase in Beta from dislocation substructures of almost 100 percent from the virgin state to roughly 95 percent full life. Negligible contributions from cracks are predicted in this range of fatigue life. However, over the last five percent of fatigue life the model predicts a rapid monotonic increase of Beta by several thousand percent that is dominated by crack growth. The theoretical predictions are in good agreement with experimental measurements of 410Cb stainless steel samples fatigued in uniaxial, stress-controlled cyclic loading at 551 MPa from zero to full tensile load with a measured f(sub WI) of 0.013.

Hierarchical multiple regression modelling on predictors of behavior and sexual practices at Takoradi Polytechnic, Ghana.

PubMed

Turkson, Anthony Joe; Otchey, James Eric

2015-01-14

Various psychosocial studies on health related lifestyles lay emphasis on the fact that the perception one has of himself as being at risk of HIV/AIDS infection was a necessary condition for preventive behaviors to be adopted. Hierarchical Multiple Regression models was used to examine the relationship between eight independent variables and one dependent variable to isolate predictors which have significant influence on behavior and sexual practices. A Cross-sectional design was used for the study. Structured close-ended interviewer-administered questionnaire was used to collect primary data. Multistage stratified technique was used to sample views from 380 students from Takoradi Polytechnic, Ghana. A Hierarchical multiple regression model was used to ascertain the significance of certain predictors of sexual behavior and practices. The variables that were extracted from the multiple regression were; for the constant; Beta=14.202, t=2.279, p=0.023, variable is significant; for the marital status; Beta=0.092, t=1.996, p<0.05, variable is significant; for the knowledge on AIDs; Beta=0.090, t=1.996, p<0.05, variable is significant; for the attitude towards HIV/AIDs; =0.486, t=10.575, p<0.001, variable is highly significant. Thus, the best fitting model for predicting behavior and sexual practices was a linear combination of the constant, one's marital status, knowledge on HIV/AIDs and Attitude towards HIV/AIDs., Y(Behavior and sexual practies)= Beta0+Beta1(Marital status)+Beta2(Knowledge on HIV/AIDs issues)+Beta3(Attitude towards HIV/AIDs issues) Beta0, Beta1, Beta2 and Beta3 are respectively 14.201, 2.038, 0.148 and 0.486; the higher the better. Attitude and behavior change education on HIV/AIDs should be intensified in the institution so that students could adopt better lifestyles.

MEG-based detection and localization of perilesional dysfunction in chronic stroke.

PubMed

Chu, Ron K O; Braun, Allen R; Meltzer, Jed A

2015-01-01

Post-stroke impairment is associated not only with structural lesions, but also with dysfunction in surviving perilesional tissue. Previous studies using equivalent current dipole source localization of MEG/EEG signals have demonstrated a preponderance of slow-wave activity localized to perilesional areas. Recent studies have also demonstrated the utility of nonlinear analyses such as multiscale entropy (MSE) for quantifying neuronal dysfunction in a wide range of pathologies. The current study utilized beamformer-based reconstruction of signals in source space to compare spectral and nonlinear measures of electrical activity in perilesional and healthy cortices. Data were collected from chronic stroke patients and healthy controls, both young and elderly. We assessed relative power in the delta (1-4 Hz), theta (4-7 Hz), alpha (8-12 Hz) and beta (15-30 Hz) frequency bands, and also measured the nonlinear complexity of electrical activity using MSE. Perilesional tissue exhibited a general slowing of the power spectrum (increased delta/theta, decreased beta) as well as a reduction in MSE. All measures tested were similarly sensitive to changes in the posterior perilesional regions, but anterior perilesional dysfunction was detected better by MSE and beta power. The findings also suggest that MSE is specifically sensitive to electrophysiological dysfunction in perilesional tissue, while spectral measures were additionally affected by an increase in rolandic beta power with advanced age. Furthermore, perilesional electrophysiological abnormalities in the left hemisphere were correlated with the degree of language task-induced activation in the right hemisphere. Finally, we demonstrate that single subject spectral and nonlinear analyses can identify dysfunctional perilesional regions within individual patients that may be ideal targets for interventions with noninvasive brain stimulation.

Method for nonlinear exponential regression analysis

NASA Technical Reports Server (NTRS)

Junkin, B. G.

1972-01-01

Two computer programs developed according to two general types of exponential models for conducting nonlinear exponential regression analysis are described. Least squares procedure is used in which the nonlinear problem is linearized by expanding in a Taylor series. Program is written in FORTRAN 5 for the Univac 1108 computer.

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

Minissale, S.; Yerci, S.; Dal Negro, L.

We investigate the nonlinear optical properties of Si-rich silicon oxide (SRO) and Si-rich silicon nitride (SRN) samples as a function of silicon content, annealing temperature, and excitation wavelength. Using the Z-scan technique, we measure the non-linear refractive index n{sub 2} and the nonlinear absorption coefficient {beta} for a large number of samples fabricated by reactive co-sputtering. Moreover, we characterize the nonlinear optical parameters of SRN in the broad spectral region 1100-1500 nm and show the strongest nonlinearity at 1500 nm. These results demonstrate the potential of the SRN matrix for the engineering of compact devices with enhanced Kerr nonlinearities formore » silicon photonics applications.« less

Comparison Between Linear and Non-parametric Regression Models for Genome-Enabled Prediction in Wheat

PubMed Central

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-01-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models. PMID:23275882

Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat.

PubMed

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-12-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.

Nonparametric regression applied to quantitative structure-activity relationships

PubMed

Constans; Hirst

2000-03-01

Several nonparametric regressors have been applied to modeling quantitative structure-activity relationship (QSAR) data. The simplest regressor, the Nadaraya-Watson, was assessed in a genuine multivariate setting. Other regressors, the local linear and the shifted Nadaraya-Watson, were implemented within additive models--a computationally more expedient approach, better suited for low-density designs. Performances were benchmarked against the nonlinear method of smoothing splines. A linear reference point was provided by multilinear regression (MLR). Variable selection was explored using systematic combinations of different variables and combinations of principal components. For the data set examined, 47 inhibitors of dopamine beta-hydroxylase, the additive nonparametric regressors have greater predictive accuracy (as measured by the mean absolute error of the predictions or the Pearson correlation in cross-validation trails) than MLR. The use of principal components did not improve the performance of the nonparametric regressors over use of the original descriptors, since the original descriptors are not strongly correlated. It remains to be seen if the nonparametric regressors can be successfully coupled with better variable selection and dimensionality reduction in the context of high-dimensional QSARs.

Nonlinear refraction and two-photon absorption in dense 2Bi{sub 2}O{sub 3}-B{sub 2}O{sub 3} glasses

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

Paramesh, Gadige; Varma, K. B. R.

2012-06-05

High density transparent glasses (7.86 g/cc) were fabricated in the 2Bi{sub 2}O{sub 3}-B{sub 2}O{sub 3} (BBO) system. Optical band gap of the obtained glasses was found to be 2.6eV. The refractive index measured for these glasses was 2.25{+-}0.05 at {lambda}=543 nm. Nonlinear refraction and absorption studies were carried out on the BBO glasses using z-scan technique at {lambda}=532 nm of 10 ns pulse width. The nonlinear refractive index obtained was n{sub 2}=12.1x10{sup -14} cm{sup 2}/W and nonlinear absorption coefficient was {beta}=15.2 cm/GW. The n{sub 2} and {beta} values of the BBO glasses were large compared to the other reported highmore » index bismuth based oxide glass systems in the literature. These were attributed to the high density, high linear refractive index, low band gap and two photon absorption associated with these glasses. The electronic origin of large nonlinearities was discussed based on bond-orbital theory.« less

The beta2- and beta3-adrenoceptor-mediated relaxation induced by fenoterol in guinea pig taenia caecum.

PubMed

Akimoto, Yurie; Horinouchi, Takahiro; Tanaka, Yoshio; Koike, Katsuo

2002-10-01

Fenoterol, a beta2-adrenoceptor selective agonist, belongs to the arylethanolamine class. To understand the receptor subtypes responsible for beta-adrenoceptor-mediated relaxation of guinea pig taenia caecum, we investigated the effect of fenoterol. Fenoterol caused concentration-dependent relaxation of the guinea pig taenia caecum. Propranolol, bupranolol and butoxamine produced shifts of the concentration-response curve for fenoterol. Schild regression analyses carried out for propranolol, butoxamine and bupranolol against fenoterol gave pA2 values of 8.41, 6.33 and 8.44, respectively. However, in the presence of 3 x 10(-4) M atenolol, 10(-4) M butoxamine and 10(-6) M phentolamine to block the beta1-, beta2- and a-adrenoceptor effects, respectively, Schild regression analysis carried out for bupranolol against fenoterol gave pA2 values of 5.80. These results suggest that the relaxant response to fenoterol in the guinea pig taenia caecum is mediated by both the beta2- and the beta3-adrenoceptors.

Incorporation of nonlinear thermorheological complexity into the phenomenologies of structural relaxation.

PubMed

Hodge, Ian M

2005-09-22

A distribution of activation energies is introduced into the nonlinear Adam-Gibbs ("Hodge-Scherer") phenomenology for structural relaxation. The resulting dependencies of the stretched exponential beta parameter on thermodynamic temperature and fictive temperature (nonlinear thermorheological complexity) are derived. No additional adjustable parameters are introduced, and contact is made with the predictions of the random first-order transition theory of aging of Lubchenko and Wolynes [J. Chem. Physics121, 2852 (2004)].

Nonlinear diffusion equations as asymptotic limits of Cahn-Hilliard systems on unbounded domains via Cauchy's criterion

NASA Astrophysics Data System (ADS)

Fukao, Takeshi; Kurima, Shunsuke; Yokota, Tomomi

2018-05-01

This paper develops an abstract theory for subdifferential operators to give existence and uniqueness of solutions to the initial-boundary problem (P) for the nonlinear diffusion equation in an unbounded domain $\\Omega\\subset\\mathbb{R}^N$ ($N\\in{\\mathbb N}$), written as \\[ \\frac{\\partial u}{\\partial t} + (-\\Delta+1)\\beta(u) = g \\quad \\mbox{in}\\ \\Omega\\times(0, T), \\] which represents the porous media, the fast diffusion equations, etc., where $\\beta$ is a single-valued maximal monotone function on $\\mathbb{R}$, and $T>0$. Existence and uniqueness for (P) were directly proved under a growth condition for $\\beta$ even though the Stefan problem was excluded from examples of (P). This paper completely removes the growth condition for $\\beta$ by confirming Cauchy's criterion for solutions of the following approximate problem (P)$_{\\varepsilon}$ with approximate parameter $\\varepsilon>0$: \\[ \\frac{\\partial u_{\\varepsilon}}{\\partial t} + (-\\Delta+1)(\\varepsilon(-\\Delta+1)u_{\\varepsilon} + \\beta(u_{\\varepsilon}) + \\pi_{\\varepsilon}(u_{\\varepsilon})) = g \\quad \\mbox{in}\\ \\Omega\\times(0, T), \\] which is called the Cahn--Hilliard system, even if $\\Omega \\subset \\mathbb{R}^N$ ($N \\in \\mathbb{N}$) is an unbounded domain. Moreover, it can be seen that the Stefan problem is covered in the framework of this paper.

Misleading Betas: An Educational Example

ERIC Educational Resources Information Center

Chong, James; Halcoussis, Dennis; Phillips, G. Michael

2012-01-01

The dual-beta model is a generalization of the CAPM model. In the dual-beta model, separate beta estimates are provided for up-market and down-market days. This paper uses the historical "Anscombe quartet" results which illustrated how very different datasets can produce the same regression coefficients to motivate a discussion of the…

Criterion for evaluating the predictive ability of nonlinear regression models without cross-validation.

PubMed

Kaneko, Hiromasa; Funatsu, Kimito

2013-09-23

We propose predictive performance criteria for nonlinear regression models without cross-validation. The proposed criteria are the determination coefficient and the root-mean-square error for the midpoints between k-nearest-neighbor data points. These criteria can be used to evaluate predictive ability after the regression models are updated, whereas cross-validation cannot be performed in such a situation. The proposed method is effective and helpful in handling big data when cross-validation cannot be applied. By analyzing data from numerical simulations and quantitative structural relationships, we confirm that the proposed criteria enable the predictive ability of the nonlinear regression models to be appropriately quantified.

Fundamental Studies and Device Development in Beta Silicon Carbide.

DTIC Science & Technology

1987-08-31

2 and Cr exhibited nonlinear I - V characteristics; however, the resistivity to current flow in either voltage direction was small, as seen in the...this material. The nonlinear I - V characteristics previously noted and shown in Fig. 1 for the as-deposited TaSi 2, became linear upon annealing at 1123K...for these three materials. Even after heating at 1473K for 1800 s, the Au-Ta-Al alloy contact showed nonlinear I - V characteristics and possessed a high

Examining the influence of link function misspecification in conventional regression models for developing crash modification factors.

PubMed

Wu, Lingtao; Lord, Dominique

2017-05-01

This study further examined the use of regression models for developing crash modification factors (CMFs), specifically focusing on the misspecification in the link function. The primary objectives were to validate the accuracy of CMFs derived from the commonly used regression models (i.e., generalized linear models or GLMs with additive linear link functions) when some of the variables have nonlinear relationships and quantify the amount of bias as a function of the nonlinearity. Using the concept of artificial realistic data, various linear and nonlinear crash modification functions (CM-Functions) were assumed for three variables. Crash counts were randomly generated based on these CM-Functions. CMFs were then derived from regression models for three different scenarios. The results were compared with the assumed true values. The main findings are summarized as follows: (1) when some variables have nonlinear relationships with crash risk, the CMFs for these variables derived from the commonly used GLMs are all biased, especially around areas away from the baseline conditions (e.g., boundary areas); (2) with the increase in nonlinearity (i.e., nonlinear relationship becomes stronger), the bias becomes more significant; (3) the quality of CMFs for other variables having linear relationships can be influenced when mixed with those having nonlinear relationships, but the accuracy may still be acceptable; and (4) the misuse of the link function for one or more variables can also lead to biased estimates for other parameters. This study raised the importance of the link function when using regression models for developing CMFs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Logistic regression of family data from retrospective study designs.

PubMed

Whittemore, Alice S; Halpern, Jerry

2003-11-01

We wish to study the effects of genetic and environmental factors on disease risk, using data from families ascertained because they contain multiple cases of the disease. To do so, we must account for the way participants were ascertained, and for within-family correlations in both disease occurrences and covariates. We model the joint probability distribution of the covariates of ascertained family members, given family disease occurrence and pedigree structure. We describe two such covariate models: the random effects model and the marginal model. Both models assume a logistic form for the distribution of one person's covariates that involves a vector beta of regression parameters. The components of beta in the two models have different interpretations, and they differ in magnitude when the covariates are correlated within families. We describe ascertainment assumptions needed to estimate consistently the parameters beta(RE) in the random effects model and the parameters beta(M) in the marginal model. Under the ascertainment assumptions for the random effects model, we show that conditional logistic regression (CLR) of matched family data gives a consistent estimate beta(RE) for beta(RE) and a consistent estimate for the covariance matrix of beta(RE). Under the ascertainment assumptions for the marginal model, we show that unconditional logistic regression (ULR) gives a consistent estimate for beta(M), and we give a consistent estimator for its covariance matrix. The random effects/CLR approach is simple to use and to interpret, but it can use data only from families containing both affected and unaffected members. The marginal/ULR approach uses data from all individuals, but its variance estimates require special computations. A C program to compute these variance estimates is available at http://www.stanford.edu/dept/HRP/epidemiology. We illustrate these pros and cons by application to data on the effects of parity on ovarian cancer risk in mother/daughter pairs, and use simulations to study the performance of the estimates. Copyright 2003 Wiley-Liss, Inc.

Pseudo second order kinetics and pseudo isotherms for malachite green onto activated carbon: comparison of linear and non-linear regression methods.

PubMed

Kumar, K Vasanth; Sivanesan, S

2006-08-25

Pseudo second order kinetic expressions of Ho, Sobkowsk and Czerwinski, Blanachard et al. and Ritchie were fitted to the experimental kinetic data of malachite green onto activated carbon by non-linear and linear method. Non-linear method was found to be a better way of obtaining the parameters involved in the second order rate kinetic expressions. Both linear and non-linear regression showed that the Sobkowsk and Czerwinski and Ritchie's pseudo second order model were the same. Non-linear regression analysis showed that both Blanachard et al. and Ho have similar ideas on the pseudo second order model but with different assumptions. The best fit of experimental data in Ho's pseudo second order expression by linear and non-linear regression method showed that Ho pseudo second order model was a better kinetic expression when compared to other pseudo second order kinetic expressions. The amount of dye adsorbed at equilibrium, q(e), was predicted from Ho pseudo second order expression and were fitted to the Langmuir, Freundlich and Redlich Peterson expressions by both linear and non-linear method to obtain the pseudo isotherms. The best fitting pseudo isotherm was found to be the Langmuir and Redlich Peterson isotherm. Redlich Peterson is a special case of Langmuir when the constant g equals unity.

Detection of Differential Item Functioning with Nonlinear Regression: A Non-IRT Approach Accounting for Guessing

ERIC Educational Resources Information Center

Drabinová, Adéla; Martinková, Patrícia

2017-01-01

In this article we present a general approach not relying on item response theory models (non-IRT) to detect differential item functioning (DIF) in dichotomous items with presence of guessing. The proposed nonlinear regression (NLR) procedure for DIF detection is an extension of method based on logistic regression. As a non-IRT approach, NLR can…

Approaches for optimizing the first electronic hyperpolarizability of conjugated organic molecules

NASA Technical Reports Server (NTRS)

Marder, S. R.; Beratan, D. N.; Cheng, L.-T.

1991-01-01

Conjugated organic molecules with electron-donating and -accepting moieties can exhibit large electronic second-order nonlinearities, or first hyperpolarizabilities, beta. The present two-state, four-orbital independent-electron analysis of beta leads to the prediction that its absolute value will be maximized at a combination of donor and acceptor strengths for a given conjugated bridge. Molecular design strategies for beta optimization are proposed which give attention to the energetic manipulations of the bridge states. Experimental results have been obtained which support the validity of this approach.

mRNA Expression of Platelet-Derived Growth Factor Receptor-{beta} and C-KIT: Correlation With Pathologic Response to Cetuximab-Based Chemoradiotherapy in Patients With Rectal Cancer

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

Erben, Philipp; Horisberger, Karoline; Muessle, Benjamin

2008-12-01

Purpose: Deviant expression of platelet-derived growth factor receptor-{beta} (PDGFR{beta}) and c-kit was shown in patients with colorectal cancer. In the present study, mRNA expression of PDGFR{beta} and c-kit in 33 patients with locally advanced rectal cancer undergoing preoperative chemoradiotherapy with cetuximab/capecitabine/irinotecan in correlation with the tumor regression rate was investigated. Methods and Materials: Pretherapeutic biopsy cores and tumor material from the resected specimens were collected in parallel with normal rectal mucosa. The expression levels of PDGFR{beta} and c-kit were measured by quantitative polymerase chain reaction. Tumors were classified as good responders (tumor regression grade [TRG], 2-3) or poor responders (TRG,more » 0-1). Results: The TRG evaluation of the resected specimen was TRG 0-1 in 11 and TRG 2-3 in 22. The median normalized ratios in the pretreatment mucosa vs. tumor biopsy cores was as follows: PDGFR{beta} ratio of 15.2 vs. 49.5 (p <0.0001) and c-kit ratio of 0.94 vs. 0.67 (p = 0.014). The same tendency was observed for the median PDGFR{beta} ratios after chemoradiotherapy completion: 34.2 vs. 170.0 (p <0.0001). The PDGFR{beta} and c-kit mRNA expression values in the pretreatment tumor biopsy cores were lower than the values in the resected specimens: PDGFR{beta} ratio 49.5 vs. 170.0 (p = 0.0002) and c-kit ratio 0.67 vs. 1.1 (p = 0.0003). Nevertheless, no correlation was seen between the pretherapeutic PDGFR{beta} and c-kit mRNA expression and the pathologic regression rate. Conclusion: Cetuximab-based chemoradiotherapy increased PDGFR{beta} levels even further compared with the pretreatment samples and deserves further investigation.« less

Improved transparency--nonlinearity trade-off with boroxine-based octupolar molecules.

PubMed

Alcaraz, Gilles; Euzenat, Lisenn; Mongin, Olivier; Katan, Claudine; Ledoux, Isabelle; Zyss, Joseph; Blanchard-Desce, Mireille; Vaultier, Michel

2003-11-21

A series of octupolar molecules derived from the boroxine framework were designed and their optical nonlinearities were investigated by performing harmonic light scattering experiments in solution; the molecules were found to combine excellent transparency in the near UV-visible region (lambdamax < or = 280 nm) and significant first-order hyperpolarisabilities (up to beta(0) = 56 x 10(-30) esu).

Fluctuations in work motivation: tasks do not matter!

PubMed

Navarro, Jose; Curioso, Fernando; Gomes, Duarte; Arrieta, Carlos; Cortes, Mauricio

2013-01-01

Previous studies have shown that work motivation fluctuates considerably and in a nonlinear way over time. In the present research, we are interested in studying if the task at hand does or does not influence the presence of these fluctuations. We gathered daily registers from 69 workers during 21 consecutive working days (7036 registers) of task developed and levels of motivation, self-efficacy beliefs and instrumentalities perception. These registers were then categorized into a list of labor activities in main tasks and subtasks by means of three judges with a high level of agreement (97.47% for tasks, and 98.64% for subtasks). Taking the MSSD statistic (mean squared successive difference) of the average of motivation, self-efficacy and instrumentality, and using hierarchical regression analysis we have found that tasks (beta = .03; p = .188) and subtasks (beta = .10; p = .268) do not affect the presence of fluctuations in motivation. These results reveal instability in work motivation independently from the tasks and subtasks that the workers do. We proceed to find that fluctuations in work motivation show a fractal structure across the different tasks we do in a working day. Implications of these results to motivational theory will be discussed as well as possible explanations (e.g. the influence of affect in work motivation) and directions for future research are provided.

Regression modeling of ground-water flow

USGS Publications Warehouse

Cooley, R.L.; Naff, R.L.

1985-01-01

Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)

Finite-sample and asymptotic sign-based tests for parameters of non-linear quantile regression with Markov noise

NASA Astrophysics Data System (ADS)

Sirenko, M. A.; Tarasenko, P. F.; Pushkarev, M. I.

2017-01-01

One of the most noticeable features of sign-based statistical procedures is an opportunity to build an exact test for simple hypothesis testing of parameters in a regression model. In this article, we expanded a sing-based approach to the nonlinear case with dependent noise. The examined model is a multi-quantile regression, which makes it possible to test hypothesis not only of regression parameters, but of noise parameters as well.

Xenon elimination kinetics following brief exposure.

PubMed

Schaefer, Maximilian S; Piper, Thomas; Geyer, Hans; Schneemann, Julia; Neukirchen, Martin; Thevis, Mario; Kienbaum, Peter

2017-05-01

Xenon is a modern inhalative anaesthetic with a very low solubility in tissues providing rapid elimination and weaning from anaesthesia. Besides its anaesthetic properties, Xenon promotes the endogenous erythropoietin biosynthesis and thus has been enlisted as prohibited substance by the World Anti-Doping Agency (WADA). For effective doping controls, knowledge about the elimination kinetics of Xenon and the duration of traceability are of particular importance. Seventy-seven full blood samples were obtained from 7 normal weight patients undergoing routine Xenon-based general anaesthesia with a targeted inspiratory concentration of 60% Xenon in oxygen. Samples were taken before and during Xenon inhalation as well as one, two, 4, 8, 16, 24, 32, 40, and 48 h after exposure. Xenon concentrations were assessed in full blood by gas chromatography and triple quadrupole tandem mass spectrometry with a detection limit of 0.25 µmol/L. The elimination of Xenon was characterized by linear regression of log-transformed Xenon blood concentrations, as well as non-linear regression. Xenon exposure yielded maximum concentrations in arterial blood of 1.3 [1.1; 1.6] mmol/L. Xenon was traceable for 24 to 48 h. The elimination profile was characterized by a biphasic pattern with a rapid alpha phase, followed by a slower beta phase showing a first order kinetics (c[Xe] = 69.1e -0.26x , R 2  = 0.83, t 1/2  = 2.7 h). Time in hours after exposure could be estimated by 50*ln(1.39/c[Xe] 0.077 ). Xenon's elimination kinetics is biphasic with a delayed beta phase following a first order kinetics. Xenon can reliably be detected for at least 24 h after brief exposure. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

An Excel Solver Exercise to Introduce Nonlinear Regression

ERIC Educational Resources Information Center

Pinder, Jonathan P.

2013-01-01

Business students taking business analytics courses that have significant predictive modeling components, such as marketing research, data mining, forecasting, and advanced financial modeling, are introduced to nonlinear regression using application software that is a "black box" to the students. Thus, although correct models are…

Does Nonlinear Modeling Play a Role in Plasmid Bioprocess Monitoring Using Fourier Transform Infrared Spectra?

PubMed

Lopes, Marta B; Calado, Cecília R C; Figueiredo, Mário A T; Bioucas-Dias, José M

2017-06-01

The monitoring of biopharmaceutical products using Fourier transform infrared (FT-IR) spectroscopy relies on calibration techniques involving the acquisition of spectra of bioprocess samples along the process. The most commonly used method for that purpose is partial least squares (PLS) regression, under the assumption that a linear model is valid. Despite being successful in the presence of small nonlinearities, linear methods may fail in the presence of strong nonlinearities. This paper studies the potential usefulness of nonlinear regression methods for predicting, from in situ near-infrared (NIR) and mid-infrared (MIR) spectra acquired in high-throughput mode, biomass and plasmid concentrations in Escherichia coli DH5-α cultures producing the plasmid model pVAX-LacZ. The linear methods PLS and ridge regression (RR) are compared with their kernel (nonlinear) versions, kPLS and kRR, as well as with the (also nonlinear) relevance vector machine (RVM) and Gaussian process regression (GPR). For the systems studied, RR provided better predictive performances compared to the remaining methods. Moreover, the results point to further investigation based on larger data sets whenever differences in predictive accuracy between a linear method and its kernelized version could not be found. The use of nonlinear methods, however, shall be judged regarding the additional computational cost required to tune their additional parameters, especially when the less computationally demanding linear methods herein studied are able to successfully monitor the variables under study.

Center for the Study of Plasma Microturbulence

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

Parker, Scott E.

We have discovered a possible "natural fueling" mechanism in tokamak fusion reactors using large scale gyrokinetic turbulence simulation. In the presence of a heat flux dominated tokamak plasma, cold ions naturally pinch radially inward. If cold DT fuel is introduced near the edge using shallow pellet injection, the cold fuel will pinch inward, at the expense of hot helium ash going radially outward. By adjusting the cold DT fuel concentration, the core DT density profiles can be maintained. We have also shown that cold source ions from edge recycling of cold neutrals are pinched radially inward. This mechanism may bemore » important for fully understanding the edge pedestal buildup after an ELM crash. Work includes benchmarking the gyrokinetic turbulence codes in the electromagnetic regime. This includes cyclone base case parameters with an increasing plasma beta. The code comparisons include GEM, GYRO and GENE. There is good linear agreement between the codes using the Cyclone base case, but including electromagnetics and scanning the plasma beta. All the codes have difficulty achieving nonlinear saturation as the kinetic ballooning limit is approached. GEM does not saturate well when beta gets above about 1/2 of the ideal ballooning limit. We find that the lack of saturation is due to the long wavelength k{sub y} modes being nonlinearly pumped to high levels. If the fundamental k{sub y} mode is zeroed out, higher values of beta nonlinearly saturate well. Additionally, there have been studies to better understand CTEM nonlinear saturation and the importance of zonal flows. We have continued our investigation of trapped electron mode (TEM) turbulence. More recently, we have focused on the nonlinear saturation of TEM turbulence. An important feature of TEM is that in many parameter regimes, the zonal flow is unimportant. We find that when zonal flows are unimportant, zonal density is the dominant saturation mechanism. We developed a simple theory that agrees with the simulation and predicts zonal density generation and feedback stabilization of the most unstable mode even in the absence of zonal flow. We are using GEM to simulate NSTX discharges. We have also done verification and validation on DIII-D. Good agreement with GYRO and DIII-D flux levels were reported in the core region.« less

General Nonlinear Ferroelectric Model v. Beta

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

Dong, Wen; Robbins, Josh

2017-03-14

The purpose of this software is to function as a generalized ferroelectric material model. The material model is designed to work with existing finite element packages by providing updated information on material properties that are nonlinear and dependent on loading history. The two major nonlinear phenomena this model captures are domain-switching and phase transformation. The software itself does not contain potentially sensitive material information and instead provides a framework for different physical phenomena observed within ferroelectric materials. The model is calibrated to a specific ferroelectric material through input parameters provided by the user.

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

Brodde, O.E.; Leifert, F.J.; Krehl, H.J.

We determined the amount of beta 1- and beta 2-adrenoceptors in right and left atria and ventricles of rabbits. For this purpose inhibition of specific (-)-/sup 3/H-dihydroalprenolol ((-)-/sup 3/H-DHA) binding (5 nM) by beta 1-selective (practolol, metoprolol) and beta 2-selective (zinterol, IPS 339) adrenergic drugs was determined and analyzed by pseudo-Scatchard (Hofstee) plots. For both atria, inhibition of binding by the four selective beta-adrenergic drugs resulted in non-linear Hofstee plots, suggesting the coexistence of both beta-adrenoceptor subtypes. From these plots we calculated a beta 1:beta 2-adrenoceptor ratio of 72:28 for the right atrium and of 82:18 for the left. Inmore » contrast, only a very small amount of beta 2-adrenoceptors (approximately 5-7% of the total beta-adrenoceptor population) could be detected in the ventricles. For comparison we analyzed the inhibition of specific (-)-/sup 3/H-DHA binding in tissues with homogeneous population of beta-adrenoceptors (beta 1:guinea pig left ventricle; beta 2: cerebellum of mature rats). For both tissues the four selective beta-adrenergic drugs showed linear Hofstee plots, demonstrating that in tissues with homogeneous beta-receptor population interaction of each drug with the receptor followed simple mass-action kinetics. We conclude that beta 1- and beta 2-adrenoceptors coexist in rabbit atria while the ventricles are predominantly endowed the beta 1-adrenoceptors.« less

Learning accurate and interpretable models based on regularized random forests regression

PubMed Central

2014-01-01

Background Many biology related research works combine data from multiple sources in an effort to understand the underlying problems. It is important to find and interpret the most important information from these sources. Thus it will be beneficial to have an effective algorithm that can simultaneously extract decision rules and select critical features for good interpretation while preserving the prediction performance. Methods In this study, we focus on regression problems for biological data where target outcomes are continuous. In general, models constructed from linear regression approaches are relatively easy to interpret. However, many practical biological applications are nonlinear in essence where we can hardly find a direct linear relationship between input and output. Nonlinear regression techniques can reveal nonlinear relationship of data, but are generally hard for human to interpret. We propose a rule based regression algorithm that uses 1-norm regularized random forests. The proposed approach simultaneously extracts a small number of rules from generated random forests and eliminates unimportant features. Results We tested the approach on some biological data sets. The proposed approach is able to construct a significantly smaller set of regression rules using a subset of attributes while achieving prediction performance comparable to that of random forests regression. Conclusion It demonstrates high potential in aiding prediction and interpretation of nonlinear relationships of the subject being studied. PMID:25350120

A stepwise regression tree for nonlinear approximation: applications to estimating subpixel land cover

USGS Publications Warehouse

Huang, C.; Townshend, J.R.G.

2003-01-01

A stepwise regression tree (SRT) algorithm was developed for approximating complex nonlinear relationships. Based on the regression tree of Breiman et al . (BRT) and a stepwise linear regression (SLR) method, this algorithm represents an improvement over SLR in that it can approximate nonlinear relationships and over BRT in that it gives more realistic predictions. The applicability of this method to estimating subpixel forest was demonstrated using three test data sets, on all of which it gave more accurate predictions than SLR and BRT. SRT also generated more compact trees and performed better than or at least as well as BRT at all 10 equal forest proportion interval ranging from 0 to 100%. This method is appealing to estimating subpixel land cover over large areas.

Application of nonlinear least-squares regression to ground-water flow modeling, west-central Florida

USGS Publications Warehouse

Yobbi, D.K.

2000-01-01

A nonlinear least-squares regression technique for estimation of ground-water flow model parameters was applied to an existing model of the regional aquifer system underlying west-central Florida. The regression technique minimizes the differences between measured and simulated water levels. Regression statistics, including parameter sensitivities and correlations, were calculated for reported parameter values in the existing model. Optimal parameter values for selected hydrologic variables of interest are estimated by nonlinear regression. Optimal estimates of parameter values are about 140 times greater than and about 0.01 times less than reported values. Independently estimating all parameters by nonlinear regression was impossible, given the existing zonation structure and number of observations, because of parameter insensitivity and correlation. Although the model yields parameter values similar to those estimated by other methods and reproduces the measured water levels reasonably accurately, a simpler parameter structure should be considered. Some possible ways of improving model calibration are to: (1) modify the defined parameter-zonation structure by omitting and/or combining parameters to be estimated; (2) carefully eliminate observation data based on evidence that they are likely to be biased; (3) collect additional water-level data; (4) assign values to insensitive parameters, and (5) estimate the most sensitive parameters first, then, using the optimized values for these parameters, estimate the entire data set.

Application of factor analysis of infrared spectra for quantitative determination of beta-tricalcium phosphate in calcium hydroxylapatite.

PubMed

Arsenyev, P A; Trezvov, V V; Saratovskaya, N V

1997-01-01

This work represents a method, which allows to determine phase composition of calcium hydroxylapatite basing on its infrared spectrum. The method uses factor analysis of the spectral data of calibration set of samples to determine minimal number of factors required to reproduce the spectra within experimental error. Multiple linear regression is applied to establish correlation between factor scores of calibration standards and their properties. The regression equations can be used to predict the property value of unknown sample. The regression model was built for determination of beta-tricalcium phosphate content in hydroxylapatite. Statistical estimation of quality of the model was carried out. Application of the factor analysis on spectral data allows to increase accuracy of beta-tricalcium phosphate determination and expand the range of determination towards its less concentration. Reproducibility of results is retained.

SU-E-J-03: A Comprehensive Comparison Between Alpha and Beta Emitters for Cancer Radioimmunotherapy

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

Huang, C.Y.; Guatelli, S; Oborn, B

2014-06-01

Purpose: The purpose of this study is to perform a comprehensive comparison of the therapeutic efficacy and cytotoxicity of alpha and beta emitters for Radioimmunotherapy (RIT). For each stage of cancer development, specific models were built for the separate objectives of RIT to be addressed:a) kill isolated cancer cells in transit in the lymphatic and vascular circulation,b) regress avascular cell clusters,c) regress tumor vasculature and tumors. Methods: Because of the nature of short range, high LET alpha and long energy beta radiation and heterogeneous antigen expression among cancer cells, the microdosimetric approach is essential for the RIT assessment. Geant4 basedmore » microdosimetric models are developed for the three different stages of cancer progression: cancer cells, cell clusters and tumors. The energy deposition, specific energy resulted from different source distribution in the three models was calculated separately for 4 alpha emitting radioisotopes ({sup 211}At, {sup 213}Bi, {sup 223}Ra and {sup 225}Ac) and 6 beta emitters ({sup 32}P, {sup 33}P, {sup 67}Cu, {sup 90}Y, {sup 131}I and {sup 177}Lu). The cell survival, therapeutic efficacy and cytotoxicity are determined and compared between alpha and beta emitters. Results: We show that internal targeted alpha radiation has advantages over beta radiation for killing isolated cancer cells, regressing small cell clusters and also solid tumors. Alpha particles have much higher dose specificity and potency than beta particles. They can deposit 3 logs more dose than beta emitters to single cells and solid tumor. Tumor control probability relies on deep penetration of radioisotopes to cancer cell clusters and solid tumors. Conclusion: The results of this study provide a quantitative understanding of the efficacy and cytotoxicity of RIT for each stage of cancer development.« less

A comparative study between nonlinear regression and nonparametric approaches for modelling Phalaris paradoxa seedling emergence

USDA-ARS?s Scientific Manuscript database

Parametric non-linear regression (PNR) techniques commonly are used to develop weed seedling emergence models. Such techniques, however, require statistical assumptions that are difficult to meet. To examine and overcome these limitations, we compared PNR with a nonparametric estimation technique. F...

Kernel Partial Least Squares for Nonlinear Regression and Discrimination

NASA Technical Reports Server (NTRS)

Rosipal, Roman; Clancy, Daniel (Technical Monitor)

2002-01-01

This paper summarizes recent results on applying the method of partial least squares (PLS) in a reproducing kernel Hilbert space (RKHS). A previously proposed kernel PLS regression model was proven to be competitive with other regularized regression methods in RKHS. The family of nonlinear kernel-based PLS models is extended by considering the kernel PLS method for discrimination. Theoretical and experimental results on a two-class discrimination problem indicate usefulness of the method.

A comparison of methods for the analysis of binomial clustered outcomes in behavioral research.

PubMed

Ferrari, Alberto; Comelli, Mario

2016-12-01

In behavioral research, data consisting of a per-subject proportion of "successes" and "failures" over a finite number of trials often arise. This clustered binary data are usually non-normally distributed, which can distort inference if the usual general linear model is applied and sample size is small. A number of more advanced methods is available, but they are often technically challenging and a comparative assessment of their performances in behavioral setups has not been performed. We studied the performances of some methods applicable to the analysis of proportions; namely linear regression, Poisson regression, beta-binomial regression and Generalized Linear Mixed Models (GLMMs). We report on a simulation study evaluating power and Type I error rate of these models in hypothetical scenarios met by behavioral researchers; plus, we describe results from the application of these methods on data from real experiments. Our results show that, while GLMMs are powerful instruments for the analysis of clustered binary outcomes, beta-binomial regression can outperform them in a range of scenarios. Linear regression gave results consistent with the nominal level of significance, but was overall less powerful. Poisson regression, instead, mostly led to anticonservative inference. GLMMs and beta-binomial regression are generally more powerful than linear regression; yet linear regression is robust to model misspecification in some conditions, whereas Poisson regression suffers heavily from violations of the assumptions when used to model proportion data. We conclude providing directions to behavioral scientists dealing with clustered binary data and small sample sizes. Copyright © 2016 Elsevier B.V. All rights reserved.

Linearity versus Nonlinearity of Offspring-Parent Regression: An Experimental Study of Drosophila Melanogaster

PubMed Central

Gimelfarb, A.; Willis, J. H.

1994-01-01

An experiment was conducted to investigate the offspring-parent regression for three quantitative traits (weight, abdominal bristles and wing length) in Drosophila melanogaster. Linear and polynomial models were fitted for the regressions of a character in offspring on both parents. It is demonstrated that responses by the characters to selection predicted by the nonlinear regressions may differ substantially from those predicted by the linear regressions. This is true even, and especially, if selection is weak. The realized heritability for a character under selection is shown to be determined not only by the offspring-parent regression but also by the distribution of the character and by the form and strength of selection. PMID:7828818

Two Photon Absorption And Refraction in Bulk of the Semiconducting Materials

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

Kumari, Vinay; Department of Physics, DCRUST Murthal, Haryana; Kumar, Vinod

2011-10-20

Fast electronic detection systems have opened up a number of new fields like nonlinear optics, optical communication, coherent optics, optical bistability, two/four wave mixing. The interest in this field has been stimulated by the importance of multiphoton processes in many fundamental aspects of physics. It has proved to be an invaluable tool for determining the optical and electronic properties of the solids because of the fact that one gets the information about the bulk of the material rather than the surface one. In this paper we report, the measurement of the nonlinear absorption and refraction from the band gap tomore » half-band gap region of bulk of semiconductors in the direct and indirect band gap crystals with nanosecond laser. The measured theoretical calculated values of two-photon absorption coefficients ({beta}) and nonlinear refraction n{sub 2}({omega}) of direct band gap crystal match the earlier reported theoretical predictions. By making use of these theoretical calculated values, we have estimated {beta} and n{sub 2}({omega}) in the case of indirect band gap crystals. Low value of absorption coefficient in case of indirect band gap crystals have been attributed to phonon assisted transition while reduction in nonlinear refraction is due to the rise in saturation taking place in the absorption.« less

A comparative study between nonlinear regression and artificial neural network approaches for modelling wild oat (Avena fatua) field emergence

USDA-ARS?s Scientific Manuscript database

Non-linear regression techniques are used widely to fit weed field emergence patterns to soil microclimatic indices using S-type functions. Artificial neural networks present interesting and alternative features for such modeling purposes. In this work, a univariate hydrothermal-time based Weibull m...

Hierarchical cluster-based partial least squares regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models.

PubMed

Tøndel, Kristin; Indahl, Ulf G; Gjuvsland, Arne B; Vik, Jon Olav; Hunter, Peter; Omholt, Stig W; Martens, Harald

2011-06-01

Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR), where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR) and ordinary least squares (OLS) regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback loops. HC-PLSR is a promising approach for metamodelling in systems biology, especially for highly nonlinear or non-monotone parameter to phenotype maps. The algorithm can be flexibly adjusted to suit the complexity of the dynamic model behaviour, inviting automation in the metamodelling of complex systems.

Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models

PubMed Central

2011-01-01

Background Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR), where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR) and ordinary least squares (OLS) regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Results Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback loops. Conclusions HC-PLSR is a promising approach for metamodelling in systems biology, especially for highly nonlinear or non-monotone parameter to phenotype maps. The algorithm can be flexibly adjusted to suit the complexity of the dynamic model behaviour, inviting automation in the metamodelling of complex systems. PMID:21627852

Relation between burnout syndrome and job satisfaction among mental health workers.

PubMed

Ogresta, Jelena; Rusac, Silvia; Zorec, Lea

2008-06-01

To identify predictors of burnout syndrome, such as job satisfaction and manifestations of occupational stress, in mental health workers. The study included a snowball sample of 174 mental health workers in Croatia. The following measurement instruments were used: Maslach Burnout Inventory, Manifestations of Occupational Stress Survey, and Job Satisfaction Survey. We correlated dimensions of burnout syndrome with job satisfaction and manifestations of occupational stress dimensions. We also performed multiple regression analysis using three dimensions of burnout syndrome--emotional exhaustion, depersonalization, and personal accomplishment. Stepwise multiple regression analysis showed that pay and rewards satisfaction (beta=-0.37), work climate (beta=-0.18), advancement opportunities (beta=0.17), the degree of psychological (beta=0.41), and physical manifestations of occupational stress (beta=0.29) were significant predictors of emotional exhaustion (R=0.76; F=30.02; P<0.001). The frequency of negative emotional and behavioral reactions toward patients and colleagues (beta=0.48), psychological (beta=0.27) and physical manifestations of occupational stress (beta=0.24), and pay and rewards satisfaction (beta=0.22) were significant predictors of depersonalization (R=0.57; F=13,01; P<0.001). Satisfaction with the work climate (beta=-0.20) was a significant predictor of lower levels of personal accomplishment (R=0.20; F=5.06; P<0.005). Mental health workers exhibited a moderate degree of burnout syndrome, but there were no significant differences regarding their occupation. Generally, both dimensions of job satisfaction and manifestations of occupational stress proved to be relevant predictors of burnout syndrome.

Multilayer Perceptron for Robust Nonlinear Interval Regression Analysis Using Genetic Algorithms

PubMed Central

2014-01-01

On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for interval regression analysis have been an interesting area of research. Several approaches involving computational intelligence are effective for resisting outliers, but the required parameters for these approaches are related to whether the collected data contain outliers or not. Since it seems difficult to prespecify the degree of contamination beforehand, this paper uses multilayer perceptron to construct the robust nonlinear interval regression model using the genetic algorithm. Outliers beyond or beneath the data interval will impose slight effect on the determination of data interval. Simulation results demonstrate that the proposed method performs well for contaminated datasets. PMID:25110755

Multilayer perceptron for robust nonlinear interval regression analysis using genetic algorithms.

PubMed

Hu, Yi-Chung

2014-01-01

On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for interval regression analysis have been an interesting area of research. Several approaches involving computational intelligence are effective for resisting outliers, but the required parameters for these approaches are related to whether the collected data contain outliers or not. Since it seems difficult to prespecify the degree of contamination beforehand, this paper uses multilayer perceptron to construct the robust nonlinear interval regression model using the genetic algorithm. Outliers beyond or beneath the data interval will impose slight effect on the determination of data interval. Simulation results demonstrate that the proposed method performs well for contaminated datasets.

New methods of testing nonlinear hypothesis using iterative NLLS estimator

NASA Astrophysics Data System (ADS)

Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.

2017-11-01

This research paper discusses the method of testing nonlinear hypothesis using iterative Nonlinear Least Squares (NLLS) estimator. Takeshi Amemiya [1] explained this method. However in the present research paper, a modified Wald test statistic due to Engle, Robert [6] is proposed to test the nonlinear hypothesis using iterative NLLS estimator. An alternative method for testing nonlinear hypothesis using iterative NLLS estimator based on nonlinear hypothesis using iterative NLLS estimator based on nonlinear studentized residuals has been proposed. In this research article an innovative method of testing nonlinear hypothesis using iterative restricted NLLS estimator is derived. Pesaran and Deaton [10] explained the methods of testing nonlinear hypothesis. This paper uses asymptotic properties of nonlinear least squares estimator proposed by Jenrich [8]. The main purpose of this paper is to provide very innovative methods of testing nonlinear hypothesis using iterative NLLS estimator, iterative NLLS estimator based on nonlinear studentized residuals and iterative restricted NLLS estimator. Eakambaram et al. [12] discussed least absolute deviation estimations versus nonlinear regression model with heteroscedastic errors and also they studied the problem of heteroscedasticity with reference to nonlinear regression models with suitable illustration. William Grene [13] examined the interaction effect in nonlinear models disused by Ai and Norton [14] and suggested ways to examine the effects that do not involve statistical testing. Peter [15] provided guidelines for identifying composite hypothesis and addressing the probability of false rejection for multiple hypotheses.

Association of T-cell reactivity with beta-cell function in recent onset type 1 diabetes patients.

PubMed

Pfleger, Christian; Meierhoff, Guido; Kolb, Hubert; Schloot, Nanette C

2010-03-01

The aim of the current study was to investigate whether autoantigen directed T-cell reactivity relates to beta-cell function during the first 78 weeks after diagnosis of type 1 diabetes. 50 adults and 49 children (mean age 27.3 and 10.9 years respectively) with recent onset type 1 diabetes who participated in a placebo-controlled trial of immune intervention with DiaPep277 were analyzed. Secretion of interferon (IFN)-gamma, interleukin (IL)-5, IL-13 and IL-10 by single peripheral mononuclear cells (PBMC) upon stimulation with islet antigens GAD65, heat shock protein 60 (Hsp60) protein-tyrosine-phosphatase-like-antigen (pIA2) or tetanus toxoid (TT) was determined applying ELISPOT; beta-cell function was evaluated by glucagon stimulated C-peptide. Multivariate regression analysis was applied. In general, number of islet antigen-reactive cells decreased over 78 weeks in both adults and children, whereas reactivity to TT was not reduced. In addition, there was an association between the quality of immune cell responses and beta-cell function. Overall, increased responses by IFN-gamma secreting cells were associated with lower beta-cell function whereas IL-5, IL-13 and IL-10 cytokine responses were positively associated with beta-cell function in adults and children. Essentially, the same results were obtained with three different models of regression analysis. The number of detectable islet-reactive immune cells decreases within 1-2 years after diagnosis of type 1 diabetes. Cytokine production by antigen-specific PBMC reactivity is related to beta-cell function as measured by stimulated C-peptide. Cellular immunity appears to regress soon after disease diagnosis and begin of insulin therapy. Copyright 2009 Elsevier Ltd. All rights reserved.

Does the high–tech industry consistently reduce CO{sub 2} emissions? Results from nonparametric additive regression model

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

Xu, Bin; Research Center of Applied Statistics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi 330013; Lin, Boqiang, E-mail: bqlin@xmu.edu.cn

China is currently the world's largest carbon dioxide (CO{sub 2}) emitter. Moreover, total energy consumption and CO{sub 2} emissions in China will continue to increase due to the rapid growth of industrialization and urbanization. Therefore, vigorously developing the high–tech industry becomes an inevitable choice to reduce CO{sub 2} emissions at the moment or in the future. However, ignoring the existing nonlinear links between economic variables, most scholars use traditional linear models to explore the impact of the high–tech industry on CO{sub 2} emissions from an aggregate perspective. Few studies have focused on nonlinear relationships and regional differences in China. Basedmore » on panel data of 1998–2014, this study uses the nonparametric additive regression model to explore the nonlinear effect of the high–tech industry from a regional perspective. The estimated results show that the residual sum of squares (SSR) of the nonparametric additive regression model in the eastern, central and western regions are 0.693, 0.054 and 0.085 respectively, which are much less those that of the traditional linear regression model (3.158, 4.227 and 7.196). This verifies that the nonparametric additive regression model has a better fitting effect. Specifically, the high–tech industry produces an inverted “U–shaped” nonlinear impact on CO{sub 2} emissions in the eastern region, but a positive “U–shaped” nonlinear effect in the central and western regions. Therefore, the nonlinear impact of the high–tech industry on CO{sub 2} emissions in the three regions should be given adequate attention in developing effective abatement policies. - Highlights: • The nonlinear effect of the high–tech industry on CO{sub 2} emissions was investigated. • The high–tech industry yields an inverted “U–shaped” effect in the eastern region. • The high–tech industry has a positive “U–shaped” nonlinear effect in other regions. • The linear impact of the high–tech industry in the eastern region is the strongest.« less

Finite Group Invariance and Solution of Jaynes-Cummings Hamiltonian

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

Haydargil, Derya; Koc, Ramazan

2004-10-04

The finite group invariance of the E x {beta} and Jaynes-Cummings models are studied. A method is presented to obtain finite group invariance of the E x {beta} system.A suitable transformation of a Jaynes-Cummings Hamiltonian leads to equivalence of E x {beta} system. Then a general method is applied to obtain the solution of Jaynes-Cummings Hamiltonian with Kerr nonlinearity. Number operator for this structure and the generators of su(2) algebra are used to find the eigenvalues of the Jaynes-Cummings Hamiltonian for different states. By using the invariance of number operator the solution of modified Jaynes-Cummings Hamiltonian is also discussed.

The modulational instability for the TDNLS equations for weakly nonlinear dispersive MHD waves

NASA Technical Reports Server (NTRS)

Webb, G. M.; Brio, M.; Zank, G. P.

1995-01-01

In this paper we study the modulational instability for the TDNLS equations derived by Hada (1993) and Brio, Hunter, and Johnson to describe the propagation of weakly nonlinear dispersive MHD waves in beta approximately 1 plasmas. We employ Whitham's averaged Lagrangian method to study the modulational instability. This complements studies of the modulational instability by Hada (1993) and Hollweg (1994), who did not use the averaged Lagrangian approach.

Using Recursive Regression to Explore Nonlinear Relationships and Interactions: A Tutorial Applied to a Multicultural Education Study

ERIC Educational Resources Information Center

Strang, Kenneth David

2009-01-01

This paper discusses how a seldom-used statistical procedure, recursive regression (RR), can numerically and graphically illustrate data-driven nonlinear relationships and interaction of variables. This routine falls into the family of exploratory techniques, yet a few interesting features make it a valuable compliment to factor analysis and…

The ice age cycle and the deglaciations: an application of nonlinear regression modelling

NASA Astrophysics Data System (ADS)

Dalgleish, A. N.; Boulton, G. S.; Renshaw, E.

2000-03-01

We have applied the nonlinear regression technique known as additivity and variance stabilisation (AVAS) to time series which reflect Earth's climate over the last 600 ka. AVAS estimates a smooth, nonlinear transform for each variable, under the assumption of an additive model. The Earth's orbital parameters and insolation variations have been used as regression variables. Analysis of the contribution of each variable shows that the deglaciations are characterised by periods of increasing obliquity and perihelion approaching the vernal equinox, but not by any systematic change in eccentricity. The magnitude of insolation changes also plays no role. By approximating the transforms we can obtain a future prediction, with a glacial maximum at 60 ka AP, and a subsequent obliquity and precession forced deglaciation.

Role of residual kidney function and convective volume on change in beta2-microglobulin levels in hemodiafiltration patients.

PubMed

Penne, E Lars; van der Weerd, Neelke C; Blankestijn, Peter J; van den Dorpel, Marinus A; Grooteman, Muriel P C; Nubé, Menso J; Ter Wee, Piet M; Lévesque, Renée; Bots, Michiel L

2010-01-01

Removal of beta2-microglobulin (beta2M) can be increased by adding convective transport to hemodialysis (HD). The aim of this study was to investigate the change in beta2M levels after 6-mo treatment with hemodiafiltration (HDF) and to evaluate the role of residual kidney function (RKF) and the amount of convective volume with this change. Predialysis serum beta2M levels were evaluated in 230 patients with and 176 patients without RKF from the CONvective TRAnsport STudy (CONTRAST) at baseline and 6 mo after randomization for online HDF or low-flux HD. In HDF patients, potential determinants of change in beta2M were analyzed using multivariable linear regression models. Mean serum beta2M levels decreased from 29.5 +/- 0.8 (+/-SEM) at baseline to 24.3 +/- 0.6 mg/L after 6 mo in HDF patients and increased from 31.9 +/- 0.9 to 34.4 +/- 1.0 mg/L in HD patients, with the difference of change between treatment groups being statistically significant (regression coefficient -7.7 mg/L, 95% confidence interval -9.5 to -5.6, P < 0.001). This difference was more pronounced in patients without RKF as compared with patients with RKF. In HDF patients, beta2M levels remained unchanged in patients with GFR >4.2 ml/min/1.73 m2. The beta2M decrease was not related to convective volume. This study demonstrated effective lowering of beta2M levels by HDF, especially in patients without RKF. The role of the amount of convective volume on beta2M decrease appears limited, possibly because of resistance to beta2M transfer between body compartments.

Influence of plasma beta on the generation of lower hybrid and whistler waves by an ion velocity ring distribution

DOE PAGES

Winske, D.; Daughton, W.

2015-02-02

We present results of three-dimensional electromagnetic particle-in-cell simulations of the lower hybrid ion ring instability, similar to our earlier results [D. Winske and W. Daughton, Phys. Plasma, 19, 072109, 2012], but at higher electron beta (βe = ratio of electron thermal pressure to magnetic pressure = 0.06, rather than at 0.006) with Ti = Te. At higher electron beta the level of lower hybrid waves at saturation normalized to the ion thermal energy (βi = 0.06 also) is only slightly smaller, but the corresponding magnetic fluctuations are about an order of magnitude larger, consistent with linear theory. After saturation, themore » waves evolve into whistler waves, through a number of possible mechanisms, with an average growth rate considerably smaller than the linear growth rate of the lower hybrid waves, to a peak fluctuation level that is about 20% above the lower hybrid wave saturation level. The ratio of the peak magnetic fluctuations associated with the whistler waves relative to those of the saturated lower hybrid waves, the ratio of the nonlinear growth rate of whistlers relative to the linear growth rate of lower hybrid waves, the amount of energy extracted from the ring and the amount of heating of the background ions and electrons are comparable to those in the lower electron beta 3-D simulation. This suggests that even at higher electron beta, the linear and nonlinear physics of the lower hybrid ion ring instability is dominated by electrostatic, wave-particle rather than wave-wave interactions.« less

A method for nonlinear exponential regression analysis

NASA Technical Reports Server (NTRS)

Junkin, B. G.

1971-01-01

A computer-oriented technique is presented for performing a nonlinear exponential regression analysis on decay-type experimental data. The technique involves the least squares procedure wherein the nonlinear problem is linearized by expansion in a Taylor series. A linear curve fitting procedure for determining the initial nominal estimates for the unknown exponential model parameters is included as an integral part of the technique. A correction matrix was derived and then applied to the nominal estimate to produce an improved set of model parameters. The solution cycle is repeated until some predetermined criterion is satisfied.

Regressive changes in finasteride-treated human hyperplastic prostates correlate with an upregulation of TGF-beta receptor expression.

PubMed

Sáez, C; González-Baena, A C; Japón, M A; Giráldez, J; Segura, D I; Miranda, G; Rodríguez-Vallejo, J M; González-Esteban, J; Torrubia, F

1998-10-01

Prostatic atrophy has been documented histologically as a consequence of finasteride action on human hyperplastic prostates. An increase in apoptotic rates has also been reported in androgen-deprived hyperplastic prostates. Transforming growth factor beta (TGF-beta) signaling is implicated in apoptotic cell death. TGF-betas have been detected in normal and diseased human prostate. In the normal prostate, TGF-beta acts as a predominantly negative growth regulator. TGF-beta signaling receptors TbetaRI and TbetaRII have been shown to be negatively regulated by androgens. We studied the histological changes in 9 selected finasteride-treated patients with benign prostatic hyperplasia (BPH), and analyzed the levels of expression and localization of TGF-beta receptor types TbetaRI and TbetaRII in these patients as compared to selected BPH controls. The prostatic epithelial compartment seemed to be a primary target site for finasteride action, since we observed moderate to severe glandular atrophy after 4-6 months of treatment. TGF-beta receptors were upregulated in treated cases. We assessed a twofold increase in TbetaRII mRNA levels in treated cases as compared to controls. An increase in both TbetaRI and TbetaRII at the protein level by immunostaining was observed, which also provided a helpful means for detecting glands undergoing regression. We conclude that finasteride may modulate the TGF-beta signaling system to promote changes leading to apoptosis of epithelial cells and prostatic glandular atrophy.

Z-Scan Measurement of the Nonlinear Absorption of a Thin Gold Film

NASA Technical Reports Server (NTRS)

Smith, David D.; Yoon, Youngkwon; Boyd, Robert W.; Campbell, Joseph K.; Baker, Lane A.; Crooks, Richard M.; George, Michael

1999-01-01

We have used the z-scan technique at a wavelength (532 nm) near the transmission window of bulk gold to measure the nonlinear absorption coefficient of continuous approximately 50-Angstrom-thick gold films, deposited onto surface-modified quartz substrates. For highly absorbing media such as metals, we demonstrate that determination of either the real or imaginary part of the third-order susceptibility requires a measurement of both nonlinear absorption and nonlinear refraction, i.e. both open- and closed-aperture z-scans must be performed. Closed-aperture z-scans did not yield a sufficient signal for the determination of the nonlinear refraction. However, open-aperture z-scans yielded values ranging from Beta = 1.9 x 10(exp -3) to 5.3 x 10(exp -3) cm/W in good agreement with predictions which ascribe the nonlinear response to a Fermi smearing mechanism. We note that the sign of the nonlinearity is reversed from that of gold nanoparticle composites, in accordance with the predictions of mean field theories.

Brain necrosis after fractionated radiation therapy: Is the halftime for repair longer than we thought?

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

Bender, Edward T.

Purpose: To derive a radiobiological model that enables the estimation of brain necrosis and spinal cord myelopathy rates for a variety of fractionation schemes, and to compare repair effects between brain and spinal cord. Methods: Sigmoidal dose response relationships for brain radiation necrosis and spinal cord myelopathy are derived from clinical data using nonlinear regression. Three different repair models are considered and the repair halftimes are included as regression parameters. Results: For radiation necrosis, a repair halftime of 38.1 (range 6.9-76) h is found with monoexponential repair, while for spinal cord myelopathy, a repair halftime of 4.1 (range 0-8) hmore » is found. The best-fit alpha beta ratio is 0.96 (range 0.24-1.73)Conclusions: A radiobiological model that includes repair corrections can describe the clinical data for a variety of fraction sizes, fractionation schedules, and total doses. Modeling suggests a relatively long repair halftime for brain necrosis. This study suggests that the repair halftime for late radiation effects in the brain may be longer than is currently thought. If confirmed in future studies, this may lead to a re-evaluation of radiation fractionation schedules for some CNS diseases, particularly for those diseases where fractionated stereotactic radiation therapy is used.« less

Non-linear isotope and fast ions effects: routes for low turbulence in DT plasmas

NASA Astrophysics Data System (ADS)

Garcia, Jeronimo

2017-10-01

The isotope effect, i.e. the fact that heat and particle fluxes do not follow the expected Gyro-Bohm estimate for turbulent transport when the plasma mass is changed, is one of the main challenges in plasma theory. Of particular interest is the isotope exchange between the fusion of deuterium (DD) and deuterium-tritium (DT) nuclei as there are no clear indications of what kind of transport difference can be expected in burning plasmas. The GENE code is therefore used for computing DD vs DT linear and nonlinear microturbulence characteristics in the core plasma region of a previously ITER hybrid scenario at high beta obtained in the framework of simplified integrated modelling. Scans on common turbulence related quantitates as external ExB flow shear, Parallel Velocity Gradient (PVG), plasma beta, colisionality or the number of ion species have been performed. Additionally, the role of energetic particles, known to reduce Ion Temperature Gradient (ITG) turbulence has been also addressed. It is obtained that the ITER operational point will be close to threshold and in these conditions turbulence is dominated by ITG modes. A purely weak non-linear isotope effect, absent in linear scans, can be found when separately adding moderate ExB flow shear or electromagnetic effects, whereas collisionality just modulates the intensity. The isotope effect, on the other hand, becomes very strong in conditions with simultaneously moderate ExB flow shear, beta and low q profile with significant reductions of ion heat transport from DD to DT. By analyzing the radial structure of the two point electrostatic potential correlation function it has been found that the inherent Gyro-Bohm scaling for plasma microturbulence, which increases the radial correlation length at short scales form DD to DT, is counteracted by the concomitant appearance of a complex nonlinear multiscale space interaction involving external ExB flow shear, zonal flow activity, magnetic geometry and electromagnetic effects. The number of ion species and the fast ion population is also found to play a role in this non-linear process whereas a symmetry breaking between D and T, with systematic reduced heat and particle transport for T, is always obtained.

The effect of postoperative medical treatment on left ventricular mass regression after aortic valve replacement.

PubMed

Helder, Meghana R K; Ugur, Murat; Bavaria, Joseph E; Kshettry, Vibhu R; Groh, Mark A; Petracek, Michael R; Jones, Kent W; Suri, Rakesh M; Schaff, Hartzell V

2015-03-01

The study objective was to analyze factors associated with left ventricular mass regression in patients undergoing aortic valve replacement with a newer bioprosthesis, the Trifecta valve pericardial bioprosthesis (St Jude Medical Inc, St Paul, Minn). A total of 444 patients underwent aortic valve replacement with the Trifecta bioprosthesis from 2007 to 2009 at 6 US institutions. The clinical and echocardiographic data of 200 of these patients who had left ventricular hypertrophy and follow-up studies 1 year postoperatively were reviewed and compared to analyze factors affecting left ventricular mass regression. Mean (standard deviation) age of the 200 study patients was 73 (9) years, 66% were men, and 92% had pure or predominant aortic valve stenosis. Complete left ventricular mass regression was observed in 102 patients (51%) by 1 year postoperatively. In univariate analysis, male sex, implantation of larger valves, larger left ventricular end-diastolic volume, and beta-blocker or calcium-channel blocker treatment at dismissal were significantly associated with complete mass regression. In the multivariate model, odds ratios (95% confidence intervals) indicated that male sex (3.38 [1.39-8.26]) and beta-blocker or calcium-channel blocker treatment at dismissal (3.41 [1.40-8.34]) were associated with increased probability of complete left ventricular mass regression. Patients with higher preoperative systolic blood pressure were less likely to have complete left ventricular mass regression (0.98 [0.97-0.99]). Among patients with left ventricular hypertrophy, postoperative treatment with beta-blockers or calcium-channel blockers may enhance mass regression. This highlights the need for close medical follow-up after operation. Labeled valve size was not predictive of left ventricular mass regression. Copyright © 2015 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Nonlinear mode coupling theory of the lower-hybrid-drift instability

NASA Technical Reports Server (NTRS)

Drake, J. F.; Guzdar, P. N.; Hassam, A. B.; Huba, J. D.

1984-01-01

A nonlinear mode coupling theory of the lower-hybrid-drift instability is presented. A two-dimensional nonlinear wave equation is derived which describes lower-hybrid drift wave turbulence in the plane transverse to B (k.B = 0), and which is valid for finite beta, collisional and collisionless plasmas. The instability saturates by transferring energy from growing, long wavelength modes to damped, short wavelength modes. Detailed numerical results are presented which compare favorably to both recent computer simulations and experimental observations. Applications of this theory to space plasmas, the earth's magnetotail and the equatorial F region ionosphere, are discussed. Previously announced in STAR as N84-17734

Modulation of kinetic Alfvén waves in an intermediate low-beta magnetoplasma

NASA Astrophysics Data System (ADS)

Chatterjee, Debjani; Misra, A. P.

2018-05-01

We study the amplitude modulation of nonlinear kinetic Alfvén waves (KAWs) in an intermediate low-beta magnetoplasma. Starting from a set of fluid equations coupled to the Maxwell's equations, we derive a coupled set of nonlinear partial differential equations (PDEs) which govern the evolution of KAW envelopes in the plasma. The modulational instability (MI) of such KAW envelopes is then studied by a nonlinear Schrödinger equation derived from the coupled PDEs. It is shown that the KAWs can evolve into bright envelope solitons or can undergo damping depending on whether the characteristic ratio ( α ) of the Alfvén to ion-acoustic speeds remains above or below a critical value. The parameter α is also found to shift the MI domains around the k x k z plane, where k x ( k z ) is the KAW number perpendicular (parallel) to the external magnetic field. The growth rate of MI, as well as the frequency shift and the energy transfer rate, are obtained and analyzed. The results can be useful for understanding the existence and formation of bright and dark envelope solitons, or damping of KAW envelopes in space plasmas, e.g., interplanetary space, solar winds, etc.

Electrical and Nonlinear Optical Studies of Specific Organic Molecular and Nonconjugated Conductive Polymeric Systems

NASA Astrophysics Data System (ADS)

Narayanan, Ananthakrishnan

In this research, structural, electrical and nonlinear optical characteristics of: (a) single crystal films involving a noncentrosymmetric molecule DAST and a laser dye IR125 and (b) specific nonconjugated conducting polymers including poly(beta-pinene) and polynorbornene have been studied. 4'-dimethylamino-N-methyl-4-stilbazolium tosylate (DAST) is a well known second order nonlinear optical material. This material has exceptionally high electro-optic coefficients, high thermal stability and ultrafast response time. In this work single crystal films involving a combination of DAST and IR125 have been prepared using modified shear method and the films have been characterized using polarized optical microscopy, X-ray diffraction, polarization dependent optical absorption and photoluminescence spectroscopy. The electro-optic coefficient of these films measured at 633nm was found to be 300pm/V. Since IR-125 has a strong absorption band from 500nm to 800nm, these films are promising for various applications in nonlinear optics at longer wavelength and for light emission. Nonconjugated conducting polymers are a class of polymers that have at least one double bond in their repeat units. 1,4-cis polyisoprene, polyalloocimene, styrene butadiene rubber, poly(ethylenepyrrolediyl) derivatives, and poly(beta-pinene) are some of the well known examples of nonconjugated conducting polymers. In this work, polynorborne, a new addition to the class of nonconjugated conducting polymers is discussed. Like other polymers in this class, polynorbornene exhibits increase in electrical conductivity by many orders of magnitude upon doping with iodine. The maximum electrical conductivity of this material is 0.01 S/cm. As shown by using FTIR microscopy, the C=C bonds are transformed into cation radicals when polynorborne is doped. This is due to the charge-transfer from the double bond to the dopant (iodine). These materials like other nonconjugated conducting polymers have significant applications in electro-optics and photonics. Electron paramagnetic resonance measurements on poly(beta-pinene) before and after doping with iodine are reported in this work. The EPR signal of this polymer increases proportionally with the iodine concentration due to the formation of cation radicals upon doping and charge-transfer. The results agree well with the doping mechanism of nonconjugated conducting polymers discussed earlier in literature. Hyperfine splitting in heavily doped polymers is observed due to the reduced distance between the cation radical and the iodine anion. Off-resonant electro-optic measurements in doped poly(beta-pinene) at 790nm, 800nm, 810nm and 1.55microm using field-induced birefringence technique have been studied. The results show that this material exhibits the highest cubic nonlinearities of all known materials. The Kerr coefficient measured at 1.55microm is 1.6x10-10 m/V2 which is about 30 times higher than that of conjugated polymers. Results of two photon measurements in this doped polymer using pump-probe technique with a pulsed, mode-locked (150 fs pulses) beam from a Ti-Sapphire laser are reported. The measured value of alpha2 at 790 nm and 795 nm were found to be 2.28+/-0.1 cm/MW and 2.5+/-0.1 cm/MW respectively. The data confirms that the nonlinearity in this material is ultrafast and electronic in nature. Such large nonlinearities in these materials are attributed the charge confinement in these materials in a sub-nanometer domain (upon doping) resulting in a metal-like quantum dot structure. Photovoltaic measurements in a composite involving poly(beta-pinene) and C60 are discussed. This is the first time a nonconjugated conducting polymer based photovoltaic cell has been fabricated. A composite involving 4% C60 by weight produced a photovoltage of 280mV for an incident light intensity of 6mW/sq.cm. These low cost devices have applications in solar cells, photodetectors etc. A nonlinear optical waveguide was prepared by casting a thin film of poly(beta-pinene) on bare multi-mode optical fiber and doping it with iodine. The doped fibers were of excellent optical quality. Two-photon absorption experiments were conducted using these waveguides and large changes in transmission upto 28% was observed in 15cm long fiber. More work needs to be done to confirm this result. This is a significant step in the direction of making these materials a viable choice for ultrafast (femtosecond time-scale) optical devices. To summarize, these works included detailed investigations of structural, electrical and nonlinear optical characteristics of specific molecular crystal films and nonconjugated conducting polymers.

Nonlinear Optical Properties of High-Temperature Organic Structures

NASA Astrophysics Data System (ADS)

Shi, Rui-Fang

In this thesis, we report the discovery of a new class of electro-optic organic structures, 1,8-naphthoylene -benzimidazoles, developed with computer aided molecular design combined with actual syntheses. These structures are similar to polyimide repeat units and possess high thermal, chemical and photo stabilities. Thermal analysis shows that the new class retains its linear and nonlinear optical properties well above 300^circ C in both pure forms and guest/host polyimide systems. Importantly, side group substitutions not only increase the second-order optical responses but also enhance the thermal stability. The origin of the relatively large second order optical responses of the new class is revealed by quantum many-electron calculations that explicitly take electron -electron correlations into consideration. Contour diagrams indicate that electrons are decreased on the benzimidazole -donor-substituted side and increased on the naphthoylene side upon virtual excitations, illustrating the fact that the naphthoylene group acts both as an electron acceptor and a pi-bridge that provides the necessary electron delocalization. Results for most structures show that the most dominant virtual excitation process to beta_{ijk}(-omega _3;omega_1,omega_2) involves the ground (S_0) and first excited (S_1) pi -electronic states. Importantly, increasing the electron donor strength increase the electric dipole moments and transition moments, therefore second order optical responses are enhanced. Interestingly, it is found that the position of a donor group in the new class has a significant effect on second order optical responses. DC-induced second harmonic generation (DCSHG) dispersion measurements characterize the nonlinear optical properties of the new class, using both nanosecond and picosecond tunable laser sources ranging from 1400 to 2148 nm in wavelength. Comparison between theory and experiment demonstrates that there is good agreement between them over a wide nonresonant photon energy region, illustrating the great success of our understanding of the nonlinear optical responses even in these relatively complicated organic structures. In addition, it is found that these chromophores have large beta_{ijk }: for SY177 in solution with 1,4-dioxane, mu_{x}beta_ {x}(-2omega;omega,omega) + < gamma(-2omega;omega,omega,0) > 5kT = 418 times 10 ^{-48} esu and beta _{x}(-2omega;omega,omega ) 92 times 10^ {-30} esu at hbaromega = 0.65 eV. For SY215 in solution with CH _2Cl_2, mu_ {x}beta_{x}(-2omega; omega,omega) + < gamma( -2omega;omega,omega,0) > 5kT = 1468 times 10^{-48} esu and beta_{x}(-2omega; omega,omega) = 268 times 10^{-30} esu at hbaromega = 0.65 eV. The discovery and characterization of the new high temperature class represents a critical step in the development of new materials that are suitable for practical device applications. Work is underway to optimize these structures and incorporate them into waveguide devices.

EFFECT OF SYSTEMIC BETA-BLOCKERS, ACE INHIBITORS, AND ANGIOTENSIN RECEPTOR BLOCKERS ON DEVELOPMENT OF CHOROIDAL NEOVASCULARIZATION IN PATIENTS WITH AGE-RELATED MACULAR DEGENERATION.

PubMed

Thomas, Akshay S; Redd, Travis; Hwang, Thomas

2015-10-01

Recent studies have suggested that the use of systemic beta-blockers, angiotensin-converting enzyme inhibitors, and angiotensin receptor blockers can induce regression of choroidal neovascularization in rodent models. The purpose of this study is to evaluate if these agents have a protective effect against the development of choroidal neovascularization in patients with age-related macular degeneration. In this single-center retrospective case-control study, the charts of 250 patients with neovascular age-related macular degeneration were compared with those of 250 controls with dry age-related macular degeneration. Charts were reviewed for current and past use of beta-blockers, angiotensin-converting enzyme inhibitors, and angiotensin receptor blockers. Frequency tables were generated, and associations were examined using chi-square tests, t-tests, and multivariate logistic regression. There was no statistically significant difference between rates of beta-blocker use (P = 0.57), angiotensin-converting enzyme inhibitors use (P = 0.20), or angiotensin receptor blockers use (P = 0.61) between the 2 groups. Additionally, there was no statistically significant difference between rates of use of combinations of the above drugs between the two groups. Although there is growing evidence that beta-blockers, angiotensin-converting enzyme inhibitors, and angiotensin receptor blockers can induce regression of choroidal neovascularization in rodent models, these medications do not seem to confer a protective effect against the development of choroidal neovascularization in patients with age-related macular degeneration.

Ideal and resistive plasma resistive wall modes and control: linear and nonlinear

NASA Astrophysics Data System (ADS)

Finn, J. M.; Chacon, L.

2004-11-01

Our recent work* on control of linear and nonlinear resistive wall modes (RWM) showed that if there is an ideal plasma mode and a resistive plasma mode, and if the beta limit for the latter is lower (as is typical), then nonlinear resistive wall modes behave basically as nonlinear tearing-like modes locked to the wall. We investigate here the effect of plasma rotation sufficient to stabilize the resistive-plasma RWM but not the ideal plasma RWM. We also review results** showing the effect of normal and poloidal magnetic field sensing, and describe a simple model which is amenable to analytic solution, and which makes previously obtained simulation results transparent. *J. Finn and L. Chacon, 'Control of linear and nonlinear resistive wall modes', Phys. Plas 11, 1866 (2004). **J. Finn, 'Control of resistive wall modes in a cylindrical tokamak with radial and poloidal magnetic field sensors', to appear in Phys. Plasmas, 2004.

Theoretical analyses of the effects on the linear and quadratic nonlinear optical properties of N-arylation of pyridinium groups in stilbazolium dyes.

PubMed

Coe, Benjamin J; Beljonne, David; Vogel, Henryk; Garín, Javier; Orduna, Jesús

2005-11-10

N-Arylation of the pyridinium electron acceptor unit in stilbazolium chromophores has been found by previous experimental hyper-Rayleigh scattering and electronic Stark effect (electroabsorption) spectroscopic studies to lead to substantial increases in the static first hyperpolarizability beta(0). We show here that INDO/SCI calculations on the isolated cations trans-4'-(dimethylamino)-N-R-4-stilbazolium (R = methyl 1, phenyl 2, 2,4-dinitrophenyl 3, or 2-pyrimidyl 4) predict only slight red-shifts in the energy of the intramolecular charge-transfer (ICT) transition and accompanying relatively small changes in beta(0) on moving along the series. The inclusion of acetonitrile solvent using a polarizable continuum model affords a somewhat better agreement with the experimental data, especially the red-shifting of the ICT transition and the increase in beta(0) on going from 1 to 4. Time-dependent density functional theory (TD-DFT), finite field, and coupled perturbed Hartree-Fock calculations reproduce even more closely the empirical data and trends; the latter two approaches lead to the highest quadratic nonlinear optical (NLO) response of the studied chromophores for 3, for which the predicted beta(0) is ca. 50-100% larger than that of the analogous N-methylated cation 1. Although the TD-DFT and INDO/SCI approaches give quite different results for ground- and excited-state dipole moments, the overall conclusions of these two methods regarding the ICT absorption and NLO responses are similar.

Detecting influential observations in nonlinear regression modeling of groundwater flow

USGS Publications Warehouse

Yager, Richard M.

1998-01-01

Nonlinear regression is used to estimate optimal parameter values in models of groundwater flow to ensure that differences between predicted and observed heads and flows do not result from nonoptimal parameter values. Parameter estimates can be affected, however, by observations that disproportionately influence the regression, such as outliers that exert undue leverage on the objective function. Certain statistics developed for linear regression can be used to detect influential observations in nonlinear regression if the models are approximately linear. This paper discusses the application of Cook's D, which measures the effect of omitting a single observation on a set of estimated parameter values, and the statistical parameter DFBETAS, which quantifies the influence of an observation on each parameter. The influence statistics were used to (1) identify the influential observations in the calibration of a three-dimensional, groundwater flow model of a fractured-rock aquifer through nonlinear regression, and (2) quantify the effect of omitting influential observations on the set of estimated parameter values. Comparison of the spatial distribution of Cook's D with plots of model sensitivity shows that influential observations correspond to areas where the model heads are most sensitive to certain parameters, and where predicted groundwater flow rates are largest. Five of the six discharge observations were identified as influential, indicating that reliable measurements of groundwater flow rates are valuable data in model calibration. DFBETAS are computed and examined for an alternative model of the aquifer system to identify a parameterization error in the model design that resulted in overestimation of the effect of anisotropy on horizontal hydraulic conductivity.

Estimating monotonic rates from biological data using local linear regression.

PubMed

Olito, Colin; White, Craig R; Marshall, Dustin J; Barneche, Diego R

2017-03-01

Accessing many fundamental questions in biology begins with empirical estimation of simple monotonic rates of underlying biological processes. Across a variety of disciplines, ranging from physiology to biogeochemistry, these rates are routinely estimated from non-linear and noisy time series data using linear regression and ad hoc manual truncation of non-linearities. Here, we introduce the R package LoLinR, a flexible toolkit to implement local linear regression techniques to objectively and reproducibly estimate monotonic biological rates from non-linear time series data, and demonstrate possible applications using metabolic rate data. LoLinR provides methods to easily and reliably estimate monotonic rates from time series data in a way that is statistically robust, facilitates reproducible research and is applicable to a wide variety of research disciplines in the biological sciences. © 2017. Published by The Company of Biologists Ltd.

Order Selection for General Expression of Nonlinear Autoregressive Model Based on Multivariate Stepwise Regression

NASA Astrophysics Data System (ADS)

Shi, Jinfei; Zhu, Songqing; Chen, Ruwen

2017-12-01

An order selection method based on multiple stepwise regressions is proposed for General Expression of Nonlinear Autoregressive model which converts the model order problem into the variable selection of multiple linear regression equation. The partial autocorrelation function is adopted to define the linear term in GNAR model. The result is set as the initial model, and then the nonlinear terms are introduced gradually. Statistics are chosen to study the improvements of both the new introduced and originally existed variables for the model characteristics, which are adopted to determine the model variables to retain or eliminate. So the optimal model is obtained through data fitting effect measurement or significance test. The simulation and classic time-series data experiment results show that the method proposed is simple, reliable and can be applied to practical engineering.

Regression Commonality Analysis: A Technique for Quantitative Theory Building

ERIC Educational Resources Information Center

Nimon, Kim; Reio, Thomas G., Jr.

2011-01-01

When it comes to multiple linear regression analysis (MLR), it is common for social and behavioral science researchers to rely predominately on beta weights when evaluating how predictors contribute to a regression model. Presenting an underutilized statistical technique, this article describes how organizational researchers can use commonality…

Digital In, Digital Out: Digital Editing with Firewire.

ERIC Educational Resources Information Center

Doyle, Bob; Sauer, Jeff

1997-01-01

Reviews linear and nonlinear digital video (DV) editing equipment and software, using the IEEE 1394 (FireWire) connector. Includes a chart listing specifications and rating eight DV editing systems, reviews two DV still-photo cameras, and previews beta DV products. (PEN)

A simplified competition data analysis for radioligand specific activity determination.

PubMed

Venturino, A; Rivera, E S; Bergoc, R M; Caro, R A

1990-01-01

Non-linear regression and two-step linear fit methods were developed to determine the actual specific activity of 125I-ovine prolactin by radioreceptor self-displacement analysis. The experimental results obtained by the different methods are superposable. The non-linear regression method is considered to be the most adequate procedure to calculate the specific activity, but if its software is not available, the other described methods are also suitable.

Data-driven methods towards learning the highly nonlinear inverse kinematics of tendon-driven surgical manipulators.

PubMed

Xu, Wenjun; Chen, Jie; Lau, Henry Y K; Ren, Hongliang

2017-09-01

Accurate motion control of flexible surgical manipulators is crucial in tissue manipulation tasks. The tendon-driven serpentine manipulator (TSM) is one of the most widely adopted flexible mechanisms in minimally invasive surgery because of its enhanced maneuverability in torturous environments. TSM, however, exhibits high nonlinearities and conventional analytical kinematics model is insufficient to achieve high accuracy. To account for the system nonlinearities, we applied a data driven approach to encode the system inverse kinematics. Three regression methods: extreme learning machine (ELM), Gaussian mixture regression (GMR) and K-nearest neighbors regression (KNNR) were implemented to learn a nonlinear mapping from the robot 3D position states to the control inputs. The performance of the three algorithms was evaluated both in simulation and physical trajectory tracking experiments. KNNR performed the best in the tracking experiments, with the lowest RMSE of 2.1275 mm. The proposed inverse kinematics learning methods provide an alternative and efficient way to accurately model the tendon driven flexible manipulator. Copyright © 2016 John Wiley & Sons, Ltd.

Demonstration of leapfrogging for implementing nonlinear model predictive control on a heat exchanger.

PubMed

Sridhar, Upasana Manimegalai; Govindarajan, Anand; Rhinehart, R Russell

2016-01-01

This work reveals the applicability of a relatively new optimization technique, Leapfrogging, for both nonlinear regression modeling and a methodology for nonlinear model-predictive control. Both are relatively simple, yet effective. The application on a nonlinear, pilot-scale, shell-and-tube heat exchanger reveals practicability of the techniques. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Regression of non-linear coupling of noise in LIGO detectors

NASA Astrophysics Data System (ADS)

Da Silva Costa, C. F.; Billman, C.; Effler, A.; Klimenko, S.; Cheng, H.-P.

2018-03-01

In 2015, after their upgrade, the advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) detectors started acquiring data. The effort to improve their sensitivity has never stopped since then. The goal to achieve design sensitivity is challenging. Environmental and instrumental noise couple to the detector output with different, linear and non-linear, coupling mechanisms. The noise regression method we use is based on the Wiener–Kolmogorov filter, which uses witness channels to make noise predictions. We present here how this method helped to determine complex non-linear noise couplings in the output mode cleaner and in the mirror suspension system of the LIGO detector.

A controlled experiment in ground water flow model calibration

USGS Publications Warehouse

Hill, M.C.; Cooley, R.L.; Pollock, D.W.

1998-01-01

Nonlinear regression was introduced to ground water modeling in the 1970s, but has been used very little to calibrate numerical models of complicated ground water systems. Apparently, nonlinear regression is thought by many to be incapable of addressing such complex problems. With what we believe to be the most complicated synthetic test case used for such a study, this work investigates using nonlinear regression in ground water model calibration. Results of the study fall into two categories. First, the study demonstrates how systematic use of a well designed nonlinear regression method can indicate the importance of different types of data and can lead to successive improvement of models and their parameterizations. Our method differs from previous methods presented in the ground water literature in that (1) weighting is more closely related to expected data errors than is usually the case; (2) defined diagnostic statistics allow for more effective evaluation of the available data, the model, and their interaction; and (3) prior information is used more cautiously. Second, our results challenge some commonly held beliefs about model calibration. For the test case considered, we show that (1) field measured values of hydraulic conductivity are not as directly applicable to models as their use in some geostatistical methods imply; (2) a unique model does not necessarily need to be identified to obtain accurate predictions; and (3) in the absence of obvious model bias, model error was normally distributed. The complexity of the test case involved implies that the methods used and conclusions drawn are likely to be powerful in practice.Nonlinear regression was introduced to ground water modeling in the 1970s, but has been used very little to calibrate numerical models of complicated ground water systems. Apparently, nonlinear regression is thought by many to be incapable of addressing such complex problems. With what we believe to be the most complicated synthetic test case used for such a study, this work investigates using nonlinear regression in ground water model calibration. Results of the study fall into two categories. First, the study demonstrates how systematic use of a well designed nonlinear regression method can indicate the importance of different types of data and can lead to successive improvement of models and their parameterizations. Our method differs from previous methods presented in the ground water literature in that (1) weighting is more closely related to expected data errors than is usually the case; (2) defined diagnostic statistics allow for more effective evaluation of the available data, the model, and their interaction; and (3) prior information is used more cautiously. Second, our results challenge some commonly held beliefs about model calibration. For the test case considered, we show that (1) field measured values of hydraulic conductivity are not as directly applicable to models as their use in some geostatistical methods imply; (2) a unique model does not necessarily need to be identified to obtain accurate predictions; and (3) in the absence of obvious model bias, model error was normally distributed. The complexity of the test case involved implies that the methods used and conclusions drawn are likely to be powerful in practice.

Improving near-infrared prediction model robustness with support vector machine regression: a pharmaceutical tablet assay example.

PubMed

Igne, Benoît; Drennen, James K; Anderson, Carl A

2014-01-01

Changes in raw materials and process wear and tear can have significant effects on the prediction error of near-infrared calibration models. When the variability that is present during routine manufacturing is not included in the calibration, test, and validation sets, the long-term performance and robustness of the model will be limited. Nonlinearity is a major source of interference. In near-infrared spectroscopy, nonlinearity can arise from light path-length differences that can come from differences in particle size or density. The usefulness of support vector machine (SVM) regression to handle nonlinearity and improve the robustness of calibration models in scenarios where the calibration set did not include all the variability present in test was evaluated. Compared to partial least squares (PLS) regression, SVM regression was less affected by physical (particle size) and chemical (moisture) differences. The linearity of the SVM predicted values was also improved. Nevertheless, although visualization and interpretation tools have been developed to enhance the usability of SVM-based methods, work is yet to be done to provide chemometricians in the pharmaceutical industry with a regression method that can supplement PLS-based methods.

The Use of Linear Instrumental Variables Methods in Health Services Research and Health Economics: A Cautionary Note

PubMed Central

Terza, Joseph V; Bradford, W David; Dismuke, Clara E

2008-01-01

Objective To investigate potential bias in the use of the conventional linear instrumental variables (IV) method for the estimation of causal effects in inherently nonlinear regression settings. Data Sources Smoking Supplement to the 1979 National Health Interview Survey, National Longitudinal Alcohol Epidemiologic Survey, and simulated data. Study Design Potential bias from the use of the linear IV method in nonlinear models is assessed via simulation studies and real world data analyses in two commonly encountered regression setting: (1) models with a nonnegative outcome (e.g., a count) and a continuous endogenous regressor; and (2) models with a binary outcome and a binary endogenous regressor. Principle Findings The simulation analyses show that substantial bias in the estimation of causal effects can result from applying the conventional IV method in inherently nonlinear regression settings. Moreover, the bias is not attenuated as the sample size increases. This point is further illustrated in the survey data analyses in which IV-based estimates of the relevant causal effects diverge substantially from those obtained with appropriate nonlinear estimation methods. Conclusions We offer this research as a cautionary note to those who would opt for the use of linear specifications in inherently nonlinear settings involving endogeneity. PMID:18546544

Enzyme replacement therapy for Anderson-Fabry disease: A complementary overview of a Cochrane publication through a linear regression and a pooled analysis of proportions from cohort studies

PubMed Central

El Dib, Regina; Gomaa, Huda; Ortiz, Alberto; Politei, Juan; Kapoor, Anil; Barreto, Fellype

2017-01-01

Background Anderson-Fabry disease (AFD) is an X-linked recessive inborn error of glycosphingolipid metabolism caused by a deficiency of alpha-galactosidase A. Renal failure, heart and cerebrovascular involvement reduce survival. A Cochrane review provided little evidence on the use of enzyme replacement therapy (ERT). We now complement this review through a linear regression and a pooled analysis of proportions from cohort studies. Objectives To evaluate the efficacy and safety of ERT for AFD. Materials and methods For the systematic review, a literature search was performed, from inception to March 2016, using Medline, EMBASE and LILACS. Inclusion criteria were cohort studies, patients with AFD on ERT or natural history, and at least one patient-important outcome (all-cause mortality, renal, cardiovascular or cerebrovascular events, and adverse events) reported. The pooled proportion and the confidence interval (CI) are shown for each outcome. Simple linear regressions for composite endpoints were performed. Results 77 cohort studies involving 15,305 participants proved eligible. The pooled proportions were as follows: a) for renal complications, agalsidase alfa 15.3% [95% CI 0.048, 0.303; I2 = 77.2%, p = 0.0005]; agalsidase beta 6% [95% CI 0.04, 0.07; I2 = not applicable]; and untreated patients 21.4% [95% CI 0.1522, 0.2835; I2 = 89.6%, p<0.0001]. Effect differences favored agalsidase beta compared to untreated patients; b) for cardiovascular complications, agalsidase alfa 28% [95% CI 0.07, 0.55; I2 = 96.7%, p<0.0001]; agalsidase beta 7% [95% CI 0.05, 0.08; I2 = not applicable]; and untreated patients 26.2% [95% CI 0.149, 0.394; I2 = 98.8%, p<0.0001]. Effect differences favored agalsidase beta compared to untreated patients; and c) for cerebrovascular complications, agalsidase alfa 11.1% [95% CI 0.058, 0.179; I2 = 70.5%, p = 0.0024]; agalsidase beta 3.5% [95% CI 0.024, 0.046; I2 = 0%, p = 0.4209]; and untreated patients 18.3% [95% CI 0.129, 0.245; I2 = 95% p < 0.0001]. Effect differences favored agalsidase beta over agalsidase alfa or untreated patients. A linear regression showed that Fabry patients receiving agalsidase alfa are more likely to have higher rates of composite endpoints compared to those receiving agalsidase beta. Conclusions Agalsidase beta is associated to a significantly lower incidence of renal, cardiovascular and cerebrovascular events than no ERT, and to a significantly lower incidence of cerebrovascular events than agalsidase alfa. In view of these results, the use of agalsidase beta for preventing major organ complications related to AFD can be recommended. PMID:28296917

Enzyme replacement therapy for Anderson-Fabry disease: A complementary overview of a Cochrane publication through a linear regression and a pooled analysis of proportions from cohort studies.

PubMed

El Dib, Regina; Gomaa, Huda; Ortiz, Alberto; Politei, Juan; Kapoor, Anil; Barreto, Fellype

2017-01-01

Anderson-Fabry disease (AFD) is an X-linked recessive inborn error of glycosphingolipid metabolism caused by a deficiency of alpha-galactosidase A. Renal failure, heart and cerebrovascular involvement reduce survival. A Cochrane review provided little evidence on the use of enzyme replacement therapy (ERT). We now complement this review through a linear regression and a pooled analysis of proportions from cohort studies. To evaluate the efficacy and safety of ERT for AFD. For the systematic review, a literature search was performed, from inception to March 2016, using Medline, EMBASE and LILACS. Inclusion criteria were cohort studies, patients with AFD on ERT or natural history, and at least one patient-important outcome (all-cause mortality, renal, cardiovascular or cerebrovascular events, and adverse events) reported. The pooled proportion and the confidence interval (CI) are shown for each outcome. Simple linear regressions for composite endpoints were performed. 77 cohort studies involving 15,305 participants proved eligible. The pooled proportions were as follows: a) for renal complications, agalsidase alfa 15.3% [95% CI 0.048, 0.303; I2 = 77.2%, p = 0.0005]; agalsidase beta 6% [95% CI 0.04, 0.07; I2 = not applicable]; and untreated patients 21.4% [95% CI 0.1522, 0.2835; I2 = 89.6%, p<0.0001]. Effect differences favored agalsidase beta compared to untreated patients; b) for cardiovascular complications, agalsidase alfa 28% [95% CI 0.07, 0.55; I2 = 96.7%, p<0.0001]; agalsidase beta 7% [95% CI 0.05, 0.08; I2 = not applicable]; and untreated patients 26.2% [95% CI 0.149, 0.394; I2 = 98.8%, p<0.0001]. Effect differences favored agalsidase beta compared to untreated patients; and c) for cerebrovascular complications, agalsidase alfa 11.1% [95% CI 0.058, 0.179; I2 = 70.5%, p = 0.0024]; agalsidase beta 3.5% [95% CI 0.024, 0.046; I2 = 0%, p = 0.4209]; and untreated patients 18.3% [95% CI 0.129, 0.245; I2 = 95% p < 0.0001]. Effect differences favored agalsidase beta over agalsidase alfa or untreated patients. A linear regression showed that Fabry patients receiving agalsidase alfa are more likely to have higher rates of composite endpoints compared to those receiving agalsidase beta. Agalsidase beta is associated to a significantly lower incidence of renal, cardiovascular and cerebrovascular events than no ERT, and to a significantly lower incidence of cerebrovascular events than agalsidase alfa. In view of these results, the use of agalsidase beta for preventing major organ complications related to AFD can be recommended.

Tropical Cyclone Motion: Environmental Interaction Plus a Beta Effect,

DTIC Science & Technology

1982-11-01

il)-Ai3l 808 TROPICA YL ONE NOTION: ENVIRONMENTAL INTERCIION PLUS 1/1 A BETA EFFECT (U) C LORADO STATE UNIV FORT COLLINS DEPT OF ATMOSPHERIC SCIENCE... EFFECT -~~ BY G RE G J. HOLLAND P 1. WILLIAM M. GRAY t’ :’ - .T Atmospheric Science S"TPAPER 󈧎. AUG 2 9 1983 . •4. . .. . . . . . .. ". . . .i L’S I g...causes a westward deviation from the pure steering flow. The nonlinear marner in which these two processes combine together with the effect of as

Dopamine-dependent non-linear correlation between subthalamic rhythms in Parkinson's disease.

PubMed

Marceglia, S; Foffani, G; Bianchi, A M; Baselli, G; Tamma, F; Egidi, M; Priori, A

2006-03-15

The basic information architecture in the basal ganglia circuit is under debate. Whereas anatomical studies quantify extensive convergence/divergence patterns in the circuit, suggesting an information sharing scheme, neurophysiological studies report an absence of linear correlation between single neurones in normal animals, suggesting a segregated parallel processing scheme. In 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated monkeys and in parkinsonian patients single neurones become linearly correlated, thus leading to a loss of segregation between neurones. Here we propose a possible integrative solution to this debate, by extending the concept of functional segregation from the cellular level to the network level. To this end, we recorded local field potentials (LFPs) from electrodes implanted for deep brain stimulation (DBS) in the subthalamic nucleus (STN) of parkinsonian patients. By applying bispectral analysis, we found that in the absence of dopamine stimulation STN LFP rhythms became non-linearly correlated, thus leading to a loss of segregation between rhythms. Non-linear correlation was particularly consistent between the low-beta rhythm (13-20 Hz) and the high-beta rhythm (20-35 Hz). Levodopa administration significantly decreased these non-linear correlations, therefore increasing segregation between rhythms. These results suggest that the extensive convergence/divergence in the basal ganglia circuit is physiologically necessary to sustain LFP rhythms distributed in large ensembles of neurones, but is not sufficient to induce correlated firing between neurone pairs. Conversely, loss of dopamine generates pathological linear correlation between neurone pairs, alters the patterns within LFP rhythms, and induces non-linear correlation between LFP rhythms operating at different frequencies. The pathophysiology of information processing in the human basal ganglia therefore involves not only activities of individual rhythms, but also interactions between rhythms.

Dopamine-dependent non-linear correlation between subthalamic rhythms in Parkinson's disease

PubMed Central

Marceglia, S; Foffani, G; Bianchi, A M; Baselli, G; Tamma, F; Egidi, M; Priori, A

2006-01-01

The basic information architecture in the basal ganglia circuit is under debate. Whereas anatomical studies quantify extensive convergence/divergence patterns in the circuit, suggesting an information sharing scheme, neurophysiological studies report an absence of linear correlation between single neurones in normal animals, suggesting a segregated parallel processing scheme. In 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated monkeys and in parkinsonian patients single neurones become linearly correlated, thus leading to a loss of segregation between neurones. Here we propose a possible integrative solution to this debate, by extending the concept of functional segregation from the cellular level to the network level. To this end, we recorded local field potentials (LFPs) from electrodes implanted for deep brain stimulation (DBS) in the subthalamic nucleus (STN) of parkinsonian patients. By applying bispectral analysis, we found that in the absence of dopamine stimulation STN LFP rhythms became non-linearly correlated, thus leading to a loss of segregation between rhythms. Non-linear correlation was particularly consistent between the low-beta rhythm (13–20 Hz) and the high-beta rhythm (20–35 Hz). Levodopa administration significantly decreased these non-linear correlations, therefore increasing segregation between rhythms. These results suggest that the extensive convergence/divergence in the basal ganglia circuit is physiologically necessary to sustain LFP rhythms distributed in large ensembles of neurones, but is not sufficient to induce correlated firing between neurone pairs. Conversely, loss of dopamine generates pathological linear correlation between neurone pairs, alters the patterns within LFP rhythms, and induces non-linear correlation between LFP rhythms operating at different frequencies. The pathophysiology of information processing in the human basal ganglia therefore involves not only activities of individual rhythms, but also interactions between rhythms. PMID:16410285

Robust ridge regression estimators for nonlinear models with applications to high throughput screening assay data.

PubMed

Lim, Changwon

2015-03-30

Nonlinear regression is often used to evaluate the toxicity of a chemical or a drug by fitting data from a dose-response study. Toxicologists and pharmacologists may draw a conclusion about whether a chemical is toxic by testing the significance of the estimated parameters. However, sometimes the null hypothesis cannot be rejected even though the fit is quite good. One possible reason for such cases is that the estimated standard errors of the parameter estimates are extremely large. In this paper, we propose robust ridge regression estimation procedures for nonlinear models to solve this problem. The asymptotic properties of the proposed estimators are investigated; in particular, their mean squared errors are derived. The performances of the proposed estimators are compared with several standard estimators using simulation studies. The proposed methodology is also illustrated using high throughput screening assay data obtained from the National Toxicology Program. Copyright © 2014 John Wiley & Sons, Ltd.

Neck-focused panic attacks among Cambodian refugees; a logistic and linear regression analysis.

PubMed

Hinton, Devon E; Chhean, Dara; Pich, Vuth; Um, Khin; Fama, Jeanne M; Pollack, Mark H

2006-01-01

Consecutive Cambodian refugees attending a psychiatric clinic were assessed for the presence and severity of current--i.e., at least one episode in the last month--neck-focused panic. Among the whole sample (N=130), in a logistic regression analysis, the Anxiety Sensitivity Index (ASI; odds ratio=3.70) and the Clinician-Administered PTSD Scale (CAPS; odds ratio=2.61) significantly predicted the presence of current neck panic (NP). Among the neck panic patients (N=60), in the linear regression analysis, NP severity was significantly predicted by NP-associated flashbacks (beta=.42), NP-associated catastrophic cognitions (beta=.22), and CAPS score (beta=.28). Further analysis revealed the effect of the CAPS score to be significantly mediated (Sobel test [Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182]) by both NP-associated flashbacks and catastrophic cognitions. In the care of traumatized Cambodian refugees, NP severity, as well as NP-associated flashbacks and catastrophic cognitions, should be specifically assessed and treated.

Beta Regression Finite Mixture Models of Polarization and Priming

ERIC Educational Resources Information Center

Smithson, Michael; Merkle, Edgar C.; Verkuilen, Jay

2011-01-01

This paper describes the application of finite-mixture general linear models based on the beta distribution to modeling response styles, polarization, anchoring, and priming effects in probability judgments. These models, in turn, enhance our capacity for explicitly testing models and theories regarding the aforementioned phenomena. The mixture…

Interpreting Regression Results: beta Weights and Structure Coefficients are Both Important.

ERIC Educational Resources Information Center

Thompson, Bruce

Various realizations have led to less frequent use of the "OVA" methods (analysis of variance--ANOVA--among others) and to more frequent use of general linear model approaches such as regression. However, too few researchers understand all the various coefficients produced in regression. This paper explains these coefficients and their…

A multiple linear regression analysis of factors affecting the simulated Basic Life Support (BLS) performance with Automated External Defibrillator (AED) in Flemish lifeguards.

PubMed

Iserbyt, Peter; Schouppe, Gilles; Charlier, Nathalie

2015-04-01

Research investigating lifeguards' performance of Basic Life Support (BLS) with Automated External Defibrillator (AED) is limited. Assessing simulated BLS/AED performance in Flemish lifeguards and identifying factors affecting this performance. Six hundred and sixteen (217 female and 399 male) certified Flemish lifeguards (aged 16-71 years) performed BLS with an AED on a Laerdal ResusciAnne manikin simulating an adult victim of drowning. Stepwise multiple linear regression analysis was conducted with BLS/AED performance as outcome variable and demographic data as explanatory variables. Mean BLS/AED performance for all lifeguards was 66.5%. Compression rate and depth adhered closely to ERC 2010 guidelines. Ventilation volume and flow rate exceeded the guidelines. A significant regression model, F(6, 415)=25.61, p<.001, ES=.38, explained 27% of the variance in BLS performance (R2=.27). Significant predictors were age (beta=-.31, p<.001), years of certification (beta=-.41, p<.001), time on duty per year (beta=-.25, p<.001), practising BLS skills (beta=.11, p=.011), and being a professional lifeguard (beta=-.13, p=.029). 71% of lifeguards reported not practising BLS/AED. Being young, recently certified, few days of employment per year, practising BLS skills and not being a professional lifeguard are factors associated with higher BLS/AED performance. Measures should be taken to prevent BLS/AED performances from decaying with age and longer certification. Refresher courses could include a formal skills test and lifeguards should be encouraged to practise their BLS/AED skills. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Nonlinear interaction of kinetic Alfven wave and whistler: Turbulent spectra and anisotropic scaling

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

Kumar Dwivedi, Navin; Sharma, R. P.

2013-04-15

In this work, we are presenting the excitation of oblique propagating whistler wave as a consequence of nonlinear interaction between whistler wave and kinetic Alfven wave (KAW) in intermediate beta plasmas. Numerical simulation has been done to study the transient evolution of magnetic field structures of KAW when the nonlinearity arises due to ponderomotive effects by taking the adiabatic response of the background density. Weak oblique propagating whistler signals in these nonlinear plasma density filaments (produced by KAW localization) get amplified. The spectral indices of the power spectrum at different times are calculated with given initial conditions of the simulations.more » Anisotropic scaling laws for KAW and whistlers are presented. The relevance of the present investigation to solar wind turbulence and its acceleration is also pointed out.« less

Nonlinear times series analysis of epileptic human electroencephalogram (EEG)

NASA Astrophysics Data System (ADS)

Li, Dingzhou

The problem of seizure anticipation in patients with epilepsy has attracted significant attention in the past few years. In this paper we discuss two approaches, using methods of nonlinear time series analysis applied to scalp electrode recordings, which is able to distinguish between epochs temporally distant from and just prior to, the onset of a seizure in patients with temporal lobe epilepsy. First we describe a method involving a comparison of recordings taken from electrodes adjacent to and remote from the site of the seizure focus. In particular, we define a nonlinear quantity which we call marginal predictability. This quantity is computed using data from remote and from adjacent electrodes. We find that the difference between the marginal predictabilities computed for the remote and adjacent electrodes decreases several tens of minutes prior to seizure onset, compared to its value interictally. We also show that these difl'crcnc es of marginal predictability intervals are independent of the behavior state of the patient. Next we examine the please coherence between different electrodes both in the long-range and the short-range. When time is distant from seizure onsets ("interictally"), epileptic patients have lower long-range phase coherence in the delta (1-4Hz) and beta (18-30Hz) frequency band compared to nonepileptic subjects. When seizures approach (''preictally"), we observe an increase in phase coherence in the beta band. However, interictally there is no difference in short-range phase coherence between this cohort of patients and non-epileptic subjects. Preictally short-range phase coherence also increases in the alpha (10-13Hz) and the beta band. Next we apply the quantity marginal predictability on the phase difference time series. Such marginal predictabilities are lower in the patients than in the non-epileptic subjects. However, when seizure approaches, the former moves asymptotically towards the latter.

Biodiversity patterns along ecological gradients: unifying β-diversity indices.

PubMed

Szava-Kovats, Robert C; Pärtel, Meelis

2014-01-01

Ecologists have developed an abundance of conceptions and mathematical expressions to define β-diversity, the link between local (α) and regional-scale (γ) richness, in order to characterize patterns of biodiversity along ecological (i.e., spatial and environmental) gradients. These patterns are often realized by regression of β-diversity indices against one or more ecological gradients. This practice, however, is subject to two shortcomings that can undermine the validity of the biodiversity patterns. First, many β-diversity indices are constrained to range between fixed lower and upper limits. As such, regression analysis of β-diversity indices against ecological gradients can result in regression curves that extend beyond these mathematical constraints, thus creating an interpretational dilemma. Second, despite being a function of the same measured α- and γ-diversity, the resultant biodiversity pattern depends on the choice of β-diversity index. We propose a simple logistic transformation that rids beta-diversity indices of their mathematical constraints, thus eliminating the possibility of an uninterpretable regression curve. Moreover, this transformation results in identical biodiversity patterns for three commonly used classical beta-diversity indices. As a result, this transformation eliminates the difficulties of both shortcomings, while allowing the researcher to use whichever beta-diversity index deemed most appropriate. We believe this method can help unify the study of biodiversity patterns along ecological gradients.

Biodiversity Patterns along Ecological Gradients: Unifying β-Diversity Indices

PubMed Central

Szava-Kovats, Robert C.; Pärtel, Meelis

2014-01-01

Ecologists have developed an abundance of conceptions and mathematical expressions to define β-diversity, the link between local (α) and regional-scale (γ) richness, in order to characterize patterns of biodiversity along ecological (i.e., spatial and environmental) gradients. These patterns are often realized by regression of β-diversity indices against one or more ecological gradients. This practice, however, is subject to two shortcomings that can undermine the validity of the biodiversity patterns. First, many β-diversity indices are constrained to range between fixed lower and upper limits. As such, regression analysis of β-diversity indices against ecological gradients can result in regression curves that extend beyond these mathematical constraints, thus creating an interpretational dilemma. Second, despite being a function of the same measured α- and γ-diversity, the resultant biodiversity pattern depends on the choice of β-diversity index. We propose a simple logistic transformation that rids beta-diversity indices of their mathematical constraints, thus eliminating the possibility of an uninterpretable regression curve. Moreover, this transformation results in identical biodiversity patterns for three commonly used classical beta-diversity indices. As a result, this transformation eliminates the difficulties of both shortcomings, while allowing the researcher to use whichever beta-diversity index deemed most appropriate. We believe this method can help unify the study of biodiversity patterns along ecological gradients. PMID:25330181

A Learning Progression Should Address Regression: Insights from Developing Non-Linear Reasoning in Ecology

ERIC Educational Resources Information Center

Hovardas, Tasos

2016-01-01

Although ecological systems at varying scales involve non-linear interactions, learners insist thinking in a linear fashion when they deal with ecological phenomena. The overall objective of the present contribution was to propose a hypothetical learning progression for developing non-linear reasoning in prey-predator systems and to provide…

Development of non-linear models predicting daily fine particle concentrations using aerosol optical depth retrievals and ground-based measurements at a municipality in the Brazilian Amazon region

NASA Astrophysics Data System (ADS)

Gonçalves, Karen dos Santos; Winkler, Mirko S.; Benchimol-Barbosa, Paulo Roberto; de Hoogh, Kees; Artaxo, Paulo Eduardo; de Souza Hacon, Sandra; Schindler, Christian; Künzli, Nino

2018-07-01

Epidemiological studies generally use particulate matter measurements with diameter less 2.5 μm (PM2.5) from monitoring networks. Satellite aerosol optical depth (AOD) data has considerable potential in predicting PM2.5 concentrations, and thus provides an alternative method for producing knowledge regarding the level of pollution and its health impact in areas where no ground PM2.5 measurements are available. This is the case in the Brazilian Amazon rainforest region where forest fires are frequent sources of high pollution. In this study, we applied a non-linear model for predicting PM2.5 concentration from AOD retrievals using interaction terms between average temperature, relative humidity, sine, cosine of date in a period of 365,25 days and the square of the lagged relative residual. Regression performance statistics were tested comparing the goodness of fit and R2 based on results from linear regression and non-linear regression for six different models. The regression results for non-linear prediction showed the best performance, explaining on average 82% of the daily PM2.5 concentrations when considering the whole period studied. In the context of Amazonia, it was the first study predicting PM2.5 concentrations using the latest high-resolution AOD products also in combination with the testing of a non-linear model performance. Our results permitted a reliable prediction considering the AOD-PM2.5 relationship and set the basis for further investigations on air pollution impacts in the complex context of Brazilian Amazon Region.

Revisiting tests for neglected nonlinearity using artificial neural networks.

PubMed

Cho, Jin Seo; Ishida, Isao; White, Halbert

2011-05-01

Tests for regression neglected nonlinearity based on artificial neural networks (ANNs) have so far been studied by separately analyzing the two ways in which the null of regression linearity can hold. This implies that the asymptotic behavior of general ANN-based tests for neglected nonlinearity is still an open question. Here we analyze a convenient ANN-based quasi-likelihood ratio statistic for testing neglected nonlinearity, paying careful attention to both components of the null. We derive the asymptotic null distribution under each component separately and analyze their interaction. Somewhat remarkably, it turns out that the previously known asymptotic null distribution for the type 1 case still applies, but under somewhat stronger conditions than previously recognized. We present Monte Carlo experiments corroborating our theoretical results and showing that standard methods can yield misleading inference when our new, stronger regularity conditions are violated.

Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 1. Theory

USGS Publications Warehouse

Cooley, Richard L.

1982-01-01

Prior information on the parameters of a groundwater flow model can be used to improve parameter estimates obtained from nonlinear regression solution of a modeling problem. Two scales of prior information can be available: (1) prior information having known reliability (that is, bias and random error structure) and (2) prior information consisting of best available estimates of unknown reliability. A regression method that incorporates the second scale of prior information assumes the prior information to be fixed for any particular analysis to produce improved, although biased, parameter estimates. Approximate optimization of two auxiliary parameters of the formulation is used to help minimize the bias, which is almost always much smaller than that resulting from standard ridge regression. It is shown that if both scales of prior information are available, then a combined regression analysis may be made.

Using the Coefficient of Determination "R"[superscript 2] to Test the Significance of Multiple Linear Regression

ERIC Educational Resources Information Center

Quinino, Roberto C.; Reis, Edna A.; Bessegato, Lupercio F.

2013-01-01

This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. (Contains 3 figures.)

A multiplicative process for generating a beta-like survival function with application to the UK 2016 EU referendum results

NASA Astrophysics Data System (ADS)

Fenner, Trevor; Kaufmann, Eric; Levene, Mark; Loizou, George

Human dynamics and sociophysics suggest statistical models that may explain and provide us with better insight into social phenomena. Contextual and selection effects tend to produce extreme values in the tails of rank-ordered distributions of both census data and district-level election outcomes. Models that account for this nonlinearity generally outperform linear models. Fitting nonlinear functions based on rank-ordering census and election data therefore improves the fit of aggregate voting models. This may help improve ecological inference, as well as election forecasting in majoritarian systems. We propose a generative multiplicative decrease model that gives rise to a rank-order distribution and facilitates the analysis of the recent UK EU referendum results. We supply empirical evidence that the beta-like survival function, which can be generated directly from our model, is a close fit to the referendum results, and also may have predictive value when covariate data are available.

Megaplumes on Venus

NASA Technical Reports Server (NTRS)

Kaula, W. M.

1993-01-01

The geoid and topography heights of Atla Regio and Beta Regio, both peaks and slopes, appear explicable as steady-state plumes, if non-linear viscosity eta(Tau, epsilon) is taken into account. Strongly constrained by the data are an effective plume depth of about 700 km, with a temperature anomaly thereat of about 30 degrees, leading to more than 400 degrees at the plume head. Also well constrained is the combination Q(eta)/s(sup 4)(sub 0) = (volume flow rate)(viscosity)/(plume radius): about 11 Pa/m/sec. The topographic slopes dh/ds constrain the combination Q/A, where A is the thickness of the spreading layer, since the slope varies inversely with velocity. The geoid slopes dN/ds require enhancement of the deeper flow, as expected from non-linear viscosity. The Beta data are best fit by Q = 500 m(sup 3)/sec and A equals 140 km; the Atla, by Q equals 440 m(exp 3)/sec and A equals 260 km. The dynamic contribution to the topographic slope is minor.

Piezoelectricity and Ferroelectricity in Amino Acid Glycine =

NASA Astrophysics Data System (ADS)

Seyedhosseini, Ensieh

Bioorganic ferroelectrics and piezoelectrics are becoming increasingly important in view of their intrinsic compatibility with biological environment and biofunctionality combined with strong piezoelectric effect and switchable polarization at room temperature. Here we study piezoelectricity and ferroelectricity in the smallest amino acid glycine, representing a broad class of non-centrosymmetric amino acids. Glycine is one of the basic and important elements in biology, as it serves as a building block for proteins. Three polymorphic forms with different physical properties are possible in glycine (alpha, beta and gamma), Of special interest for various applications are non-centrosymmetric polymorphs: beta-glycine and gamma-glycine. The most useful beta-polymorph being ferroelectric took much less attention than the other due to its instability under ambient conditions. In this work, we could grow stable microcrystals of beta-glycine by the evaporation of aqueous solution on a (111)Pt/Ti/SiO2/Si substrate as a template. The effects of the solution concentration and Pt-assisted nucleation on the crystal growth and phase evolution were characterized by X-ray diffraction analysis and Raman spectroscopy. In addition, spin-coating technique was used for the fabrication of highly aligned nano-islands of beta-glycine with regular orientation of the crystallographic axes relative the underlying substrate (Pt). Further we study both as-grown and tip-induced domain structures and polarization switching in the beta-glycine molecular systems by Piezoresponse Force Microscopy (PFM) and compare the results with molecular modeling and computer simulations. We show that beta-glycine is indeed a room-temperature ferroelectric and polarization can be switched by applying a bias to non-polar cuts via a conducting tip of atomic force microscope (AFM). Dynamics of these in-plane domains is studied as a function of applied voltage and pulse duration. The domain shape is dictated by both internal and external polarization screening mediated by defects and topographic features. Thermodynamic theory is applied to explain the domain propagation induced by the AFM tip. Our findings suggest that beta-glycine is a uniaxial ferroelectric with the properties controlled by the charged domain walls which in turn can be manipulated by external bias. Besides, nonlinear optical properties of beta-glycine were investigated by a second harmonic generation (SHG) method. SHG method confirmed that the 2-fold symmetry is preserved in as-grown crystals, thus reflecting the expected P21 symmetry of the beta-phase. Spontaneous polarization direction is found to be parallel to the monoclinic [010] axis and directed along the crystal length. These data are confirmed by computational molecular modeling. Optical measurements revealed also relatively high values of the nonlinear optical susceptibility (50% greater than in the z-cut quartz). The potential of using stable beta-glycine crystals in various applications are discussed in this work.

Period of vibration of axially vibrating truly nonlinear rod

NASA Astrophysics Data System (ADS)

Cveticanin, L.

2016-07-01

In this paper the axial vibration of a muscle whose fibers are parallel to the direction of muscle compression is investigated. The model is a clamped-free rod with a strongly nonlinear elastic property. Axial vibration is described by a nonlinear partial differential equation. A solution of the equation is constructed for special initial conditions by using the method of separation of variables. The partial differential equation is separated into two uncoupled strongly nonlinear second order differential equations. Both equations, with displacement function and with time function are exactly determined. Exact solutions are given in the form of inverse incomplete and inverse complete Beta function. Using boundary and initial conditions, the frequency of vibration is obtained. It has to be mentioned that the determined frequency represents the exact analytic description for the axially vibrating truly nonlinear clamped-free rod. The procedure suggested in this paper is applied for calculation of the frequency of the longissimus dorsi muscle of a cow. The influence of elasticity order and elasticity coefficient on the frequency property is tested.

A Better Lemon Squeezer? Maximum-Likelihood Regression with Beta-Distributed Dependent Variables

ERIC Educational Resources Information Center

Smithson, Michael; Verkuilen, Jay

2006-01-01

Uncorrectable skew and heteroscedasticity are among the "lemons" of psychological data, yet many important variables naturally exhibit these properties. For scales with a lower and upper bound, a suitable candidate for models is the beta distribution, which is very flexible and models skew quite well. The authors present…

Observation of the hot electron interchange instability in a high beta dipolar confined plasma

NASA Astrophysics Data System (ADS)

Ortiz, Eugenio Enrique

In this thesis the first study of the high beta, hot electron interchange (HEI) instability in a laboratory, dipolar confined plasma is presented. The Levitated Dipole Experiment (LDX) is a new research facility that explores the confinement and stability of plasma created within the dipole field produced by a strong superconducting magnet. In initial experiments long-pulse, quasi-steady state microwave discharges lasting more than 10 sec have been produced with equilibria having peak beta values of 20%. Creation of high-pressure, high beta plasma is possible only when intense HEI instabilities are stabilized by sufficiently high background plasma density. LDX plasma exist within one of three regimes characterized by its response to heating and fueling. The observed HEI instability depends on the regime and can take one of three forms: as quasiperiodic bursts during the low density, low beta plasma regime, as local high beta relaxation events in the high beta plasma regime, and as global, intense energy relaxation bursts, both in the high beta and afterglow plasma regimes. Measurements of the HEI instability are made using high-impedance, floating potential probes and fast Mirnov coils. Analysis of these signals reveals the extent of the transport during high beta plasmas. During intense high beta HEI instabilities, fluctuations at the edge significantly exceed the magnitude of the equilibrium field generated by the high beta electrons and energetic electron confinement ends in under 100 musec. For heated plasmas, one of the consequences of the observed high beta transport is the presence of hysteresis in the neutral gas fueling required to stabilize and maintain the high beta plasma. Finally, a nonlinear, self-consistent numerical simulation of the growth and saturation of the HEI instability has been adapted for LDX and compared to experimental observations.

Selective extinction drives taxonomic and functional alpha and beta diversities in island bird assemblages.

PubMed

Si, Xingfeng; Baselga, Andrés; Leprieur, Fabien; Song, Xiao; Ding, Ping

2016-03-01

Taxonomic diversity considers all species being equally different from each other and thus disregards species' different ecological functions. Exploring taxonomic and functional aspects of biodiversity simultaneously can better understand the processes of community assembly. We analysed taxonomic and functional alpha and beta diversities of breeding bird assemblages on land-bridge islands in the Thousand Island Lake, China. Given the high dispersal ability of most birds at this spatial scale (several kilometres), we predicted (i) selective extinction driving alpha and beta diversities after the creation of land-bridge islands of varying area and (ii) low taxonomic and functional beta diversities that were not correlated to spatial distance. Breeding birds were surveyed on 37 islands annually from 2007 to 2014. We decomposed beta diversity of breeding birds into spatial turnover and nestedness-resultant components, and related taxonomic and functional diversities to island area and isolation using power regression models (for alpha diversity) and multiple regression models on distance matrices (for beta diversity). We then ran simulations to assess the strength of the correlations between taxonomic and functional diversities. Results revealed that both taxonomic and functional alpha diversities increased with island area. The taxonomic nestedness-resultant and turnover components increased and decreased with difference in area, respectively, but functional counterparts did not. Isolation played a minor role in explaining alpha- and beta-diversity patterns. By partitioning beta diversity, we found low levels of overall taxonomic and functional beta diversities. The functional nestedness-resultant component dominated overall functional beta diversity, whereas taxonomic turnover was the dominant component for taxonomic beta diversity. The simulation showed that functional alpha and beta diversities were significantly correlated with taxonomic diversities, and the observed values of correlations were significantly different from null expectations of random extinction. Our assessment of island bird assemblages validated the predictions of no distance effects and low beta diversity due to pervasive dispersal events among islands and also suggested that selective extinction drives taxonomic and functional alpha and beta diversities. The contrasting turnover and nestedness-resultant components of taxonomic and functional beta diversities demonstrate the importance of considering the multifaceted nature of biodiversity when examining community assembly. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

Influence of Thermal Anisotropy on Equilibrium Stellarator Beta Limits

NASA Astrophysics Data System (ADS)

Bechtel, T. A.; Hegna, C. C.; Sovinec, C. R.

2017-10-01

The effect of anisotropic heat conduction on the upper beta limit of stellarator plasmas is studied using the nonlinear, extended MHD code NIMROD. The configuration under investigation is an l=2, M=10 torsatron with vacuum rotational transform near unity. Finite-beta plasmas are created using a volumetric heating source and temperature dependent resistivity; modeled with 22 stellarator symmetric (integer multiples of M) toroidal modes. Extended MHD simulations are then performed to generate steady state solutions that represent 3D equilibria. With increased heating, Shafranov shifts occur, and the associated break up of edge magnetic surfaces limits the achievable beta. Due to the presence of finite parallel heat conduction, pressure profiles can exist in regions of magnetic stochasticity. Here, we present results of independently varying the parallel and perpendicular thermal anisotropy. In particular, simulations show that the attained stored energy is a function of the magnitude of parallel and perpendicular thermal conduction for a given heat source, indicating that equilibrium beta limits are sensitive to anisotropic transport properties. Preliminary studies of MHD stability with non-stellarator symmetric modes, near the highest achievable beta, are also presented. Research supported by US DOE under Grant No. DE-FG02-99ER54546.

Dark and grey compressional dispersive Alfven solitons in plasmas

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

Shukla, P. K.; Eliasson, B.; Stenflo, L.

2011-06-15

The amplitude modulation of compressional dispersive Alfven (CDA) waves in a low-{beta} plasma is considered. It is shown that the dynamics of modulated CDA waves is governed by a cubic nonlinear Schroedinger equation, which depicts the formation of a dark/grey envelope CDA soliton.

Design of a 6 TeV muon collider

DOE PAGES

Wang, M-H.; Nosochkov, Y.; Cai, Y.; ...

2016-09-09

Here, a preliminary design of a muon collider ring with the center of mass (CM) energy of 6 TeV is presented. The ring circumference is 6.3 km, and themore » $$\\beta$$ functions at collision point are 1 cm in each plane. The ring linear optics, the non-linear chromaticity compensation in the Interaction Region (IR), and the additional non-linear orthogonal correcting knobs are described. Magnet specifications are based on the maximum pole-tip field of 20T in dipoles and 15T in quadrupoles. Careful compensation of the non-linear chromatic and amplitude dependent effects provide a sufficiently large dynamic aperture for the momentum range of up to $$\\pm$$0.5% without considering magnet errors.« less

A different approach to estimate nonlinear regression model using numerical methods

NASA Astrophysics Data System (ADS)

Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.

2017-11-01

This research paper concerns with the computational methods namely the Gauss-Newton method, Gradient algorithm methods (Newton-Raphson method, Steepest Descent or Steepest Ascent algorithm method, the Method of Scoring, the Method of Quadratic Hill-Climbing) based on numerical analysis to estimate parameters of nonlinear regression model in a very different way. Principles of matrix calculus have been used to discuss the Gradient-Algorithm methods. Yonathan Bard [1] discussed a comparison of gradient methods for the solution of nonlinear parameter estimation problems. However this article discusses an analytical approach to the gradient algorithm methods in a different way. This paper describes a new iterative technique namely Gauss-Newton method which differs from the iterative technique proposed by Gorden K. Smyth [2]. Hans Georg Bock et.al [10] proposed numerical methods for parameter estimation in DAE’s (Differential algebraic equation). Isabel Reis Dos Santos et al [11], Introduced weighted least squares procedure for estimating the unknown parameters of a nonlinear regression metamodel. For large-scale non smooth convex minimization the Hager and Zhang (HZ) conjugate gradient Method and the modified HZ (MHZ) method were presented by Gonglin Yuan et al [12].

An evaluation of bias in propensity score-adjusted non-linear regression models.

PubMed

Wan, Fei; Mitra, Nandita

2018-03-01

Propensity score methods are commonly used to adjust for observed confounding when estimating the conditional treatment effect in observational studies. One popular method, covariate adjustment of the propensity score in a regression model, has been empirically shown to be biased in non-linear models. However, no compelling underlying theoretical reason has been presented. We propose a new framework to investigate bias and consistency of propensity score-adjusted treatment effects in non-linear models that uses a simple geometric approach to forge a link between the consistency of the propensity score estimator and the collapsibility of non-linear models. Under this framework, we demonstrate that adjustment of the propensity score in an outcome model results in the decomposition of observed covariates into the propensity score and a remainder term. Omission of this remainder term from a non-collapsible regression model leads to biased estimates of the conditional odds ratio and conditional hazard ratio, but not for the conditional rate ratio. We further show, via simulation studies, that the bias in these propensity score-adjusted estimators increases with larger treatment effect size, larger covariate effects, and increasing dissimilarity between the coefficients of the covariates in the treatment model versus the outcome model.

Multi-Target Regression via Robust Low-Rank Learning.

PubMed

Zhen, Xiantong; Yu, Mengyang; He, Xiaofei; Li, Shuo

2018-02-01

Multi-target regression has recently regained great popularity due to its capability of simultaneously learning multiple relevant regression tasks and its wide applications in data mining, computer vision and medical image analysis, while great challenges arise from jointly handling inter-target correlations and input-output relationships. In this paper, we propose Multi-layer Multi-target Regression (MMR) which enables simultaneously modeling intrinsic inter-target correlations and nonlinear input-output relationships in a general framework via robust low-rank learning. Specifically, the MMR can explicitly encode inter-target correlations in a structure matrix by matrix elastic nets (MEN); the MMR can work in conjunction with the kernel trick to effectively disentangle highly complex nonlinear input-output relationships; the MMR can be efficiently solved by a new alternating optimization algorithm with guaranteed convergence. The MMR leverages the strength of kernel methods for nonlinear feature learning and the structural advantage of multi-layer learning architectures for inter-target correlation modeling. More importantly, it offers a new multi-layer learning paradigm for multi-target regression which is endowed with high generality, flexibility and expressive ability. Extensive experimental evaluation on 18 diverse real-world datasets demonstrates that our MMR can achieve consistently high performance and outperforms representative state-of-the-art algorithms, which shows its great effectiveness and generality for multivariate prediction.

Kinetic treatment of nonlinear magnetized plasma motions - General geometry and parallel waves

NASA Technical Reports Server (NTRS)

Khabibrakhmanov, I. KH.; Galinskii, V. L.; Verheest, F.

1992-01-01

The expansion of kinetic equations in the limit of a strong magnetic field is presented. This gives a natural description of the motions of magnetized plasmas, which are slow compared to the particle gyroperiods and gyroradii. Although the approach is 3D, this very general result is used only to focus on the parallel propagation of nonlinear Alfven waves. The derivative nonlinear Schroedinger-like equation is obtained. Two new terms occur compared to earlier treatments, a nonlinear term proportional to the heat flux along the magnetic field line and a higher-order dispersive term. It is shown that kinetic description avoids the singularities occurring in magnetohydrodynamic or multifluid approaches, which correspond to the degenerate case of sound speeds equal to the Alfven speed, and that parallel heat fluxes cannot be neglected, not even in the case of low parallel plasma beta. A truly stationary soliton solution is derived.

Risk factors for persistent gestational trophoblastic neoplasia.

PubMed

Kuyumcuoglu, Umur; Guzel, Ali Irfan; Erdemoglu, Mahmut; Celik, Yusuf

2011-01-01

This retrospective study evaluated the risk factors for persistent gestational trophoblastic disease (GTN) and determined their odds ratios. This study included 100 cases with GTN admitted to our clinic. Possible risk factors recorded were age, gravidity, parity, size of the neoplasia, and beta-human chorionic gonadotropin levels (beta-hCG) before and after the procedure. Statistical analyses consisted of the independent sample t-test and logistic regression using the statistical package SPSS ver. 15.0 for Windows (SPSS, Chicago, IL, USA). Twenty of the cases had persistent GTN, and the differences between these and the others cases were evaluated. The size of the neoplasia and histopathological type of GTN had no statistical relationship with persistence, whereas age, gravidity, and beta-hCG levels were significant risk factors for persistent GTN (p < 0.05). The odds ratios (95% confidence interval (CI)) for age, gravidity, and pre- and post-evacuation beta-hCG levels determined using logistic regression were 4.678 (0.97-22.44), 7.315 (1.16-46.16), 2.637 (1.41-4.94), and 2.339 (1.52-3.60), respectively. Patient age, gravidity, and beta-hCG levels were risk factors for persistent GTN, whereas the size of the neoplasia and histopathological type of GTN were not significant risk factors.

Geographical variation of cerebrovascular disease in New York State: the correlation with income

PubMed Central

Han, Daikwon; Carrow, Shannon S; Rogerson, Peter A; Munschauer, Frederick E

2005-01-01

Background Income is known to be associated with cerebrovascular disease; however, little is known about the more detailed relationship between cerebrovascular disease and income. We examined the hypothesis that the geographical distribution of cerebrovascular disease in New York State may be predicted by a nonlinear model using income as a surrogate socioeconomic risk factor. Results We used spatial clustering methods to identify areas with high and low prevalence of cerebrovascular disease at the ZIP code level after smoothing rates and correcting for edge effects; geographic locations of high and low clusters of cerebrovascular disease in New York State were identified with and without income adjustment. To examine effects of income, we calculated the excess number of cases using a non-linear regression with cerebrovascular disease rates taken as the dependent variable and income and income squared taken as independent variables. The resulting regression equation was: excess rate = 32.075 - 1.22*10-4(income) + 8.068*10-10(income2), and both income and income squared variables were significant at the 0.01 level. When income was included as a covariate in the non-linear regression, the number and size of clusters of high cerebrovascular disease prevalence decreased. Some 87 ZIP codes exceeded the critical value of the local statistic yielding a relative risk of 1.2. The majority of low cerebrovascular disease prevalence geographic clusters disappeared when the non-linear income effect was included. For linear regression, the excess rate of cerebrovascular disease falls with income; each $10,000 increase in median income of each ZIP code resulted in an average reduction of 3.83 observed cases. The significant nonlinear effect indicates a lessening of this income effect with increasing income. Conclusion Income is a non-linear predictor of excess cerebrovascular disease rates, with both low and high observed cerebrovascular disease rate areas associated with higher income. Income alone explains a significant amount of the geographical variance in cerebrovascular disease across New York State since both high and low clusters of cerebrovascular disease dissipate or disappear with income adjustment. Geographical modeling, including non-linear effects of income, may allow for better identification of other non-traditional risk factors. PMID:16242043

A phenomenological biological dose model for proton therapy based on linear energy transfer spectra.

PubMed

Rørvik, Eivind; Thörnqvist, Sara; Stokkevåg, Camilla H; Dahle, Tordis J; Fjaera, Lars Fredrik; Ytre-Hauge, Kristian S

2017-06-01

The relative biological effectiveness (RBE) of protons varies with the radiation quality, quantified by the linear energy transfer (LET). Most phenomenological models employ a linear dependency of the dose-averaged LET (LET d ) to calculate the biological dose. However, several experiments have indicated a possible non-linear trend. Our aim was to investigate if biological dose models including non-linear LET dependencies should be considered, by introducing a LET spectrum based dose model. The RBE-LET relationship was investigated by fitting of polynomials from 1st to 5th degree to a database of 85 data points from aerobic in vitro experiments. We included both unweighted and weighted regression, the latter taking into account experimental uncertainties. Statistical testing was performed to decide whether higher degree polynomials provided better fits to the data as compared to lower degrees. The newly developed models were compared to three published LET d based models for a simulated spread out Bragg peak (SOBP) scenario. The statistical analysis of the weighted regression analysis favored a non-linear RBE-LET relationship, with the quartic polynomial found to best represent the experimental data (P = 0.010). The results of the unweighted regression analysis were on the borderline of statistical significance for non-linear functions (P = 0.053), and with the current database a linear dependency could not be rejected. For the SOBP scenario, the weighted non-linear model estimated a similar mean RBE value (1.14) compared to the three established models (1.13-1.17). The unweighted model calculated a considerably higher RBE value (1.22). The analysis indicated that non-linear models could give a better representation of the RBE-LET relationship. However, this is not decisive, as inclusion of the experimental uncertainties in the regression analysis had a significant impact on the determination and ranking of the models. As differences between the models were observed for the SOBP scenario, both non-linear LET spectrum- and linear LET d based models should be further evaluated in clinically realistic scenarios. © 2017 American Association of Physicists in Medicine.

An acoustic method for predicting relative strengths of cohesive sediment deposits

NASA Astrophysics Data System (ADS)

Reed, A. H.; Sanders, W. M.

2017-12-01

Cohesive sediment dynamics are fundamentally determined by sediment mineralogy, organic matter composition, ionic strength of water, and currents. These factors work to bind the cohesive sediments and to determine depositional rates. Once deposited the sediments exhibit a nonlinear response to stress and they develop increases in shear strength. Shear strength is critically important in resuspension, transport, creep, and failure predictions. Typically, shear strength is determined by point measurements, both indirectly from free-fall penetrometers or directly on cores with a shear vane. These values are then used to interpolate over larger areas. However, the remote determination of these properties would provide continuos coverage, yet it has proven difficult with sonar systems. Recently, findings from an acoustic study on cohesive sediments in a laboratory setting suggests that cohesive sediments may be differentiated using parametric acoustics; this method pulses two primary frequencies into the sediment and the resultant difference frequency is used to determine the degree of acoustic nonlinearity within the sediment. In this study, two marine clay species, kaolinite and montmorillonite, and two biopolymers, guar gum and xanthan gum were mixed to make nine different samples. The samples were evaluated in a parametric acoustic measurement tank. From the parametric acoustic measurements, the quadratic nonlinearity coefficient (beta) was determined. beta was correlated with the cation exchange capacity (CEC), an indicator of shear strength. The results indicate that increased acoustic nonlinearity correlates with increased CEC. From this work, laboratory measurements indicate that this correlation may be used evaluate geotechnical properties of cohesive sediments and may provide a means to predict sediment weakness in subaqueous environments.

Non-Linear Approach in Kinesiology Should Be Preferred to the Linear--A Case of Basketball.

PubMed

Trninić, Marko; Jeličić, Mario; Papić, Vladan

2015-07-01

In kinesiology, medicine, biology and psychology, in which research focus is on dynamical self-organized systems, complex connections exist between variables. Non-linear nature of complex systems has been discussed and explained by the example of non-linear anthropometric predictors of performance in basketball. Previous studies interpreted relations between anthropometric features and measures of effectiveness in basketball by (a) using linear correlation models, and by (b) including all basketball athletes in the same sample of participants regardless of their playing position. In this paper the significance and character of linear and non-linear relations between simple anthropometric predictors (AP) and performance criteria consisting of situation-related measures of effectiveness (SE) in basketball were determined and evaluated. The sample of participants consisted of top-level junior basketball players divided in three groups according to their playing time (8 minutes and more per game) and playing position: guards (N = 42), forwards (N = 26) and centers (N = 40). Linear (general model) and non-linear (general model) regression models were calculated simultaneously and separately for each group. The conclusion is viable: non-linear regressions are frequently superior to linear correlations when interpreting actual association logic among research variables.

A Modified Double Multiple Nonlinear Regression Constitutive Equation for Modeling and Prediction of High Temperature Flow Behavior of BFe10-1-2 Alloy

NASA Astrophysics Data System (ADS)

Cai, Jun; Wang, Kuaishe; Shi, Jiamin; Wang, Wen; Liu, Yingying

2018-01-01

Constitutive analysis for hot working of BFe10-1-2 alloy was carried out by using experimental stress-strain data from isothermal hot compression tests, in a wide range of temperature of 1,023 1,273 K, and strain rate range of 0.001 10 s-1. A constitutive equation based on modified double multiple nonlinear regression was proposed considering the independent effects of strain, strain rate, temperature and their interrelation. The predicted flow stress data calculated from the developed equation was compared with the experimental data. Correlation coefficient (R), average absolute relative error (AARE) and relative errors were introduced to verify the validity of the developed constitutive equation. Subsequently, a comparative study was made on the capability of strain-compensated Arrhenius-type constitutive model. The results showed that the developed constitutive equation based on modified double multiple nonlinear regression could predict flow stress of BFe10-1-2 alloy with good correlation and generalization.

TG study of the Li0.4Fe2.4Zn0.2O4 ferrite synthesis

NASA Astrophysics Data System (ADS)

Lysenko, E. N.; Nikolaev, E. V.; Surzhikov, A. P.

2016-02-01

In this paper, the kinetic analysis of Li-Zn ferrite synthesis was studied using thermogravimetry (TG) method through the simultaneous application of non-linear regression to several measurements run at different heating rates (multivariate non-linear regression). Using TG-curves obtained for the four heating rates and Netzsch Thermokinetics software package, the kinetic models with minimal adjustable parameters were selected to quantitatively describe the reaction of Li-Zn ferrite synthesis. It was shown that the experimental TG-curves clearly suggest a two-step process for the ferrite synthesis and therefore a model-fitting kinetic analysis based on multivariate non-linear regressions was conducted. The complex reaction was described by a two-step reaction scheme consisting of sequential reaction steps. It is established that the best results were obtained using the Yander three-dimensional diffusion model at the first stage and Ginstling-Bronstein model at the second step. The kinetic parameters for lithium-zinc ferrite synthesis reaction were found and discussed.

Comparative Efficacy of Tongxinluo Capsule and Beta-Blockers in Treating Angina Pectoris: Meta-Analysis of Randomized Controlled Trials.

PubMed

Jia, Yongliang; Leung, Siu-wai

2015-11-01

There have been no systematic reviews, let alone meta-analyses, of randomized controlled trials (RCTs) comparing tongxinluo capsule (TXL) and beta-blockers in treating angina pectoris. This study aimed to evaluate the efficacy of TXL and beta-blockers in treating angina pectoris by a meta-analysis of eligible RCTs. The RCTs comparing TXL with beta-blockers (including metoprolol) in treating angina pectoris were searched and retrieved from databases including PubMed, Chinese National Knowledge Infrastructure, and WanFang Data. Eligible RCTs were selected according to prespecified criteria. Meta-analysis was performed on the odds ratios (OR) of symptomatic and electrocardiographic (ECG) improvements after treatment. Subgroup analysis, sensitivity analysis, meta-regression, and publication biases analysis were conducted to evaluate the robustness of the results. Seventy-three RCTs published between 2000 and 2014 with 7424 participants were eligible. Overall ORs comparing TXL with beta-blockers were 3.40 (95% confidence interval [CI], 2.97-3.89; p<0.0001) for symptomatic improvement and 2.63 (95% CI, 2.29-3.02; p<0.0001) for ECG improvement. Subgroup analysis and sensitivity analysis found no statistically significant dependence of overall ORs on specific study characteristics except efficacy criteria. Meta-regression found no significant except sample sizes for data on symptomatic improvement. Publication biases were statistically significant. TXL seems to be more effective than beta-blockers in treating angina pectoris, on the basis of the eligible RCTs. Further RCTs are warranted to reduce publication bias and verify efficacy.

Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models.

PubMed

Shah, A A; Xing, W W; Triantafyllidis, V

2017-04-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.

Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models

PubMed Central

Xing, W. W.; Triantafyllidis, V.

2017-01-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach. PMID:28484327

Can neutrino mass be deduced from beta particle spectrum?

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

Semkow, T.M.

1993-12-31

With 17-keV neutrino faith being uncertain, it is important to examine the effects of detector resolution and response on the detection limits of massive neutrino. The authors use Fermi theory and generate by Monte Carlo up to 5-10{sup 9} {beta}{sup {minus}} decay events from {sup 35}S. The {beta}{sup {minus}} spectra are then resolved by {chi}{sup 2} minimization. We show that given high statistics and accurate knowledge of the response function it should be possible to detect neutrino mass with a proportional detector, particularly with the gas-scintillation proportional detector, in addition to semiconductor, in addition to semiconductor detectors. This paper presentsmore » a design of double-chamber Xe gas-scintillation proportional detector in which the backscattering effects are suppressed. However, even the slight uncertainties in the response functions as well as {approximately} 10{sup {minus}3} relative energy nonlinearities in the {beta}{sup {minus}} spectrum may create an artificial effect of neutrino mass.« less

The electronic structure and second-order nonlinear optical properties of donor-acceptor acetylenes - A detailed investigation of structure-property relationships

NASA Technical Reports Server (NTRS)

Stiegman, A. E.; Graham, Eva; Khundkar, Lutfur R.; Perry, Joseph W.; Cheng, L.-T.; Perry, Kelly J.

1991-01-01

A series of donor-acceptor acetylene compounds was synthesized in which systematic changes in both the conjugation length and the donor-acceptor strength were made. The effect of these structural changes on the spectroscopic and electronic properties of the molecules and, ultimately, on the measured second-order molecular hyperpolarizabilities (beta) was investigated. It was found that increases in the donor-acceptor strength resulted in increases in the magnitude of beta. For this class of molecules, the increase is dominated by the energy of the intramolecular charge-transfer transition, while factors such as the ground to excited-state dipole moment change and the transition-moment integral are much less important. Increasing the conjugation length from one to two acetylene linkers did not result in an increase in the value of beta; however, beta increased sharply in going from two acetylenes to three. This increase is attributed to the superposition of several nearly isoenergetic excited states.

Lewis acid-Lewis acid heterobimetallic cooperative catalysis: mechanistic studies and application in enantioselective aza-Michael reaction.

PubMed

Yamagiwa, Noriyuki; Qin, Hongbo; Matsunaga, Shigeki; Shibasaki, Masakatsu

2005-09-28

The full details of a catalytic asymmetric aza-Michael reaction of methoxylamine promoted by rare earth-alkali metal heterobimetallic complexes are described, demonstrating the effectiveness of Lewis acid-Lewis acid cooperative catalysis. First, enones were used as substrates, and the 1,4-adducts were obtained in good yield (57-98%) and high ee (81-96%). Catalyst loading was successfully reduced to 0.3-3 mol % with enones. To broaden the substrate scope of the reaction to carboxylic acid derivatives, alpha,beta-unsaturated N-acylpyrroles were used as monodentate, carboxylic acid derivatives. With beta-alkyl-substituted N-acylpyrroles, the reaction proceeded smoothly and the products were obtained in high yield and good ee. Transformation of the 1,4-adducts from enones and alpha,beta-unsaturated N-acylpyrroles afforded corresponding chiral aziridines and beta-amino acids. Detailed mechanistic studies, including kinetics, NMR analysis, nonlinear effects, and rare earth metal effects, are also described. The Lewis acid-Lewis acid cooperative mechanism, including the substrate coordination mode, is discussed in detail.

The application of neural network model to the simulation nitrous oxide emission in the hydro-fluctuation belt of Three Gorges Reservoir

NASA Astrophysics Data System (ADS)

Song, Lanlan

2017-04-01

Nitrous oxide is much more potent greenhouse gas than carbon dioxide. However, the estimation of N2O flux is usually clouded with uncertainty, mainly due to high spatial and temporal variations. This hampers the development of general mechanistic models for N2O emission as well, as most previously developed models were empirical or exhibited low predictability with numerous assumptions. In this study, we tested General Regression Neural Networks (GRNN) as an alternative to classic empirical models for simulating N2O emission in riparian zones of Reservoirs. GRNN and nonlinear regression (NLR) were applied to estimate the N2O flux of 1-year observations in riparian zones of Three Gorge Reservoir. NLR resulted in lower prediction power and higher residuals compared to GRNN. Although nonlinear regression model estimated similar average values of N2O, it could not capture the fluctuation patterns accurately. In contrast, GRNN model achieved a fairly high predictability, with an R2 of 0.59 for model validation, 0.77 for model calibration (training), and a low root mean square error (RMSE), indicating a high capacity to simulate the dynamics of N2O flux. According to a sensitivity analysis of the GRNN, nonlinear relationships between input variables and N2O flux were well explained. Our results suggest that the GRNN developed in this study has a greater performance in simulating variations in N2O flux than nonlinear regressions.

Designing Predictive Models for Beta-Lactam Allergy Using the Drug Allergy and Hypersensitivity Database.

PubMed

Chiriac, Anca Mirela; Wang, Youna; Schrijvers, Rik; Bousquet, Philippe Jean; Mura, Thibault; Molinari, Nicolas; Demoly, Pascal

Beta-lactam antibiotics represent the main cause of allergic reactions to drugs, inducing both immediate and nonimmediate allergies. The diagnosis is well established, usually based on skin tests and drug provocation tests, but cumbersome. To design predictive models for the diagnosis of beta-lactam allergy, based on the clinical history of patients with suspicions of allergic reactions to beta-lactams. The study included a retrospective phase, in which records of patients explored for a suspicion of beta-lactam allergy (in the Allergy Unit of the University Hospital of Montpellier between September 1996 and September 2012) were used to construct predictive models based on a logistic regression and decision tree method; a prospective phase, in which we performed an external validation of the chosen models in patients with suspicion of beta-lactam allergy recruited from 3 allergy centers (Montpellier, Nîmes, Narbonne) between March and November 2013. Data related to clinical history and allergy evaluation results were retrieved and analyzed. The retrospective and prospective phases included 1991 and 200 patients, respectively, with a different prevalence of confirmed beta-lactam allergy (23.6% vs 31%, P = .02). For the logistic regression method, performances of the models were similar in both samples: sensitivity was 51% (vs 60%), specificity 75% (vs 80%), positive predictive value 40% (vs 57%), and negative predictive value 83% (vs 82%). The decision tree method reached a sensitivity of 29.5% (vs 43.5%), specificity of 96.4% (vs 94.9%), positive predictive value of 71.6% (vs 79.4%), and negative predictive value of 81.6% (vs 81.3%). Two different independent methods using clinical history predictors were unable to accurately predict beta-lactam allergy and replace a conventional allergy evaluation for suspected beta-lactam allergy. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Symmetries of the TDNLS equations for weakly nonlinear dispersive MHD waves

NASA Technical Reports Server (NTRS)

Webb, G. M.; Brio, M.; Zank, G. P.

1995-01-01

In this paper we consider the symmetries and conservation laws for the TDNLS equations derived by Hada (1993) and Brio, Hunter and Johnson, to describe the propagation of weakly nonlinear dispersive MHD waves in beta approximately 1 plasmas. The equations describe the interaction of the Alfven and magnetoacoustic modes near the triple umbilic, where the fast magnetosonic, slow magnetosonic and Alfven speeds coincide and a(g)(exp 2) = V(A)(exp 2) where a(g) is the gas sound speed and V(A) is the Alfven speed. We discuss Lagrangian and Hamiltonian formulations, and similarity solutions for the equations.

Application of the thermorheologically complex nonlinear Adam-Gibbs model for the glass transition to molecular motion in hydrated proteins.

PubMed

Hodge, Ian M

2006-08-01

The nonlinear thermorheologically complex Adam Gibbs (extended "Scherer-Hodge") model for the glass transition is applied to enthalpy relaxation data reported by Sartor, Mayer, and Johari for hydrated methemoglobin. A sensible range in values for the average localized activation energy is obtained (100-200 kJ mol(-1)). The standard deviation in the inferred Gaussian distribution of activation energies, computed from the reported KWW beta-parameter, is approximately 30% of the average, consistent with the suggestion that some relaxation processes in hydrated proteins have exceptionally low activation energies.

Spectral distance decay: Assessing species beta-diversity by quantile regression

USGS Publications Warehouse

Rocchinl, D.; Nagendra, H.; Ghate, R.; Cade, B.S.

2009-01-01

Remotely sensed data represents key information for characterizing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance may allow us to quantitatively estimate how beta-diversity in species changes with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological datasets are characterized by a high number of zeroes that can add noise to the regression model. Quantile regression can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this paper, we used ordinary least square (ols) and quantile regression to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p < 0.05) considering both ols and quantile regression. Nonetheless, ols regression estimate of mean decay rate was only half the decay rate indicated by the upper quantiles. Moreover, the intercept value, representing the similarity reached when spectral distance approaches zero, was very low compared with the intercepts of upper quantiles, which detected high species similarity when habitats are more similar. In this paper we demonstrated the power of using quantile regressions applied to spectral distance decay in order to reveal species diversity patterns otherwise lost or underestimated by ordinary least square regression. ?? 2009 American Society for Photogrammetry and Remote Sensing.

Three-dimensional kinetic simulations of whistler turbulence in solar wind on parallel supercomputers

NASA Astrophysics Data System (ADS)

Chang, Ouliang

The objective of this dissertation is to study the physics of whistler turbulence evolution and its role in energy transport and dissipation in the solar wind plasmas through computational and theoretical investigations. This dissertation presents the first fully three-dimensional (3D) particle-in-cell (PIC) simulations of whistler turbulence forward cascade in a homogeneous, collisionless plasma with a uniform background magnetic field B o, and the first 3D PIC simulation of whistler turbulence with both forward and inverse cascades. Such computationally demanding research is made possible through the use of massively parallel, high performance electromagnetic PIC simulations on state-of-the-art supercomputers. Simulations are carried out to study characteristic properties of whistler turbulence under variable solar wind fluctuation amplitude (epsilon e) and electron beta (betae), relative contributions to energy dissipation and electron heating in whistler turbulence from the quasilinear scenario and the intermittency scenario, and whistler turbulence preferential cascading direction and wavevector anisotropy. The 3D simulations of whistler turbulence exhibit a forward cascade of fluctuations into broadband, anisotropic, turbulent spectrum at shorter wavelengths with wavevectors preferentially quasi-perpendicular to B o. The overall electron heating yields T ∥ > T⊥ for all epsilone and betae values, indicating the primary linear wave-particle interaction is Landau damping. But linear wave-particle interactions play a minor role in shaping the wavevector spectrum, whereas nonlinear wave-wave interactions are overall stronger and faster processes, and ultimately determine the wavevector anisotropy. Simulated magnetic energy spectra as function of wavenumber show a spectral break to steeper slopes, which scales as k⊥lambda e ≃ 1 independent of betae values, where lambdae is electron inertial length, qualitatively similar to solar wind observations. Specific spectral indices from simulated wavevector energy spectra do not match the frequency spectral indices from observations due to the inapplicability of Taylor's hypothesis. In contrast, the direct comparison of simulated frequency energy spectra and solar wind observations shows a closer similarity. Electron density fluctuations power spectra also exhibit a close similarity to solar wind observations and MHD predications, both qualitatively and quantitatively. Linear damping represents an intermediate fraction of the total dissipation of whistler turbulence over a wide range of betae and epsilone. The relative importance of linear damping by comparison to nonlinear dissipation increases with increasing beta e but decreases with increasing epsilone. Correlation coefficient calculations imply that the nonlinear dissipation processes in our simulation are primarily associated with dissipation in regions of intermittent current sheet structures. The simulation results suggest that whistler fluctuations could be the substantial constituent of solar wind turbulence at higher frequencies and short wavelengths, and support the magnetosonic-whistler interpretation of the quasilinear scenario. An even larger scale 3D whistler turbulence simulation exhibits both a forward cascade to shorter wavelengths with wavevectors preferentially k⊥ > k∥, and an inverse cascade to longer wavelengths with wavevectors k ≳ k⊥. The inverse cascade process is primarily driven by the nonlinear wave-wave interaction. It is shown that the energy inverse cascade rate is similar to the energy forward cascade rate at early times although the overall energy in the two cascades is very different. The presence of inverse cascade process does not affect qualitative conclusions established from the whistler turbulence forward cascade simulations.

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

Cao, Jianjun; Shen, Dongyi; Feng, Yaming

Negative refraction has attracted much interest for its promising capability in imaging applications. Such an effect can be implemented by negative index meta-materials, however, which are usually accompanied by high loss and demanding fabrication processes. Recently, alternative nonlinear approaches like phase conjugation and four wave mixing have shown advantages of low-loss and easy-to-implement, but associated problems like narrow accepting angles can still halt their practical applications. Here, we demonstrate theoretically and experimentally a scheme to realize negative refraction by nonlinear difference frequency generation with wide tunability, where a thin Beta barium borate slice serves as a negative refraction layer bendingmore » the input signal beam to the idler beam at a negative angle. Furthermore, we realize optical focusing effect using such nonlinear negative refraction, which may enable many potential applications in imaging science.« less

Heart rate dynamics before spontaneous onset of ventricular fibrillation in patients with healed myocardial infarcts

NASA Technical Reports Server (NTRS)

Makikallio, T. H.; Koistinen, J.; Jordaens, L.; Tulppo, M. P.; Wood, N.; Golosarsky, B.; Peng, C. K.; Goldberger, A. L.; Huikuri, H. V.

1999-01-01

The traditional methods of analyzing heart rate (HR) variability have failed to predict imminent ventricular fibrillation (VF). We sought to determine whether new methods of analyzing RR interval variability based on nonlinear dynamics and fractal analysis may help to detect subtle abnormalities in RR interval behavior before the onset of life-threatening arrhythmias. RR interval dynamics were analyzed from 24-hour Holter recordings of 15 patients who experienced VF during electrocardiographic recording. Thirty patients without spontaneous or inducible arrhythmia events served as a control group in this retrospective case control study. Conventional time- and frequency-domain measurements, the short-term fractal scaling exponent (alpha) obtained by detrended fluctuation analysis, and the slope (beta) of the power-law regression line (log power - log frequency, 10(-4)-10(-2) Hz) of RR interval dynamics were determined. The short-term correlation exponent alpha of RR intervals (0.64 +/- 0.19 vs 1.05 +/- 0.12; p <0.001) and the power-law slope beta (-1.63 +/- 0.28 vs -1.31 +/- 0.20, p <0.001) were lower in the patients before the onset of VF than in the control patients, but the SD and the low-frequency spectral components of RR intervals did not differ between the groups. The short-term scaling exponent performed better than any other measurement of HR variability in differentiating between the patients with VF and controls. Altered fractal correlation properties of HR behavior precede the spontaneous onset of VF. Dynamic analysis methods of analyzing RR intervals may help to identify abnormalities in HR behavior before VF.

[Predictors of employment intention for mentally disabled persons].

PubMed

Han, Sang-Sook; Han, Jeong Hye; Yun, Eun Kyoung

2008-08-01

This study was conducted to determine the predictors of employment intention for mentally disabled persons. Mentally disabled persons who had participated in rehabilitation programs in one of 16 mental health centers and 9 community rehabilitation centers located in Seoul and Kyunggi province were recruited for this study. A random sampling method was used and 414 respondents were used for final analysis. Data was analyzed by Pearson's correlation, and stepwise multiple regression using the SPSS Win 14.0. The predictors influencing employment intention of the mentally disabled person were observed as employment desire (beta=.48), guardian's expectation (beta=.26), professional's support (beta=.23), financial management (beta=.10), eating habits (beta=.07), and quality of life (beta=-.01). Six factors explained 61.1% of employment intention of mentally disabled persons. The employment intention of a mentally disabled person was influenced by employment desire, diet self-efficacy, guardian's expectation, professional's support, quality of life, financial management and eating habits.

A regularization corrected score method for nonlinear regression models with covariate error.

PubMed

Zucker, David M; Gorfine, Malka; Li, Yi; Tadesse, Mahlet G; Spiegelman, Donna

2013-03-01

Many regression analyses involve explanatory variables that are measured with error, and failing to account for this error is well known to lead to biased point and interval estimates of the regression coefficients. We present here a new general method for adjusting for covariate error. Our method consists of an approximate version of the Stefanski-Nakamura corrected score approach, using the method of regularization to obtain an approximate solution of the relevant integral equation. We develop the theory in the setting of classical likelihood models; this setting covers, for example, linear regression, nonlinear regression, logistic regression, and Poisson regression. The method is extremely general in terms of the types of measurement error models covered, and is a functional method in the sense of not involving assumptions on the distribution of the true covariate. We discuss the theoretical properties of the method and present simulation results in the logistic regression setting (univariate and multivariate). For illustration, we apply the method to data from the Harvard Nurses' Health Study concerning the relationship between physical activity and breast cancer mortality in the period following a diagnosis of breast cancer. Copyright © 2013, The International Biometric Society.

Contribution of beta 1- and beta 2-adrenoceptors of human atrium and ventricle to the effects of noradrenaline and adrenaline as assessed with (-)-atenolol.

PubMed Central

Lemoine, H.; Schönell, H.; Kaumann, A. J.

1988-01-01

1. (-)-Atenolol was used as a tool to assess the function of beta 1- and beta 2-adrenoceptors in human heart. Right atrial and left ventricular preparations from patients undergoing open heart surgery were set up to contract isometrically. Membrane particles were prepared for beta-adrenoceptor labelling with [3H]-(-)-bupranolol and adenylate cyclase assays. 2. The positive inotropic effects of (-)-noradrenaline were antagonized to a similar extent by (-)-atenolol in atrial and ventricular preparations. (-)-Atenolol consistently antagonized the effects of (-)-adrenaline to a lesser extent than those of (-)-noradrenaline in atrial preparations. In ventricular preparations (-)-atenolol antagonized the effects of low concentrations of (-)-adrenaline to a lesser extent than those of high concentrations. 3. pKB values (M) of (-)-atenolol, estimated with non-linear analysis from the blockade of the positive inotropic effects of the catecholamines, were 7.4 for beta 1-adrenoceptors and 6.0 for beta 2-adrenoceptors. 4. (-)-Atenolol inhibited the binding of [3H]-(-)-bupranolol to ventricular beta 1-adrenoceptors with a pKD (M) of 5.9 and to ventricular beta 2-adrenoceptors with a pKD of 4.6. 5. (-)-Atenolol inhibited the catecholamine-induced adenylate cyclase stimulation in the atrium and ventricle with pKB values of 5.8-6.4 for beta 1- and pKB values of 4.7-5.7 for beta 2-adrenoceptors. The binding and cyclase assays suggest a partial affinity loss for (-)-atenolol inherent to membrane preparations. 6. beta 1-Adrenoceptors mediate the maximum positive inotropic effects of (-)-noradrenaline in both the atrium and ventricle of man. beta 2-Adrenoceptors appear to be capable of mediating maximal positive inotropic effects of (-)-adrenaline in atrium. In contrast, ventricular beta 2-adrenoceptors mediated only submaximal effects of (-)-adrenaline. PMID:2851354

An ensemble Kalman filter for statistical estimation of physics constrained nonlinear regression models

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

Harlim, John, E-mail: jharlim@psu.edu; Mahdi, Adam, E-mail: amahdi@ncsu.edu; Majda, Andrew J., E-mail: jonjon@cims.nyu.edu

2014-01-15

A central issue in contemporary science is the development of nonlinear data driven statistical–dynamical models for time series of noisy partial observations from nature or a complex model. It has been established recently that ad-hoc quadratic multi-level regression models can have finite-time blow-up of statistical solutions and/or pathological behavior of their invariant measure. Recently, a new class of physics constrained nonlinear regression models were developed to ameliorate this pathological behavior. Here a new finite ensemble Kalman filtering algorithm is developed for estimating the state, the linear and nonlinear model coefficients, the model and the observation noise covariances from available partialmore » noisy observations of the state. Several stringent tests and applications of the method are developed here. In the most complex application, the perfect model has 57 degrees of freedom involving a zonal (east–west) jet, two topographic Rossby waves, and 54 nonlinearly interacting Rossby waves; the perfect model has significant non-Gaussian statistics in the zonal jet with blocked and unblocked regimes and a non-Gaussian skewed distribution due to interaction with the other 56 modes. We only observe the zonal jet contaminated by noise and apply the ensemble filter algorithm for estimation. Numerically, we find that a three dimensional nonlinear stochastic model with one level of memory mimics the statistical effect of the other 56 modes on the zonal jet in an accurate fashion, including the skew non-Gaussian distribution and autocorrelation decay. On the other hand, a similar stochastic model with zero memory levels fails to capture the crucial non-Gaussian behavior of the zonal jet from the perfect 57-mode model.« less

Nonlinear calculation of the m=1 internal kink instability in current carrying stellarators

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

Wakatani, M.

1978-02-01

Nonlinear properties of the m=1 internal kink mode are shown in a low beta current carrying stellarator. The effects of the external helical magnetic fields are considered through a rotational transform and the magnetic surface is assumed to be circular. Magnetic surfaces inside the iota sub eta + iota sub sigma = 1 surface shift and deform non-circularly, while magnetic surfaces outside the iota sub eta + iota sub sigma = 1 are not disturbed, where iota sub eta is a rotational transform due to helical magnetic fields and iota sub sigma is due to a plasma current. Many highermore » harmonics are excited after the fundamental mode saturates. When the external helical magnetic fields are lowered, the m=1 tearing mode similar to that in a low beta Tokamak grows and magnetic islands appear near the iota sub eta + iota sub sigma = 1 surface. For adequate helical magnetic fields, the current carrying stellarator becomes stable against both the m=1 internal kink mode and the m=1 internal kink mode and the m=1 tearing mode, without lowering the rotational transform.« less

Plasma beta-endorphin levels in obese and non-obese patients with polycystic ovary disease.

PubMed

Martínez-Guisasola, J; Guerrero, M; Alonso, F; Díaz, F; Cordero, J; Ferrer, J

2001-02-01

The aim of this study was to determine the influence of body weight on circulating plasma levels of beta-endorphin and insulin in women with polycystic ovary disease (PCOD), as well as the correlation between the plasma levels of beta-endorphin and insulin. One-hundred and sixty-seven consecutive subjects with PCOD were recruited, 117 of whom had normal weight (body mass index (BMI) < 25) while 50 were obese (BMI > 25). A venous blood sample was taken and plasma concentrations of beta-endorphin, insulin, gonadotropins, prolactin, progesterone, 17 beta-estradiol, estrone, androgens, dehydroepiandrosterone sulfate and sex hormone-binding globulin (SHBG) were measured. Mean beta-endorphin and insulin plasma levels were significantly higher (p < 0.05) in obese PCOD women than in non-obese ones. Correlation analysis showed a positive association between insulin and beta-endorphin, beta-endorphin and BMI (and weight), insulin and BMI (and weight), and a negative correlation was found between insulin and SHBG. A weak association was found between beta-endorphin and luteinizing hormone (LH) in peripheral plasma. Stratified and linear regression analysis showed that plasma beta-endorphin concentrations correlate more with BMI than with insulinemia.

Nonlinear oscillator with power-form elastic-term: Fourier series expansion of the exact solution

NASA Astrophysics Data System (ADS)

Beléndez, Augusto; Francés, Jorge; Beléndez, Tarsicio; Bleda, Sergio; Pascual, Carolina; Arribas, Enrique

2015-05-01

A family of conservative, truly nonlinear, oscillators with integer or non-integer order nonlinearity is considered. These oscillators have only one odd power-form elastic-term and exact expressions for their period and solution were found in terms of Gamma functions and a cosine-Ateb function, respectively. Only for a few values of the order of nonlinearity, is it possible to obtain the periodic solution in terms of more common functions. However, for this family of conservative truly nonlinear oscillators we show in this paper that it is possible to obtain the Fourier series expansion of the exact solution, even though this exact solution is unknown. The coefficients of the Fourier series expansion of the exact solution are obtained as an integral expression in which a regularized incomplete Beta function appears. These coefficients are a function of the order of nonlinearity only and are computed numerically. One application of this technique is to compare the amplitudes for the different harmonics of the solution obtained using approximate methods with the exact ones computed numerically as shown in this paper. As an example, the approximate amplitudes obtained via a modified Ritz method are compared with the exact ones computed numerically.

The mechanical properties of high speed GTAW weld and factors of nonlinear multiple regression model under external transverse magnetic field

NASA Astrophysics Data System (ADS)

Lu, Lin; Chang, Yunlong; Li, Yingmin; He, Youyou

2013-05-01

A transverse magnetic field was introduced to the arc plasma in the process of welding stainless steel tubes by high-speed Tungsten Inert Gas Arc Welding (TIG for short) without filler wire. The influence of external magnetic field on welding quality was investigated. 9 sets of parameters were designed by the means of orthogonal experiment. The welding joint tensile strength and form factor of weld were regarded as the main standards of welding quality. A binary quadratic nonlinear regression equation was established with the conditions of magnetic induction and flow rate of Ar gas. The residual standard deviation was calculated to adjust the accuracy of regression model. The results showed that, the regression model was correct and effective in calculating the tensile strength and aspect ratio of weld. Two 3D regression models were designed respectively, and then the impact law of magnetic induction on welding quality was researched.

Nonlinear Optical Properties of Carotenoid and Chlorophyll Harmonophores

NASA Astrophysics Data System (ADS)

Tokarz, Danielle Barbara

Information regarding the structure and function of living tissues and cells is instrumental to the advancement of cell biology and biophysics. Nonlinear optical microscopy can provide such information, but only certain biological structures generate nonlinear optical signals. Therefore, structural specificity can be achieved by introducing labels for nonlinear optical microscopy. Few studies exist in the literature about labels that facilitate harmonic generation, coined "harmonophores". This thesis consists of the first major investigation of harmonophores for third harmonic generation (THG) microscopy. Carotenoids and chlorophylls were investigated as potential harmonophores. Their nonlinear optical properties were studied by the THG ratio technique. In addition, a tunable refractometer was built in order to determine their second hyperpolarizability (gamma). At 830 nm excitation wavelength, carotenoids and chlorophylls were found to have large negative gamma values however, at 1028 nm, the sign of gamma reversed for carotenoids and remained negative for chlorophylls. Consequently, at 1028 nm wavelength, THG signal is canceled with mixtures of carotenoids and chlorophylls. Furthermore, when such molecules are covalently bonded as dyads or interact within photosynthetic pigment-protein complexes, it is found that additive effects with the gamma values still play a role, however, the overall gamma value is also influenced by the intra-pigment and inter-pigment interaction. The nonlinear optical properties of aggregates containing chlorophylls and carotenoids were the target of subsequent investigations. Carotenoid aggregates were imaged with polarization-dependent second harmonic generation and THG microscopy. Both techniques revealed crystallographic information pertaining to H and J aggregates and beta-carotene crystalline aggregates found in orange carrot. In order to demonstrate THG enhancement due to labeling, cultured cells were labeled with carotenoid incorporated liposomes. In addition, Drosophila melanogaster larvae muscle as well as keratin structures in the hair cortex were labeled with beta-carotene. Polarization-dependent THG studies may be particularly useful in understanding the structural organization that occurs within biological structures containing carotenoids and chlorophylls such as photosynthetic pigment-protein complexes and carotenoid aggregates in plants and alga. Further, artificial labeling with carotenoids and chlorophylls may be useful in clinical applications since they are nontoxic, nutritionally valuable, and they can aid in visualizing structural changes in cellular components.

Elliptic Euler-Poisson-Darboux equation, critical points and integrable systems

NASA Astrophysics Data System (ADS)

Konopelchenko, B. G.; Ortenzi, G.

2013-12-01

The structure and properties of families of critical points for classes of functions W(z,{\\overline{z}}) obeying the elliptic Euler-Poisson-Darboux equation E(1/2, 1/2) are studied. General variational and differential equations governing the dependence of critical points in variational (deformation) parameters are found. Explicit examples of the corresponding integrable quasi-linear differential systems and hierarchies are presented. There are the extended dispersionless Toda/nonlinear Schrödinger hierarchies, the ‘inverse’ hierarchy and equations associated with the real-analytic Eisenstein series E(\\beta ,{\\overline{\\beta }};1/2) among them. The specific bi-Hamiltonian structure of these equations is also discussed.

Nonlinear multivariate and time series analysis by neural network methods

NASA Astrophysics Data System (ADS)

Hsieh, William W.

2004-03-01

Methods in multivariate statistical analysis are essential for working with large amounts of geophysical data, data from observational arrays, from satellites, or from numerical model output. In classical multivariate statistical analysis, there is a hierarchy of methods, starting with linear regression at the base, followed by principal component analysis (PCA) and finally canonical correlation analysis (CCA). A multivariate time series method, the singular spectrum analysis (SSA), has been a fruitful extension of the PCA technique. The common drawback of these classical methods is that only linear structures can be correctly extracted from the data. Since the late 1980s, neural network methods have become popular for performing nonlinear regression and classification. More recently, neural network methods have been extended to perform nonlinear PCA (NLPCA), nonlinear CCA (NLCCA), and nonlinear SSA (NLSSA). This paper presents a unified view of the NLPCA, NLCCA, and NLSSA techniques and their applications to various data sets of the atmosphere and the ocean (especially for the El Niño-Southern Oscillation and the stratospheric quasi-biennial oscillation). These data sets reveal that the linear methods are often too simplistic to describe real-world systems, with a tendency to scatter a single oscillatory phenomenon into numerous unphysical modes or higher harmonics, which can be largely alleviated in the new nonlinear paradigm.

Socioeconomic differences in adolescent stress: the role of psychological resources.

PubMed

Finkelstein, Daniel M; Kubzansky, Laura D; Capitman, John; Goodman, Elizabeth

2007-02-01

To investigate whether psychological resources influenced the association between parent education (PE), a marker of socioeconomic status (SES), and perceived stress. Cross-sectional analyses were conducted in a sample of 1167 non-Hispanic black and white junior and senior high school students from a Midwestern public school district in 2002-2003. Hierarchical multivariable regression analyses examined relationships between PE (high school graduate or less = E1, > high school, < college = E2, college graduate = E3, and professional degree = E4), and psychological resources (optimism and coping style) on teens' perceived stress. Greater optimism and adaptive coping were hypothesized to influence (i.e., mediate or moderate) the relationship between higher PE and lower stress. Relative to adolescents from families with a professionally educated parent, adolescents with lower parent education had higher perceived stress (E3 beta = 1.70, p < .01, E2 beta = 1.94, p < .01, E1 beta = 3.19, p < .0001). Both psychological resources were associated with stress: higher optimism (beta = -.58, p < .0001) and engagement coping (beta = -.19, p < .0001) were associated with less stress and higher disengagement coping was associated with more stress (beta = .09, p < .01). Adding optimism to the regression model attenuated the effect of SES by nearly 30%, suggesting that optimism partially mediates the inverse SES-stress relationship. Mediation was confirmed using a Sobel test (p < .01). Adolescents from families with lower parent education are less optimistic than teens from more educated families. This pessimism may be a mechanism through which lower SES increases stress in adolescence.

Beta-Zone parapapillary atrophy and the velocity of glaucoma progression.

PubMed

Teng, Christopher C; De Moraes, Carlos Gustavo V; Prata, Tiago S; Tello, Celso; Ritch, Robert; Liebmann, Jeffrey M

2010-05-01

Beta-Zone parapapillary atrophy (PPA) occurs more commonly in eyes with glaucoma. Rates of glaucomatous visual field (VF) progression in eyes with and without beta-zone PPA at the time of baseline assessment were compared. Retrospective, comparative study. Two hundred forty-five patients from the New York Glaucoma Progression Study. Subjects with glaucomatous optic neuropathy and repeatable VF loss were assessed for eligibility. Eyes with a Heidelberg Retina Tomograph II (HRT) examination, at least 5 visual field tests after the HRT in either eye, optic disc photographs, and <6 diopters of myopia were enrolled. beta-Zone PPA was defined as a region of chorioretinal atrophy with visible sclera and choroidal vessels adjacent to the optic disc. Global rates of VF progression were determined by automated pointwise linear regression analysis. Univariate analysis included age, gender, ethnicity, central corneal thickness (CCT), refractive error, baseline mean deviation, baseline intraocular pressure (IOP), mean IOP, IOP fluctuation, disc area, rim area, rim area-to-disc area ratio, beta-zone PPA area, beta-zone PPA area-to-disc area ratio, and presence or absence of beta-zone PPA. The relationship between beta-zone PPA and the rate and risk of glaucoma progression. Two hundred forty-five eyes of 245 patients (mean age, 69.6+/-12.3 years) were enrolled. The mean follow-up was 4.9+/-1.4 years and the mean number of VFs after HRT was 9.3+/-2.7. beta-Zone PPA was present in 146 eyes (65%). Eyes with beta-zone PPA progressed more rapidly (-0.84+/-0.8 dB/year) than eyes without it (-0.51+/-0.6 dB/year; P<0.01). Multivariate regression showed significant influence of mean IOP (hazard ratio [HR], 1.11; P<0.01), IOP fluctuation (HR, 1.17; P = 0.02), and presence of beta-zone PPA (HR, 2.59; P<0.01) on VF progression. Moderate (0.5-1.5 dB/year; P = 0.01) and fast (>1.5 dB/year; P = 0.08) global rates of progression occurred more commonly in eyes with beta-zone PPA than in eyes without it. Thinner CCT (<525 microm) had a weak but significant correlation with presence of beta-zone PPA (kappa = 0.13). Eyes with beta-zone PPA are at increased risk for glaucoma progression and warrant close clinical surveillance. Copyright 2010 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Nonlinear study of the parallel velocity/tearing instability using an implicit, nonlinear resistive MHD solver

NASA Astrophysics Data System (ADS)

Chacon, L.; Finn, J. M.; Knoll, D. A.

2000-10-01

Recently, a new parallel velocity instability has been found.(J. M. Finn, Phys. Plasmas), 2, 12 (1995) This mode is a tearing mode driven unstable by curvature effects and sound wave coupling in the presence of parallel velocity shear. Under such conditions, linear theory predicts that tearing instabilities will grow even in situations in which the classical tearing mode is stable. This could then be a viable seed mechanism for the neoclassical tearing mode, and hence a non-linear study is of interest. Here, the linear and non-linear stages of this instability are explored using a fully implicit, fully nonlinear 2D reduced resistive MHD code,(L. Chacon et al), ``Implicit, Jacobian-free Newton-Krylov 2D reduced resistive MHD nonlinear solver,'' submitted to J. Comput. Phys. (2000) including viscosity and particle transport effects. The nonlinear implicit time integration is performed using the Newton-Raphson iterative algorithm. Krylov iterative techniques are employed for the required algebraic matrix inversions, implemented Jacobian-free (i.e., without ever forming and storing the Jacobian matrix), and preconditioned with a ``physics-based'' preconditioner. Nonlinear results indicate that, for large total plasma beta and large parallel velocity shear, the instability results in the generation of large poloidal shear flows and large magnetic islands even in regimes when the classical tearing mode is absolutely stable. For small viscosity, the time asymptotic state can be turbulent.

Modeling the probability of giving birth at health institutions among pregnant women attending antenatal care in West Shewa Zone, Oromia, Ethiopia: a cross sectional study.

PubMed

Dida, Nagasa; Birhanu, Zewdie; Gerbaba, Mulusew; Tilahun, Dejen; Morankar, Sudhakar

2014-06-01

Although ante natal care and institutional delivery is effective means for reducing maternal morbidity and mortality, the probability of giving birth at health institutions among ante natal care attendants has not been modeled in Ethiopia. Therefore, the objective of this study was to model predictors of giving birth at health institutions among expectant mothers following antenatal care. Facility based cross sectional study design was conducted among 322 consecutively selected mothers who were following ante natal care in two districts of West Shewa Zone, Oromia Regional State, Ethiopia. Participants were proportionally recruited from six health institutions. The data were analyzed using SPSS version 17.0. Multivariable logistic regression was employed to develop the prediction model. The final regression model had good discrimination power (89.2%), optimum sensitivity (89.0%) and specificity (80.0%) to predict the probability of giving birth at health institutions. Accordingly, self efficacy (beta=0.41), perceived barrier (beta=-0.31) and perceived susceptibility (beta=0.29) were significantly predicted the probability of giving birth at health institutions. The present study showed that logistic regression model has predicted the probability of giving birth at health institutions and identified significant predictors which health care providers should take into account in promotion of institutional delivery.

Health state utility instruments compared: inquiring into nonlinearity across EQ-5D-5L, SF-6D, HUI-3 and 15D.

PubMed

Gamst-Klaussen, Thor; Chen, Gang; Lamu, Admassu N; Olsen, Jan Abel

2016-07-01

Different health state utility (HSU) instruments produce different utilities for the same individuals, thereby compromising the intended comparability of economic evaluations of health care interventions. When developing crosswalks, previous studies have indicated nonlinear relationships. This paper inquires into the degree of nonlinearity across the four most widely used HSU-instruments and proposes exchange rates that differ depending on the severity levels of the health state utility scale. Overall, 7933 respondents from six countries, 1760 in a non-diagnosed healthy group and 6173 in seven disease groups, reported their health states using four different instruments: EQ-5D-5L, SF-6D, HUI-3 and 15D. Quantile regressions investigate the degree of nonlinear relationships between these instruments. To compare the instruments across different disease severities, we split the health state utility scale into utility intervals with 0.2 successive decrements in utility starting from perfect health at 1.00. Exchange rates (ERs) are calculated as the mean utility difference between two utility intervals on one HSU-instrument divided by the difference in mean utility on another HSU-instrument. Quantile regressions reveal significant nonlinear relationships across all four HSU-instruments. The degrees of nonlinearities differ, with a maximum degree of difference in the coefficients along the health state utility scale of 3.34 when SF-6D is regressed on EQ-5D. At the lower end of the health state utility scale, the exchange rate from SF-6D to EQ-5D is 2.11, whilst at the upper end it is 0.38. Comparisons at different utility levels illustrate the fallacy of using linear functions as crosswalks between HSU-instruments. The existence of nonlinear relationships between different HSU-instruments suggests that level-specific exchange rates should be used when converting a change in utility on the instrument used, onto a corresponding utility change had another instrument been used. Accounting for nonlinearities will increase the validity of the comparison for decision makers when faced with a choice between interventions whose calculations of QALY gains have been based on different HSU-instruments.

Pentacyanoiron(II) as an electron donor group for nonlinear optics: medium-responsive properties and comparisons with related pentaammineruthenium(II) complexes.

PubMed

Coe, Benjamin J; Harries, Josephine L; Helliwell, Madeleine; Jones, Lathe A; Asselberghs, Inge; Clays, Koen; Brunschwig, Bruce S; Harris, James A; Garín, Javier; Orduna, Jesús

2006-09-20

In this article, we describe a series of complex salts in which electron-rich {Fe(II)(CN)(5)}(3)(-) centers are coordinated to pyridyl ligands with electron-accepting N-methyl/aryl-pyridinium substituents. These compounds have been characterized by using various techniques including electronic absorption spectroscopy and cyclic voltammetry. Molecular quadratic nonlinear optical (NLO) responses have been determined by using hyper-Rayleigh scattering (HRS) at 1064 nm, and also via Stark (electroabsorption) spectroscopic studies on the intense, visible d --> pi* metal-to-ligand charge-transfer (MLCT) bands. The relatively large static first hyperpolarizabilities, beta(0), increase markedly on moving from aqueous to methanol solutions, accompanied by large red-shifts in the MLCT transitions. Acidification of aqueous solutions allows reversible switching of the linear and NLO properties, as shown via both HRS and Stark experiments. Time-dependent density functional theory and finite field calculations using a polarizable continuum model yield relatively good agreement with the experimental results and confirm the large decrease in beta(0) on protonation. The Stark-derived beta(0) values are generally larger for related {Ru(II)(NH(3))(5)}(2+) complexes than for their {Fe(II)(CN)(5)}(3)(-) analogues, consistent with the HRS data in water. However, the HRS data in methanol show that the stronger solvatochromism of the Fe(II) complexes causes their NLO responses to surpass those of their Ru(II) counterparts upon changing the solvent medium.

Meta-regression analyses, meta-analyses, and trial sequential analyses of the effects of supplementation with beta-carotene, vitamin A, and vitamin E singly or in different combinations on all-cause mortality: do we have evidence for lack of harm?

PubMed

Bjelakovic, Goran; Nikolova, Dimitrinka; Gluud, Christian

2013-01-01

Evidence shows that antioxidant supplements may increase mortality. Our aims were to assess whether different doses of beta-carotene, vitamin A, and vitamin E affect mortality in primary and secondary prevention randomized clinical trials with low risk of bias. The present study is based on our 2012 Cochrane systematic review analyzing beneficial and harmful effects of antioxidant supplements in adults. Using random-effects meta-analyses, meta-regression analyses, and trial sequential analyses, we examined the association between beta-carotene, vitamin A, and vitamin E, and mortality according to their daily doses and doses below and above the recommended daily allowances (RDA). We included 53 randomized trials with low risk of bias (241,883 participants, aged 18 to 103 years, 44.6% women) assessing beta-carotene, vitamin A, and vitamin E. Meta-regression analysis showed that the dose of vitamin A was significantly positively associated with all-cause mortality. Beta-carotene in a dose above 9.6 mg significantly increased mortality (relative risk (RR) 1.06, 95% confidence interval (CI) 1.02 to 1.09, I(2) = 13%). Vitamin A in a dose above the RDA (> 800 µg) did not significantly influence mortality (RR 1.08, 95% CI 0.98 to 1.19, I(2) = 53%). Vitamin E in a dose above the RDA (> 15 mg) significantly increased mortality (RR 1.03, 95% CI 1.00 to 1.05, I(2) = 0%). Doses below the RDAs did not affect mortality, but data were sparse. Beta-carotene and vitamin E in doses higher than the RDA seem to significantly increase mortality, whereas we lack information on vitamin A. Dose of vitamin A was significantly associated with increased mortality in meta-regression. We lack information on doses below the RDA. All essential compounds to stay healthy cannot be synthesized in our body. Therefore, these compounds must be taken through our diet or obtained in other ways [1]. Oxidative stress has been suggested to cause a variety of diseases [2]. Therefore, it is speculated that antioxidant supplements could have a potential role in preventing diseases and death. Despite the fact that a normal diet in high-income countries may provide sufficient amounts of antioxidants [3,4], more than one third of adults regularly take antioxidant supplements [5,6].

Some optical properties of KTP, LiIO3, and LiNbO3

NASA Technical Reports Server (NTRS)

Gettemy, Donald J.; Harker, William C.; Lindholm, Glenn; Barnes, Norman P.

1988-01-01

Measurements of the absorption coefficient for KTP, LiIO3, and LiNbO3 are discussed. The variation of the refractive index with temperature has been measured for KTP and LiIO3. It is necessary to know both the absorption coefficient beta and the variation in the indexes of refraction with temperature change dn/dT to determine the average power limit of a nonlinear interaction. With the dn/dT information, it is also possible to estimate the temperature half width of any nonlinear interaction by calculating the variation of the phase-matching condition with temperature.

Bayesian Analysis of Nonlinear Structural Equation Models with Nonignorable Missing Data

ERIC Educational Resources Information Center

Lee, Sik-Yum

2006-01-01

A Bayesian approach is developed for analyzing nonlinear structural equation models with nonignorable missing data. The nonignorable missingness mechanism is specified by a logistic regression model. A hybrid algorithm that combines the Gibbs sampler and the Metropolis-Hastings algorithm is used to produce the joint Bayesian estimates of…

A Numerical Approach to Solving the Hall MHD Equations Including Diamagnetic Drift (Preprint)

DTIC Science & Technology

2008-02-19

SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON Dr. Jean-Luc Cambier a. REPORT...1997. [3] L. Chacon and D.A. Knoll. A 2d high-beta hall mhd implicit nonlinear solver. Journal of Computational Physics, 188:573–592, 2003. [4] Tony F

Deriving the Regression Equation without Using Calculus

ERIC Educational Resources Information Center

Gordon, Sheldon P.; Gordon, Florence S.

2004-01-01

Probably the one "new" mathematical topic that is most responsible for modernizing courses in college algebra and precalculus over the last few years is the idea of fitting a function to a set of data in the sense of a least squares fit. Whether it be simple linear regression or nonlinear regression, this topic opens the door to applying the…

On build-up of magnetic energy in the solar atmosphere

NASA Technical Reports Server (NTRS)

Nakagawa, Y.; Steinolfson, R. S.; Wu, S. T.

1976-01-01

The dynamic response of the solar atmosphere is examined with the use of self-consistent numerical solutions to the complete set of nonlinear two-dimensional hydromagnetic equations. Of particular interest are the magnetic-energy buildup and the velocity field established by emerging flux at the base of an existing magnetic loop structure in a stationary atmosphere. For a plasma with a relatively low beta (0.03), the magnetic-energy buildup is approximately twice that of the kinetic energy, while the buildup in magnetic energy first exceeds but is eventually overtaken by the kinetic energy for a plasma with an intermediate beta (3). The increased magnetic flux causes the plasma to flow upward near the loop center and downward near the loop edges for the low-beta plasma. The plasma eventually flows downward throughout the lower portion of the loop carrying the magnetic field with it for the intermediate beta plasma. It is hypothesized that this latter case, and possibly the other case as well, may provide a reasonable simulation of the disappearance of prominences by flowing down into the chromosphere (a form of disparition brusque).

Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition

EPA Science Inventory

Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base-flow conditions. Factors that affect instream biological components, based on ...

The Parkinsonian Subthalamic Network: Measures of Power, Linear, and Non-linear Synchronization and their Relationship to L-DOPA Treatment and OFF State Motor Severity.

PubMed

West, Timothy; Farmer, Simon; Berthouze, Luc; Jha, Ashwani; Beudel, Martijn; Foltynie, Thomas; Limousin, Patricia; Zrinzo, Ludvic; Brown, Peter; Litvak, Vladimir

2016-01-01

In this paper we investigated the dopaminergic modulation of neuronal interactions occurring in the subthalamic nucleus (STN) during Parkinson's disease (PD). We utilized linear measures of local and long range synchrony such as power and coherence, as well as Detrended Fluctuation Analysis for Phase Synchrony (DFA-PS)- a recently developed non-linear method that computes the extent of long tailed autocorrelations present in the phase interactions between two coupled signals. Through analysis of local field potentials (LFPs) taken from the STN we seek to determine changes in the neurodynamics that may underpin the pathophysiology of PD in a group of 12 patients who had undergone surgery for deep brain stimulation. We demonstrate up modulation of alpha-theta (5-12 Hz) band power in response to L-DOPA treatment, whilst low beta band power (15-20 Hz) band-power is suppressed. We also find evidence for significant local connectivity within the region surrounding STN although there was evidence for its modulation via administration of L-DOPA. Further to this we present evidence for a positive correlation between the phase ordering of bilateral STN interactions and the severity of bradykinetic and rigidity symptoms in PD. Although, the ability of non-linear measures to predict clinical state did not exceed standard measures such as beta power, these measures may help identify the connections which play a role in pathological dynamics.

Food insecurity and CD4% Among HIV+ children in Gaborone, Botswana.

PubMed

Mendoza, Jason A; Matshaba, Mogomotsi; Makhanda, Jeremiah; Liu, Yan; Boitshwarelo, Matshwenyego; Anabwani, Gabriel M

2014-08-01

We investigated the association between household food insecurity (HFI) and CD4% among 2-6-year old HIV+ outpatients (n = 78) at the Botswana-Baylor Children's Clinical Center of Excellence in Gaborone, Botswana. HFI was assessed by a validated survey. CD4% data were abstracted from the medical record. We used multiple linear regression with CD4% (dependent variable), HFI (independent variable), and controlled for sociodemographic and clinical covariates. Multiple linear regression showed a significant main effect for HFI [beta = -0.6, 95% confidence interval (CI): -1.0 to -0.1] and child gender (beta = 5.6, 95% CI: 1.3 to 9.8). Alleviating food insecurity may improve pediatric HIV outcomes in Botswana and similar Sub-Saharan settings.

CO2 flux determination by closed-chamber methods can be seriously biased by inappropriate application of linear regression

NASA Astrophysics Data System (ADS)

Kutzbach, L.; Schneider, J.; Sachs, T.; Giebels, M.; Nykänen, H.; Shurpali, N. J.; Martikainen, P. J.; Alm, J.; Wilmking, M.

2007-07-01

Closed (non-steady state) chambers are widely used for quantifying carbon dioxide (CO2) fluxes between soils or low-stature canopies and the atmosphere. It is well recognised that covering a soil or vegetation by a closed chamber inherently disturbs the natural CO2 fluxes by altering the concentration gradients between the soil, the vegetation and the overlying air. Thus, the driving factors of CO2 fluxes are not constant during the closed chamber experiment, and no linear increase or decrease of CO2 concentration over time within the chamber headspace can be expected. Nevertheless, linear regression has been applied for calculating CO2 fluxes in many recent, partly influential, studies. This approach was justified by keeping the closure time short and assuming the concentration change over time to be in the linear range. Here, we test if the application of linear regression is really appropriate for estimating CO2 fluxes using closed chambers over short closure times and if the application of nonlinear regression is necessary. We developed a nonlinear exponential regression model from diffusion and photosynthesis theory. This exponential model was tested with four different datasets of CO2 flux measurements (total number: 1764) conducted at three peatland sites in Finland and a tundra site in Siberia. The flux measurements were performed using transparent chambers on vegetated surfaces and opaque chambers on bare peat surfaces. Thorough analyses of residuals demonstrated that linear regression was frequently not appropriate for the determination of CO2 fluxes by closed-chamber methods, even if closure times were kept short. The developed exponential model was well suited for nonlinear regression of the concentration over time c(t) evolution in the chamber headspace and estimation of the initial CO2 fluxes at closure time for the majority of experiments. CO2 flux estimates by linear regression can be as low as 40% of the flux estimates of exponential regression for closure times of only two minutes and even lower for longer closure times. The degree of underestimation increased with increasing CO2 flux strength and is dependent on soil and vegetation conditions which can disturb not only the quantitative but also the qualitative evaluation of CO2 flux dynamics. The underestimation effect by linear regression was observed to be different for CO2 uptake and release situations which can lead to stronger bias in the daily, seasonal and annual CO2 balances than in the individual fluxes. To avoid serious bias of CO2 flux estimates based on closed chamber experiments, we suggest further tests using published datasets and recommend the use of nonlinear regression models for future closed chamber studies.

Observation of finite-. beta. MHD phenomena in tokamaks

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

McGuire, K.M.

1984-09-01

Stable high-beta plasmas are required for the tokamak to attain an economical fusion reactor. Recently, intense neutral beam heating experiments in tokamaks have shown new effects on plasma stability and confinement associated with high beta plasmas. The observed spectrum of MHD fluctuations at high beta is clearly dominated by the n = 1 mode when the q = 1 surface is in the plasma. The m/n = 1/1 mode drives other n = 1 modes through toroidal coupling and n > 1 modes through nonlinear coupling. On PDX, with near perpendicular injection, a resonant interaction between the n = 1more » internal kink and the trapped fast ions results in loss of beam particles and heating power. Key parameters in the theory are the value of q/sub 0/ and the injection angle. High frequency broadband magnetic fluctuations have been observed on ISX-B and D-III and a correlation with the deterioration of plasma confinement was reported. During enhanced confinement (H-mode) discharges in divertor plasmas, two new edge instabilities were observed, both localized radially near the separatrix. By assembling results from the different tokamak experiments, it is found that the simple theoretical ideal MHD beta limit has not been exceeded. Whether this represents an ultimate tokamak limit or if beta optimized configurations (Dee- or bean-shaped plasmas) can exceed this limit and perhaps enter a second regime of stability remains to be clarified.« less

Effect of in vitro degradation of poly(D,L-lactide)/beta-tricalcium composite on its shape-memory properties.

PubMed

Zheng, Xiaotong; Zhou, Shaobing; Yu, Xiongjun; Li, Xiaohong; Feng, Bo; Qu, Shuxin; Weng, Jie

2008-07-01

The in vitro degradation characteristic and shape-memory properties of poly(D,L-lactide) (PDLLA)/beta-tricalcium phosphate (beta-TCP) composites were investigated because of their wide application in biomedical fields. In this article, PDLLA and crystalline beta-TCP were compounded and interesting shape-memory behaviors of the composite were first investigated. Then, in vitro degradation of the PDLLA/beta-TCP composites with weight ratios of 1:1, 2:1, and 3:1 was performed in phosphate buffer saline solution (PBS) (154 mM, pH 7.4) at 37 degrees C. The effect of in vitro degradation time for PDLLA/beta-TCP composites on shape-memory properties was studied by scanning electron microscopy, differential scanning calorimetry, gel permeation chromatography, X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The changes of structural morphology, glass transition temperature (T(g)), molecular weight, and weight loss of composites matrix and pH change of degradation medium indicated that shape-memory effects at different degradation time were nonlinearly influenced because of the breaking down of polymer chain and the formation of degradation products. Furthermore, the results from XRD and FTIR implied that the degradation products, for example, hydroxyapatite (HA), calcium hydrogen phosphate (CaHPO(4)), and calcium pyrophosphate (Ca(2)P(2)O(7)) phases also had some effects on shape-memory properties during the degradation. 2007 Wiley Periodicals, Inc.

Beta-blocker use is associated with improved outcomes in adult trauma patients.

PubMed

Arbabi, Saman; Campion, Eric M; Hemmila, Mark R; Barker, Melissa; Dimo, Mary; Ahrns, Karla S; Niederbichler, Andreas D; Ipaktchi, Kyros; Wahl, Wendy L

2007-01-01

Beta-adrenoreceptor blocker (beta-blocker) therapy may improve outcomes in surgical patients by decreasing cardiac oxygen consumption and hypermetabolism. Because beta-blockers can lower the systemic blood pressure and cerebral perfusion pressure, there is concern regarding their use in patients with head injury. However, beta-blockers may protect beta-receptor rich brain cells by attenuating cerebral oxygen consumption and metabolism. We hypothesized that beta-blockers are safe in trauma patients, even if they have suffered a significant head injury. Using pharmacy and trauma registry data of a Level I trauma center, we identified a cohort of trauma patients who received beta-blockers during their hospital stay (beta-cohort). Trauma admissions who did not receive beta-blockers were in the control cohort. beta-blocker status, in combination with other variables associated with mortality, were placed in a stepwise multivariate logistic regression to identify independent predictors of fatal outcome. In all, 303 (7%) of 4,117 trauma patients received beta-blockers. In the beta-cohort, 45% of patients were on beta-blockers preinjury. The most common reason to initiate beta-blocker therapy was blood pressure (60%) and heart rate (20%) control. The overall mortality rate was 5.6% and head injury was considered to be the major cause of death. After adjusting for age, Injury Severity Scale score, blood pressure, Glasgow Coma Scale score, respiratory status, and mechanism of injury, the odds ratio for fatal outcome was 0.3 (p < 0.001) for beta-cohort as compared with control. Decreased risk of fatal outcome was more pronounced in patients with a significant head injury. beta-blocker therapy is safe and may be beneficial in selected trauma patients with or without head injury. Further studies looking at beta-blocker therapy in trauma patients and their effect on cerebral metabolism are warranted.

Comparison of Linear and Non-linear Regression Analysis to Determine Pulmonary Pressure in Hyperthyroidism.

PubMed

Scarneciu, Camelia C; Sangeorzan, Livia; Rus, Horatiu; Scarneciu, Vlad D; Varciu, Mihai S; Andreescu, Oana; Scarneciu, Ioan

2017-01-01

This study aimed at assessing the incidence of pulmonary hypertension (PH) at newly diagnosed hyperthyroid patients and at finding a simple model showing the complex functional relation between pulmonary hypertension in hyperthyroidism and the factors causing it. The 53 hyperthyroid patients (H-group) were evaluated mainly by using an echocardiographical method and compared with 35 euthyroid (E-group) and 25 healthy people (C-group). In order to identify the factors causing pulmonary hypertension the statistical method of comparing the values of arithmetical means is used. The functional relation between the two random variables (PAPs and each of the factors determining it within our research study) can be expressed by linear or non-linear function. By applying the linear regression method described by a first-degree equation the line of regression (linear model) has been determined; by applying the non-linear regression method described by a second degree equation, a parabola-type curve of regression (non-linear or polynomial model) has been determined. We made the comparison and the validation of these two models by calculating the determination coefficient (criterion 1), the comparison of residuals (criterion 2), application of AIC criterion (criterion 3) and use of F-test (criterion 4). From the H-group, 47% have pulmonary hypertension completely reversible when obtaining euthyroidism. The factors causing pulmonary hypertension were identified: previously known- level of free thyroxin, pulmonary vascular resistance, cardiac output; new factors identified in this study- pretreatment period, age, systolic blood pressure. According to the four criteria and to the clinical judgment, we consider that the polynomial model (graphically parabola- type) is better than the linear one. The better model showing the functional relation between the pulmonary hypertension in hyperthyroidism and the factors identified in this study is given by a polynomial equation of second degree where the parabola is its graphical representation.

Cutaneous beta human papillomaviruses and the development of male external genital lesions: A case-control study nested within the HIM Study.

PubMed

Pierce Campbell, Christine M; Gheit, Tarik; Tommasino, Massimo; Lin, Hui-Yi; Torres, B Nelson; Messina, Jane L; Stoler, Mark H; Rollison, Dana E; Sirak, Bradley A; Abrahamsen, Martha; Carvalho da Silva, Roberto J; Sichero, Laura; Villa, Luisa L; Lazcano-Ponce, Eduardo; Giuliano, Anna R

2016-10-01

Cutaneous human papillomaviruses (HPVs) increase the risk of non-melanoma skin cancer in sun-exposed skin. We examined the role of beta-HPV in the development of male external genital lesions (EGLs), a sun-unexposed site. In this nested case-control study (67 men with pathologically-confirmed EGLs and 134 controls), exfoliated cells collected from the surface of lesions and normal genital skin 0, 6, and 12 months preceding EGL development were tested for beta-HPV DNA using a type-specific multiplex genotyping assay. Beta-HPV prevalence was estimated and conditional logistic regression was used to evaluate the association with condyloma, the most common EGL. While beta-HPV prevalence among controls remained stable, the prevalence among cases was lowest on the surface of lesion. Detecting beta-HPV on the normal genital skin was not associated with the presence or development of condyloma. Cutaneous beta-HPV does not appear to be contributing to pathogenesis in male genital skin. Copyright © 2016. Published by Elsevier Inc.

Nonlinear Constitutive Modeling of Piezoelectric Ceramics

NASA Astrophysics Data System (ADS)

Xu, Jia; Li, Chao; Wang, Haibo; Zhu, Zhiwen

2017-12-01

Nonlinear constitutive modeling of piezoelectric ceramics is discussed in this paper. Van der Pol item is introduced to explain the simple hysteretic curve. Improved nonlinear difference items are used to interpret the hysteresis phenomena of piezoelectric ceramics. The fitting effect of the model on experimental data is proved by the partial least-square regression method. The results show that this method can describe the real curve well. The results of this paper are helpful to piezoelectric ceramics constitutive modeling.

Risk factors for low bone mineral density in children and adolescents with inflammatory bowel disease.

PubMed

Lopes, Letícia Helena Caldas; Sdepanian, Vera Lucia; Szejnfeld, Vera Lúcia; de Morais, Mauro Batista; Fagundes-Neto, Ulysses

2008-10-01

To evaluate bone mineral density of the lumbar spine in children and adolescents with inflammatory bowel disease, and to identify the clinical risk factors associated with low bone mineral density. Bone mineral density of the lumbar spine was evaluated using dual-energy X-ray absorptiometry (DXA) in 40 patients with inflammatory bowel disease. Patients were 11.8 (SD = 4.1) years old and most of them were male (52.5%). Multiple linear regression analysis was performed to identify potential associations between bone mineral density Z-score and age, height-for-age Z-score, BMI Z-score, cumulative corticosteroid dose in milligrams and in milligrams per kilogram, disease duration, number of relapses, and calcium intake according to the dietary reference intake. Low bone mineral density (Z-score bellow -2) was observed in 25% of patients. Patients with Crohn's disease and ulcerative colitis had equivalent prevalence of low bone mineral density. Multiple linear regression models demonstrated that height-for-age Z-score, BMI Z-score, and cumulative corticosteroid dose in mg had independent effects on BMD, respectively, beta = 0.492 (P = 0.000), beta = 0.460 (P = 0.001), beta = - 0.014 (P = 0.000), and these effects remained significant after adjustments for disease duration, respectively, beta = 0.489 (P = 0.013), beta = 0.467 (P = 0.001), and beta = - 0.005 (P = 0.015). The model accounted for 54.6% of the variability of the BMD Z-score (adjusted R2 = 0.546). The prevalence of low bone mineral density in children and adolescents with inflammatory bowel disease is considerably high and independent risk factors associated with bone mineral density are corticosteroid cumulative dose in milligrams, height-for-age Z-score, and BMI Z-score.

The current contribution of molecular factors to risk estimation in neuroblastoma patients.

PubMed

Berthold, F; Sahin, K; Hero, B; Christiansen, H; Gehring, M; Harms, D; Horz, S; Lampert, F; Schwab, M; Terpe, J

1997-10-01

The association of molecular characteristics with prognosis has been reported, but not their relationship with each other and their impact in the context of known clinical risk factors. In this study, data of 1249 consecutive intent-to-treat-neuroblastoma patients with more than 1 year follow-up were examined by multivariate analysis using loglinear and Cox proportional hazard regression models on a stage-related basis (stages 1-3: 600, 4S: 116, 4: 533). In a first step, risk factors were identified from 18 selected clinical variables, and risk groups defined. The second step investigated whether molecular characteristics (MYCN, LOH 1p, del 1p, CD44, N-ras, NGF-R, bcl-2, APO-1 (CD95)) contributed additional prognostic information to the model. The loglinear model demonstrated several interactions between clinical factors. By the Cox regression model, seven independent clinical risk factors were found for stages 1-3, seven for stage 4 and two for stage 4S. By subsequent introduction of all molecular variables, MYCN amplification only added significant prognostic information to the clinical factors in localised and stage 4 neuroblastoma. The models allowed the definition of risk groups for stages 1-3 patients by age (e beta = 5.09) and MYCN (e beta = 4.26), for stage 4 by MYCN (e beta = 2.78) and number of symptoms (e beta = 2.44) and for stage 4S by platelet count (e beta = 3.91) and general condition (e beta = 2.99). Molecular factors and in particular MYCN contribute significantly to risk estimation. In conjunction with clinical factors, they are powerful tools to define risk groups in neuroblastoma.

Validity of the reduced-sample insulin modified frequently-sampled intravenous glucose tolerance test using the nonlinear regression approach.

PubMed

Sumner, Anne E; Luercio, Marcella F; Frempong, Barbara A; Ricks, Madia; Sen, Sabyasachi; Kushner, Harvey; Tulloch-Reid, Marshall K

2009-02-01

The disposition index, the product of the insulin sensitivity index (S(I)) and the acute insulin response to glucose, is linked in African Americans to chromosome 11q. This link was determined with S(I) calculated with the nonlinear regression approach to the minimal model and data from the reduced-sample insulin-modified frequently-sampled intravenous glucose tolerance test (Reduced-Sample-IM-FSIGT). However, the application of the nonlinear regression approach to calculate S(I) using data from the Reduced-Sample-IM-FSIGT has been challenged as being not only inaccurate but also having a high failure rate in insulin-resistant subjects. Our goal was to determine the accuracy and failure rate of the Reduced-Sample-IM-FSIGT using the nonlinear regression approach to the minimal model. With S(I) from the Full-Sample-IM-FSIGT considered the standard and using the nonlinear regression approach to the minimal model, we compared the agreement between S(I) from the Full- and Reduced-Sample-IM-FSIGT protocols. One hundred African Americans (body mass index, 31.3 +/- 7.6 kg/m(2) [mean +/- SD]; range, 19.0-56.9 kg/m(2)) had FSIGTs. Glucose (0.3 g/kg) was given at baseline. Insulin was infused from 20 to 25 minutes (total insulin dose, 0.02 U/kg). For the Full-Sample-IM-FSIGT, S(I) was calculated based on the glucose and insulin samples taken at -1, 1, 2, 3, 4, 5, 6, 7, 8,10, 12, 14, 16, 19, 22, 23, 24, 25, 27, 30, 40, 50, 60, 70, 80, 90, 100, 120, 150, and 180 minutes. For the Reduced-Sample-FSIGT, S(I) was calculated based on the time points that appear in bold. Agreement was determined by Spearman correlation, concordance, and the Bland-Altman method. In addition, for both protocols, the population was divided into tertiles of S(I). Insulin resistance was defined by the lowest tertile of S(I) from the Full-Sample-IM-FSIGT. The distribution of subjects across tertiles was compared by rank order and kappa statistic. We found that the rate of failure of resolution of S(I) by the Reduced-Sample-IM-FSIGT was 3% (3/100). For the remaining 97 subjects, S(I) for the Full- and Reduced-Sample-IM-FSIGTs were as follows: 3.76 +/- 2.41 L mU(-1) min(-1) (range, 0.58-14.50) and 4.29 +/- 2.89 L mU(-1) min(-1) (range, 0.52-14.42); relative error, 21% +/- 18%; Spearman r = 0.97; and concordance, 0.94 (both P < .001). After log transformation, the Bland-Altman limits of agreement were -0.29 and 0.53. The exact agreement for distribution of the population in the insulin-resistant tertile vs the insulin-sensitive tertiles was 92%, kappa of 0.82 +/- 0.06. Using the nonlinear regression approach and data from the Reduced-Sample-IM-FSIGT in subjects with a wide range of insulin sensitivity, failure to resolve S(I) occurred in only 3% of subjects. The agreement and maintenance of rank order of S(I) between protocols support the use of the nonlinear regression approach to the minimal model and the Reduced-Sample-IM-FSIGT in clinical studies.

Problems with the Baade-Wesselink method

NASA Technical Reports Server (NTRS)

Bohm-Vitense, E.; Garnavich, P.; Lawler, M.; Mena-Werth, J.; Morgan, S.

1989-01-01

The discrepancy noted in radii obtained by the Baade-Wesselink method when different colors are used to determine the effective temperatures is explored. The discrepancy is found to be due to an inconsistency in the applied temperature-color calibrations. The assumption of the maximum likelihood method that beta (the effective temperature + 0.1 times the bolometric correction) is a linear function of the color is valid for the B-V and V-I colors, but not for the V-R colors. It is suggested that the errors introduced by the nonlinearity in the relation between beta and the V-R colors will produce radii which are too large. The radii derived from the V-B colors appear to be too small.

Numerical studies of electron dynamics in oblique quasi-perpendicular collisionless shock waves

NASA Technical Reports Server (NTRS)

Liewer, P. C.; Decyk, V. K.; Dawson, J. M.; Lembege, B.

1991-01-01

Linear and nonlinear electron damping of the whistler precursor wave train to low Mach number quasi-perpendicular oblique shocks is studied using a one-dimensional electromagnetic plasma simulation code with particle electrons and ions. In some parameter regimes, electrons are observed to trap along the magnetic field lines in the potential of the whistler precursor wave train. This trapping can lead to significant electron heating in front of the shock for low beta(e). Use of a 64-processor hypercube concurrent computer has enabled long runs using realistic mass ratios in the full particle in-cell code and thus simulate shock parameter regimes and phenomena not previously studied numerically.

Comparison of various error functions in predicting the optimum isotherm by linear and non-linear regression analysis for the sorption of basic red 9 by activated carbon.

PubMed

Kumar, K Vasanth; Porkodi, K; Rocha, F

2008-01-15

A comparison of linear and non-linear regression method in selecting the optimum isotherm was made to the experimental equilibrium data of basic red 9 sorption by activated carbon. The r(2) was used to select the best fit linear theoretical isotherm. In the case of non-linear regression method, six error functions namely coefficient of determination (r(2)), hybrid fractional error function (HYBRID), Marquardt's percent standard deviation (MPSD), the average relative error (ARE), sum of the errors squared (ERRSQ) and sum of the absolute errors (EABS) were used to predict the parameters involved in the two and three parameter isotherms and also to predict the optimum isotherm. Non-linear regression was found to be a better way to obtain the parameters involved in the isotherms and also the optimum isotherm. For two parameter isotherm, MPSD was found to be the best error function in minimizing the error distribution between the experimental equilibrium data and predicted isotherms. In the case of three parameter isotherm, r(2) was found to be the best error function to minimize the error distribution structure between experimental equilibrium data and theoretical isotherms. The present study showed that the size of the error function alone is not a deciding factor to choose the optimum isotherm. In addition to the size of error function, the theory behind the predicted isotherm should be verified with the help of experimental data while selecting the optimum isotherm. A coefficient of non-determination, K(2) was explained and was found to be very useful in identifying the best error function while selecting the optimum isotherm.

Waveguide structures in anisotropic nonlinear crystals

NASA Astrophysics Data System (ADS)

Li, Da; Hong, Pengda; Meissner, Helmuth E.

2017-02-01

We report on the design and manufacturing parameters of waveguiding structures of anisotropic nonlinear crystals that are employed for harmonic conversions, using Adhesive-Free Bonding (AFB®). This technology enables a full range of predetermined refractive index differences that are essential for the design of single mode or low-mode propagation with high efficiency in anisotropic nonlinear crystals which in turn results in compact frequency conversion systems. Examples of nonlinear optical waveguides include periodically bonded walk-off corrected nonlinear optical waveguides and periodically poled waveguide components, such as lithium triborate (LBO), beta barium borate (β-BBO), lithium niobate (LN), potassium titanyl phosphate (KTP), zinc germanium phosphide (ZGP) and silver selenogallate (AGSE). Simulation of planar LN waveguide shows that when the electric field vector E lies in the k-c plane, the power flow is directed precisely along the propagation direction, demonstrating waveguiding effect in the planar waveguide. Employment of anisotropic nonlinear optical waveguides, for example in combination with AFB® crystalline fiber waveguides (CFW), provides access to the design of a number of novel high power and high efficiency light sources spanning the range of wavelengths from deep ultraviolet (as short as 200 nm) to mid-infrared (as long as about 18 μm). To our knowledge, the technique is the only generally applicable one because most often there are no compatible cladding crystals available to nonlinear optical cores, especially not with an engineer-able refractive index difference and large mode area.

QSRR modeling for diverse drugs using different feature selection methods coupled with linear and nonlinear regressions.

PubMed

Goodarzi, Mohammad; Jensen, Richard; Vander Heyden, Yvan

2012-12-01

A Quantitative Structure-Retention Relationship (QSRR) is proposed to estimate the chromatographic retention of 83 diverse drugs on a Unisphere poly butadiene (PBD) column, using isocratic elutions at pH 11.7. Previous work has generated QSRR models for them using Classification And Regression Trees (CART). In this work, Ant Colony Optimization is used as a feature selection method to find the best molecular descriptors from a large pool. In addition, several other selection methods have been applied, such as Genetic Algorithms, Stepwise Regression and the Relief method, not only to evaluate Ant Colony Optimization as a feature selection method but also to investigate its ability to find the important descriptors in QSRR. Multiple Linear Regression (MLR) and Support Vector Machines (SVMs) were applied as linear and nonlinear regression methods, respectively, giving excellent correlation between the experimental, i.e. extrapolated to a mobile phase consisting of pure water, and predicted logarithms of the retention factors of the drugs (logk(w)). The overall best model was the SVM one built using descriptors selected by ACO. Copyright © 2012 Elsevier B.V. All rights reserved.

Visualizing Confidence Bands for Semiparametrically Estimated Nonlinear Relations among Latent Variables

ERIC Educational Resources Information Center

Pek, Jolynn; Chalmers, R. Philip; Kok, Bethany E.; Losardo, Diane

2015-01-01

Structural equation mixture models (SEMMs), when applied as a semiparametric model (SPM), can adequately recover potentially nonlinear latent relationships without their specification. This SPM is useful for exploratory analysis when the form of the latent regression is unknown. The purpose of this article is to help users familiar with structural…

Estimating riparian understory vegetation cover with beta regression and copula models

USGS Publications Warehouse

Eskelson, Bianca N.I.; Madsen, Lisa; Hagar, Joan C.; Temesgen, Hailemariam

2011-01-01

Understory vegetation communities are critical components of forest ecosystems. As a result, the importance of modeling understory vegetation characteristics in forested landscapes has become more apparent. Abundance measures such as shrub cover are bounded between 0 and 1, exhibit heteroscedastic error variance, and are often subject to spatial dependence. These distributional features tend to be ignored when shrub cover data are analyzed. The beta distribution has been used successfully to describe the frequency distribution of vegetation cover. Beta regression models ignoring spatial dependence (BR) and accounting for spatial dependence (BRdep) were used to estimate percent shrub cover as a function of topographic conditions and overstory vegetation structure in riparian zones in western Oregon. The BR models showed poor explanatory power (pseudo-R2 ≤ 0.34) but outperformed ordinary least-squares (OLS) and generalized least-squares (GLS) regression models with logit-transformed response in terms of mean square prediction error and absolute bias. We introduce a copula (COP) model that is based on the beta distribution and accounts for spatial dependence. A simulation study was designed to illustrate the effects of incorrectly assuming normality, equal variance, and spatial independence. It showed that BR, BRdep, and COP models provide unbiased parameter estimates, whereas OLS and GLS models result in slightly biased estimates for two of the three parameters. On the basis of the simulation study, 93–97% of the GLS, BRdep, and COP confidence intervals covered the true parameters, whereas OLS and BR only resulted in 84–88% coverage, which demonstrated the superiority of GLS, BRdep, and COP over OLS and BR models in providing standard errors for the parameter estimates in the presence of spatial dependence.

INNOVATIVE INSTRUMENTATION AND ANALYSIS OF THE TEMPERATURE MEASUREMENT FOR HIGH TEMPERATURE GASIFICATION

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

Seong W. Lee

2004-10-01

The systematic tests of the gasifier simulator on the clean thermocouple were completed in this reporting period. Within the systematic tests on the clean thermocouple, five (5) factors were considered as the experimental parameters including air flow rate, water flow rate, fine dust particle amount, ammonia addition and high/low frequency device (electric motor). The fractional factorial design method was used in the experiment design with sixteen (16) data sets of readings. Analysis of Variances (ANOVA) was applied to the results from systematic tests. The ANOVA results show that the un-balanced motor vibration frequency did not have the significant impact onmore » the temperature changes in the gasifier simulator. For the fine dust particles testing, the amount of fine dust particles has significant impact to the temperature measurements in the gasifier simulator. The effects of the air and water on the temperature measurements show the same results as reported in the previous report. The ammonia concentration was included as an experimental parameter for the reducing environment in this reporting period. The ammonia concentration does not seem to be a significant factor on the temperature changes. The linear regression analysis was applied to the temperature reading with five (5) factors. The accuracy of the linear regression is relatively low, which is less than 10% accuracy. Nonlinear regression was also conducted to the temperature reading with the same factors. Since the experiments were designed in two (2) levels, the nonlinear regression is not very effective with the dataset (16 readings). An extra central point test was conducted. With the data of the center point testing, the accuracy of the nonlinear regression is much better than the linear regression.« less

Non-Linear Relationship between Economic Growth and CO2 Emissions in China: An Empirical Study Based on Panel Smooth Transition Regression Models

PubMed Central

Wang, Zheng-Xin; Hao, Peng; Yao, Pei-Yi

2017-01-01

The non-linear relationship between provincial economic growth and carbon emissions is investigated by using panel smooth transition regression (PSTR) models. The research indicates that, on the condition of separately taking Gross Domestic Product per capita (GDPpc), energy structure (Es), and urbanisation level (Ul) as transition variables, three models all reject the null hypothesis of a linear relationship, i.e., a non-linear relationship exists. The results show that the three models all contain only one transition function but different numbers of location parameters. The model taking GDPpc as the transition variable has two location parameters, while the other two models separately considering Es and Ul as the transition variables both contain one location parameter. The three models applied in the study all favourably describe the non-linear relationship between economic growth and CO2 emissions in China. It also can be seen that the conversion rate of the influence of Ul on per capita CO2 emissions is significantly higher than those of GDPpc and Es on per capita CO2 emissions. PMID:29236083

Analysis of nonlinear relationships in dual epidemics, and its application to the management of grapevine downy and powdery mildews.

PubMed

Savary, Serge; Delbac, Lionel; Rochas, Amélie; Taisant, Guillaume; Willocquet, Laetitia

2009-08-01

Dual epidemics are defined as epidemics developing on two or several plant organs in the course of a cropping season. Agricultural pathosystems where such epidemics develop are often very important, because the harvestable part is one of the organs affected. These epidemics also are often difficult to manage, because the linkage between epidemiological components occurring on different organs is poorly understood, and because prediction of the risk toward the harvestable organs is difficult. In the case of downy mildew (DM) and powdery mildew (PM) of grapevine, nonlinear modeling and logistic regression indicated nonlinearity in the foliage-cluster relationships. Nonlinear modeling enabled the parameterization of a transmission coefficient that numerically links the two components, leaves and clusters, in DM and PM epidemics. Logistic regression analysis yielded a series of probabilistic models that enabled predicting preset levels of cluster infection risks based on DM and PM severities on the foliage at successive crop stages. The usefulness of this framework for tactical decision-making for disease control is discussed.

Non-Linear Relationship between Economic Growth and CO₂ Emissions in China: An Empirical Study Based on Panel Smooth Transition Regression Models.

PubMed

Wang, Zheng-Xin; Hao, Peng; Yao, Pei-Yi

2017-12-13

The non-linear relationship between provincial economic growth and carbon emissions is investigated by using panel smooth transition regression (PSTR) models. The research indicates that, on the condition of separately taking Gross Domestic Product per capita (GDPpc), energy structure (Es), and urbanisation level (Ul) as transition variables, three models all reject the null hypothesis of a linear relationship, i.e., a non-linear relationship exists. The results show that the three models all contain only one transition function but different numbers of location parameters. The model taking GDPpc as the transition variable has two location parameters, while the other two models separately considering Es and Ul as the transition variables both contain one location parameter. The three models applied in the study all favourably describe the non-linear relationship between economic growth and CO₂ emissions in China. It also can be seen that the conversion rate of the influence of Ul on per capita CO₂ emissions is significantly higher than those of GDPpc and Es on per capita CO₂ emissions.

DYCAST: A finite element program for the crash analysis of structures

NASA Technical Reports Server (NTRS)

Pifko, A. B.; Winter, R.; Ogilvie, P.

1987-01-01

DYCAST is a nonlinear structural dynamic finite element computer code developed for crash simulation. The element library contains stringers, beams, membrane skin triangles, plate bending triangles and spring elements. Changing stiffnesses in the structure are accounted for by plasticity and very large deflections. Material nonlinearities are accommodated by one of three options: elastic-perfectly plastic, elastic-linear hardening plastic, or elastic-nonlinear hardening plastic of the Ramberg-Osgood type. Geometric nonlinearities are handled in an updated Lagrangian formulation by reforming the structure into its deformed shape after small time increments while accumulating deformations, strains, and forces. The nonlinearities due to combined loadings are maintained, and stiffness variation due to structural failures are computed. Numerical time integrators available are fixed-step central difference, modified Adams, Newmark-beta, and Wilson-theta. The last three have a variable time step capability, which is controlled internally by a solution convergence error measure. Other features include: multiple time-load history tables to subject the structure to time dependent loading; gravity loading; initial pitch, roll, yaw, and translation of the structural model with respect to the global system; a bandwidth optimizer as a pre-processor; and deformed plots and graphics as post-processors.

Equilibrium, kinetics and process design of acid yellow 132 adsorption onto red pine sawdust.

PubMed

Can, Mustafa

2015-01-01

Linear and non-linear regression procedures have been applied to the Langmuir, Freundlich, Tempkin, Dubinin-Radushkevich, and Redlich-Peterson isotherms for adsorption of acid yellow 132 (AY132) dye onto red pine (Pinus resinosa) sawdust. The effects of parameters such as particle size, stirring rate, contact time, dye concentration, adsorption dose, pH, and temperature were investigated, and interaction was characterized by Fourier transform infrared spectroscopy and field emission scanning electron microscope. The non-linear method of the Langmuir isotherm equation was found to be the best fitting model to the equilibrium data. The maximum monolayer adsorption capacity was found as 79.5 mg/g. The calculated thermodynamic results suggested that AY132 adsorption onto red pine sawdust was an exothermic, physisorption, and spontaneous process. Kinetics was analyzed by four different kinetic equations using non-linear regression analysis. The pseudo-second-order equation provides the best fit with experimental data.

Chemokines, macrophage inflammatory protein-2 and stromal cell-derived factor-1{alpha}, suppress amyloid {beta}-induced neurotoxicity

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

Raman, Dayanidhi; Milatovic, Snjezana-Zaja; Milatovic, Dejan

2011-11-15

Alzheimer's disease (AD) is characterized by a progressive cognitive decline and accumulation of neurotoxic oligomeric peptides amyloid-{beta} (A{beta}). Although the molecular events are not entirely known, it has become evident that inflammation, environmental and other risk factors may play a causal, disruptive and/or protective role in the development of AD. The present study investigated the ability of the chemokines, macrophage inflammatory protein-2 (MIP-2) and stromal cell-derived factor-1{alpha} (SDF-1{alpha}), the respective ligands for chemokine receptors CXCR2 and CXCR4, to suppress A{beta}-induced neurotoxicity in vitro and in vivo. Pretreatment with MIP-2 or SDF-1{alpha} significantly protected neurons from A{beta}-induced dendritic regression and apoptosismore » in vitro through activation of Akt, ERK1/2 and maintenance of metalloproteinase ADAM17 especially with SDF-1{alpha}. Intra-cerebroventricular (ICV) injection of A{beta} led to reduction in dendritic length and spine density of pyramidal neurons in the CA1 area of the hippocampus and increased oxidative damage 24 h following the exposure. The A{beta}-induced morphometric changes of neurons and increase in biomarkers of oxidative damage, F{sub 2}-isoprostanes, were significantly inhibited by pretreatment with the chemokines MIP-2 or SDF-1{alpha}. Additionally, MIP-2 or SDF-1{alpha} was able to suppress the aberrant mislocalization of p21-activated kinase (PAK), one of the proteins involved in the maintenance of dendritic spines. Furthermore, MIP-2 also protected neurons against A{beta} neurotoxicity in CXCR2-/- mice, potentially through observed up regulation of CXCR1 mRNA. Understanding the neuroprotective potential of chemokines is crucial in defining the role for their employment during the early stages of neurodegeneration. -- Research highlights: Black-Right-Pointing-Pointer Neuroprotective ability of the chemokines MIP2 and CXCL12 against A{beta} toxicity. Black-Right-Pointing-Pointer MIP-2 or CXCL12 prevented dendritic regression and apoptosis in vitro. Black-Right-Pointing-Pointer Neuroprotection through activation of Akt, ERK1/2 and maintenance of ADAM17. Black-Right-Pointing-Pointer Neuroprotection of hippocampal pyramidal neurons in vivo by MIP-2 or CXCL12. Black-Right-Pointing-Pointer MIP-2 or CXCL12 prevent elevation of F2-Isoprostanes against A{beta} treatment.« less

Linkage mapping of beta 2 EEG waves via non-parametric regression.

PubMed

Ghosh, Saurabh; Begleiter, Henri; Porjesz, Bernice; Chorlian, David B; Edenberg, Howard J; Foroud, Tatiana; Goate, Alison; Reich, Theodore

2003-04-01

Parametric linkage methods for analyzing quantitative trait loci are sensitive to violations in trait distributional assumptions. Non-parametric methods are relatively more robust. In this article, we modify the non-parametric regression procedure proposed by Ghosh and Majumder [2000: Am J Hum Genet 66:1046-1061] to map Beta 2 EEG waves using genome-wide data generated in the COGA project. Significant linkage findings are obtained on chromosomes 1, 4, 5, and 15 with findings at multiple regions on chromosomes 4 and 15. We analyze the data both with and without incorporating alcoholism as a covariate. We also test for epistatic interactions between regions of the genome exhibiting significant linkage with the EEG phenotypes and find evidence of epistatic interactions between a region each on chromosome 1 and chromosome 4 with one region on chromosome 15. While regressing out the effect of alcoholism does not affect the linkage findings, the epistatic interactions become statistically insignificant. Copyright 2003 Wiley-Liss, Inc.

Thermal effects in high average power optical parametric amplifiers.

PubMed

Rothhardt, Jan; Demmler, Stefan; Hädrich, Steffen; Peschel, Thomas; Limpert, Jens; Tünnermann, Andreas

2013-03-01

Optical parametric amplifiers (OPAs) have the reputation of being average power scalable due to the instantaneous nature of the parametric process (zero quantum defect). This Letter reveals serious challenges originating from thermal load in the nonlinear crystal caused by absorption. We investigate these thermal effects in high average power OPAs based on beta barium borate. Absorption of both pump and idler waves is identified to contribute significantly to heating of the nonlinear crystal. A temperature increase of up to 148 K with respect to the environment is observed and mechanical tensile stress up to 40 MPa is found, indicating a high risk of crystal fracture under such conditions. By restricting the idler to a wavelength range far from absorption bands and removing the crystal coating we reduce the peak temperature and the resulting temperature gradient significantly. Guidelines for further power scaling of OPAs and other nonlinear devices are given.

Spatial walk-off compensated beta-barium borate stack for efficient deep-UV generation

NASA Astrophysics Data System (ADS)

Li, Da; Lee, Huai-Chuan; Meissner, Stephanie K.; Meissner, Helmuth E.

2018-02-01

Beta-Barium Borate (β-BBO) crystal is commonly used in nonlinear frequency conversion from visible to deep ultraviolet (DUV). However, in a single crystal BBO, its large spatial walk-off effect will reduce spatial overlap of ordinary and extraordinary beam, and thus degrade the conversion efficiency. To overcome the restrictions in current DUV conversion systems, Onyx applies adhesive-free bonding technique to replace the single crystal BBO with a spatial Walk-off Compensated (WOC) BBO stack, which is capable of correcting the spatial walk-off while retaining a constant nonlinear coefficient in the adjacent bonding layers. As a result, the β-BBO stack will provide good beam quality, high conversion efficiency, and broader acceptance angle and spectral linewidth, when compared with a single crystal of BBO. In this work, we report on performance of a spatial walk-off compensated β-BBO stack with adhesive-free bonding technique, for efficiently converting from the visible to DUV range. The physics behind the WOC BBO stack are demonstrated, followed by simulation of DUV conversion efficiency in an external resonance cavity. We also demonstrate experimentally the beam quality improvement in a 4-layer WOC BBO stack over a single BBO crystal.

The nonlinear light output of NaI(Tl) detectors in the Modular Total Absorption Spectrometer

DOE PAGES

Rasco, B. C.; Fijałkowska, A.; Karny, M.; ...

2015-04-08

New detector array, the Modular Total Absorption Spectrometer (MTAS),was commissioned at the Holifield Radioactive Ion Beam Facility (HRIBF) at Oak Ridge National Lab(ORNL).Total absorption gamma spectra measured with MTAS are expected to improve beta-feeding patterns and beta strength functions in fission products.MTAS is constructed out of hexagonal NaI(Tl) detectors with a unique central module surrounded by 18 identical crystals assembled in three rings. The total NaI(Tl) mass of MTAS is over1000 kg.The response of the central and other 18 MTAS modules to -radiation was simulated using the GEANT4 tool kit modified to analyze the nonlinear light output of NaI(Tl).A detailedmore » description oftheGEANT4modifications madeisdiscussed.SimulatedenergyresolutionofMTAS modules is found to agree well with the measurements for single transitions of 662keV (137Cs) with 8.2% full width half maximum (FWHM),835keV (54Mn) with FWHM of 7.5% FWHM, and 1115keV (65Zn) with FWHM of 6.5%.Simulations of single and multiple -rays from 60Co are also discussed.« less

Comparison of Sub-Pixel Classification Approaches for Crop-Specific Mapping

EPA Science Inventory

This paper examined two non-linear models, Multilayer Perceptron (MLP) regression and Regression Tree (RT), for estimating sub-pixel crop proportions using time-series MODIS-NDVI data. The sub-pixel proportions were estimated for three major crop types including corn, soybean, a...

Influence of Health Behaviors and Occupational Stress on Prediabetic State among Male Office Workers.

PubMed

Ryu, Hosihn; Moon, Jihyeon; Jung, Jiyeon

2018-06-14

This study examined the influence of health behaviors and occupational stress on the prediabetic state of male office workers, and identified related risks and influencing factors. The study used a cross-sectional design and performed an integrative analysis on data from regular health checkups, health questionnaires, and a health behavior-related survey of employees of a company, using Spearman’s correlation coefficients and multiple logistic regression analysis. The results showed significant relationships of prediabetic state with health behaviors and occupational stress. Among health behaviors, a diet without vegetables and fruits (Odds Ratio (OR) = 3.74, 95% Confidence Interval (CI) = 1.93⁻7.66) was associated with a high risk of prediabetic state. In the subscales on occupational stress, organizational system in the 4th quartile (OR = 4.83, 95% CI = 2.40⁻9.70) was significantly associated with an increased likelihood of prediabetic state. To identify influencing factors of prediabetic state, the multiple logistic regression was performed using regression models. The results showed that dietary habits (β = 1.20, p = 0.002), total occupational stress score (β = 1.33, p = 0.024), and organizational system (β = 1.13, p = 0.009) were significant influencing factors. The present findings indicate that active interventions are needed at workplace for the systematic and comprehensive management of health behaviors and occupational stress that influence prediabetic state of office workers.

CO2 flux determination by closed-chamber methods can be seriously biased by inappropriate application of linear regression

NASA Astrophysics Data System (ADS)

Kutzbach, L.; Schneider, J.; Sachs, T.; Giebels, M.; Nykänen, H.; Shurpali, N. J.; Martikainen, P. J.; Alm, J.; Wilmking, M.

2007-11-01

Closed (non-steady state) chambers are widely used for quantifying carbon dioxide (CO2) fluxes between soils or low-stature canopies and the atmosphere. It is well recognised that covering a soil or vegetation by a closed chamber inherently disturbs the natural CO2 fluxes by altering the concentration gradients between the soil, the vegetation and the overlying air. Thus, the driving factors of CO2 fluxes are not constant during the closed chamber experiment, and no linear increase or decrease of CO2 concentration over time within the chamber headspace can be expected. Nevertheless, linear regression has been applied for calculating CO2 fluxes in many recent, partly influential, studies. This approach has been justified by keeping the closure time short and assuming the concentration change over time to be in the linear range. Here, we test if the application of linear regression is really appropriate for estimating CO2 fluxes using closed chambers over short closure times and if the application of nonlinear regression is necessary. We developed a nonlinear exponential regression model from diffusion and photosynthesis theory. This exponential model was tested with four different datasets of CO2 flux measurements (total number: 1764) conducted at three peatlands sites in Finland and a tundra site in Siberia. Thorough analyses of residuals demonstrated that linear regression was frequently not appropriate for the determination of CO2 fluxes by closed-chamber methods, even if closure times were kept short. The developed exponential model was well suited for nonlinear regression of the concentration over time c(t) evolution in the chamber headspace and estimation of the initial CO2 fluxes at closure time for the majority of experiments. However, a rather large percentage of the exponential regression functions showed curvatures not consistent with the theoretical model which is considered to be caused by violations of the underlying model assumptions. Especially the effects of turbulence and pressure disturbances by the chamber deployment are suspected to have caused unexplainable curvatures. CO2 flux estimates by linear regression can be as low as 40% of the flux estimates of exponential regression for closure times of only two minutes. The degree of underestimation increased with increasing CO2 flux strength and was dependent on soil and vegetation conditions which can disturb not only the quantitative but also the qualitative evaluation of CO2 flux dynamics. The underestimation effect by linear regression was observed to be different for CO2 uptake and release situations which can lead to stronger bias in the daily, seasonal and annual CO2 balances than in the individual fluxes. To avoid serious bias of CO2 flux estimates based on closed chamber experiments, we suggest further tests using published datasets and recommend the use of nonlinear regression models for future closed chamber studies.

Socio-environmental predictors of Barmah forest virus transmission in coastal areas, Queensland, Australia.

PubMed

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S; Dale, Pat; McMichael, Anthony J; Tong, Shilu

2009-02-01

To assess the socio-environmental predictors of Barmah forest virus (BFV) transmission in coastal areas, Queensland, Australia. Data on BFV notified cases, climate, tidal levels and socioeconomic index for area (SEIFA) in six coastal cities, Queensland, for the period 1992-2001 were obtained from the relevant government agencies. Negative binomial regression models were used to assess the socio-environmental predictors of BFV transmission. The results show that maximum and minimum temperature, rainfall, relative humidity, high and low tide were statistically significantly associated with BFV incidence at lags 0-2 months. The fitted negative binomial regression models indicate a significant independent association of each of maximum temperature (beta = 0.139, P = 0.000), high tide (beta = 0.005, P = 0.000) and SEIFA index (beta = -0.010, P = 0.000) with BFV transmission after adjustment for confounding variables. The transmission of BFV disease in Queensland coastal areas seemed to be determined by a combination of local social and environmental factors. The model developed in this study may have applications in the control and prevention of BFV disease in these areas.

Applications of Support Vector Machines In Chemo And Bioinformatics

NASA Astrophysics Data System (ADS)

Jayaraman, V. K.; Sundararajan, V.

2010-10-01

Conventional linear & nonlinear tools for classification, regression & data driven modeling are being replaced on a rapid scale by newer techniques & tools based on artificial intelligence and machine learning. While the linear techniques are not applicable for inherently nonlinear problems, newer methods serve as attractive alternatives for solving real life problems. Support Vector Machine (SVM) classifiers are a set of universal feed-forward network based classification algorithms that have been formulated from statistical learning theory and structural risk minimization principle. SVM regression closely follows the classification methodology. In this work recent applications of SVM in Chemo & Bioinformatics will be described with suitable illustrative examples.

Improved spatial regression analysis of diffusion tensor imaging for lesion detection during longitudinal progression of multiple sclerosis in individual subjects

NASA Astrophysics Data System (ADS)

Liu, Bilan; Qiu, Xing; Zhu, Tong; Tian, Wei; Hu, Rui; Ekholm, Sven; Schifitto, Giovanni; Zhong, Jianhui

2016-03-01

Subject-specific longitudinal DTI study is vital for investigation of pathological changes of lesions and disease evolution. Spatial Regression Analysis of Diffusion tensor imaging (SPREAD) is a non-parametric permutation-based statistical framework that combines spatial regression and resampling techniques to achieve effective detection of localized longitudinal diffusion changes within the whole brain at individual level without a priori hypotheses. However, boundary blurring and dislocation limit its sensitivity, especially towards detecting lesions of irregular shapes. In the present study, we propose an improved SPREAD (dubbed improved SPREAD, or iSPREAD) method by incorporating a three-dimensional (3D) nonlinear anisotropic diffusion filtering method, which provides edge-preserving image smoothing through a nonlinear scale space approach. The statistical inference based on iSPREAD was evaluated and compared with the original SPREAD method using both simulated and in vivo human brain data. Results demonstrated that the sensitivity and accuracy of the SPREAD method has been improved substantially by adapting nonlinear anisotropic filtering. iSPREAD identifies subject-specific longitudinal changes in the brain with improved sensitivity, accuracy, and enhanced statistical power, especially when the spatial correlation is heterogeneous among neighboring image pixels in DTI.

A Bayesian Approach for Evaluation of Determinants of Health System Efficiency Using Stochastic Frontier Analysis and Beta Regression.

PubMed

Şenel, Talat; Cengiz, Mehmet Ali

2016-01-01

In today's world, Public expenditures on health are one of the most important issues for governments. These increased expenditures are putting pressure on public budgets. Therefore, health policy makers have focused on the performance of their health systems and many countries have introduced reforms to improve the performance of their health systems. This study investigates the most important determinants of healthcare efficiency for OECD countries using second stage approach for Bayesian Stochastic Frontier Analysis (BSFA). There are two steps in this study. First we measure 29 OECD countries' healthcare efficiency by BSFA using the data from the OECD Health Database. At second stage, we expose the multiple relationships between the healthcare efficiency and characteristics of healthcare systems across OECD countries using Bayesian beta regression.

Beta-Adrenergic Modulation of Tremor and Corticomuscular Coherence in Humans

PubMed Central

Baker, Mark R.; Baker, Stuart N.

2012-01-01

Coherence between the bioelectric activity of sensorimotor cortex and contralateral muscles can be observed around 20 Hz. By contrast, physiological tremor has a dominant frequency around 10 Hz. Although tremor has multiple sources, it is partly central in origin, reflecting a component of motoneuron discharge at this frequency. The motoneuron response to ∼20 Hz descending input could be altered by non-linear interactions with ∼10 Hz motoneuron firing. We investigated this further in eight healthy human subjects by testing the effects of the beta-adrenergic agents propranolol (non-selective β-antagonist) and salbutamol (β2-agonist), which are known to alter the size of physiological tremor. Corticomuscular coherence was assessed during an auxotonic precision grip task; tremor was quantified using accelerometry during index finger extension. Experiments with propranolol used a double-blind, placebo-controlled crossover design. A single oral dose of propranolol (40 mg) significantly increased beta band (15.3–32.2 Hz) corticomuscular coherence compared with placebo, but reduced tremor in the 6.2–11.9 Hz range. Salbutamol (2.5 mg) was administered by inhalation. Whilst salbutamol significantly increased tremor amplitude as expected, it did not change corticomuscular coherence. The opposite direction of the effects of propranolol on corticomuscular coherence and tremor, and the fact that salbutamol enhances tremor but does not affect coherence, implies that the magnitude of corticomuscular coherence is little influenced by non-linear interactions with 10 Hz oscillations in motoneurons or the periphery. Instead, we suggest that propranolol and salbutamol may affect both tremor and corticomuscular coherence partly via a central site of action. PMID:23185297

Influences on Academic Achievement Across High and Low Income Countries: A Re-Analysis of IEA Data.

ERIC Educational Resources Information Center

Heyneman, S.; Loxley, W.

Previous international studies of science achievement put the data through a process of winnowing to decide which variables to keep in the final regressions. Variables were allowed to enter the final regressions if they met a minimum beta coefficient criterion of 0.05 averaged across rich and poor countries alike. The criterion was an average…

Inverse models: A necessary next step in ground-water modeling

USGS Publications Warehouse

Poeter, E.P.; Hill, M.C.

1997-01-01

Inverse models using, for example, nonlinear least-squares regression, provide capabilities that help modelers take full advantage of the insight available from ground-water models. However, lack of information about the requirements and benefits of inverse models is an obstacle to their widespread use. This paper presents a simple ground-water flow problem to illustrate the requirements and benefits of the nonlinear least-squares repression method of inverse modeling and discusses how these attributes apply to field problems. The benefits of inverse modeling include: (1) expedited determination of best fit parameter values; (2) quantification of the (a) quality of calibration, (b) data shortcomings and needs, and (c) confidence limits on parameter estimates and predictions; and (3) identification of issues that are easily overlooked during nonautomated calibration.Inverse models using, for example, nonlinear least-squares regression, provide capabilities that help modelers take full advantage of the insight available from ground-water models. However, lack of information about the requirements and benefits of inverse models is an obstacle to their widespread use. This paper presents a simple ground-water flow problem to illustrate the requirements and benefits of the nonlinear least-squares regression method of inverse modeling and discusses how these attributes apply to field problems. The benefits of inverse modeling include: (1) expedited determination of best fit parameter values; (2) quantification of the (a) quality of calibration, (b) data shortcomings and needs, and (c) confidence limits on parameter estimates and predictions; and (3) identification of issues that are easily overlooked during nonautomated calibration.

A non-linear theory of the parallel firehose and gyrothermal instabilities in a weakly collisional plasma

NASA Astrophysics Data System (ADS)

Rosin, M. S.; Schekochihin, A. A.; Rincon, F.; Cowley, S. C.

2011-05-01

Weakly collisional magnetized cosmic plasmas have a dynamical tendency to develop pressure anisotropies with respect to the local direction of the magnetic field. These anisotropies trigger plasma instabilities at scales just above the ion Larmor radius ρi and much below the mean free path λmfp. They have growth rates of a fraction of the ion cyclotron frequency, which is much faster than either the global dynamics or even local turbulence. Despite their microscopic nature, these instabilities dramatically modify the transport properties and, therefore, the macroscopic dynamics of the plasma. The non-linear evolution of these instabilities is expected to drive pressure anisotropies towards marginal stability values, controlled by the plasma beta βi. Here this non-linear evolution is worked out in an ab initio kinetic calculation for the simplest analytically tractable example - the parallel (k⊥= 0) firehose instability in a high-beta plasma. An asymptotic theory is constructed, based on a particular physical ordering and leading to a closed non-linear equation for the firehose turbulence. In the non-linear regime, both the analytical theory and the numerical solution predict secular (∝t) growth of magnetic fluctuations. The fluctuations develop a k-3∥ spectrum, extending from scales somewhat larger than ρi to the maximum scale that grows secularly with time (∝t1/2); the relative pressure anisotropy (p⊥-p∥)/p∥ tends to the marginal value -2/βi. The marginal state is achieved via changes in the magnetic field, not particle scattering. When a parallel ion heat flux is present, the parallel firehose mutates into the new gyrothermal instability (GTI), which continues to exist up to firehose-stable values of pressure anisotropy, which can be positive and are limited by the magnitude of the ion heat flux. The non-linear evolution of the GTI also features secular growth of magnetic fluctuations, but the fluctuation spectrum is eventually dominated by modes around a maximal scale ˜ρilT/λmfp, where lT is the scale of the parallel temperature variation. Implications for momentum and heat transport are speculated about. This study is motivated by our interest in the dynamics of galaxy cluster plasmas (which are used as the main astrophysical example), but its relevance to solar wind and accretion flow plasmas is also briefly discussed.

Prediction of Battery Life and Behavior from Analysis of Voltage Data

NASA Technical Reports Server (NTRS)

Mcdermott, P. P.

1984-01-01

A method for simulating charge and discharge characteristics of secondary batteries is discussed. The analysis utilizes a nonlinear regression technique where empirical data is computer fitted with a five coefficient nonlinear equation. The equations for charge and discharge voltage are identical except for a change of sign before the second and third terms.

A Comparative Investigation of the Combined Effects of Pre-Processing, Wavelength Selection, and Regression Methods on Near-Infrared Calibration Model Performance.

PubMed

Wan, Jian; Chen, Yi-Chieh; Morris, A Julian; Thennadil, Suresh N

2017-07-01

Near-infrared (NIR) spectroscopy is being widely used in various fields ranging from pharmaceutics to the food industry for analyzing chemical and physical properties of the substances concerned. Its advantages over other analytical techniques include available physical interpretation of spectral data, nondestructive nature and high speed of measurements, and little or no need for sample preparation. The successful application of NIR spectroscopy relies on three main aspects: pre-processing of spectral data to eliminate nonlinear variations due to temperature, light scattering effects and many others, selection of those wavelengths that contribute useful information, and identification of suitable calibration models using linear/nonlinear regression . Several methods have been developed for each of these three aspects and many comparative studies of different methods exist for an individual aspect or some combinations. However, there is still a lack of comparative studies for the interactions among these three aspects, which can shed light on what role each aspect plays in the calibration and how to combine various methods of each aspect together to obtain the best calibration model. This paper aims to provide such a comparative study based on four benchmark data sets using three typical pre-processing methods, namely, orthogonal signal correction (OSC), extended multiplicative signal correction (EMSC) and optical path-length estimation and correction (OPLEC); two existing wavelength selection methods, namely, stepwise forward selection (SFS) and genetic algorithm optimization combined with partial least squares regression for spectral data (GAPLSSP); four popular regression methods, namely, partial least squares (PLS), least absolute shrinkage and selection operator (LASSO), least squares support vector machine (LS-SVM), and Gaussian process regression (GPR). The comparative study indicates that, in general, pre-processing of spectral data can play a significant role in the calibration while wavelength selection plays a marginal role and the combination of certain pre-processing, wavelength selection, and nonlinear regression methods can achieve superior performance over traditional linear regression-based calibration.

Rapid decay of nonlinear whistler waves in two dimensions: Full particle simulation

NASA Astrophysics Data System (ADS)

Umeda, Takayuki; Saito, Shinji; Nariyuki, Yasuhiro

2017-05-01

The decay of a nonlinear, short-wavelength, and monochromatic electromagnetic whistler wave is investigated by utilizing a two-dimensional (2D) fully relativistic electromagnetic particle-in-cell code. The simulation is performed under a low-beta condition in which the plasma pressure is much lower than the magnetic pressure. It has been shown that the nonlinear (large-amplitude) parent whistler wave decays through the parametric instability in a one-dimensional (1D) system. The present study shows that there is another channel for the decay of the parent whistler wave in 2D, which is much faster than in the timescale of the parametric decay in 1D. The parent whistler wave decays into two sideband daughter whistlers propagating obliquely with respect to the ambient magnetic field with a frequency close to the parent wave and two quasi-perpendicular electromagnetic modes with a frequency close to zero via a 2D decay instability. The two sideband daughter oblique whistlers also enhance a nonlinear longitudinal electrostatic wave via a three-wave interaction as a secondary process.

Quantifying Mold Biomass on Gypsum Board: Comparison of Ergosterol and Beta-N-Acetylhexosaminidase as Mold Biomass Parameters

PubMed Central

Reeslev, M.; Miller, M.; Nielsen, K. F.

2003-01-01

Two mold species, Stachybotrys chartarum and Aspergillus versicolor, were inoculated onto agar overlaid with cellophane, allowing determination of a direct measurement of biomass density by weighing. Biomass density, ergosterol content, and beta-N-acetylhexosaminidase (3.2.1.52) activity were monitored from inoculation to stationary phase. Regression analysis showed a good linear correlation to biomass density for both ergosterol content and beta-N-acetylhexosaminidase activity. The same two mold species were inoculated onto wallpapered gypsum board, from which a direct biomass measurement was not possible. Growth was measured as an increase in ergosterol content and beta-N-acetylhexosaminidase activity. A good linear correlation was seen between ergosterol content and beta-N-acetylhexosaminidase activity. From the experiments performed on agar medium, conversion factors (CFs) for estimating biomass density from ergosterol content and beta-N-acetylhexosaminidase activity were determined. The CFs were used to estimate the biomass density of the molds grown on gypsum board. The biomass densities estimated from ergosterol content and beta-N-acetylhexosaminidase activity data gave similar results, showing significantly slower growth and lower stationary-phase biomass density on gypsum board than on agar. PMID:12839773

[Recent advances in the treatment of type 1 diabetes mellitus].

PubMed

Schloot, N C; Roden, M; Bornstein, S R; Brendel, M D

2011-02-01

INTERVENTIONAL APPROACHES TO BETA CELL PRESERVATION: In a pilot study, initial attempts at primary prevention by preserving islet beta cells have been successful with highly hydrolyzed milk formula in children who are at high genetic risk of diabetes. Attempts at secondary prevention by intranasal application in children with a high-risk HLA genotype and positive islet autoantibodies have been disappointing. But in tertiary prevention anti-inflammatory, antigen-directed and T-cell targeted treatment has been partially successful in slowing down the destruction of beta cells. BIOLOGICAL BETA CELL SUBSTITUTION: Transplantation of a vascularised pancreas or islet cells results in disease regression and the prevention of secondary/tertiary complications of diabetes. A principal aim is the avoidance of frequent, severe hypoglycaemic episodes resulting from markedly reduced awareness of hypoglycaemia or its counter-regulation. © Georg Thieme Verlag KG Stuttgart · New York.

Stable Spheromaks Sustained by Neutral Beam Injection

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

Fowler, T K; Jayakumar, R; McLean, H S

It is shown that spheromak equilibria, stable at zero-beta but departing from the Taylor state, could be sustained by non-inductive current drive at acceptable power levels. Stability to both ideal MHD and tearing modes is verified using the NIMROD code for linear stability analysis. Non-linear NIMROD calculations with non-inductive current drive and pressure effects could point the way to improved fusion reactors.

Linear and nonlinear mechanical properties of a series of epoxy resins

NASA Technical Reports Server (NTRS)

Curliss, D. B.; Caruthers, J. M.

1987-01-01

The linear viscoelastic properties have been measured for a series of bisphenol-A-based epoxy resins cured with the diamine DDS. The linear viscoelastic master curves were constructed via time-temperature superposition of frequency dependent G-prime and G-double-prime isotherms. The G-double-prime master curves exhibited two sub-Tg transitions. Superposition of isotherms in the glass-to-rubber transition (i.e., alpha) and the beta transition at -60 C was achieved by simple horizontal shifts in the log frequency axis; however, in the region between alpha and beta, superposition could not be effected by simple horizontal shifts along the log frequency axis. The different temperature dependency of the alpha and beta relaxation mechanisms causes a complex response of G-double-prime in the so called alpha-prime region. A novel numerical procedure has been developed to extract the complete relaxation spectra and its temperature dependence from the G-prime and G-double-prime isothermal data in the alpha-prime region.

Rational enhancement of second-order nonlinearity: bis-(4-methoxyphenyl)hetero-aryl-amino donor-based chromophores: design, synthesis, and electrooptic activity.

PubMed

Davies, Joshua A; Elangovan, Arumugasamy; Sullivan, Philip A; Olbricht, Benjamin C; Bale, Denise H; Ewy, Todd R; Isborn, Christine M; Eichinger, Bruce E; Robinson, Bruce H; Reid, Philip J; Li, Xiaosong; Dalton, Larry R

2008-08-13

Two new highly hyperpolarizable chromophores, based on N,N- bis-(4-methoxyphenyl) aryl-amino donors and phenyl-trifluoromethyl-tricyanofuran (CF3-Ph-TCF) acceptor linked together via pi-conjugation through 2,5-divinylenethienyl moieties as the bridge, have been designed and synthesized successfully for the first time. The aryl moieties on the donor side of the chromophore molecules were varied as to be thiophene and 1-n-hexylpyrrole. The linear and nonlinear optical (NLO) properties of all compounds were evaluated in addition to recording relevant thermal and electrochemical data. The properties of the two new molecules were comparatively studied. These results are critically analyzed along with two other compounds, reported earlier from our laboratories and our collaborator's, that contain (i) aliphatic chain-bearing aniline and (ii) dianisylaniline as donors, keeping the bridge (2,5-divinylenethienyl-), and the acceptor (CF3-Ph-TCF), constant. Trends in theoretically (density functional theory, DFT) predicted, zero-frequency gas-phase hyperpolarizability [beta(0;0,0)] values are shown to be consistent with the trends in beta HRS(-2omega;omega,omega), as measured by Hyper-Rayleigh Scattering (HRS), when corrected to zero-frequency using the two-level model (TLM) approximation. Similarly, trends in poling efficiency data (r33/E(p)) and wavelength dispersion measured by reflection ellipsometry (using a Teng-Man apparatus) and attenuated total reflection (ATR) are found to fit the TLM and DFT predictions. A 3-fold enhancement in bulk nonlinearity (r33) is realized as the donor subunits are changed from alkylaniline to dianisylaminopyrrole donors. The results of these studies provide insight into the complicated effects on molecular hyperpolarizability of substituting heteroaromatic subunits into the donor group structures. These studies also demonstrate that, when frequency dependence and electric-field-induced ordering behavior are correctly accounted for, ab initio DFT generated beta(0;0,0) is effective as a predictor of changes in r33 behavior based on chromophore structure modification. Thus DFT can provide valuable insight into the electronic structure origin of complex optical phenomena in organic media.

Polarizabilites and Rydberg States in the Presence of a Debye Potential

NASA Technical Reports Server (NTRS)

Bhatia, A. K.; Drachman, Richard J.

2010-01-01

Polarizabilities and hyperpolarizabilities, alpha(1), beta(1),gamma(1), alpha(2), beta(2),gamma(2), alpha(3), beta(3),gamma(3), delta and epsilon of hydrogenic systems have been calculated by Drachman. We have now calculated these quantities by using pseudostates for the S. P. D and F states. All of them converge very fast as the number of terms in the pseudostates is increased, and are essentially independent of the nonlinear parameters. All the results are in good agreement with the results obtained by Drachman. except for delta, which is of the third-order in perturbation formalism. We have calculated Rydberg states of He for high N and L. The effective potential is -alpha(sub 1)/x(exp 4)+{6 * Beta(sub 1) -alpha(sub 2)/x(exp6), where x is the distance of the outer electron from the nucleus. The exchange and electron-electron correlations are unimportant because the outer electron is far away from the nucleus. This implies that the conventional variational calculations are not necessary. The results agree well with the results of Drachman. We have generalized this approach in the presence of a Debye potential.

Combined genetic algorithm and multiple linear regression (GA-MLR) optimizer: Application to multi-exponential fluorescence decay surface.

PubMed

Fisz, Jacek J

2006-12-07

The optimization approach based on the genetic algorithm (GA) combined with multiple linear regression (MLR) method, is discussed. The GA-MLR optimizer is designed for the nonlinear least-squares problems in which the model functions are linear combinations of nonlinear functions. GA optimizes the nonlinear parameters, and the linear parameters are calculated from MLR. GA-MLR is an intuitive optimization approach and it exploits all advantages of the genetic algorithm technique. This optimization method results from an appropriate combination of two well-known optimization methods. The MLR method is embedded in the GA optimizer and linear and nonlinear model parameters are optimized in parallel. The MLR method is the only one strictly mathematical "tool" involved in GA-MLR. The GA-MLR approach simplifies and accelerates considerably the optimization process because the linear parameters are not the fitted ones. Its properties are exemplified by the analysis of the kinetic biexponential fluorescence decay surface corresponding to a two-excited-state interconversion process. A short discussion of the variable projection (VP) algorithm, designed for the same class of the optimization problems, is presented. VP is a very advanced mathematical formalism that involves the methods of nonlinear functionals, algebra of linear projectors, and the formalism of Fréchet derivatives and pseudo-inverses. Additional explanatory comments are added on the application of recently introduced the GA-NR optimizer to simultaneous recovery of linear and weakly nonlinear parameters occurring in the same optimization problem together with nonlinear parameters. The GA-NR optimizer combines the GA method with the NR method, in which the minimum-value condition for the quadratic approximation to chi(2), obtained from the Taylor series expansion of chi(2), is recovered by means of the Newton-Raphson algorithm. The application of the GA-NR optimizer to model functions which are multi-linear combinations of nonlinear functions, is indicated. The VP algorithm does not distinguish the weakly nonlinear parameters from the nonlinear ones and it does not apply to the model functions which are multi-linear combinations of nonlinear functions.

Saturated fat consumption and the Theory of Planned Behaviour: exploring additive and interactive effects of habit strength.

PubMed

de Bruijn, Gert-Jan; Kroeze, Willemieke; Oenema, Anke; Brug, Johannes

2008-09-01

The additive and interactive effects of habit strength in the explanation of saturated fat intake were explored within the framework of the Theory of Planned Behaviour (TPB). Cross-sectional data were gathered in a Dutch adult sample (n=764) using self-administered questionnaires and analyzed using hierarchical regression analyses and simple slope analyses. Results showed that habit strength was a significant correlate of fat intake (beta=-0.11) and significantly increased the amount of explained variance in fat intake (R(2-change)=0.01). Furthermore, based on a significant interaction effect (beta=0.11), simple slope analyses revealed that intention was a significant correlate of fat intake for low levels (beta=-0.29) and medium levels (beta=-0.19) of habit strength, but a weaker and non-significant correlate for high levels (beta=-0.07) of habit strength. Higher habit strength may thus make limiting fat intake a non-intentional behaviour. Implications for information and motivation-based interventions are discussed.

Protection from sunburn with beta-Carotene--a meta-analysis.

PubMed

Köpcke, Wolfgang; Krutmann, Jean

2008-01-01

Nutritional protection against skin damage from sunlight is increasingly advocated to the general public, but its effectiveness is controversial. In this meta-analysis, we have systematically reviewed the existing literature on human supplementation studies on dietary protection against sunburn by beta-carotene. A review of literature until June 2007 was performed in PubMed, ISI Web of Science and EBM Cochrane library and identified a total of seven studies which evaluated the effectiveness of beta-carotene in protection against sunburn. Data were abstracted from these studies by means of a standardized data collection protocol. The subsequent meta-analysis showed that (1) beta-carotene supplementation protects against sunburn and (2) the study duration had a significant influence on the effected size. Regression plot analysis revealed that protection required a minimum of 10 weeks of supplementation with a mean increase of the protective effect of 0.5 standard deviations with every additional month of supplementation. Thus, dietary supplementation of humans with beta-carotene provides protection against sunburn in a time-dependent manner.

Modeling the survival of Salmonella spp. in chorizos.

PubMed

Hajmeer, M; Basheer, I; Hew, C; Cliver, D O

2006-03-01

The survival of Salmonella spp. in chorizos has been studied under the effect of storage conditions; namely temperature (T=6, 25, 30 degrees C), air inflow velocity (F=0, 28.4 m/min), and initial water activity (a(w0)=0.85, 0.90, 0.93, 0.95, 0.97). The pH was held at 5.0. A total of 20 survival curves were experimentally obtained at various combinations of operating conditions. The chorizos were stored under four conditions: in the refrigerator (Ref: T=6 degrees C, F=0 m/min), at room temperature (RT: T=25 degrees C, F=0 m/min), in the hood (Hd: T=25 degrees C, F=28.4 m/min), and in the incubator (Inc: T=30 degrees C, F=0 m/min). Semi-logarithmic plots of counts vs. time revealed nonlinear trends for all the survival curves, indicating that the first-order kinetics model (exponential distribution function) was not suitable. The Weibull cumulative distribution function, for which the exponential function is only a special case, was selected and used to model the survival curves. The Weibull model was fitted to the 20 curves and the model parameters (alpha and beta) were determined. The fitted survival curves agreed with the experimental data with R(2)=0.951, 0.969, 0.908, and 0.871 for the Ref, RT, Hd, and Inc curves, respectively. Regression models relating alpha and beta to T, F, and a(w0) resulted in R(2) values of 0.975 for alpha and 0.988 for beta. The alpha and beta models can be used to generate a survival curve for Salmonella in chorizos for a given set of operating conditions. Additionally, alpha and beta can be used to determine the times needed to reduce the count by 1 or 2 logs t(1D) and t(2D). It is concluded that the Weibull cumulative distribution function offers a powerful model for describing microbial survival data. A comparison with the pathogen modeling program (PMP) revealed that the survival kinetics of Salmonella spp. in chorizos could not be adequately predicted using PMP which underestimated the t(1D) and t(2D). The mean of the Weibull probability density function correlated strongly with t(1D) and t(2D), and can serve as an alternative to the D-values normally used with first-order kinetic models. Parametric studies were conducted and sensitivity of survival to operating conditions was evaluated and discussed in the paper. The models derived herein provide a means for the development of a reliable risk assessment system for controlling Salmonella spp. in chorizos.

Linear and nonlinear regression techniques for simultaneous and proportional myoelectric control.

PubMed

Hahne, J M; Biessmann, F; Jiang, N; Rehbaum, H; Farina, D; Meinecke, F C; Muller, K-R; Parra, L C

2014-03-01

In recent years the number of active controllable joints in electrically powered hand-prostheses has increased significantly. However, the control strategies for these devices in current clinical use are inadequate as they require separate and sequential control of each degree-of-freedom (DoF). In this study we systematically compare linear and nonlinear regression techniques for an independent, simultaneous and proportional myoelectric control of wrist movements with two DoF. These techniques include linear regression, mixture of linear experts (ME), multilayer-perceptron, and kernel ridge regression (KRR). They are investigated offline with electro-myographic signals acquired from ten able-bodied subjects and one person with congenital upper limb deficiency. The control accuracy is reported as a function of the number of electrodes and the amount and diversity of training data providing guidance for the requirements in clinical practice. The results showed that KRR, a nonparametric statistical learning method, outperformed the other methods. However, simple transformations in the feature space could linearize the problem, so that linear models could achieve similar performance as KRR at much lower computational costs. Especially ME, a physiologically inspired extension of linear regression represents a promising candidate for the next generation of prosthetic devices.

The Effect of Multicollinearity and the Violation of the Assumption of Normality on the Testing of Hypotheses in Regression Analysis.

ERIC Educational Resources Information Center

Vasu, Ellen S.; Elmore, Patricia B.

The effects of the violation of the assumption of normality coupled with the condition of multicollinearity upon the outcome of testing the hypothesis Beta equals zero in the two-predictor regression equation is investigated. A monte carlo approach was utilized in which three differenct distributions were sampled for two sample sizes over…

Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 2. Applications

USGS Publications Warehouse

Cooley, Richard L.

1983-01-01

This paper investigates factors influencing the degree of improvement in estimates of parameters of a nonlinear regression groundwater flow model by incorporating prior information of unknown reliability. Consideration of expected behavior of the regression solutions and results of a hypothetical modeling problem lead to several general conclusions. First, if the parameters are properly scaled, linearized expressions for the mean square error (MSE) in parameter estimates of a nonlinear model will often behave very nearly as if the model were linear. Second, by using prior information, the MSE in properly scaled parameters can be reduced greatly over the MSE of ordinary least squares estimates of parameters. Third, plots of estimated MSE and the estimated standard deviation of MSE versus an auxiliary parameter (the ridge parameter) specifying the degree of influence of the prior information on regression results can help determine the potential for improvement of parameter estimates. Fourth, proposed criteria can be used to make appropriate choices for the ridge parameter and another parameter expressing degree of overall bias in the prior information. Results of a case study of Truckee Meadows, Reno-Sparks area, Washoe County, Nevada, conform closely to the results of the hypothetical problem. In the Truckee Meadows case, incorporation of prior information did not greatly change the parameter estimates from those obtained by ordinary least squares. However, the analysis showed that both sets of estimates are more reliable than suggested by the standard errors from ordinary least squares.

The 11-year solar cycle in current reanalyses: a (non)linear attribution study of the middle atmosphere

NASA Astrophysics Data System (ADS)

Kuchar, A.; Sacha, P.; Miksovsky, J.; Pisoft, P.

2015-06-01

This study focusses on the variability of temperature, ozone and circulation characteristics in the stratosphere and lower mesosphere with regard to the influence of the 11-year solar cycle. It is based on attribution analysis using multiple nonlinear techniques (support vector regression, neural networks) besides the multiple linear regression approach. The analysis was applied to several current reanalysis data sets for the 1979-2013 period, including MERRA, ERA-Interim and JRA-55, with the aim to compare how these types of data resolve especially the double-peaked solar response in temperature and ozone variables and the consequent changes induced by these anomalies. Equatorial temperature signals in the tropical stratosphere were found to be in qualitative agreement with previous attribution studies, although the agreement with observational results was incomplete, especially for JRA-55. The analysis also pointed to the solar signal in the ozone data sets (i.e. MERRA and ERA-Interim) not being consistent with the observed double-peaked ozone anomaly extracted from satellite measurements. The results obtained by linear regression were confirmed by the nonlinear approach through all data sets, suggesting that linear regression is a relevant tool to sufficiently resolve the solar signal in the middle atmosphere. The seasonal evolution of the solar response was also discussed in terms of dynamical causalities in the winter hemispheres. The hypothetical mechanism of a weaker Brewer-Dobson circulation at solar maxima was reviewed together with a discussion of polar vortex behaviour.

Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.

PubMed

Ritz, Christian; Van der Vliet, Leana

2009-09-01

The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.

Pointwise influence matrices for functional-response regression.

PubMed

Reiss, Philip T; Huang, Lei; Wu, Pei-Shien; Chen, Huaihou; Colcombe, Stan

2017-12-01

We extend the notion of an influence or hat matrix to regression with functional responses and scalar predictors. For responses depending linearly on a set of predictors, our definition is shown to reduce to the conventional influence matrix for linear models. The pointwise degrees of freedom, the trace of the pointwise influence matrix, are shown to have an adaptivity property that motivates a two-step bivariate smoother for modeling nonlinear dependence on a single predictor. This procedure adapts to varying complexity of the nonlinear model at different locations along the function, and thereby achieves better performance than competing tensor product smoothers in an analysis of the development of white matter microstructure in the brain. © 2017, The International Biometric Society.

An Application to the Prediction of LOD Change Based on General Regression Neural Network

NASA Astrophysics Data System (ADS)

Zhang, X. H.; Wang, Q. J.; Zhu, J. J.; Zhang, H.

2011-07-01

Traditional prediction of the LOD (length of day) change was based on linear models, such as the least square model and the autoregressive technique, etc. Due to the complex non-linear features of the LOD variation, the performances of the linear model predictors are not fully satisfactory. This paper applies a non-linear neural network - general regression neural network (GRNN) model to forecast the LOD change, and the results are analyzed and compared with those obtained with the back propagation neural network and other models. The comparison shows that the performance of the GRNN model in the prediction of the LOD change is efficient and feasible.

Understanding Child Stunting in India: A Comprehensive Analysis of Socio-Economic, Nutritional and Environmental Determinants Using Additive Quantile Regression

PubMed Central

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A.

2013-01-01

Background Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. Objective We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Design Using cross-sectional data for children aged 0–24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. Results At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Conclusions Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role. PMID:24223839

Understanding child stunting in India: a comprehensive analysis of socio-economic, nutritional and environmental determinants using additive quantile regression.

PubMed

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A

2013-01-01

Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Using cross-sectional data for children aged 0-24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role.

Hybrid simulation of fishbone instabilities in the EAST tokamak

DOE PAGES

Shen, Wei; Wang, Feng; Fu, G. Y.; ...

2017-08-11

Hybrid simulations with the global kinetic-magnetohydrodynamic (MHD) code M3D-K have been carried out to investigate the linear stability and nonlinear dynamics of beam-driven fishbone in the experimental advanced superconducting tokamak (EAST) experiment. Linear simulations show that a low frequency fishbone instability is excited at experimental value of beam ion pressure. The mode is mainly driven by low energy beam ions via precessional resonance. Our results are consistent with the experimental measurement with respect to mode frequency and mode structure. When the beam ion pressure is increased to exceed a critical value, the low frequency mode transits to a beta-induced Alfvenmore » eigenmode (BAE) with much higher frequency. This BAE is driven by higher energy beam ions. Nonlinear simulations show that the frequency of the low frequency fishbone chirps up and down with corresponding hole-clump structures in phase space, consistent with the Berk-Breizman theory. In addition to the low frequency mode, the high frequency BAE is excited during the nonlinear evolution. Furthermore, for the transient case of beam pressure fraction where the low and high frequency modes are simultaneously excited in the linear phase, only one dominant mode appears in the nonlinear phase with frequency jumps up and down during nonlinear evolution.« less

Single point dilution method for the quantitative analysis of antibodies to the gag24 protein of HIV-1.

PubMed

Palenzuela, D O; Benítez, J; Rivero, J; Serrano, R; Ganzó, O

1997-10-13

In the present work a concept proposed in 1992 by Dopotka and Giesendorf was applied to the quantitative analysis of antibodies to the p24 protein of HIV-1 in infected asymptomatic individuals and AIDS patients. Two approaches were analyzed, a linear model OD = b0 + b1.log(titer) and a nonlinear log(titer) = alpha.OD beta, similar to the Dopotka-Giesendorf's model. The above two proposed models adequately fit the dependence of the optical density values at a single point dilution, and titers achieved by the end point dilution method (EPDM). Nevertheless, the nonlinear model better fits the experimental data, according to residuals analysis. Classical EPDM was compared with the new single point dilution method (SPDM) using both models. The best correlation between titers calculated using both models and titers achieved by EPDM was obtained with the nonlinear model. The correlation coefficients for the nonlinear and linear models were r = 0.85 and r = 0.77, respectively. A new correction factor was introduced into the nonlinear model and this reduced the day-to-day variation of titer values. In general, SPDM saves time, reagents and is more precise and sensitive to changes in antibody levels, and therefore has a higher resolution than EPDM.

Minimizing bias in biomass allometry: Model selection and log transformation of data

Treesearch

Joseph Mascaro; undefined undefined; Flint Hughes; Amanda Uowolo; Stefan A. Schnitzer

2011-01-01

Nonlinear regression is increasingly used to develop allometric equations for forest biomass estimation (i.e., as opposed to the raditional approach of log-transformation followed by linear regression). Most statistical software packages, however, assume additive errors by default, violating a key assumption of allometric theory and possibly producing spurious models....

A Comparison of Methods for Estimating Quadratic Effects in Nonlinear Structural Equation Models

ERIC Educational Resources Information Center

Harring, Jeffrey R.; Weiss, Brandi A.; Hsu, Jui-Chen

2012-01-01

Two Monte Carlo simulations were performed to compare methods for estimating and testing hypotheses of quadratic effects in latent variable regression models. The methods considered in the current study were (a) a 2-stage moderated regression approach using latent variable scores, (b) an unconstrained product indicator approach, (c) a latent…

Logarithmic Transformations in Regression: Do You Transform Back Correctly?

ERIC Educational Resources Information Center

Dambolena, Ismael G.; Eriksen, Steven E.; Kopcso, David P.

2009-01-01

The logarithmic transformation is often used in regression analysis for a variety of purposes such as the linearization of a nonlinear relationship between two or more variables. We have noticed that when this transformation is applied to the response variable, the computation of the point estimate of the conditional mean of the original response…

Photonic single nonlinear-delay dynamical node for information processing

NASA Astrophysics Data System (ADS)

Ortín, Silvia; San-Martín, Daniel; Pesquera, Luis; Gutiérrez, José Manuel

2012-06-01

An electro-optical system with a delay loop based on semiconductor lasers is investigated for information processing by performing numerical simulations. This system can replace a complex network of many nonlinear elements for the implementation of Reservoir Computing. We show that a single nonlinear-delay dynamical system has the basic properties to perform as reservoir: short-term memory and separation property. The computing performance of this system is evaluated for two prediction tasks: Lorenz chaotic time series and nonlinear auto-regressive moving average (NARMA) model. We sweep the parameters of the system to find the best performance. The results achieved for the Lorenz and the NARMA-10 tasks are comparable to those obtained by other machine learning methods.

MANOVA vs nonlinear mixed effects modeling: The comparison of growth patterns of female and male quail

NASA Astrophysics Data System (ADS)

Gürcan, Eser Kemal

2017-04-01

The most commonly used methods for analyzing time-dependent data are multivariate analysis of variance (MANOVA) and nonlinear regression models. The aim of this study was to compare some MANOVA techniques and nonlinear mixed modeling approach for investigation of growth differentiation in female and male Japanese quail. Weekly individual body weight data of 352 male and 335 female quail from hatch to 8 weeks of age were used to perform analyses. It is possible to say that when all the analyses are evaluated, the nonlinear mixed modeling is superior to the other techniques because it also reveals the individual variation. In addition, the profile analysis also provides important information.

A step-by-step guide to non-linear regression analysis of experimental data using a Microsoft Excel spreadsheet.

PubMed

Brown, A M

2001-06-01

The objective of this present study was to introduce a simple, easily understood method for carrying out non-linear regression analysis based on user input functions. While it is relatively straightforward to fit data with simple functions such as linear or logarithmic functions, fitting data with more complicated non-linear functions is more difficult. Commercial specialist programmes are available that will carry out this analysis, but these programmes are expensive and are not intuitive to learn. An alternative method described here is to use the SOLVER function of the ubiquitous spreadsheet programme Microsoft Excel, which employs an iterative least squares fitting routine to produce the optimal goodness of fit between data and function. The intent of this paper is to lead the reader through an easily understood step-by-step guide to implementing this method, which can be applied to any function in the form y=f(x), and is well suited to fast, reliable analysis of data in all fields of biology.

Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

NASA Astrophysics Data System (ADS)

Minh, Vu Trieu; Katushin, Dmitri; Antonov, Maksim; Veinthal, Renno

2017-03-01

This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM) based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), rock brittleness index (BI), the distance between planes of weakness (DPW), and the alpha angle (Alpha) between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP). Four (4) statistical regression models (two linear and two nonlinear) are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2) of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

Multivariate meta-analysis for non-linear and other multi-parameter associations

PubMed Central

Gasparrini, A; Armstrong, B; Kenward, M G

2012-01-01

In this paper, we formalize the application of multivariate meta-analysis and meta-regression to synthesize estimates of multi-parameter associations obtained from different studies. This modelling approach extends the standard two-stage analysis used to combine results across different sub-groups or populations. The most straightforward application is for the meta-analysis of non-linear relationships, described for example by regression coefficients of splines or other functions, but the methodology easily generalizes to any setting where complex associations are described by multiple correlated parameters. The modelling framework of multivariate meta-analysis is implemented in the package mvmeta within the statistical environment R. As an illustrative example, we propose a two-stage analysis for investigating the non-linear exposure–response relationship between temperature and non-accidental mortality using time-series data from multiple cities. Multivariate meta-analysis represents a useful analytical tool for studying complex associations through a two-stage procedure. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22807043

Cocaine Dependence Treatment Data: Methods for Measurement Error Problems With Predictors Derived From Stationary Stochastic Processes

PubMed Central

Guan, Yongtao; Li, Yehua; Sinha, Rajita

2011-01-01

In a cocaine dependence treatment study, we use linear and nonlinear regression models to model posttreatment cocaine craving scores and first cocaine relapse time. A subset of the covariates are summary statistics derived from baseline daily cocaine use trajectories, such as baseline cocaine use frequency and average daily use amount. These summary statistics are subject to estimation error and can therefore cause biased estimators for the regression coefficients. Unlike classical measurement error problems, the error we encounter here is heteroscedastic with an unknown distribution, and there are no replicates for the error-prone variables or instrumental variables. We propose two robust methods to correct for the bias: a computationally efficient method-of-moments-based method for linear regression models and a subsampling extrapolation method that is generally applicable to both linear and nonlinear regression models. Simulations and an application to the cocaine dependence treatment data are used to illustrate the efficacy of the proposed methods. Asymptotic theory and variance estimation for the proposed subsampling extrapolation method and some additional simulation results are described in the online supplementary material. PMID:21984854

Creep analysis of silicone for podiatry applications.

PubMed

Janeiro-Arocas, Julia; Tarrío-Saavedra, Javier; López-Beceiro, Jorge; Naya, Salvador; López-Canosa, Adrián; Heredia-García, Nicolás; Artiaga, Ramón

2016-10-01

This work shows an effective methodology to characterize the creep-recovery behavior of silicones before their application in podiatry. The aim is to characterize, model and compare the creep-recovery properties of different types of silicone used in podiatry orthotics. Creep-recovery phenomena of silicones used in podiatry orthotics is characterized by dynamic mechanical analysis (DMA). Silicones provided by Herbitas are compared by observing their viscoelastic properties by Functional Data Analysis (FDA) and nonlinear regression. The relationship between strain and time is modeled by fixed and mixed effects nonlinear regression to compare easily and intuitively podiatry silicones. Functional ANOVA and Kohlrausch-Willians-Watts (KWW) model with fixed and mixed effects allows us to compare different silicones observing the values of fitting parameters and their physical meaning. The differences between silicones are related to the variations of breadth of creep-recovery time distribution and instantaneous deformation-permanent strain. Nevertheless, the mean creep-relaxation time is the same for all the studied silicones. Silicones used in palliative orthoses have higher instantaneous deformation-permanent strain and narrower creep-recovery distribution. The proposed methodology based on DMA, FDA and nonlinear regression is an useful tool to characterize and choose the proper silicone for each podiatry application according to their viscoelastic properties. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modulation of lung molecular biomarkers by beta-carotene in the Physicians' Health Study.

PubMed

Liu, Chun; Wang, Xiang-Dong; Mucci, Lorelei; Gaziano, J Michael; Zhang, Shumin M

2009-03-01

Beta-Carotene supplementation showed neither benefit nor harm among apparently healthy physicians (all men) in the Physicians' Health Study (PHS) trial. The objective of the current investigation was to evaluate how long-term beta-carotene supplementation affects molecular markers of lung carcinogenesis in the PHS. The protein levels of total p53, cyclin D1, proliferating cellular nuclear antigen (PCNA), retinoic acid receptor beta (RARbeta), and cytochrome p450 enzyme 1A1 (CYP1A1) were measured using the immunohistochemical method in 40 available archival lung tissue samples from patients who were diagnosed with lung cancer in the PHS. The protein levels of these markers were compared by category of beta-carotene treatment assignment and other characteristics using unconditional logistic regression models. The positivity for total p53, RARbeta, cyclin D1, and PCNA was nonsignificantly lower among lung cancer patients who were assigned to receive beta-carotene than those who were assigned to receive beta-carotene placebo. There was a borderline significant difference in CYP1A1 positivity with an OR of 0.2 (95% confidence interval, 0.2-1.1; P = .06) in a comparison of men who received beta-carotene and men who received beta-carotene placebo. The 50-mg beta-carotene supplementation on alternate days had no significant influence on molecular markers of lung carcinogenesis that were evaluated in the PHS. This finding provides mechanistic support for the main PHS trial results of beta-carotene, which demonstrated no benefit or harm to the risk of developing lung cancer. (c) 2009 American Cancer Society.

Non-linear dynamics of compound sawteeth in tokamaks

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

Ahn, J.-H., E-mail: jae-heon.ahn@polytechnique.edu; Garbet, X.; Sabot, R.

2016-05-15

Compound sawteeth is studied with the XTOR-2F code. Non-linear full 3D magnetohydrodynamic simulations show that the plasma hot core is radially displaced and rotates during the partial crash, but is not fully expelled out of the q = 1 surface. Partial crashes occur when the radius of the q = 1 surface exceeds a critical value, at fixed poloidal beta. This critical value depends on the plasma elongation. The partial crash time is larger than the collapse time of an ordinary sawtooth, likely due to a weaker diamagnetic stabilization. This suggests that partial crashes result from a competition between destabilizing effects such as themore » q = 1 radius and diamagnetic stabilization.« less

Small amplitude Kinetic Alfven waves in a superthermal electron-positron-ion plasma

NASA Astrophysics Data System (ADS)

Adnan, Muhammad; Mahmood, Sahahzad; Qamar, Anisa; Tribeche, Mouloud

2016-11-01

We are investigating the propagating properties of coupled Kinetic Alfven-acoustic waves in a low beta plasma having superthermal electrons and positrons. Using the standard reductive perturbation method, a nonlinear Korteweg-de Vries (KdV) type equation is derived which describes the evolution of Kinetic Alfven waves. It is found that nonlinearity and Larmor radius effects can compromise and give rise to solitary structures. The parametric role of superthermality and positron content on the characteristics of solitary wave structures is also investigated. It is found that only sub-Alfvenic and compressive solitons are supported in the present model. The present study may find applications in a low β electron-positron-ion plasma having superthermal electrons and positrons.

Numerical modeling of the atmosphere with an isentropic vertical coordinate

NASA Technical Reports Server (NTRS)

Hsu, Yueh-Jiuan G.; Arakawa, Akio

1990-01-01

A theta-coordinate model simulating the nonlinear evolution of a baroclinic wave is presented. In the model, vertical discretization maintains important integral constraints such as conservation of the angular momentum and total energy. A massless-layer approach is used in the treatment of the intersections of coordinate surfaces with the lower boundary. This formally eliminates the intersection problem, but raises other computational problems. Horizontal discretization of the continuity and momentum equations in the model are designed to overcome these problems. Selected results from a 10-day integration with the 25-layer, beta-plane version of the model are presented. It is concluded that the model can simulate the nonlinear evolution of a baroclinic wave and associated dynamical processes without major computational difficulties.

Parapapillary Gamma Zone and Progression of Myopia in School Children: The Beijing Children Eye Study.

PubMed

Guo, Yin; Liu, Li Juan; Tang, Ping; Feng, Yi; Lv, Yan Yun; Wu, Min; Xu, Liang; Jonas, Jost B

2018-03-01

To assess the development and enlargement of the parapapillary gamma zone in school children. This school-based prospective longitudinal study included Chinese children attending grade 1 in 2011 and returning for yearly follow-up examinations until 2016. These examinations consisted of a comprehensive ocular examination with biometry and color fundus photographs. The parents underwent a standardized interview. The parapapillary gamma zone was defined as the area with visible sclera at the temporal optic disc margin, and the optic disc itself was measured on fundus photographs. The study included 294 children (mean age in 2016, 11.4 ± 0.5 years [range, 10-13 years]; mean axial length, 24.1 ± 1.1 mm [range, 21.13-27.29 mm]). In multivariate analysis, larger increases in the gamma zone area during the study period were correlated (coefficient of determination for bivariate analysis [r2], r2 = 0.69) with larger increases in the vertical-to-horizontal disc diameter ratios (P < 0.001; standardized regression coefficient beta [beta], 0.53; nonstandardized regression coefficient B [B], 4.05; 95% confidence intervals [CI], 3.37-4.73), larger axial elongation (P < 0.001; beta, 0.32; B, 0.37; 95% CI, 0.26-0.47), a larger vertical disc diameter at baseline (P < 0.001; beta, 0.22; B, 0.98; 95% CI, 0.62-1.33), a larger gamma zone area at baseline (P < 0.001; beta, 0.14; B, 0.41; 95% CI, 0.17-0.64), and more time spent indoors studying (P = 0.015; beta, 0.10; B, 0.09; 95% CI, 0.02-0.17). The development and enlargement of the gamma zone in the temporal parapapillary region were associated with an optic disc rotation around the vertical disc axis as indicated by an increasing vertical-to-horizontal disc diameter ratio. These morphologic findings fit with the notion of a backward pull of the temporal peripapillary sclera through the optic nerve dura mater in axially elongated eyes.

Relationship of carotid arterial functional and structural changes to left atrial volume in untreated hypertension.

PubMed

Jaroch, Joanna; Rzyczkowska, Barbara; Bociąga, Zbigniew; Vriz, Olga; Driussi, Caterina; Loboz-Rudnicka, Maria; Dudek, Krzysztof; Łoboz-Grudzień, Krystyna

2016-04-01

The contribution of arterial functional and structural changes to left ventricular (LV) diastolic dysfunction has been the area of recent research. There are some studies on the relationship between arterial stiffness (a.s.) and left atrial (LA) remodelling as a marker of diastolic burden. Little is known about the association of arterial structural changes and LA remodelling in hypertension (H). The aim of this study was to examine the relationship between carotid a.s. and intima-media thickness (IMT) and LA volume in subjects with H. The study included 245 previously untreated hypertensives (166 women and 79 men, mean age 53.7 ± 11.8 years). Each patient was subjected to echocardiography with measurement of LA volume, evaluation of left ventricular hypertrophy (LVH) and LV systolic/diastolic function indices, integrated assessment of carotid IMT and echo-tracking of a.s. and wave reflection parameters. Univariate regression analysis revealed significant correlations between indexed LA volume and selected clinical characteristics, echocardiographic indices of LVH and LV diastolic/systolic function and a.s./wave reflection parameters. The following parameters were identified as independent determinants of indexed LA volume on multivariate regression analysis: diastolic blood pressure (beta = -0.229, P < 0.001), left ventricular mass index (LVMI; beta = 0.258, P < 0.001), E/e’ index (ratio of early mitral flow wave velocity – E to early diastolic mitral annular velocity – e’; beta = 0.266, P = 0.001), augmentation index (AI; beta = 0.143, P = 0.008) and body mass index (BMI; beta = 0.132, P = 0.017). No correlations between indexed LA volume and IMT were found. There is a significant relationship between carotid arterial stiffness but not intima-media thickness and LA volume in patients with untreated hypertension.

Associations between strain in domestic work and self-rated health: a study of employed women in Sweden.

PubMed

Staland-Nyman, Carin; Alexanderson, Kristina; Hensing, Gunnel

2008-01-01

The aim of this study was to analyse the association between strain in domestic work and self-rated health among employed women in Sweden, using two different methods of measuring strain in domestic work. Questionnaire data were collected on health and living conditions in paid and unpaid work for employed women (n=1,417), aged 17-64 years. "Domestic job strain'' was an application of the demand-control model developed by Karasek and Theorell, and "Domestic work equity and marital satisfaction'' was measured by questions on the division of and responsibility for domestic work and relationship with spouse/cohabiter. Self-rated health was measured using the SF-36 Health Survey. Associations were analysed by bivariate and multivariate linear regression analyses, and reported as standardized regression coefficients. Higher strain in domestic work was associated with lower self-rated health, also after controlling for potential confounders and according to both strain measures. "Domestic work equity and marital satisfaction'' showed for example negative associations with mental health beta -0.211 (p<0.001), vitality beta -0.195 (p<0.001), social function -0.132 (p<0.01) and physical role beta -0.115 (p<0.01). The highest associations between "Domestic job strain'' and SF-36 were found for vitality beta -0.156 (p<0.001), mental health beta -0.123 (p<0.001). Strain in domestic work, including perceived inequity in the relationship and lack of a satisfactory relationship with a spouse/cohabiter, was associated with lower self-rated health in this cross-sectional study. Future research needs to address the specific importance of strain in domestic work as a contributory factor to women's ill-health.

Financial market dynamics: superdiffusive or not?

NASA Astrophysics Data System (ADS)

Devi, Sandhya

2017-08-01

The behavior of stock market returns over a period of 1-60 d has been investigated for S&P 500 and Nasdaq within the framework of nonextensive Tsallis statistics. Even for such long terms, the distributions of the returns are non-Gaussian. They have fat tails indicating that the stock returns do not follow a random walk model. In this work, a good fit to a Tsallis q-Gaussian distribution is obtained for the distributions of all the returns using the method of Maximum Likelihood Estimate. For all the regions of data considered, the values of the scaling parameter q, estimated from 1 d returns, lie in the range 1.4-1.65. The estimated inverse mean square deviations (beta) show a power law behavior in time with exponent values between  -0.91 and  -1.1 indicating normal to mildly subdiffusive behavior. Quite often, the dynamics of market return distributions is modelled by a Fokker-Plank (FP) equation either with a linear drift and a nonlinear diffusion term or with just a nonlinear diffusion term. Both of these cases support a q-Gaussian distribution as a solution. The distributions obtained from current estimated parameters are compared with the solutions of the FP equations. For negligible drift term, the inverse mean square deviations (betaFP) from the FP model follow a power law with exponent values between  -1.25 and  -1.48 indicating superdiffusion. When the drift term is non-negligible, the corresponding betaFP do not follow a power law and become stationary after certain characteristic times that depend on the values of the drift parameter and q. Neither of these behaviors is supported by the results of the empirical fit.

On Insensitivity of the Chi-Square Model Test to Nonlinear Misspecification in Structural Equation Models

ERIC Educational Resources Information Center

Mooijaart, Ab; Satorra, Albert

2009-01-01

In this paper, we show that for some structural equation models (SEM), the classical chi-square goodness-of-fit test is unable to detect the presence of nonlinear terms in the model. As an example, we consider a regression model with latent variables and interactions terms. Not only the model test has zero power against that type of…

Nonlinear Simulation of the Tooth Enamel Spectrum for EPR Dosimetry

NASA Astrophysics Data System (ADS)

Kirillov, V. A.; Dubovsky, S. V.

2016-07-01

Software was developed where initial EPR spectra of tooth enamel were deconvoluted based on nonlinear simulation, line shapes and signal amplitudes in the model initial spectrum were calculated, the regression coefficient was evaluated, and individual spectra were summed. Software validation demonstrated that doses calculated using it agreed excellently with the applied radiation doses and the doses reconstructed by the method of additive doses.

Peginterferon Beta-1a Shows Antitumor Activity as a Single Agent and Enhances Efficacy of Standard of Care Cancer Therapeutics in Human Melanoma, Breast, Renal, and Colon Xenograft Models.

PubMed

Boccia, Antonio; Virata, Cyrus; Lindner, Daniel; English, Nicki; Pathan, Nuzhat; Brickelmaier, Margot; Hu, Xiao; Gardner, Jennifer L; Peng, Liaomin; Wang, Xinzhong; Zhang, Xiamei; Yang, Lu; Perron, Keli; Yco, Grace; Kelly, Rebecca; Gamez, James; Scripps, Thomas; Bennett, Donald; Joseph, Ingrid B; Baker, Darren P

2017-01-01

Because of its tumor-suppressive effect, interferon-based therapy has been used for the treatment of melanoma. However, limited data are available regarding the antitumor effects of pegylated interferons, either alone or in combination with approved anticancer drugs. We report that treatment of human WM-266-4 melanoma cells with peginterferon beta-1a induced apoptotic markers. Additionally, peginterferon beta-1a significantly inhibited the growth of human SK-MEL-1, A-375, and WM-266-4 melanoma xenografts established in immunocompromised mice. Peginterferon beta-1a regressed large, established WM-266-4 xenografts in nude mice. Treatment of SK-MEL-1 tumor-bearing mice with a combination of peginterferon beta-1a and the MEK inhibitor PD325901 ((R)-N-(2,3-dihydroxypropoxy)-3,4-difluoro-2-(2-fluoro-4-iodophenylamino)benzamide) significantly improved tumor growth inhibition compared with either agent alone. Examination of the antitumor activity of peginterferon beta-1a in combination with approved anticancer drugs in breast and renal carcinomas revealed improved antitumor activity in these preclinical xenograft models, as did the combination of peginterferon beta-1a and bevacizumab in a colon carcinoma xenograft model.

Disentangling the drivers of taxonomic and phylogenetic beta diversities in disturbed and undisturbed subtropical forests

NASA Astrophysics Data System (ADS)

Liu, Jinliang; Qian, Hong; Jin, Yi; Wu, Chuping; Chen, Jianhua; Yu, Shuquan; Wei, Xinliang; Jin, Xiaofeng; Liu, Jiajia; Yu, Mingjian

2016-10-01

Understanding the relative importance of dispersal limitation and environmental filtering processes in structuring the beta diversities of subtropical forests in human disturbed landscapes is still limited. Here we used taxonomic (TBD) and phylogenetic (PBD), including terminal PBD (PBDt) and basal PBD (PBDb), beta diversity indices to quantify the taxonomic and phylogenetic turnovers at different depths of evolutionary history in disturbed and undisturbed subtropical forests. Multiple linear regression model and distance-based redundancy analysis were used to disentangle the relative importance of environmental and spatial variables. Environmental variables were significantly correlated with TBD and PBDt metrics. Temperature and precipitation were major environmental drivers of beta diversity patterns, which explained 7-27% of the variance in TBD and PBDt, whereas the spatial variables independently explained less than 1% of the variation for all forests. The relative importance of environmental and spatial variables differed between disturbed and undisturbed forests (e.g., when Bray-Curtis was used as a beta diversity metric, environmental variable had a significant effect on beta diversity for disturbed forests but had no effect on undisturbed forests). We conclude that environmental filtering plays a more important role than geographical limitation and disturbance history in driving taxonomic and terminal phylogenetic beta diversity.

Disentangling the drivers of taxonomic and phylogenetic beta diversities in disturbed and undisturbed subtropical forests

PubMed Central

Liu, Jinliang; Qian, Hong; Jin, Yi; Wu, Chuping; Chen, Jianhua; Yu, Shuquan; Wei, Xinliang; Jin, Xiaofeng; Liu, Jiajia; Yu, Mingjian

2016-01-01

Understanding the relative importance of dispersal limitation and environmental filtering processes in structuring the beta diversities of subtropical forests in human disturbed landscapes is still limited. Here we used taxonomic (TBD) and phylogenetic (PBD), including terminal PBD (PBDt) and basal PBD (PBDb), beta diversity indices to quantify the taxonomic and phylogenetic turnovers at different depths of evolutionary history in disturbed and undisturbed subtropical forests. Multiple linear regression model and distance-based redundancy analysis were used to disentangle the relative importance of environmental and spatial variables. Environmental variables were significantly correlated with TBD and PBDt metrics. Temperature and precipitation were major environmental drivers of beta diversity patterns, which explained 7–27% of the variance in TBD and PBDt, whereas the spatial variables independently explained less than 1% of the variation for all forests. The relative importance of environmental and spatial variables differed between disturbed and undisturbed forests (e.g., when Bray-Curtis was used as a beta diversity metric, environmental variable had a significant effect on beta diversity for disturbed forests but had no effect on undisturbed forests). We conclude that environmental filtering plays a more important role than geographical limitation and disturbance history in driving taxonomic and terminal phylogenetic beta diversity. PMID:27775021

Correlation between increased urinary sodium excretion and decreased left ventricular diastolic function in patients with type 2 diabetes mellitus.

PubMed

Kagiyama, Shuntaro; Koga, Tokushi; Kaseda, Shigeru; Ishihara, Shiro; Kawazoe, Nobuyuki; Sadoshima, Seizo; Matsumura, Kiyoshi; Takata, Yutaka; Tsuchihashi, Takuya; Iida, Mitsuo

2009-10-01

Increased salt intake may induce hypertension, lead to cardiac hypertrophy, and exacerbate heart failure. When elderly patients develop heart failure, diastolic dysfunction is often observed, although the ejection fraction has decreased. Diabetes mellitus (DM) is an established risk factor for heart failure. However, little is known about the relationship between cardiac function and urinary sodium excretion (U-Na) in patients with DM. We measured 24-hour U-Na; cardiac function was evaluated directly during coronary catheterization in type 2 DM (n = 46) or non-DM (n = 55) patients with preserved cardiac systolic function (ejection fraction > or = 60%). Cardiac diastolic and systolic function was evaluated as - dp/dt and + dp/dt, respectively. The average of U-Na was 166.6 +/- 61.2 mEq/24 hour (mean +/- SD). In all patients, stepwise multivariate regression analysis revealed that - dp/dt had a negative correlation with serum B-type natriuretic peptide (BNP; beta = - 0.23, P = .021) and U-Na (beta = - 0.24, P = .013). On the other hand, + dp/dt negatively correlated with BNP (beta = - 0.30, P < .001), but did not relate to U-Na. In the DM-patients, stepwise multivariate regression analysis showed that - dp/dt still had a negative correlation with U-Na (beta = - 0.33, P = .025). The results indicated that increased urinary sodium excretion is associated with an impairment of cardiac diastolic function, especially in patients with DM, suggesting that a reduction of salt intake may improve cardiac diastolic function.

Evaluation of confidence intervals for a steady-state leaky aquifer model

USGS Publications Warehouse

Christensen, S.; Cooley, R.L.

1999-01-01

The fact that dependent variables of groundwater models are generally nonlinear functions of model parameters is shown to be a potentially significant factor in calculating accurate confidence intervals for both model parameters and functions of the parameters, such as the values of dependent variables calculated by the model. The Lagrangian method of Vecchia and Cooley [Vecchia, A.V. and Cooley, R.L., Water Resources Research, 1987, 23(7), 1237-1250] was used to calculate nonlinear Scheffe-type confidence intervals for the parameters and the simulated heads of a steady-state groundwater flow model covering 450 km2 of a leaky aquifer. The nonlinear confidence intervals are compared to corresponding linear intervals. As suggested by the significant nonlinearity of the regression model, linear confidence intervals are often not accurate. The commonly made assumption that widths of linear confidence intervals always underestimate the actual (nonlinear) widths was not correct. Results show that nonlinear effects can cause the nonlinear intervals to be asymmetric and either larger or smaller than the linear approximations. Prior information on transmissivities helps reduce the size of the confidence intervals, with the most notable effects occurring for the parameters on which there is prior information and for head values in parameter zones for which there is prior information on the parameters.The fact that dependent variables of groundwater models are generally nonlinear functions of model parameters is shown to be a potentially significant factor in calculating accurate confidence intervals for both model parameters and functions of the parameters, such as the values of dependent variables calculated by the model. The Lagrangian method of Vecchia and Cooley was used to calculate nonlinear Scheffe-type confidence intervals for the parameters and the simulated heads of a steady-state groundwater flow model covering 450 km2 of a leaky aquifer. The nonlinear confidence intervals are compared to corresponding linear intervals. As suggested by the significant nonlinearity of the regression model, linear confidence intervals are often not accurate. The commonly made assumption that widths of linear confidence intervals always underestimate the actual (nonlinear) widths was not correct. Results show that nonlinear effects can cause the nonlinear intervals to be asymmetric and either larger or smaller than the linear approximations. Prior information on transmissivities helps reduce the size of the confidence intervals, with the most notable effects occurring for the parameters on which there is prior information and for head values in parameter zones for which there is prior information on the parameters.

Advanced Statistical Analyses to Reduce Inconsistency of Bond Strength Data.

PubMed

Minamino, T; Mine, A; Shintani, A; Higashi, M; Kawaguchi-Uemura, A; Kabetani, T; Hagino, R; Imai, D; Tajiri, Y; Matsumoto, M; Yatani, H

2017-11-01

This study was designed to clarify the interrelationship of factors that affect the value of microtensile bond strength (µTBS), focusing on nondestructive testing by which information of the specimens can be stored and quantified. µTBS test specimens were prepared from 10 noncarious human molars. Six factors of µTBS test specimens were evaluated: presence of voids at the interface, X-ray absorption coefficient of resin, X-ray absorption coefficient of dentin, length of dentin part, size of adhesion area, and individual differences of teeth. All specimens were observed nondestructively by optical coherence tomography and micro-computed tomography before µTBS testing. After µTBS testing, the effect of these factors on µTBS data was analyzed by the general linear model, linear mixed effects regression model, and nonlinear regression model with 95% confidence intervals. By the general linear model, a significant difference in individual differences of teeth was observed ( P < 0.001). A significantly positive correlation was shown between µTBS and length of dentin part ( P < 0.001); however, there was no significant nonlinearity ( P = 0.157). Moreover, a significantly negative correlation was observed between µTBS and size of adhesion area ( P = 0.001), with significant nonlinearity ( P = 0.014). No correlation was observed between µTBS and X-ray absorption coefficient of resin ( P = 0.147), and there was no significant nonlinearity ( P = 0.089). Additionally, a significantly positive correlation was observed between µTBS and X-ray absorption coefficient of dentin ( P = 0.022), with significant nonlinearity ( P = 0.036). A significant difference was also observed between the presence and absence of voids by linear mixed effects regression analysis. Our results showed correlations between various parameters of tooth specimens and µTBS data. To evaluate the performance of the adhesive more precisely, the effect of tooth variability and a method to reduce variation in bond strength values should also be considered.

Mode structure symmetry breaking of energetic particle driven beta-induced Alfvén eigenmode

NASA Astrophysics Data System (ADS)

Lu, Z. X.; Wang, X.; Lauber, Ph.; Zonca, F.

2018-01-01

The mode structure symmetry breaking of energetic particle driven Beta-induced Alfvén Eigenmode (BAE) is studied based on global theory and simulation. The weak coupling formula gives a reasonable estimate of the local eigenvalue compared with global hybrid simulation using XHMGC. The non-perturbative effect of energetic particles on global mode structure symmetry breaking in radial and parallel (along B) directions is demonstrated. With the contribution from energetic particles, two dimensional (radial and poloidal) BAE mode structures with symmetric/asymmetric tails are produced using an analytical model. It is demonstrated that the symmetry breaking in radial and parallel directions is intimately connected. The effects of mode structure symmetry breaking on nonlinear physics, energetic particle transport, and the possible insight for experimental studies are discussed.

Associations of beta-endorphin with HVA and MHPG in the plasma of prepubertal boys: effects of familial drug abuse and antisocial personality disorder liability.

PubMed

Moss, H B; Yao, J K

1996-06-01

It is well-established that the secretion of the opioid neuropeptide beta-endorphin is perturbed by the administration of various drugs of abuse. Several investigators have speculated that variations in beta-endorphin secretory regulation may precede the development of a substance use disorder, and thus be a component of the liability for substance abuse. In order to test this hypothesis, we examined fasting, morning plasma concentrations of beta-endorphin and two catecholamine metabolites in prepubertal boys naive to drugs of abuse and at elevated familial risk for a substance use disorder (SA+), and in controls (SA-). Specifically, the dopaminergic metabolite homovanillic acid (pHVA), and the noradrenergic metabolite, 3-methoxy-4-hydroxy-phenylglycol (pMHPG) were measured. Between-group differences were not found for beta-endorphin, pHVA, or pMHPG. Similarly, such differences did not differentiate sons of fathers with Antisocial Personality Disorder and controls. However, regression analysis revealed that although both pHVA and pMHPG predicted beta-endorphin concentrations to similar degrees, the directions of influence were the opposite. pHVA was found to be positively associated with beta-endorphin while pMHPG was found to be negatively associated with beta-endorphin. No between-group differences in these relationships were found. The results suggest an opponent process in catecholaminergic regulation of beta-endorphin in humans, and are consistent with observations in the central nervous system of animal models.

Frequency-domain nonlinear regression algorithm for spectral analysis of broadband SFG spectroscopy.

PubMed

He, Yuhan; Wang, Ying; Wang, Jingjing; Guo, Wei; Wang, Zhaohui

2016-03-01

The resonant spectral bands of the broadband sum frequency generation (BB-SFG) spectra are often distorted by the nonresonant portion and the lineshapes of the laser pulses. Frequency domain nonlinear regression (FDNLR) algorithm was proposed to retrieve the first-order polarization induced by the infrared pulse and to improve the analysis of SFG spectra through simultaneous fitting of a series of time-resolved BB-SFG spectra. The principle of FDNLR was presented, and the validity and reliability were tested by the analysis of the virtual and measured SFG spectra. The relative phase, dephasing time, and lineshapes of the resonant vibrational SFG bands can be retrieved without any preset assumptions about the SFG bands and the incident laser pulses.

Application of General Regression Neural Network to the Prediction of LOD Change

NASA Astrophysics Data System (ADS)

Zhang, Xiao-Hong; Wang, Qi-Jie; Zhu, Jian-Jun; Zhang, Hao

2012-01-01

Traditional methods for predicting the change in length of day (LOD change) are mainly based on some linear models, such as the least square model and autoregression model, etc. However, the LOD change comprises complicated non-linear factors and the prediction effect of the linear models is always not so ideal. Thus, a kind of non-linear neural network — general regression neural network (GRNN) model is tried to make the prediction of the LOD change and the result is compared with the predicted results obtained by taking advantage of the BP (back propagation) neural network model and other models. The comparison result shows that the application of the GRNN to the prediction of the LOD change is highly effective and feasible.

The third-order optical nonlinearities of Ge-Ga-Sb(In)-S chalcogenide glasses

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

Guo, Haitao, E-mail: guoht_001@opt.ac.cn; Chen, Hongyan; Hou, Chaoqi

2011-05-15

Research highlights: {yields} It is firstly demonstrated that the nonlinear refractive index n{sub 2} is dependent on the covalency of bonds in chalcogenide glass. {yields} Homopolar metallic bonds in chalcogenide glass have positive contribution to large nonlinear refractive index n{sub 2} also. {yields} The 80GeS{sub 2}.20Sb{sub 2}S{sub 3} glass would be expected to be used in the all-optical switches working at 1330 nm and 1550 nm telecommunication wavelengths. -- Abstract: The third-order optical nonlinearities of 80GeS{sub 2}.(20 - x)Ga{sub 2}S{sub 3}.xY{sub 2}S{sub 3} (x = 0, 5, 10, 15, 20 and Y = Sb or In) chalcogenide glasses were investigatedmore » utilizing the Z-scan method at the wavelength of 800 nm and their linear optical properties and structure were also studied. By analyzing the compositional dependences and possible influencing factors including the linear refractive index, the concentration of lone electron pairs, the optical bandgap and the amount of weak covalent/homopolar bonds, it indicates that the electronic contribution in weak heteropolar covalent and homopolar metallic bonds is responsible for large nonlinear refractive index n{sub 2} in the chalcogenide glasses. These chalcogenide glasses have characteristics of environmentally friendship, wide transparency in the visible region, high nonlinear refractive index n{sub 2} and low nonlinear absorption coefficient {beta}, and would be expected to be used in the all-optical switches working at 1330 nm and 1550 nm telecommunication wavelengths.« less

Anticipating Mathematics Performance: A Cross-Validation Comparison of AID3 and Regression. AIR 1988 Annual Forum Paper.

ERIC Educational Resources Information Center

Bloom, Allan M.; And Others

In response to the increasing importance of student performance in required classes, research was conducted to compare two prediction procedures, linear modeling using multiple regression and nonlinear modeling using AID3. Performance in the first college math course (College Mathematics, Calculus, or Business Calculus Matrices) was the dependent…

Modeling maximum daily temperature using a varying coefficient regression model

Treesearch

Han Li; Xinwei Deng; Dong-Yum Kim; Eric P. Smith

2014-01-01

Relationships between stream water and air temperatures are often modeled using linear or nonlinear regression methods. Despite a strong relationship between water and air temperatures and a variety of models that are effective for data summarized on a weekly basis, such models did not yield consistently good predictions for summaries such as daily maximum temperature...

Naval Research Logistics Quarterly. Volume 28. Number 3,

DTIC Science & Technology

1981-09-01

denotes component-wise maximum. f has antone (isotone) differences on C x D if for cl < c2 and d, < d2, NAVAL RESEARCH LOGISTICS QUARTERLY VOL. 28...or negative correlations and linear or nonlinear regressions. Given are the mo- ments to order two and, for special cases, (he regression function and...data sets. We designate this bnb distribution as G - B - N(a, 0, v). The distribution admits only of positive correlation and linear regressions

Use of instrumental variables in the analysis of generalized linear models in the presence of unmeasured confounding with applications to epidemiological research.

PubMed

Johnston, K M; Gustafson, P; Levy, A R; Grootendorst, P

2008-04-30

A major, often unstated, concern of researchers carrying out epidemiological studies of medical therapy is the potential impact on validity if estimates of treatment are biased due to unmeasured confounders. One technique for obtaining consistent estimates of treatment effects in the presence of unmeasured confounders is instrumental variables analysis (IVA). This technique has been well developed in the econometrics literature and is being increasingly used in epidemiological studies. However, the approach to IVA that is most commonly used in such studies is based on linear models, while many epidemiological applications make use of non-linear models, specifically generalized linear models (GLMs) such as logistic or Poisson regression. Here we present a simple method for applying IVA within the class of GLMs using the generalized method of moments approach. We explore some of the theoretical properties of the method and illustrate its use within both a simulation example and an epidemiological study where unmeasured confounding is suspected to be present. We estimate the effects of beta-blocker therapy on one-year all-cause mortality after an incident hospitalization for heart failure, in the absence of data describing disease severity, which is believed to be a confounder. 2008 John Wiley & Sons, Ltd

Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder (ADHD).

PubMed

Poil, S-S; Bollmann, S; Ghisleni, C; O'Gorman, R L; Klaver, P; Ball, J; Eich-Höchli, D; Brandeis, D; Michels, L

2014-08-01

Objective biomarkers for attention-deficit/hyperactivity disorder (ADHD) could improve diagnostics or treatment monitoring of this psychiatric disorder. The resting electroencephalogram (EEG) provides non-invasive spectral markers of brain function and development. Their accuracy as ADHD markers is increasingly questioned but may improve with pattern classification. This study provides an integrated analysis of ADHD and developmental effects in children and adults using regression analysis and support vector machine classification of spectral resting (eyes-closed) EEG biomarkers in order to clarify their diagnostic value. ADHD effects on EEG strongly depend on age and frequency. We observed typical non-linear developmental decreases in delta and theta power for both ADHD and control groups. However, for ADHD adults we found a slowing in alpha frequency combined with a higher power in alpha-1 (8-10Hz) and beta (13-30Hz). Support vector machine classification of ADHD adults versus controls yielded a notable cross validated sensitivity of 67% and specificity of 83% using power and central frequency from all frequency bands. ADHD children were not classified convincingly with these markers. Resting state electrophysiology is altered in ADHD, and these electrophysiological impairments persist into adulthood. Spectral biomarkers may have both diagnostic and prognostic value. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Nonlinear System Identification for Aeroelastic Systems with Application to Experimental Data

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2008-01-01

Representation and identification of a nonlinear aeroelastic pitch-plunge system as a model of the Nonlinear AutoRegressive, Moving Average eXogenous (NARMAX) class is considered. A nonlinear difference equation describing this aircraft model is derived theoretically and shown to be of the NARMAX form. Identification methods for NARMAX models are applied to aeroelastic dynamics and its properties demonstrated via continuous-time simulations of experimental conditions. Simulation results show that (1) the outputs of the NARMAX model closely match those generated using continuous-time methods, and (2) NARMAX identification methods applied to aeroelastic dynamics provide accurate discrete-time parameter estimates. Application of NARMAX identification to experimental pitch-plunge dynamics data gives a high percent fit for cross-validated data.

Boosting structured additive quantile regression for longitudinal childhood obesity data.

PubMed

Fenske, Nora; Fahrmeir, Ludwig; Hothorn, Torsten; Rzehak, Peter; Höhle, Michael

2013-07-25

Childhood obesity and the investigation of its risk factors has become an important public health issue. Our work is based on and motivated by a German longitudinal study including 2,226 children with up to ten measurements on their body mass index (BMI) and risk factors from birth to the age of 10 years. We introduce boosting of structured additive quantile regression as a novel distribution-free approach for longitudinal quantile regression. The quantile-specific predictors of our model include conventional linear population effects, smooth nonlinear functional effects, varying-coefficient terms, and individual-specific effects, such as intercepts and slopes. Estimation is based on boosting, a computer intensive inference method for highly complex models. We propose a component-wise functional gradient descent boosting algorithm that allows for penalized estimation of the large variety of different effects, particularly leading to individual-specific effects shrunken toward zero. This concept allows us to flexibly estimate the nonlinear age curves of upper quantiles of the BMI distribution, both on population and on individual-specific level, adjusted for further risk factors and to detect age-varying effects of categorical risk factors. Our model approach can be regarded as the quantile regression analog of Gaussian additive mixed models (or structured additive mean regression models), and we compare both model classes with respect to our obesity data.

Economic benefits associated with beta blocker persistence in the treatment of hypertension: a retrospective database analysis.

PubMed

Chen, Stephanie; Swallow, Elyse; Li, Nanxin; Faust, Elizabeth; Kelley, Caroline; Xie, Jipan; Wu, Eric

2015-04-01

To assess the association between medical costs and persistence with beta blockers among hypertensive patients, and to quantify persistence related medical cost differences with nebivolol, which is associated with improved tolerability, versus other beta blockers. Adults who initiated hypertension treatment with a beta blocker were identified from the MarketScan * claims database (2008-2012). Patients were classified based on their first beta blocker use: nebivolol, atenolol, carvedilol, metoprolol, and other beta blockers. Patients with compelling indications for atenolol, carvedilol or metoprolol (acute coronary syndrome and congestive heart failure) were excluded. Patients enrolled in health maintenance organization or capitated point of service insurance plans were also excluded. Persistence was defined as continuous use of the index drug (<60 day gap). The average effect of persistence on medical costs (2012 USD) was estimated using generalized linear models (GLMs). Regression estimates were used to predict medical cost differences associated with persistence between nebivolol and the other cohorts. A total of 587,424 hypertensive patients met the inclusion criteria. Each additional month of persistence with any one beta blocker was associated with $152.51 in all-cause medical cost savings; continuous treatment for 1 year was associated with $1585.98 in all-cause medical cost savings. Patients treated with nebivolol had longer persistence during the 1 year study period (median: 315 days) than all other beta blockers (median: 156-292 days). Longer persistence with nebivolol translated into $305.74 all-cause medical cost savings relative to all other beta blockers. The results may not be generalizable to hypertensive patients with acute coronary syndrome or congestive heart failure. Longer persistence with beta blockers for the treatment of hypertension was associated with lower medical costs. There may be greater cost savings due to better persistence with nebivolol than other beta blockers.

Resolving model parameter values from carbon and nitrogen stock measurements in a wide range of tropical mature forests using nonlinear inversion and regression trees

Treesearch

Shuguang Liua; Pamela Anderson; Guoyi Zhoud; Boone Kauffman; Flint Hughes; David Schimel; Vicente Watson; Joseph Tosi

2008-01-01

Objectively assessing the performance of a model and deriving model parameter values from observations are critical and challenging in landscape to regional modeling. In this paper, we applied a nonlinear inversion technique to calibrate the ecosystem model CENTURY against carbon (C) and nitrogen (N) stock measurements collected from 39 mature tropical forest sites in...

Linear and non-linear regression analysis for the sorption kinetics of methylene blue onto activated carbon.

PubMed

Kumar, K Vasanth

2006-10-11

Batch kinetic experiments were carried out for the sorption of methylene blue onto activated carbon. The experimental kinetics were fitted to the pseudo first-order and pseudo second-order kinetics by linear and a non-linear method. The five different types of Ho pseudo second-order expression have been discussed. A comparison of linear least-squares method and a trial and error non-linear method of estimating the pseudo second-order rate kinetic parameters were examined. The sorption process was found to follow a both pseudo first-order kinetic and pseudo second-order kinetic model. Present investigation showed that it is inappropriate to use a type 1 and type pseudo second-order expressions as proposed by Ho and Blanachard et al. respectively for predicting the kinetic rate constants and the initial sorption rate for the studied system. Three correct possible alternate linear expressions (type 2 to type 4) to better predict the initial sorption rate and kinetic rate constants for the studied system (methylene blue/activated carbon) was proposed. Linear method was found to check only the hypothesis instead of verifying the kinetic model. Non-linear regression method was found to be the more appropriate method to determine the rate kinetic parameters.

[Relationship between shift work and overweight/obesity in male steel workers].

PubMed

Xiao, M Y; Wang, Z Y; Fan, H M; Che, C L; Lu, Y; Cong, L X; Gao, X J; Liu, Y J; Yuan, J X; Li, X M; Hu, B; Chen, Y P

2016-11-10

Objective: To investigate the relationship between shift work and overweight/obesity in male steel workers. Methods: A questionnaire survey was conducted among the male steel workers selected during health examination in Tangshan Steel Company from March 2015 to March 2016. The relationship between shift work and overweight/obesity in the male steel workers were analyzed by using logistic regression model and restricted cubic splinemodel. Results: A total of 7 262 male steel workers were surveyed, the overall prevalence of overweight/obesitywas 64.5% (4 686/7 262), the overweight rate was 34.3% and the obesity rate was 30.2%, respectively. After adjusting for age, educational level and average family income level per month by multivariable logistic regression analysis, shift work was associated with overweight/obesity and obesity in the male steel workers. The OR was 1.19(95% CI : 1.05-1.35) and 1.15(95% CI : 1.00-1.32). Restricted cubic spline model analysis showed that the relationship between shift work years and overweight/obesity in the male steel workers was a nonlinear dose response one (nonlinear test χ 2 =7.43, P <0.05). Restricted cubic spline model analysis showed that the relationship between shift work years and obesity in the male steel workers was a nonlinear dose response one (nonlinear test χ 2 =10.48, P <0.05). Conclusion: Shift work was associated with overweight and obesity in the male steel workers, and shift work years and overweight/obesity had a nonlinear relationship.

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws.

PubMed

Xiao, Xiao; White, Ethan P; Hooten, Mevin B; Durham, Susan L

2011-10-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.

In vitro evaluation of Augmentin by broth microdilution and disk diffusion susceptibility testing: regression analysis, tentative interpretive criteria, and quality control limits.

PubMed Central

Fuchs, P C; Barry, A L; Thornsberry, C; Gavan, T L; Jones, R N

1983-01-01

Augmentin (Beecham Laboratories, Bristol, Tenn.), a combination drug consisting of two parts amoxicillin to one part clavulanic acid and a potent beta-lactamase inhibitor, was evaluated in vitro in comparison with ampicillin or amoxicillin or both for its inhibitory and bactericidal activities against selected clinical isolates. Regression analysis was performed and tentative disk diffusion susceptibility breakpoints were determined. A multicenter performance study of the disk diffusion test was conducted with three quality control organisms to determine tentative quality control limits. All methicillin-susceptible staphylococci and Haemophilus influenzae isolates were susceptible to Augmentin, although the minimal inhibitory concentrations for beta-lactamase-producing strains of both groups were, on the average, fourfold higher than those for enzyme-negative strains. Among the Enterobacteriaceae, Augmentin exhibited significantly greater activity than did ampicillin against Klebsiella pneumoniae, Citrobacter diversus, Proteus vulgaris, and about one-third of the Escherichia coli strains tested. Bactericidal activity usually occurred at the minimal inhibitory concentration. There was a slight inoculum concentration effect on the Augmentin minimal inhibitory concentrations. On the basis of regression and error rate-bounded analyses, the suggested interpretive disk diffusion susceptibility breakpoints for Augmentin are: susceptible, greater than or equal to 18 mm; resistant, less than or equal to 13 mm (gram-negative bacilli); and susceptible, greater than or equal to 20 mm (staphylococci and H. influenzae). The use of a beta-lactamase-producing organism, such as E. coli Beecham 1532, is recommended for quality assurance of Augmentin susceptibility testing. PMID:6625554

A statistical methodology for estimating transport parameters: Theory and applications to one-dimensional advectivec-dispersive systems

USGS Publications Warehouse

Wagner, Brian J.; Gorelick, Steven M.

1986-01-01

A simulation nonlinear multiple-regression methodology for estimating parameters that characterize the transport of contaminants is developed and demonstrated. Finite difference contaminant transport simulation is combined with a nonlinear weighted least squares multiple-regression procedure. The technique provides optimal parameter estimates and gives statistics for assessing the reliability of these estimates under certain general assumptions about the distributions of the random measurement errors. Monte Carlo analysis is used to estimate parameter reliability for a hypothetical homogeneous soil column for which concentration data contain large random measurement errors. The value of data collected spatially versus data collected temporally was investigated for estimation of velocity, dispersion coefficient, effective porosity, first-order decay rate, and zero-order production. The use of spatial data gave estimates that were 2–3 times more reliable than estimates based on temporal data for all parameters except velocity. Comparison of estimated linear and nonlinear confidence intervals based upon Monte Carlo analysis showed that the linear approximation is poor for dispersion coefficient and zero-order production coefficient when data are collected over time. In addition, examples demonstrate transport parameter estimation for two real one-dimensional systems. First, the longitudinal dispersivity and effective porosity of an unsaturated soil are estimated using laboratory column data. We compare the reliability of estimates based upon data from individual laboratory experiments versus estimates based upon pooled data from several experiments. Second, the simulation nonlinear regression procedure is extended to include an additional governing equation that describes delayed storage during contaminant transport. The model is applied to analyze the trends, variability, and interrelationship of parameters in a mourtain stream in northern California.

More green space is related to less antidepressant prescription rates in the Netherlands: A Bayesian geoadditive quantile regression approach.

PubMed

Helbich, Marco; Klein, Nadja; Roberts, Hannah; Hagedoorn, Paulien; Groenewegen, Peter P

2018-06-20

Exposure to green space seems to be beneficial for self-reported mental health. In this study we used an objective health indicator, namely antidepressant prescription rates. Current studies rely exclusively upon mean regression models assuming linear associations. It is, however, plausible that the presence of green space is non-linearly related with different quantiles of the outcome antidepressant prescription rates. These restrictions may contribute to inconsistent findings. Our aim was: a) to assess antidepressant prescription rates in relation to green space, and b) to analyze how the relationship varies non-linearly across different quantiles of antidepressant prescription rates. We used cross-sectional data for the year 2014 at a municipality level in the Netherlands. Ecological Bayesian geoadditive quantile regressions were fitted for the 15%, 50%, and 85% quantiles to estimate green space-prescription rate correlations, controlling for physical activity levels, socio-demographics, urbanicity, etc. RESULTS: The results suggested that green space was overall inversely and non-linearly associated with antidepressant prescription rates. More important, the associations differed across the quantiles, although the variation was modest. Significant non-linearities were apparent: The associations were slightly positive in the lower quantile and strongly negative in the upper one. Our findings imply that an increased availability of green space within a municipality may contribute to a reduction in the number of antidepressant prescriptions dispensed. Green space is thus a central health and community asset, whilst a minimum level of 28% needs to be established for health gains. The highest effectiveness occurred at a municipality surface percentage higher than 79%. This inverse dose-dependent relation has important implications for setting future community-level health and planning policies. Copyright © 2018 Elsevier Inc. All rights reserved.

Mid-IR femtosecond frequency conversion by soliton-probe collision in phase-mismatched quadratic nonlinear crystals.

PubMed

Liu, Xing; Zhou, Binbin; Guo, Hairun; Bache, Morten

2015-08-15

We show numerically that ultrashort self-defocusing temporal solitons colliding with a weak pulsed probe in the near-IR can convert the probe to the mid-IR. A near-perfect conversion efficiency is possible for a high effective soliton order. The near-IR self-defocusing soliton can form in a quadratic nonlinear crystal (beta-barium borate) in the normal dispersion regime due to cascaded (phase-mismatched) second-harmonic generation, and the mid-IR converted wave is formed in the anomalous dispersion regime between λ=2.2-2.4  μm as a resonant dispersive wave. This process relies on nondegenerate four-wave mixing mediated by an effective negative cross-phase modulation term caused by cascaded soliton-probe sum-frequency generation.

A robust direct-integration method for rotorcraft maneuver and periodic response

NASA Technical Reports Server (NTRS)

Panda, Brahmananda

1992-01-01

The Newmark-Beta method and the Newton-Raphson iteration scheme are combined to develop a direct-integration method for evaluating the maneuver and periodic-response expressions for rotorcraft. The method requires the generation of Jacobians and includes higher derivatives in the formulation of the geometric stiffness matrix to enhance the convergence of the system. The method leads to effective convergence with nonlinear structural dynamics and aerodynamic terms. Singularities in the matrices can be addressed with the method as they arise from a Lagrange multiplier approach for coupling equations with nonlinear constraints. The method is also shown to be general enough to handle singularities from quasisteady control-system models. The method is shown to be more general and robust than the similar 2GCHAS method for analyzing rotorcraft dynamics.

Two-dimensional magnetohydrodynamic model of emerging magnetic flux in the solar atmosphere

NASA Technical Reports Server (NTRS)

Shibata, K.; Tajima, T.; Steinolfson, R. S.; Matsumoto, R.

1989-01-01

The nonlinear undular mode of the magnetic buoyancy instability in an isolated horizontal magnetic flux embedded in a two-temperature layered atmosphere (solar corona-chromosphere/photosphere) is investigated using a two-dimensional magnetohydrodynamic code. The results show that the flux sheet with beta of about 1 is initially located at the bottom of the photosphere, and that the gas slides down the expanding loop as the instability develops, with the evacuated loop rising as a result of enhanced magnetic buoyancy. The expansion of the magnetic loop in the nonlinear regime displays self-similar behavior. The rise velocity of the magnetic loop in the high chromosphere (10-15 km/s) and the velocity of downflow noted along the loop (30-50 km/s) are consistent with observed values for arch filament systems.

A METHOD TO EXTRACT THE REDSHIFT DISTORTION {beta} PARAMETER IN CONFIGURATION SPACE FROM MINIMAL COSMOLOGICAL ASSUMPTIONS

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

Tocchini-Valentini, Domenico; Barnard, Michael; Bennett, Charles L.

2012-10-01

We present a method to extract the redshift-space distortion {beta} parameter in configuration space with a minimal set of cosmological assumptions. We show that a novel combination of the observed monopole and quadrupole correlation functions can remove efficiently the impact of mild nonlinearities and redshift errors. The method offers a series of convenient properties: it does not depend on the theoretical linear correlation function, the mean galaxy density is irrelevant, only convolutions are used, and there is no explicit dependence on linear bias. Analyses based on dark matter N-body simulations and Fisher matrix demonstrate that errors of a few percentmore » on {beta} are possible with a full-sky, 1 (h {sup -1} Gpc){sup 3} survey centered at a redshift of unity and with negligible shot noise. We also find a baryonic feature in the normalized quadrupole in configuration space that should complicate the extraction of the growth parameter from the linear theory asymptote, but that does not have a major impact on our method.« less

Self-consistent asset pricing models

NASA Astrophysics Data System (ADS)

Malevergne, Y.; Sornette, D.

2007-08-01

We discuss the foundations of factor or regression models in the light of the self-consistency condition that the market portfolio (and more generally the risk factors) is (are) constituted of the assets whose returns it is (they are) supposed to explain. As already reported in several articles, self-consistency implies correlations between the return disturbances. As a consequence, the alphas and betas of the factor model are unobservable. Self-consistency leads to renormalized betas with zero effective alphas, which are observable with standard OLS regressions. When the conditions derived from internal consistency are not met, the model is necessarily incomplete, which means that some sources of risk cannot be replicated (or hedged) by a portfolio of stocks traded on the market, even for infinite economies. Analytical derivations and numerical simulations show that, for arbitrary choices of the proxy which are different from the true market portfolio, a modified linear regression holds with a non-zero value αi at the origin between an asset i's return and the proxy's return. Self-consistency also introduces “orthogonality” and “normality” conditions linking the betas, alphas (as well as the residuals) and the weights of the proxy portfolio. Two diagnostics based on these orthogonality and normality conditions are implemented on a basket of 323 assets which have been components of the S&P500 in the period from January 1990 to February 2005. These two diagnostics show interesting departures from dynamical self-consistency starting about 2 years before the end of the Internet bubble. Assuming that the CAPM holds with the self-consistency condition, the OLS method automatically obeys the resulting orthogonality and normality conditions and therefore provides a simple way to self-consistently assess the parameters of the model by using proxy portfolios made only of the assets which are used in the CAPM regressions. Finally, the factor decomposition with the self-consistency condition derives a risk-factor decomposition in the multi-factor case which is identical to the principal component analysis (PCA), thus providing a direct link between model-driven and data-driven constructions of risk factors. This correspondence shows that PCA will therefore suffer from the same limitations as the CAPM and its multi-factor generalization, namely lack of out-of-sample explanatory power and predictability. In the multi-period context, the self-consistency conditions force the betas to be time-dependent with specific constraints.

Advances in simultaneous atmospheric profile and cloud parameter regression based retrieval from high-spectral resolution radiance measurements

NASA Astrophysics Data System (ADS)

Weisz, Elisabeth; Smith, William L.; Smith, Nadia

2013-06-01

The dual-regression (DR) method retrieves information about the Earth surface and vertical atmospheric conditions from measurements made by any high-spectral resolution infrared sounder in space. The retrieved information includes temperature and atmospheric gases (such as water vapor, ozone, and carbon species) as well as surface and cloud top parameters. The algorithm was designed to produce a high-quality product with low latency and has been demonstrated to yield accurate results in real-time environments. The speed of the retrieval is achieved through linear regression, while accuracy is achieved through a series of classification schemes and decision-making steps. These steps are necessary to account for the nonlinearity of hyperspectral retrievals. In this work, we detail the key steps that have been developed in the DR method to advance accuracy in the retrieval of nonlinear parameters, specifically cloud top pressure. The steps and their impact on retrieval results are discussed in-depth and illustrated through relevant case studies. In addition to discussing and demonstrating advances made in addressing nonlinearity in a linear geophysical retrieval method, advances toward multi-instrument geophysical analysis by applying the DR to three different operational sounders in polar orbit are also noted. For any area on the globe, the DR method achieves consistent accuracy and precision, making it potentially very valuable to both the meteorological and environmental user communities.

Delineating chalk sand distribution of Ekofisk formation using probabilistic neural network (PNN) and stepwise regression (SWR): Case study Danish North Sea field

NASA Astrophysics Data System (ADS)

Haris, A.; Nafian, M.; Riyanto, A.

2017-07-01

Danish North Sea Fields consist of several formations (Ekofisk, Tor, and Cromer Knoll) that was started from the age of Paleocene to Miocene. In this study, the integration of seismic and well log data set is carried out to determine the chalk sand distribution in the Danish North Sea field. The integration of seismic and well log data set is performed by using the seismic inversion analysis and seismic multi-attribute. The seismic inversion algorithm, which is used to derive acoustic impedance (AI), is model-based technique. The derived AI is then used as external attributes for the input of multi-attribute analysis. Moreover, the multi-attribute analysis is used to generate the linear and non-linear transformation of among well log properties. In the case of the linear model, selected transformation is conducted by weighting step-wise linear regression (SWR), while for the non-linear model is performed by using probabilistic neural networks (PNN). The estimated porosity, which is resulted by PNN shows better suited to the well log data compared with the results of SWR. This result can be understood since PNN perform non-linear regression so that the relationship between the attribute data and predicted log data can be optimized. The distribution of chalk sand has been successfully identified and characterized by porosity value ranging from 23% up to 30%.

Wave excitation by nonlinear coupling among shear Alfvén waves in a mirror-confined plasma

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

Ikezoe, R., E-mail: ikezoe@prc.tsukuba.ac.jp; Ichimura, M.; Okada, T.

2015-09-15

A shear Alfvén wave at slightly below the ion-cyclotron frequency overcomes the ion-cyclotron damping and grows because of the strong anisotropy of the ion temperature in the magnetic mirror configuration, and is called the Alfvén ion-cyclotron (AIC) wave. Density fluctuations caused by the AIC waves and the ion-cyclotron range of frequencies (ICRF) waves used for ion heating have been detected using a reflectometer in a wide radial region of the GAMMA 10 tandem mirror plasma. Various wave-wave couplings are clearly observed in the density fluctuations in the interior of the plasma, but these couplings are not so clear in themore » magnetic fluctuations at the plasma edge when measured using a pick-up coil. A radial dependence of the nonlinearity is found, particularly in waves with the difference frequencies of the AIC waves; bispectral analysis shows that such wave-wave coupling is significant near the core, but is not so evident at the periphery. In contrast, nonlinear coupling with the low-frequency background turbulence is quite distinct at the periphery. Nonlinear coupling associated with the AIC waves may play a significant role in the beta- and anisotropy-limits of a mirror-confined plasma through decay of the ICRF heating power and degradation of the plasma confinement by nonlinearly generated waves.« less

Kinetic theory of turbulence for parallel propagation revisited: Low-to-intermediate frequency regime

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

Yoon, Peter H., E-mail: yoonp@umd.edu; School of Space Research, Kyung Hee University, Yongin, Gyeonggi 446-701

2015-09-15

A previous paper [P. H. Yoon, “Kinetic theory of turbulence for parallel propagation revisited: Formal results,” Phys. Plasmas 22, 082309 (2015)] revisited the second-order nonlinear kinetic theory for turbulence propagating in directions parallel/anti-parallel to the ambient magnetic field, in which the original work according to Yoon and Fang [Phys. Plasmas 15, 122312 (2008)] was refined, following the paper by Gaelzer et al. [Phys. Plasmas 22, 032310 (2015)]. The main finding involved the dimensional correction pertaining to discrete-particle effects in Yoon and Fang's theory. However, the final result was presented in terms of formal linear and nonlinear susceptibility response functions. Inmore » the present paper, the formal equations are explicitly written down for the case of low-to-intermediate frequency regime by making use of approximate forms for the response functions. The resulting equations are sufficiently concrete so that they can readily be solved by numerical means or analyzed by theoretical means. The derived set of equations describe nonlinear interactions of quasi-parallel modes whose frequency range covers the Alfvén wave range to ion-cyclotron mode, but is sufficiently lower than the electron cyclotron mode. The application of the present formalism may range from the nonlinear evolution of whistler anisotropy instability in the high-beta regime, and the nonlinear interaction of electrons with whistler-range turbulence.« less

Localization and identification of structural nonlinearities using cascaded optimization and neural networks

NASA Astrophysics Data System (ADS)

Koyuncu, A.; Cigeroglu, E.; Özgüven, H. N.

2017-10-01

In this study, a new approach is proposed for identification of structural nonlinearities by employing cascaded optimization and neural networks. Linear finite element model of the system and frequency response functions measured at arbitrary locations of the system are used in this approach. Using the finite element model, a training data set is created, which appropriately spans the possible nonlinear configurations space of the system. A classification neural network trained on these data sets then localizes and determines the types of all nonlinearities associated with the nonlinear degrees of freedom in the system. A new training data set spanning the parametric space associated with the determined nonlinearities is created to facilitate parametric identification. Utilizing this data set, initially, a feed forward regression neural network is trained, which parametrically identifies the classified nonlinearities. Then, the results obtained are further improved by carrying out an optimization which uses network identified values as starting points. Unlike identification methods available in literature, the proposed approach does not require data collection from the degrees of freedoms where nonlinear elements are attached, and furthermore, it is sufficiently accurate even in the presence of measurement noise. The application of the proposed approach is demonstrated on an example system with nonlinear elements and on a real life experimental setup with a local nonlinearity.

The Changing Nonlinear Relationship between Income and Terrorism

PubMed Central

Enders, Walter; Hoover, Gary A.

2014-01-01

This article reinvestigates the relationship between real per capita gross domestic product (GDP) and terrorism. We devise a terrorism Lorenz curve to show that domestic and transnational terrorist attacks are each more concentrated in middle-income countries, thereby suggesting a nonlinear income–terrorism relationship. Moreover, this point of concentration shifted to lower income countries after the rising influence of the religious fundamentalist and nationalist/separatist terrorists in the early 1990s. For transnational terrorist attacks, this shift characterized not only the attack venue but also the perpetrators’ nationality. The article then uses nonlinear smooth transition regressions to establish the relationship between real per capita GDP and terrorism for eight alternative terrorism samples, accounting for venue, perpetrators’ nationality, terrorism type, and the period. Our nonlinear estimates are shown to be favored over estimates using linear or quadratic income determinants of terrorism. These nonlinear estimates are robust to additional controls. PMID:28579636

Model-free inference of direct network interactions from nonlinear collective dynamics.

PubMed

Casadiego, Jose; Nitzan, Mor; Hallerberg, Sarah; Timme, Marc

2017-12-19

The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

Using nonlinear quantile regression to estimate the self-thinning boundary curve

Treesearch

Quang V. Cao; Thomas J. Dean

2015-01-01

The relationship between tree size (quadratic mean diameter) and tree density (number of trees per unit area) has been a topic of research and discussion for many decades. Starting with Reineke in 1933, the maximum size-density relationship, on a log-log scale, has been assumed to be linear. Several techniques, including linear quantile regression, have been employed...

A New SEYHAN's Approach in Case of Heterogeneity of Regression Slopes in ANCOVA.

PubMed

Ankarali, Handan; Cangur, Sengul; Ankarali, Seyit

2018-06-01

In this study, when the assumptions of linearity and homogeneity of regression slopes of conventional ANCOVA are not met, a new approach named as SEYHAN has been suggested to use conventional ANCOVA instead of robust or nonlinear ANCOVA. The proposed SEYHAN's approach involves transformation of continuous covariate into categorical structure when the relationship between covariate and dependent variable is nonlinear and the regression slopes are not homogenous. A simulated data set was used to explain SEYHAN's approach. In this approach, we performed conventional ANCOVA in each subgroup which is constituted according to knot values and analysis of variance with two-factor model after MARS method was used for categorization of covariate. The first model is a simpler model than the second model that includes interaction term. Since the model with interaction effect has more subjects, the power of test also increases and the existing significant difference is revealed better. We can say that linearity and homogeneity of regression slopes are not problem for data analysis by conventional linear ANCOVA model by helping this approach. It can be used fast and efficiently for the presence of one or more covariates.

The Influential Effect of Blending, Bump, Changing Period, and Eclipsing Cepheids on the Leavitt Law

NASA Astrophysics Data System (ADS)

García-Varela, A.; Muñoz, J. R.; Sabogal, B. E.; Vargas Domínguez, S.; Martínez, J.

2016-06-01

The investigation of the nonlinearity of the Leavitt law (LL) is a topic that began more than seven decades ago, when some of the studies in this field found that the LL has a break at about 10 days. The goal of this work is to investigate a possible statistical cause of this nonlinearity. By applying linear regressions to OGLE-II and OGLE-IV data, we find that to obtain the LL by using linear regression, robust techniques to deal with influential points and/or outliers are needed instead of the ordinary least-squares regression traditionally used. In particular, by using M- and MM-regressions we establish firmly and without doubt the linearity of the LL in the Large Magellanic Cloud, without rejecting or excluding Cepheid data from the analysis. This implies that light curves of Cepheids suggesting blending, bumps, eclipses, or period changes do not affect the LL for this galaxy. For the Small Magellanic Cloud, when including Cepheids of this kind, it is not possible to find an adequate model, probably because of the geometry of the galaxy. In that case, a possible influence of these stars could exist.

Higher-order Multivariable Polynomial Regression to Estimate Human Affective States

NASA Astrophysics Data System (ADS)

Wei, Jie; Chen, Tong; Liu, Guangyuan; Yang, Jiemin

2016-03-01

From direct observations, facial, vocal, gestural, physiological, and central nervous signals, estimating human affective states through computational models such as multivariate linear-regression analysis, support vector regression, and artificial neural network, have been proposed in the past decade. In these models, linear models are generally lack of precision because of ignoring intrinsic nonlinearities of complex psychophysiological processes; and nonlinear models commonly adopt complicated algorithms. To improve accuracy and simplify model, we introduce a new computational modeling method named as higher-order multivariable polynomial regression to estimate human affective states. The study employs standardized pictures in the International Affective Picture System to induce thirty subjects’ affective states, and obtains pure affective patterns of skin conductance as input variables to the higher-order multivariable polynomial model for predicting affective valence and arousal. Experimental results show that our method is able to obtain efficient correlation coefficients of 0.98 and 0.96 for estimation of affective valence and arousal, respectively. Moreover, the method may provide certain indirect evidences that valence and arousal have their brain’s motivational circuit origins. Thus, the proposed method can serve as a novel one for efficiently estimating human affective states.

Higher-order Multivariable Polynomial Regression to Estimate Human Affective States

PubMed Central

Wei, Jie; Chen, Tong; Liu, Guangyuan; Yang, Jiemin

2016-01-01

From direct observations, facial, vocal, gestural, physiological, and central nervous signals, estimating human affective states through computational models such as multivariate linear-regression analysis, support vector regression, and artificial neural network, have been proposed in the past decade. In these models, linear models are generally lack of precision because of ignoring intrinsic nonlinearities of complex psychophysiological processes; and nonlinear models commonly adopt complicated algorithms. To improve accuracy and simplify model, we introduce a new computational modeling method named as higher-order multivariable polynomial regression to estimate human affective states. The study employs standardized pictures in the International Affective Picture System to induce thirty subjects’ affective states, and obtains pure affective patterns of skin conductance as input variables to the higher-order multivariable polynomial model for predicting affective valence and arousal. Experimental results show that our method is able to obtain efficient correlation coefficients of 0.98 and 0.96 for estimation of affective valence and arousal, respectively. Moreover, the method may provide certain indirect evidences that valence and arousal have their brain’s motivational circuit origins. Thus, the proposed method can serve as a novel one for efficiently estimating human affective states. PMID:26996254

Relationship of cognitive and perceptual abilities to functional independence in adults who have had a stroke.

PubMed

Brown, Ted; Mapleston, Jennifer; Nairn, Allison; Molloy, Andrew

2013-03-01

Most individuals who have had a stroke present with some degree of residual cognitive and/or perceptual impairment. Occupational therapists often utilize standardized cognitive and perceptual assessments with clients to establish a baseline of skill performance as well as to inform goal setting and intervention planning. Being able to predict the functional independence of individuals who have had a stroke based on cognitive and perceptual impairments would assist with appropriate discharge planning and follow-up resource allocation. The study objective was to investigate the ability of the Developmental Test of Visual Perception - Adolescents and Adults (DTVP-A) and the Neurobehavioural Cognitive Status Exam (Cognistat) to predict the functional performance as measured by the Barthel Index of individuals who have had a stroke. Data was collected using the DTVP-A, Cognistat and the Barthal Index from 32 adults recovering from stroke. Two standard multiple regression models were used to determine predictive variables of the functional independence dependent variable. Both the Cognistat and DTVP-A had a statistically significant ability to predict functional performance (as measured by the Barthel Index) accounting for 64.4% and 27.9% of each regression model, respectively. Two Cognistat subscales (Comprehension [beta = 0.48; p < 0.001)] and Repetition [beta = 0.45; p < 0.004]) and one DTVP-A subscale (Copying [beta = 0.46; p < 0.014]) made statistically significant contributions to the regression models as independent variables. On the basis of the regression model findings, it appears that DTVP-A's Copying and the Cognistat's Comprehension and Repetition subscales are useful in predicting the functional independence (as measured by the Barthel Index) in those individuals who have had a stroke. Given the fundamental importance that cognition and perception has for one's ability to function independently, further investigation is warranted to determine other predictors of functional performance of individuals with a stroke. Copyright © 2012 John Wiley & Sons, Ltd.

On the interannual oscillations in the northern temperate total ozone

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

Krzyscin, J.W.

1994-07-01

The interannual variations in total ozone are studied using revised Dobson total ozone records (1961-1990) from 17 stations located within the latitude band 30 deg N - 60 deg N. To obtain the quasi-biennial oscillation (QBO), El Nino-Southern Oscillation (ENSO), and 11-year solar cycle manifestation in the `northern temperate` total ozone data, various multiple regression models are constructed by the least squares fitting to the observed ozone. The statistical relationships between the selected indices of the atmospheric variabilities and total ozone are described in the linear and nonlinear regression models. Nonlinear relationships to the predictor variables are found. That is,more » the total ozone variations are statistically modeled by nonlinear terms accounting for the coupling between QBO and ENSO, QBO and solar activity, and ENSO and solar activity. It is suggested that large reduction of total ozone values over the `northern temperate` region occurs in cold season when a strong ENSO warm event meets the west phase of the QBO during the period of high solar activity.« less

MATERNAL CHRONOLOGICAL AGE, PRENATAL AND PERINATAL HISTORY, SOCIAL SUPPORT, AND PARENTING OF INFANTS

PubMed Central

Bornstein, Marc H.; Putnick, Diane L.; Suwalsky, Joan T. D.; Gini, Motti

2018-01-01

The role of maternal chronological age in prenatal and perinatal history, social support, and parenting practices of new mothers (N = 335) was examined. Primiparas of 5-month-old infants ranged in age from 13 to 42 years. Age effects were zero, linear, and nonlinear. Nonlinear age effects were significantly associated up to a certain age with little or no association afterward; by spline regression, estimated points at which the slope of the regression line changed were 25 years for prenatal and perinatal history, 31 years for social supports, and 27 years for parenting practices. Given the expanding age range of first-time parents, these findings underscore the importance of incorporating maternal age as a factor in studies of parenting and child development. PMID:16942495

Tools to Support Interpreting Multiple Regression in the Face of Multicollinearity

PubMed Central

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K.

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses. PMID:22457655

Tools to support interpreting multiple regression in the face of multicollinearity.

PubMed

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses.

Interaction of ibogaine with human alpha3beta4-nicotinic acetylcholine receptors in different conformational states.

PubMed

Arias, Hugo R; Rosenberg, Avraham; Targowska-Duda, Katarzyna M; Feuerbach, Dominik; Yuan, Xiao Juan; Jozwiak, Krzysztof; Moaddel, Ruin; Wainer, Irving W

2010-09-01

The interaction of ibogaine and phencyclidine (PCP) with human (h) alpha3beta4-nicotinic acetylcholine receptors (AChRs) in different conformational states was determined by functional and structural approaches including, radioligand binding assays, Ca2+ influx detections, and thermodynamic and kinetics measurements. The results established that (a) ibogaine inhibits (+/-)-epibatidine-induced Ca2+ influx in h(alpha)3beta4 AChRs with approximately 9-fold higher potency than that for PCP, (b) [3H]ibogaine binds to a single site in the h(alpha)3beta4 AChR ion channel with relatively high affinity (Kd = 0.46 +/- 0.06 microM), and ibogaine inhibits [3H]ibogaine binding to the desensitized h(alpha)3beta4 AChR with slightly higher affinity compared to the resting AChR. This is explained by a slower dissociation rate from the desensitized ion channel compared to the resting ion channel, and (c) PCP inhibits [3H]ibogaine binding to the h(alpha)3beta4 AChR, suggesting overlapping sites. The experimental results correlate with the docking simulations suggesting that ibogaine and PCP interact with a binding domain located between the serine (position 6') and valine/phenylalanine (position 13') rings. This interaction is mediated mainly by van der Waals contacts, which is in agreement with the observed enthalpic contribution determined by non-linear chromatography. However, the calculated entropic contribution also indicates local conformational changes. Collectively our data suggest that ibogaine and PCP bind to overlapping sites located between the serine and valine/phenylalanine rings, to finally block the AChR ion channel, and in the case of ibogaine, to probably maintain the AChR in the desensitized state for longer time.

Dispersive waves induced by self-defocusing temporal solitons in a beta-barium-borate crystal.

PubMed

Zhou, Binbin; Bache, Morten

2015-09-15

We experimentally observe dispersive waves in the anomalous dispersion regime of a beta-barium-borate (BBO) crystal, induced by a self-defocusing few-cycle temporal soliton. Together the soliton and dispersive waves form an energetic octave-spanning supercontinuum. The soliton was excited in the normal dispersion regime of BBO through a negative cascaded quadratic nonlinearity. Using pump wavelengths from 1.24 to 1.4 μm, dispersive waves are found from 1.9 to 2.2 μm, agreeing well with calculated resonant phase-matching wavelengths due to degenerate four-wave mixing to the soliton. We also observe resonant radiation from nondegenerate four-wave mixing between the soliton and a probe wave, which was formed by leaking part of the pump spectrum into the anomalous dispersion regime. We confirm the experimental results through simulations.

Association between Personality Traits and Sleep Quality in Young Korean Women

PubMed Central

Kim, Han-Na; Cho, Juhee; Chang, Yoosoo; Ryu, Seungho

2015-01-01

Personality is a trait that affects behavior and lifestyle, and sleep quality is an important component of a healthy life. We analyzed the association between personality traits and sleep quality in a cross-section of 1,406 young women (from 18 to 40 years of age) who were not reporting clinically meaningful depression symptoms. Surveys were carried out from December 2011 to February 2012, using the Revised NEO Personality Inventory and the Pittsburgh Sleep Quality Index (PSQI). All analyses were adjusted for demographic and behavioral variables. We considered beta weights, structure coefficients, unique effects, and common effects when evaluating the importance of sleep quality predictors in multiple linear regression models. Neuroticism was the most important contributor to PSQI global scores in the multiple regression models. By contrast, despite being strongly correlated with sleep quality, conscientiousness had a near-zero beta weight in linear regression models, because most variance was shared with other personality traits. However, conscientiousness was the most noteworthy predictor of poor sleep quality status (PSQI≥6) in logistic regression models and individuals high in conscientiousness were least likely to have poor sleep quality, which is consistent with an OR of 0.813, with conscientiousness being protective against poor sleep quality. Personality may be a factor in poor sleep quality and should be considered in sleep interventions targeting young women. PMID:26030141

Neurotoxic effects of ecstasy on the thalamus.

PubMed

de Win, Maartje M L; Jager, Gerry; Booij, Jan; Reneman, Liesbeth; Schilt, Thelma; Lavini, Cristina; Olabarriaga, Sílvia D; Ramsey, Nick F; Heeten, Gerard J den; van den Brink, Wim

2008-10-01

Neurotoxic effects of ecstasy have been reported, although it remains unclear whether effects can be attributed to ecstasy, other recreational drugs or a combination of these. To assess specific/independent neurotoxic effects of heavy ecstasy use and contributions of amphetamine, cocaine and cannabis as part of The Netherlands XTC Toxicity (NeXT) study. Effects of ecstasy and other substances were assessed with (1)H-magnetic resonance spectroscopy, diffusion tensor imaging, perfusion weighted imaging and [(123)I]2beta-carbomethoxy-3beta-(4-iodophenyl)-tropane ([(123)I]beta-CIT) single photon emission computed tomography (serotonin transporters) in a sample (n=71) with broad variation in drug use, using multiple regression analyses. Ecstasy showed specific effects in the thalamus with decreased [(123)I]beta-CIT binding, suggesting serotonergic axonal damage; decreased fractional anisotropy, suggesting axonal loss; and increased cerebral blood volume probably caused by serotonin depletion. Ecstasy had no effect on brain metabolites and apparent diffusion coefficients. Converging evidence was found for a specific toxic effect of ecstasy on serotonergic axons in the thalamus.

Non-Linear Cosmological Power Spectra in Real and Redshift Space

NASA Technical Reports Server (NTRS)

Taylor, A. N.; Hamilton, A. J. S.

1996-01-01

We present an expression for the non-linear evolution of the cosmological power spectrum based on Lagrangian trajectories. This is simplified using the Zel'dovich approximation to trace particle displacements, assuming Gaussian initial conditions. The model is found to exhibit the transfer of power from large to small scales expected in self-gravitating fields. Some exact solutions are found for power-law initial spectra. We have extended this analysis into red-shift space and found a solution for the non-linear, anisotropic redshift-space power spectrum in the limit of plane-parallel redshift distortions. The quadrupole-to-monopole ratio is calculated for the case of power-law initial spectra. We find that the shape of this ratio depends on the shape of the initial spectrum, but when scaled to linear theory depends only weakly on the redshift-space distortion parameter, beta. The point of zero-crossing of the quadrupole, kappa(sub o), is found to obey a simple scaling relation and we calculate this scale in the Zel'dovich approximation. This model is found to be in good agreement with a series of N-body simulations on scales down to the zero-crossing of the quadrupole, although the wavenumber at zero-crossing is underestimated. These results are applied to the quadrupole-to-monopole ratio found in the merged QDOT plus 1.2-Jy-IRAS redshift survey. Using a likelihood technique we have estimated that the distortion parameter is constrained to be beta greater than 0.5 at the 95 percent level. Our results are fairly insensitive to the local primordial spectral slope, but the likelihood analysis suggests n = -2 un the translinear regime. The zero-crossing scale of the quadrupole is k(sub 0) = 0.5 +/- 0.1 h Mpc(exp -1) and from this we infer that the amplitude of clustering is sigma(sub 8) = 0.7 +/- 0.05. We suggest that the success of this model is due to non-linear redshift-space effects arising from infall on to caustic and is not dominated by virialized cluster cores. The latter should start to dominate on scales below the zero-crossing of the quadrupole, where our model breaks down.

Nonlinear evolution of magnetic flux ropes. 2: Finite beta plasma

NASA Technical Reports Server (NTRS)

Osherovich, V. A.; Farrugia, C. J.; Burlaga, L. F.

1995-01-01

In this second paper on the evolution of magnetic flux ropes we study the effects of gas pressure. We assume that the energy transport is described by a polytropic relationship and reduce the set of ideal MHD equations to a single, second-order, nonlinear, ordinary differential equation for the evolution function. For this conservative system we obtain a first integral of motion. To analyze the possible motions, we use a mechanical analogue -- a one-dimensional, nonlinear oscillator. We find that the effective potential for such an oscillator depends on two parameters: the polytropic index gamma and a dimensionless quantity kappa the latter being a function of the plasma beta, the strength of the azimuthal magnetic field relative to the axial field of the flux rope, and gamma. Through a study of this effective potential we classify all possible modes of evolution of the system. In the main body of the paper, we focus on magnetic flux ropes whose field and gas pressure increase steadily towards the symmetry axis. In this case, for gamma greater than 1 and all values of kappa, only oscillations are possible. For gamma less than 1, however, both oscillations and expansion are allowed. For gamma less than 1 and kappa below a critical value, the energy of the nonlinear oscillator determines whether the flux rope will oscillate or expand to infinity. For gamma less than 1 and kappa above critical, however, only expansion occurs. Thus by increasing kappa while keeping gamma fixed (less than 1), a phase transition occurs at kappa = kappa(sub critical) and the oscillatory mode disappears. We illustrate the above theoretical considerations by the example of a flux rope of constant field line twist evolving self-similarly. For this example, we present the full numerical MHD solution. In an appendix to the paper we catalogue all possible evolutions when (1) either the magnetic field or (2) the gas pressure decreases monotonically toward the axis. We find that in these cases critical conditions can occur for gamma greater than 1. While in most cases the flux rope collapses, there are notable exceptions when, for certain ranges of kappa and gamma, collapse may be averted.

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

Dhabuwala, C.B.; Ramakrishna, C.V.; Anderson, G.F.

Beta adrenergic receptor binding was performed with /sup 125/I iodocyanopindolol on human cavernous tissue membrane fractions from normal tissue and transsexual procedures obtained postoperatively, as well as from postmortem sources. Isotherm binding studies on normal fresh tissues indicated that the receptor density was 9.1 fmoles/mg. with a KD of 23 pM. Tissue stored at room temperature for 4 to 6 hours, then at 4C in saline solution for 19 to 20 hours before freezing showed no significant changes in receptor density or affinity, and provided evidence for the stability of postmortem tissue obtained within the same time period. Beta receptormore » density of 2 cavernous preparations from transsexual procedures was not significantly different from normal control tissues, and showed that high concentrations of estrogen received by these patients had no effect on beta adrenergic receptor density. Displacement of /sup 125/iodocyanopindolol by 5 beta adrenergic agents demonstrated that 1-propranolol had the greatest affinity followed by ICI 118,551, zinterol, metoprolol and practolol. When the results of these displacement studies were subjected to Scatfit, non- linear regression line analysis, a single binding site was described. Based on the relative potency of the selective beta adrenergic agents it appears that these receptors were of the beta 2 subtype.« less

Kinetics of the neuroinflammation-oxidative stress correlation in rat brain following the injection of fibrillar amyloid-beta onto the hippocampus in vivo.

PubMed

Rosales-Corral, Sergio; Tan, Dun-Xian; Reiter, Russel J; Valdivia-Velázquez, Miguel; Acosta-Martínez, J Pablo; Ortiz, Genaro G

2004-05-01

The purpose of this study was to describe-following the injection of a single intracerebral dose of fibrillar amyloid-beta(1-40) in vivo-some correlations between proinflammatory cytokines and oxidative stress indicators in function of time, as well as how these variables fit in a regression model. We found a positive, significant correlation between interleukin (IL)-1beta or IL-6 and the activity of the glutathione peroxidase enzyme (GSH-Px), but IL-1beta or IL-6 maintained a strong, negative correlation with the lipid peroxidation (LPO). The first 12 h marked a positive correlation between IL-6 and tumor necrosis factor-alpha (TNF-alpha), but starting from the 36 h, this relationship became negative. We found also particular patterns of behavior through the time for IL-1beta, nitrites and IL-6, with parallel or sequential interrelationships. Results shows clearly that, in vivo, the fibrillar amyloid-beta (Abeta) disrupts the oxidative balance and initiate a proinflammatory response, which in turn feeds the oxidative imbalance in a coordinated, sequential way. This work contributes to our understanding of the positive feedbacks, focusing the "cytokine cycle" along with the oxidative stress mediators in a complex, multicellular, and interactive environment.

Improving the chi-squared approximation for bivariate normal tolerance regions

NASA Technical Reports Server (NTRS)

Feiveson, Alan H.

1993-01-01

Let X be a two-dimensional random variable distributed according to N2(mu,Sigma) and let bar-X and S be the respective sample mean and covariance matrix calculated from N observations of X. Given a containment probability beta and a level of confidence gamma, we seek a number c, depending only on N, beta, and gamma such that the ellipsoid R = (x: (x - bar-X)'S(exp -1) (x - bar-X) less than or = c) is a tolerance region of content beta and level gamma; i.e., R has probability gamma of containing at least 100 beta percent of the distribution of X. Various approximations for c exist in the literature, but one of the simplest to compute -- a multiple of the ratio of certain chi-squared percentage points -- is badly biased for small N. For the bivariate normal case, most of the bias can be removed by simple adjustment using a factor A which depends on beta and gamma. This paper provides values of A for various beta and gamma so that the simple approximation for c can be made viable for any reasonable sample size. The methodology provides an illustrative example of how a combination of Monte-Carlo simulation and simple regression modelling can be used to improve an existing approximation.

Regression estimators for generic health-related quality of life and quality-adjusted life years.

PubMed

Basu, Anirban; Manca, Andrea

2012-01-01

To develop regression models for outcomes with truncated supports, such as health-related quality of life (HRQoL) data, and account for features typical of such data such as a skewed distribution, spikes at 1 or 0, and heteroskedasticity. Regression estimators based on features of the Beta distribution. First, both a single equation and a 2-part model are presented, along with estimation algorithms based on maximum-likelihood, quasi-likelihood, and Bayesian Markov-chain Monte Carlo methods. A novel Bayesian quasi-likelihood estimator is proposed. Second, a simulation exercise is presented to assess the performance of the proposed estimators against ordinary least squares (OLS) regression for a variety of HRQoL distributions that are encountered in practice. Finally, the performance of the proposed estimators is assessed by using them to quantify the treatment effect on QALYs in the EVALUATE hysterectomy trial. Overall model fit is studied using several goodness-of-fit tests such as Pearson's correlation test, link and reset tests, and a modified Hosmer-Lemeshow test. The simulation results indicate that the proposed methods are more robust in estimating covariate effects than OLS, especially when the effects are large or the HRQoL distribution has a large spike at 1. Quasi-likelihood techniques are more robust than maximum likelihood estimators. When applied to the EVALUATE trial, all but the maximum likelihood estimators produce unbiased estimates of the treatment effect. One and 2-part Beta regression models provide flexible approaches to regress the outcomes with truncated supports, such as HRQoL, on covariates, after accounting for many idiosyncratic features of the outcomes distribution. This work will provide applied researchers with a practical set of tools to model outcomes in cost-effectiveness analysis.

The Relationship between TOC and pH with Exchangeable Heavy Metal Levels in Lithuanian Podzols

NASA Astrophysics Data System (ADS)

Khaledian, Yones; Pereira, Paulo; Brevik, Eric C.; Pundyte, Neringa; Paliulis, Dainius

2017-04-01

Heavy metals can have a negative impact on public and environmental health. The objective of this study was to investigate the relationship between total organic carbon (TOC) and pH with exchangeable heavy metals (Pb, Cd, Cu and Zn) in order to predict exchangeable heavy metal content in soils sampled near Panevėžys and Kaunas, Lithuania. Principal component regression (PCR) and nonlinear regression methods were tested to find the statistical relationship between TOC and pH with heavy metals. The results of PCR [R2 = 0.68, RMSE = 0.07] and non-linear regression [R2 = 0.74, RMSE= 0.065] (pH with TOC and exchangeable parameters) were statistically significant. However, this was not observed in the relationships of pH and TOC separately with exchangeable heavy metals. The results indicated that pH had a higher correlation with exchangeable heavy metals (non-linear regression [R2 = 0.72, RMSE= 0.066]) than TOC with heavy metals [R2 = 0.30, RMSE= 0.004]. It can be concluded that even though there was a strong relationship between TOC and pH with exchangeable metals, the metal mobility (exchangeable metals) can be explained by pH better than TOC in this study. Finally, manipulating soil pH could likely be productive to assess and control heavy metals when financial and time limitations exist (Khaledian et al. 2016). Reference(s) Khaledian Y, Pereira P, Brevik E.C, Pundyte N, Paliulis D. 2016. The Influence of Organic Carbon and pH on Heavy Metals, Potassium, and Magnesium Levels in Lithuanian Podzols. Land Degradation and Development. DOI: 10.1002/ldr.2638

Online sparse Gaussian process based human motion intent learning for an electrically actuated lower extremity exoskeleton.

PubMed

Long, Yi; Du, Zhi-Jiang; Chen, Chao-Feng; Dong, Wei; Wang, Wei-Dong

2017-07-01

The most important step for lower extremity exoskeleton is to infer human motion intent (HMI), which contributes to achieve human exoskeleton collaboration. Since the user is in the control loop, the relationship between human robot interaction (HRI) information and HMI is nonlinear and complicated, which is difficult to be modeled by using mathematical approaches. The nonlinear approximation can be learned by using machine learning approaches. Gaussian Process (GP) regression is suitable for high-dimensional and small-sample nonlinear regression problems. GP regression is restrictive for large data sets due to its computation complexity. In this paper, an online sparse GP algorithm is constructed to learn the HMI. The original training dataset is collected when the user wears the exoskeleton system with friction compensation to perform unconstrained movement as far as possible. The dataset has two kinds of data, i.e., (1) physical HRI, which is collected by torque sensors placed at the interaction cuffs for the active joints, i.e., knee joints; (2) joint angular position, which is measured by optical position sensors. To reduce the computation complexity of GP, grey relational analysis (GRA) is utilized to specify the original dataset and provide the final training dataset. Those hyper-parameters are optimized offline by maximizing marginal likelihood and will be applied into online GP regression algorithm. The HMI, i.e., angular position of human joints, will be regarded as the reference trajectory for the mechanical legs. To verify the effectiveness of the proposed algorithm, experiments are performed on a subject at a natural speed. The experimental results show the HMI can be obtained in real time, which can be extended and employed in the similar exoskeleton systems.

Cardiac interbeat interval dynamics from childhood to senescence : comparison of conventional and new measures based on fractals and chaos theory

NASA Technical Reports Server (NTRS)

Pikkujamsa, S. M.; Makikallio, T. H.; Sourander, L. B.; Raiha, I. J.; Puukka, P.; Skytta, J.; Peng, C. K.; Goldberger, A. L.; Huikuri, H. V.

1999-01-01

BACKGROUND: New methods of R-R interval variability based on fractal scaling and nonlinear dynamics ("chaos theory") may give new insights into heart rate dynamics. The aims of this study were to (1) systematically characterize and quantify the effects of aging from early childhood to advanced age on 24-hour heart rate dynamics in healthy subjects; (2) compare age-related changes in conventional time- and frequency-domain measures with changes in newly derived measures based on fractal scaling and complexity (chaos) theory; and (3) further test the hypothesis that there is loss of complexity and altered fractal scaling of heart rate dynamics with advanced age. METHODS AND RESULTS: The relationship between age and cardiac interbeat (R-R) interval dynamics from childhood to senescence was studied in 114 healthy subjects (age range, 1 to 82 years) by measurement of the slope, beta, of the power-law regression line (log power-log frequency) of R-R interval variability (10(-4) to 10(-2) Hz), approximate entropy (ApEn), short-term (alpha(1)) and intermediate-term (alpha(2)) fractal scaling exponents obtained by detrended fluctuation analysis, and traditional time- and frequency-domain measures from 24-hour ECG recordings. Compared with young adults (<40 years old, n=29), children (<15 years old, n=27) showed similar complexity (ApEn) and fractal correlation properties (alpha(1), alpha(2), beta) of R-R interval dynamics despite lower spectral and time-domain measures. Progressive loss of complexity (decreased ApEn, r=-0.69, P<0.001) and alterations of long-term fractal-like heart rate behavior (increased alpha(2), r=0.63, decreased beta, r=-0.60, P<0.001 for both) were observed thereafter from middle age (40 to 60 years, n=29) to old age (>60 years, n=29). CONCLUSIONS: Cardiac interbeat interval dynamics change markedly from childhood to old age in healthy subjects. Children show complexity and fractal correlation properties of R-R interval time series comparable to those of young adults, despite lower overall heart rate variability. Healthy aging is associated with R-R interval dynamics showing higher regularity and altered fractal scaling consistent with a loss of complex variability.

EEG-based mild depressive detection using feature selection methods and classifiers.

PubMed

Li, Xiaowei; Hu, Bin; Sun, Shuting; Cai, Hanshu

2016-11-01

Depression has become a major health burden worldwide, and effectively detection of such disorder is a great challenge which requires latest technological tool, such as Electroencephalography (EEG). This EEG-based research seeks to find prominent frequency band and brain regions that are most related to mild depression, as well as an optimal combination of classification algorithms and feature selection methods which can be used in future mild depression detection. An experiment based on facial expression viewing task (Emo_block and Neu_block) was conducted, and EEG data of 37 university students were collected using a 128 channel HydroCel Geodesic Sensor Net (HCGSN). For discriminating mild depressive patients and normal controls, BayesNet (BN), Support Vector Machine (SVM), Logistic Regression (LR), k-nearest neighbor (KNN) and RandomForest (RF) classifiers were used. And BestFirst (BF), GreedyStepwise (GSW), GeneticSearch (GS), LinearForwordSelection (LFS) and RankSearch (RS) based on Correlation Features Selection (CFS) were applied for linear and non-linear EEG features selection. Independent Samples T-test with Bonferroni correction was used to find the significantly discriminant electrodes and features. Data mining results indicate that optimal performance is achieved using a combination of feature selection method GSW based on CFS and classifier KNN for beta frequency band. Accuracies achieved 92.00% and 98.00%, and AUC achieved 0.957 and 0.997, for Emo_block and Neu_block beta band data respectively. T-test results validate the effectiveness of selected features by search method GSW. Simplified EEG system with only FP1, FP2, F3, O2, T3 electrodes was also explored with linear features, which yielded accuracies of 91.70% and 96.00%, AUC of 0.952 and 0.972, for Emo_block and Neu_block respectively. Classification results obtained by GSW + KNN are encouraging and better than previously published results. In the spatial distribution of features, we find that left parietotemporal lobe in beta EEG frequency band has greater effect on mild depression detection. And fewer EEG channels (FP1, FP2, F3, O2 and T3) combined with linear features may be good candidates for usage in portable systems for mild depression detection. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Usefulness of Beta2-Microglobulin as a Predictor of All-Cause and Nonculprit Lesion-Related Cardiovascular Events in Acute Coronary Syndromes (from the PROSPECT Study).

PubMed

Möckel, Martin; Muller, Reinhold; Searle, Julia; Slagman, Anna; De Bruyne, Bernard; Serruys, Patrick; Weisz, Giora; Xu, Ke; Holert, Fabian; Müller, Christian; Maehara, Akiko; Stone, Gregg W

2015-10-01

In the Providing Regional Observations to Study Predictors of Events in the Coronary Tree (PROSPECT) study, plaque burden, plaque composition, and minimal luminal area were associated with an increased risk of adverse cardiovascular events arising from untreated atherosclerotic lesions (vulnerable plaques) in patients with acute coronary syndromes (ACS). We sought to evaluate the utility of biomarker profiling and clinical risk factors to predict 3-year all-cause and nonculprit lesion-related major adverse cardiac events (MACEs). Of 697 patients who underwent successful percutaneous coronary intervention (PCI) for ACS, an array of 28 baseline biomarkers was analyzed. Median follow-up was 3.4 years. Beta2-microglobulin displayed the strongest predictive power of all variables assessed for all-cause and nonculprit lesion-related MACE. In a classification and regression tree analysis, patients with beta2-microglobulin >1.92 mg/L had an estimated 28.7% 3-year incidence of all-cause MACE; C-peptide <1.32 ng/ml was associated with a further increase in MACE to 51.2%. In a classification and regression tree analysis for untreated nonculprit lesion-related MACE, beta2-microglobulin >1.92 mg/L identified a cohort with a 3-year rate of 18.5%, and C-peptide <2.22 ng/ml was associated with a further increase to 25.5%. By multivariable analysis, beta2-microglobulin was the strongest predictor of all-cause and nonculprit MACE during follow-up. High-density lipoprotein (HDL), transferrin, and history of angina pectoris were also independent predictors of all-cause MACE, and HDL was an independent predictor of nonculprit MACE. In conclusion, in the PROSPECT study, beta2-microglobulin strongly predicted all-cause and nonculprit lesion-related MACE within 3 years after PCI in ACS. C-peptide and HDL provided further risk stratification to identify angiographically mild nonculprit lesions prone to future MACE. Copyright © 2015 Elsevier Inc. All rights reserved.

Isotherm investigation for the sorption of fluoride onto Bio-F: comparison of linear and non-linear regression method

NASA Astrophysics Data System (ADS)

Yadav, Manish; Singh, Nitin Kumar

2017-12-01

A comparison of the linear and non-linear regression method in selecting the optimum isotherm among three most commonly used adsorption isotherms (Langmuir, Freundlich, and Redlich-Peterson) was made to the experimental data of fluoride (F) sorption onto Bio-F at a solution temperature of 30 ± 1 °C. The coefficient of correlation (r2) was used to select the best theoretical isotherm among the investigated ones. A total of four Langmuir linear equations were discussed and out of which linear form of most popular Langmuir-1 and Langmuir-2 showed the higher coefficient of determination (0.976 and 0.989) as compared to other Langmuir linear equations. Freundlich and Redlich-Peterson isotherms showed a better fit to the experimental data in linear least-square method, while in non-linear method Redlich-Peterson isotherm equations showed the best fit to the tested data set. The present study showed that the non-linear method could be a better way to obtain the isotherm parameters and represent the most suitable isotherm. Redlich-Peterson isotherm was found to be the best representative (r2 = 0.999) for this sorption system. It is also observed that the values of β are not close to unity, which means the isotherms are approaching the Freundlich but not the Langmuir isotherm.

Seed islands driven by turbulence and NTM dynamics

NASA Astrophysics Data System (ADS)

Muraglia, M.; Agullo, O.; Poye, A.; Benkadda, S.; Horton, W.; Dubuit, N.; Garbet, X.; Sen, A.

2014-10-01

Magnetic reconnection is an issue for tokamak plasmas. Growing magnetic islands expel energetic particles from the plasma core leading to high energy fluxes in the SOL and may cause damage to the plasma facing components. The islands grow from seeds from the bootstrap current effects that oppose the negative delta-prime producing nonlinear island growth. Experimentally, the onset of NTM is quantified in terms of the beta parameter and the sawtooth period. Indeed, in experiments, (3;2) NTM magnetic islands are often triggered by sawtooth precursors. However (2;1) magnetic islands can appear without noticeable MHD event and the seed islands origin for the NTM growth is still an open question. Macroscale MHD instabilities (magnetic islands) coexist with micro-scale turbulent fluctuations and zonal flows which impact island dynamics. Nonlinear simulations show that the nonlinear beating of the fastest growing small-scale ballooning interchange modes on a low order rational surface drive a magnetic islands located on the same surface. The island size is found to be controlled by the turbulence level and modifies the NTM threshold and dynamics.

Neutron Capture and the Antineutrino Yield from Nuclear Reactors.

PubMed

Huber, Patrick; Jaffke, Patrick

2016-03-25

We identify a new, flux-dependent correction to the antineutrino spectrum as produced in nuclear reactors. The abundance of certain nuclides, whose decay chains produce antineutrinos above the threshold for inverse beta decay, has a nonlinear dependence on the neutron flux, unlike the vast majority of antineutrino producing nuclides, whose decay rate is directly related to the fission rate. We have identified four of these so-called nonlinear nuclides and determined that they result in an antineutrino excess at low energies below 3.2 MeV, dependent on the reactor thermal neutron flux. We develop an analytic model for the size of the correction and compare it to the results of detailed reactor simulations for various real existing reactors, spanning 3 orders of magnitude in neutron flux. In a typical pressurized water reactor the resulting correction can reach ∼0.9% of the low energy flux which is comparable in size to other, known low-energy corrections from spent nuclear fuel and the nonequilibrium correction. For naval reactors the nonlinear correction may reach the 5% level by the end of cycle.

The Relationship Between Heart Rate Reserve and Oxygen Uptake Reserve in Heart Failure Patients on Optimized and Non-Optimized Beta-Blocker Therapy

PubMed Central

Carvalho, Vitor Oliveira; Guimarães, Guilherme Veiga; Bocchi, Edimar Alcides

2008-01-01

BACKGROUND The relationship between the percentage of oxygen consumption reserve and percentage of heart rate reserve in heart failure patients either on non-optimized or off beta-blocker therapy is known to be unreliable. The aim of this study was to evaluate the relationship between the percentage of oxygen consumption reserve and percentage of heart rate reserve in heart failure patients receiving optimized and non-optimized beta-blocker treatment during a treadmill cardiopulmonary exercise test. METHODS A total of 27 sedentary heart failure patients (86% male, 50±12 years) on optimized beta-blocker therapy with a left ventricle ejection fraction of 33±8% and 35 sedentary non-optimized heart failure patients (75% male, 47±10 years) with a left ventricle ejection fraction of 30±10% underwent the treadmill cardiopulmonary exercise test (Naughton protocol). Resting and peak effort values of both the percentage of oxygen consumption reserve and percentage of heart rate reserve were, by definition, 0 and 100, respectively. RESULTS The heart rate slope for the non-optimized group was derived from the points 0.949±0.088 (0 intercept) and 1.055±0.128 (1 intercept), p<0.0001. The heart rate slope for the optimized group was derived from the points 1.026±0.108 (0 intercept) and 1.012±0.108 (1 intercept), p=0.47. Regression linear plots for the heart rate slope for each patient in the non-optimized and optimized groups revealed a slope of 0.986 (almost perfect) for the optimized group, but the regression analysis for the non-optimized group was 0.030 (far from perfect, which occurs at 1). CONCLUSION The relationship between the percentage of oxygen consumption reserve and percentage of heart rate reserve in patients on optimized beta-blocker therapy was reliable, but this relationship was unreliable in non-optimized heart failure patients. PMID:19060991

The impact of service quality perception on patient satisfaction in government hospitals in southern Saudi Arabia.

PubMed

Alghamdi, Faris S

2014-10-01

To examine the impact of service quality perception on patient satisfaction and determine  which dimension from 5 dimensions (tangible, reliability, responsive, assurance, and empathy) has the greatest impact on patient satisfaction. A total of 183 eligible patients participated in this study. This study was conducted in Al-Baha province, Saudi Arabia from June 2013 to August 2013. We utilized the cross-sectional method, using a modified Assessment of Service Quality questionnaire to collect the data. To test the study hypothesis, multiple regression analysis was carried out. Analysis of variance revealed that the overall result showed a statistically significant impact of health service quality on patient satisfaction (p=0.000). The beta-weights (beta) suggested that the empathy dimension had the greatest influence on patient satisfaction (beta=0.476), followed by tangible (beta=0.198) and responsiveness dimensions (beta=0.164). Patient satisfaction was influenced by health service quality, with the empathy dimension as the greatest influence on patient satisfaction. Therefore, it should be considered a priority by government hospitals to train doctors in interpersonal relationship skills to enhance the doctor-patient relationship. 

Influence of estradiol and androstenedione on ACTH and cortisol secretion in the ovine fetus.

PubMed

Wood, C E; Saoud, C J

1997-01-01

To test the hypothesis that physiologic increases in fetal plasma 17 beta-estradiol and androstenedione modulate the activity of the fetal hypothalamic-pituitary-adrenal (HPA) axis. Seventeen pregnant ewes and their fetuses were chronically catheterized. At the time of surgery, the fetuses received implants that released 17 beta-estradiol (n = 5) alone or 17 beta-estradiol and androstenedione (n = 6), each at a rate of approximately 250 micrograms/day for each steroid. The control group (n = 6) received either no pellet (n = 2) or a "placebo" pellet, which contained no steroid (n = 4). Fetal blood samples were drawn for hormone and blood gas analysis at 1-3-day intervals until the time of spontaneous parturition. Fetal plasma ACTH and cortisol concentrations were fit to semilogarithmic equations and analyzed by stepwise multiple linear regression analysis for statistically significant effects of 17 beta-estradiol and androstenedione. Estradiol significantly increased and androstenedione significantly decreased the ACTH and cortisol concentrations. Treatment with both 17 beta-estradiol and androstenedione resulted in parturition approximately 4 days earlier than in the other groups (P < .05). Physiologic increases in fetal plasma estradiol and androstenedione modify the activity of the HPA axis.

[Factors influencing nurses' organizational citizenship behavior].

PubMed

Park, Junhee; Yun, Eunkyung; Han, Sangsook

2009-08-01

This study was conducted to identify the factors that influence nurses' organizational citizenship behavior. A cross-sectional design was used, with a convenience sample of 547 nurses from four university hospitals in Seoul and Gyeonggi province. The data were collected through a questionnaire survey done from September 22 to October 10, 2008. The tools used for this study were scales on organizational citizenship behavior (14 items), self-leadership (14 items), empowerment (10 items), organizational commitment (7 items), job satisfaction (8 items) and transformational.transactional leadership (14 items). Cronbach's alpha and factor analysis were examined to test reliability and construct validity of the scale. The data collected were processed using SPSS Window 15.0 Program for actual numbers and percentages, differences in the dependent variable according to general characteristics, and means, standard deviations, correlation coefficients and multiple regression analysis. The factors influencing nurses' organizational citizenship behavior were identified as self-leadership(beta=.247), empowerment (beta=.233), job satisfaction (beta=.209), organizational commitment (beta=.158), and transactional leadership (beta=.142). Five factors explained 42.0% of nurses' organizational citizenship behavior. The results of this study can be used to develop further management strategies for enhancement of nurses' organizational citizenship behavior.

Application of nonlinear-regression methods to a ground-water flow model of the Albuquerque Basin, New Mexico

USGS Publications Warehouse

Tiedeman, C.R.; Kernodle, J.M.; McAda, D.P.

1998-01-01

This report documents the application of nonlinear-regression methods to a numerical model of ground-water flow in the Albuquerque Basin, New Mexico. In the Albuquerque Basin, ground water is the primary source for most water uses. Ground-water withdrawal has steadily increased since the 1940's, resulting in large declines in water levels in the Albuquerque area. A ground-water flow model was developed in 1994 and revised and updated in 1995 for the purpose of managing basin ground- water resources. In the work presented here, nonlinear-regression methods were applied to a modified version of the previous flow model. Goals of this work were to use regression methods to calibrate the model with each of six different configurations of the basin subsurface and to assess and compare optimal parameter estimates, model fit, and model error among the resulting calibrations. The Albuquerque Basin is one in a series of north trending structural basins within the Rio Grande Rift, a region of Cenozoic crustal extension. Mountains, uplifts, and fault zones bound the basin, and rock units within the basin include pre-Santa Fe Group deposits, Tertiary Santa Fe Group basin fill, and post-Santa Fe Group volcanics and sediments. The Santa Fe Group is greater than 14,000 feet (ft) thick in the central part of the basin. During deposition of the Santa Fe Group, crustal extension resulted in development of north trending normal faults with vertical displacements of as much as 30,000 ft. Ground-water flow in the Albuquerque Basin occurs primarily in the Santa Fe Group and post-Santa Fe Group deposits. Water flows between the ground-water system and surface-water bodies in the inner valley of the basin, where the Rio Grande, a network of interconnected canals and drains, and Cochiti Reservoir are located. Recharge to the ground-water flow system occurs as infiltration of precipitation along mountain fronts and infiltration of stream water along tributaries to the Rio Grande; subsurface flow from adjacent regions; irrigation and septic field seepage; and leakage through the Rio Grande, canal, and Cochiti Reservoir beds. Ground water is discharged from the basin by withdrawal; evapotranspiration; subsurface flow; and flow to the Rio Grande, canals, and drains. The transient, three-dimensional numerical model of ground-water flow to which nonlinear-regression methods were applied simulates flow in the Albuquerque Basin from 1900 to March 1995. Six different basin subsurface configurations are considered in the model. These configurations are designed to test the effects of (1) varying the simulated basin thickness, (2) including a hypothesized hydrogeologic unit with large hydraulic conductivity in the western part of the basin (the west basin high-K zone), and (3) substantially lowering the simulated hydraulic conductivity of a fault in the western part of the basin (the low-K fault zone). The model with each of the subsurface configurations was calibrated using a nonlinear least- squares regression technique. The calibration data set includes 802 hydraulic-head measurements that provide broad spatial and temporal coverage of basin conditions, and one measurement of net flow from the Rio Grande and drains to the ground-water system in the Albuquerque area. Data are weighted on the basis of estimates of the standard deviations of measurement errors. The 10 to 12 parameters to which the calibration data as a whole are generally most sensitive were estimated by nonlinear regression, whereas the remaining model parameter values were specified. Results of model calibration indicate that the optimal parameter estimates as a whole are most reasonable in calibrations of the model with with configurations 3 (which contains 1,600-ft-thick basin deposits and the west basin high-K zone), 4 (which contains 5,000-ft-thick basin de

A novel approach for prediction of tacrolimus blood concentration in liver transplantation patients in the intensive care unit through support vector regression.

PubMed

Van Looy, Stijn; Verplancke, Thierry; Benoit, Dominique; Hoste, Eric; Van Maele, Georges; De Turck, Filip; Decruyenaere, Johan

2007-01-01

Tacrolimus is an important immunosuppressive drug for organ transplantation patients. It has a narrow therapeutic range, toxic side effects, and a blood concentration with wide intra- and interindividual variability. Hence, it is of the utmost importance to monitor tacrolimus blood concentration, thereby ensuring clinical effect and avoiding toxic side effects. Prediction models for tacrolimus blood concentration can improve clinical care by optimizing monitoring of these concentrations, especially in the initial phase after transplantation during intensive care unit (ICU) stay. This is the first study in the ICU in which support vector machines, as a new data modeling technique, are investigated and tested in their prediction capabilities of tacrolimus blood concentration. Linear support vector regression (SVR) and nonlinear radial basis function (RBF) SVR are compared with multiple linear regression (MLR). Tacrolimus blood concentrations, together with 35 other relevant variables from 50 liver transplantation patients, were extracted from our ICU database. This resulted in a dataset of 457 blood samples, on average between 9 and 10 samples per patient, finally resulting in a database of more than 16,000 data values. Nonlinear RBF SVR, linear SVR, and MLR were performed after selection of clinically relevant input variables and model parameters. Differences between observed and predicted tacrolimus blood concentrations were calculated. Prediction accuracy of the three methods was compared after fivefold cross-validation (Friedman test and Wilcoxon signed rank analysis). Linear SVR and nonlinear RBF SVR had mean absolute differences between observed and predicted tacrolimus blood concentrations of 2.31 ng/ml (standard deviation [SD] 2.47) and 2.38 ng/ml (SD 2.49), respectively. MLR had a mean absolute difference of 2.73 ng/ml (SD 3.79). The difference between linear SVR and MLR was statistically significant (p < 0.001). RBF SVR had the advantage of requiring only 2 input variables to perform this prediction in comparison to 15 and 16 variables needed by linear SVR and MLR, respectively. This is an indication of the superior prediction capability of nonlinear SVR. Prediction of tacrolimus blood concentration with linear and nonlinear SVR was excellent, and accuracy was superior in comparison with an MLR model.

Naphthol AS-BI (7-bromo-3-hydroxy-2-naphtho-o-anisidine) phosphatase and naphthol AS-BI. beta. -D-glucuronidase in Chinese hamster ovary cells: biochemical and flow cytometric studies

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

Dolbeare, F.A.; Phares, W.

1979-01-01

Conditions for the biochemical and flow cytometric assay of 7-bromo-3-hydroxy-2-naphtho-o-anisidine phosphatase and ..beta..-D-glucuronidase activities in Chinese hamster ovary cells were studied. In the biochemical assays, the pH optimum for the phosphatase activity was pH 4.6 with a Km of 10/sup -5/ M; the pH optimum for ..beta..-D-glucuronidase activity was pH 5.0 with a Km of 2 x 10/sup -5/ M. For intact cells the derived constants were 3 to 10 times higher. The rate of hydrolysis of both substrates was also examined by flow cytometry. Cellular fluorescence increased linearly for only about 15 min. Diffusion of the fluorescent product probablymore » caused nonlinearity of the fluorescence increase and was demonstrated by mixing cells incubated with substrate with those that had not been incubated. After 15 min, cells that had not been exposed previously to product or substrate contained the fluorescent product. Cells fractionated into size classes by centrifugal elutriation also were analyzed by flow cytometry for ..beta..-D-glucuronidase activity. The activity increased linearly with the increase in cell size corresponding to the progression from G/sub 1/ through S and into G/sub 2/-M phases of the cell cycle.« less

The order of administration of macrolides and beta-lactams may impact the outcomes of hospitalized patients with community-acquired pneumonia: results from the community-acquired pneumonia organization.

PubMed

Peyrani, Paula; Wiemken, Timothy L; Metersky, Mark L; Arnold, Forest W; Mattingly, William A; Feldman, Charles; Cavallazzi, Rodrigo; Fernandez-Botran, Rafael; Bordon, Jose; Ramirez, Julio A

2018-01-01

The beneficial effect of macrolides for the treatment of community-acquired pneumonia (CAP) in combination with beta-lactams may be due to their anti-inflammatory activity. In patients with pneumococcal meningitis, the use of steroids improves outcomes only if they are administered before beta-lactams. The objective of this study was to compare outcomes in hospitalized patients with CAP when macrolides were administered before, simultaneously with, or after beta-lactams. Secondary data analysis of the Community-Acquired Pneumonia Organization (CAPO) International Cohort Study database. Study groups were defined based on the sequence of administration of macrolides and beta-lactams. The study outcomes were time to clinical stability (TCS), length of stay (LOS) and in-hospital mortality. Accelerated failure time models were used to evaluate the adjusted impact of sequential antibiotic administration and time-to-event outcomes, while a logistic regression model was used to evaluate their adjusted impact on mortality. A total of 99 patients were included in the macrolide before group and 305 in the macrolide after group. Administration of a macrolide before a beta-lactam compared to after a beta-lactam reduced TCS (3 vs. 4 days, p = .011), LOS (6 vs. 7 days, p = .002) and mortality (3 vs. 7.2%, p = .228). The administration of macrolides before beta-lactams was associated with a statistically significant decrease in TCS and LOS and a non-statistically significant decrease in mortality. The beneficial effect of macrolides in hospitalized patient with CAP may occur only if administered before beta-lactams.

Influence of detergent concentration on aggregation and spectroscopic properties of light-harvesting complex II.

PubMed

Voigt, Bernd; Krikunova, Maria; Lokstein, Heiko

2008-01-01

Aggregation of photosynthetic light-harvesting complexes strongly influences their spectroscopic properties. Fluorescence yield and excited state lifetimes of the main light-harvesting complex (LHC II) of higher plants strongly depend on its aggregation state. Detergents are commonly used to solubilize membrane proteins and/or to circumvent their aggregation in aqueous environments. Nonlinear polarization spectroscopy in the frequency domain (NLPF) was performed with LHC II over a wide concentration range of the mild detergent n-dodecyl beta-D: -maltoside (beta-DM). Additionally, conventional absorption-, fluorescence- and circular dichroism-spectra were measured.The results indicate that: (i) conventional spectroscopic techniques are not well suited to investigate aggregation effects. NLPF provides a novel approach to overcome this problem: NLPF spectra display dramatic alterations upon even minor beta-DM concentration changes. (ii) Commonly used detergent concentrations (around or slightly above the critical micellar concentration) apparently do not lead to complete trimerization of LHC II. A long-wavelength species in the NLPF spectra (peaking at about 685 nm), indicative of residual aggregation, persists up to DM-concentrations of 0.06%. (iii) High-resolution NLPF spectra indicate the existence of a species with a considerably shortened excited state lifetime. (iv) No indication of denaturation was found even at the highest beta-DM concentrations used. (v) A specific change in interaction between certain chlorophyll(s) b and a xanthophyll molecule, probably neoxanthin, was detected upon aggregation as well as at higher beta-DM concentrations. The results are discussed with respect to the still elusive mechanism of nonradiative dissipation of excess excitation energy in the antenna system.

Influence of beta blockers on survival in dogs with severe subaortic stenosis.

PubMed

Eason, B D; Fine, D M; Leeder, D; Stauthammer, C; Lamb, K; Tobias, A H

2014-01-01

Subaortic stenosis (SAS) is one of the most common congenital cardiac defects in dogs. Severe SAS frequently is treated with a beta adrenergic receptor blocker (beta blocker), but this approach largely is empirical. To determine the influence of beta blocker treatment on survival time in dogs with severe SAS. Retrospective review of medical records of dogs diagnosed with severe, uncomplicated SAS (pressure gradient [PG] ≥80 mmHg) between 1999 and 2011. Fifty dogs met the inclusion criteria. Twenty-seven dogs were treated with a beta blocker and 23 received no treatment. Median age at diagnosis was significantly greater in the untreated group (1.2 versus 0.6 years, respectively; P = .03). Median PG at diagnosis did not differ between the treated and untreated groups (127 versus 121 mmHg, respectively; P = .2). Cox proportional hazards regression was used to identify the influence of PG at diagnosis, age at diagnosis, and beta blocker treatment on survival. In the all-cause multivariate mortality analysis, only age at diagnosis (P = .02) and PG at diagnosis (P = .03) affected survival time. In the cardiac mortality analysis, only PG influenced survival time (P = .03). Treatment with a beta blocker did not influence survival time in either the all-cause (P = .93) or cardiac-cause (P = .97) mortality analyses. Beta blocker treatment did not influence survival in dogs with severe SAS in our study, and a higher PG at diagnosis was associated with increased risk of death. Copyright © 2014 by the American College of Veterinary Internal Medicine.

Effect of menopause, anthropometry, nutrition and lifestyle on bone status of women in the northern Mediterranean.

PubMed

Pavicic Zezelj, S; Cvijanovic, O; Micovic, V; Bobinac, D; Crncevic-Orlic, Z; Malatestinic, G

2010-10-01

The purpose of this study was to explore the influence of age, menopause, anthropometry, nutrition and lifestyle on bone status of women of the Northern Mediterranean Region ofCroatia, which is considered the Adriatic Coast of Southeast Europe. Quantitative ultrasound measurement was performed on the women's right heel and the values of the primary parameters (the Broad Ultrasonic Attenuation and the Speed of Sound [BUA and SOS]) were obtained. Dietary data were assessed with specially designed semi-quantitative food frequency questionnaire. Multiple regression analysis was employed to examine the influence of age and anthropometry, as well as hormonal and nutritional factors on BUA and SOS. In all female subjects, both primary parameters were predicted by menopause. Among nutrition and lifestyle factors, carbohydrates were significant predictors for BUA (beta = -0.151, p < 0.05), and smoking is significant predictor for SOS (beta = -0.113, p < 0.05). In premenopausal women, BUA is significantly predicted by body height (beta = 0.71, p < 0.05) and body mass index (beta = 1.44, p < 0.05). In postmenopausal women, both primary parameters are strongly predicted by age and anthropometric parameters. Besides, SOS is significantly predicted by smoking (beta = -0.18, p < 0.01) and alcohol (beta = -0.13, p < 0.05). Besides, SOS is significantly predicted by smoking (beta = -0.18, p < 0.01) and alcohol (beta = -0.13, p < 0.05). Bone quality in women from the Croatian Mediterranean Region mostly depends on their hormonal status. When the effect of menopause is controlled, bone status becomes dependent on age and anthropometry.

Traffic Predictive Control: Case Study and Evaluation

DOT National Transportation Integrated Search

2017-06-26

This project developed a quantile regression method for predicting future traffic flow at a signalized intersection by combining both historical and real-time data. The algorithm exploits nonlinear correlations in historical measurements and efficien...

Fundamental Analysis of the Linear Multiple Regression Technique for Quantification of Water Quality Parameters from Remote Sensing Data. Ph.D. Thesis - Old Dominion Univ.

NASA Technical Reports Server (NTRS)

Whitlock, C. H., III

1977-01-01

Constituents with linear radiance gradients with concentration may be quantified from signals which contain nonlinear atmospheric and surface reflection effects for both homogeneous and non-homogeneous water bodies provided accurate data can be obtained and nonlinearities are constant with wavelength. Statistical parameters must be used which give an indication of bias as well as total squared error to insure that an equation with an optimum combination of bands is selected. It is concluded that the effect of error in upwelled radiance measurements is to reduce the accuracy of the least square fitting process and to increase the number of points required to obtain a satisfactory fit. The problem of obtaining a multiple regression equation that is extremely sensitive to error is discussed.

The association between hypertension-specific care management processes and blood pressure outcomes in US-based physician organizations.

PubMed

Wong, Ken; Smalarz, Amy; Wu, Ning; Boulanger, Luke; Wogen, Jenifer

2011-01-01

Care management processes (CMP) may be implemented in health systems to improve chronic disease quality of care. The objective of this study was to assess the relationship between the presence of hypertension-specific CMP and blood pressure (BP) control among hypertensive patients within selected physician organizations in the USA-modified version of the Physician Practice Connection Readiness Survey (PPC-RS), developed by The National Committee for Quality Assurance (NCQA), was administered to chief medical officers at 28 US-based physician organizations in 2010. Hypertension-specific survey items were added to the PPC-RS and focused on medication fill compliance, chronic disease management, and patient self-management. Demographic and clinical cross-sectional data from a random sample of 300 hypertensive patients age 18 years or older were collected at each site. Physician site and patient characteristics were reported. Regression models were used to assess the relationship between hypertension-specific physician practices and patient BP control. Eligible patients had at least a 1-year history of care with the physician organization and had an encounter within the past year of data collection. Of the 28 participating sites, most had electronic medical records that handle total functionality (71.4%) and had more than 50 staff members (78.6%). Across all sites, approximately 61% of patients had controlled BP. Regression analyses found that practices that used physician education as an effort to improve medication fill compliance demonstrated improvement in BP control (changes in systolic BP: beta coefficient = -1.366, P = .034; changes in diastolic BP: beta coefficient = -0.859, P = .056). The use of a systematic process to screen or assess patients for hypertension as a risk factor was also found to be associated with improvements in BP control (changes in diastolic BP: beta coefficient = -0.860, P = .006). In addition, physician practices that maintained a list of hypertensive patients along with the patients' associated clinical data demonstrated better BP control (currently controlled BP: beta coefficient = 0.282, P = .034; currently uncontrolled BP: beta coefficient = -0.292, P = .023). However, use of the following practices had a negative correlation with BP control: case management (changes in systolic BP: beta coefficient 1.649, P = .022; changes in diastolic BP: beta coefficient = 0.910, P = .078), follow-up for missed appointments (changes in systolic BP: beta coefficient = 0.937, P = .041; changes in diastolic BP: beta coefficient = 0.165, P = .627), adopted written evidence-based standards of care to treat hypertension (changes in systolic BP: beta coefficient = 0.985, P = .032; changes in diastolic BP: beta coefficient = 0.346, P = .305), and checklists for tests and interventions (changes in systolic BP: beta coefficient = 1.586, P = .004; changes in diastolic BP: beta coefficient = 0.938, P = .019). Findings from this multisite study provide evidence that the presence of some hypertension-specific CMP in physician organizations may be associated with better BP outcomes among hypertensive patients. In particular, patients may benefit from physician efforts to improve medication fill compliance as well as organizational monitoring of hypertensive patients and their clinical data. Further research is warranted to better assess the relationship between CMP and treatment of chronic diseases such as hypertension over time. Copyright © 2011 American Society of Hypertension. Published by Elsevier Inc. All rights reserved.

Solar cycle in current reanalyses: (non)linear attribution study

NASA Astrophysics Data System (ADS)

Kuchar, A.; Sacha, P.; Miksovsky, J.; Pisoft, P.

2014-12-01

This study focusses on the variability of temperature, ozone and circulation characteristics in the stratosphere and lower mesosphere with regard to the influence of the 11 year solar cycle. It is based on attribution analysis using multiple nonlinear techniques (Support Vector Regression, Neural Networks) besides the traditional linear approach. The analysis was applied to several current reanalysis datasets for the 1979-2013 period, including MERRA, ERA-Interim and JRA-55, with the aim to compare how this type of data resolves especially the double-peaked solar response in temperature and ozone variables and the consequent changes induced by these anomalies. Equatorial temperature signals in the lower and upper stratosphere were found to be sufficiently robust and in qualitative agreement with previous observational studies. The analysis also pointed to the solar signal in the ozone datasets (i.e. MERRA and ERA-Interim) not being consistent with the observed double-peaked ozone anomaly extracted from satellite measurements. Consequently the results obtained by linear regression were confirmed by the nonlinear approach through all datasets, suggesting that linear regression is a relevant tool to sufficiently resolve the solar signal in the middle atmosphere. Furthermore, the seasonal dependence of the solar response was also discussed, mainly as a source of dynamical causalities in the wave propagation characteristics in the zonal wind and the induced meridional circulation in the winter hemispheres. The hypothetical mechanism of a weaker Brewer Dobson circulation was reviewed together with discussion of polar vortex stability.

Effects of problem-based learning by learning style in medical education.

PubMed

Chae, Su-Jin

2012-12-01

Although problem-based learning (PBL) has been popularized in many colleges, few studies have analyzed the relationship between individual differences and PBL. The purpose of this study was to analyze the relationship between learning style and the perception on the effects of PBL. Grasha-Riechmann Student Learning Style Scales was used to assess the learning styles of 38 students at Ajou University School of Medicine who were enrolled in a respiratory system course in 2011. The data were analyzed by regression analysis and Spearman correlation analysis. By regression analysis, dependent beta=0.478) and avoidant styles (beta=-0.815) influenced the learner's satisfaction with PBL. By Spearman correlation analysis, there was significant link between independent, dependent, and avoidant styles and the perception of the effect of PBL. There are few significant relationships between learning style and the perception of the effects of PBL. We must determine how to teach students with different learning styles and the factors that influence PBL.

Ataque de nervios: relationship to anxiety sensitivity and dissociation predisposition.

PubMed

Hinton, Devon E; Chong, Roberto; Pollack, Mark H; Barlow, David H; McNally, Richard J

2008-01-01

We investigated the relative importance of "fear of arousal symptoms" (i.e., anxiety sensitivity) and "dissociation tendency" in generating ataque de nervios. Puerto Rican patients attending an outpatient psychiatric clinic were assessed for ataque de nervios frequency in the previous month, and they completed the Anxiety Sensitivity Index (ASI) and the Dissociation Experiences Scale (DES). ASI scores were especially high in the ataque-positive group (M=41.6, SD=12.8) as compared with the ataque-negative group (M=27.2, SD=11.7), t(2, 68)=4.6, P<.001. Among the whole sample (N=70), in a logistic regression analysis, the ASI significantly predicted (odds ratio=2.6) the presence of ataque de nervios, but the DES did not. In a linear regression analysis, ataque severity was significantly predicted by both the ASI (beta=.46) and the DES (beta=.29). The theoretical and clinical implications of the strong relationship of the ASI to ataque severity are discussed.

Modelling daily water temperature from air temperature for the Missouri River.

PubMed

Zhu, Senlin; Nyarko, Emmanuel Karlo; Hadzima-Nyarko, Marijana

2018-01-01

The bio-chemical and physical characteristics of a river are directly affected by water temperature, which thereby affects the overall health of aquatic ecosystems. It is a complex problem to accurately estimate water temperature. Modelling of river water temperature is usually based on a suitable mathematical model and field measurements of various atmospheric factors. In this article, the air-water temperature relationship of the Missouri River is investigated by developing three different machine learning models (Artificial Neural Network (ANN), Gaussian Process Regression (GPR), and Bootstrap Aggregated Decision Trees (BA-DT)). Standard models (linear regression, non-linear regression, and stochastic models) are also developed and compared to machine learning models. Analyzing the three standard models, the stochastic model clearly outperforms the standard linear model and nonlinear model. All the three machine learning models have comparable results and outperform the stochastic model, with GPR having slightly better results for stations No. 2 and 3, while BA-DT has slightly better results for station No. 1. The machine learning models are very effective tools which can be used for the prediction of daily river temperature.

The nonlinear relations of the approximate number system and mathematical language to early mathematics development.

PubMed

Purpura, David J; Logan, Jessica A R

2015-12-01

Both mathematical language and the approximate number system (ANS) have been identified as strong predictors of early mathematics performance. Yet, these relations may be different depending on a child's developmental level. The purpose of this study was to evaluate the relations between these domains across different levels of ability. Participants included 114 children who were assessed in the fall and spring of preschool on a battery of academic and cognitive tasks. Children were 3.12 to 5.26 years old (M = 4.18, SD = .58) and 53.6% were girls. Both mixed-effect and quantile regressions were conducted. The mixed-effect regressions indicated that mathematical language, but not the ANS, nor other cognitive domains, predicted mathematics performance. However, the quantile regression analyses revealed a more nuanced relation among domains. Specifically, it was found that mathematical language and the ANS predicted mathematical performance at different points on the ability continuum. These dual nonlinear relations indicate that different mechanisms may enhance mathematical acquisition dependent on children's developmental abilities. (c) 2015 APA, all rights reserved).

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws

USGS Publications Warehouse

Xiao, X.; White, E.P.; Hooten, M.B.; Durham, S.L.

2011-01-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain. ?? 2011 by the Ecological Society of America.

Demographic, socio-economic, and cultural factors affecting fertility differentials in Nepal.

PubMed

Adhikari, Ramesh

2010-04-28

Traditionally Nepalese society favors high fertility. Children are a symbol of well-being both socially and economically. Although fertility has been decreasing in Nepal since 1981, it is still high compared to many other developing countries. This paper is an attempt to examine the demographic, socio-economic, and cultural factors for fertility differentials in Nepal. This paper has used data from the Nepal Demographic and Health Survey (NDHS 2006). The analysis is confined to ever married women of reproductive age (8,644). Both bivariate and multivariate analyses have been performed to describe the fertility differentials. The bivariate analysis (one-way ANOVA) was applied to examine the association between children ever born and women's demographic, socio-economic, and cultural characteristics. Besides bivariate analysis, the net effect of each independent variable on the dependent variable after controlling for the effect of other predictors has also been measured through multivariate analysis (multiple linear regressions). The mean numbers of children ever born (CEB) among married Nepali women of reproductive age and among women aged 40-49 were three and five children, respectively. There are considerable differentials in the average number of children ever born according to women's demographic, socio-economic, and cultural settings. Regression analysis revealed that age at first marriage, perceived ideal number of children, place of residence, literacy status, religion, mass media exposure, use of family planning methods, household headship, and experience of child death were the most important variables that explained the variance in fertility. Women who considered a higher number of children as ideal (beta = 0.03; p < 0.001), those who resided in rural areas (beta = 0.02; p < 0.05), Muslim women (beta = 0.07; p < 0.001), those who had ever used family planning methods (beta = 0.08; p < 0.001), and those who had a child-death experience (beta = 0.31; p < 0.001) were more likely to have a higher number of CEB compared to their counterparts. On the other hand, those who married at a later age (beta = -0.15; p < 0.001), were literate (beta = -0.05; p < 0.001), were exposed to both (radio/TV) mass media (beta = -0.05; p < 0.001), were richest (beta = -0.12; p < 0.001), and were from female-headed households (beta = -0.02; p < 0.05) had a lower number of children ever born than their counterparts. The average number of children ever born is high among women in Nepal. There are many contributing factors for the high fertility, among which are age at first marriage, perceived ideal number of children, literacy status, mass media exposure, wealth status, and child-death experience by mothers. All of these were strong predictors for CEB. It can be concluded that programs should aim to reduce fertility rates by focusing on these identified factors so that fertility as well as infant and maternal mortality and morbidity will be decreased and the overall well-being of the family maintained and enhanced.

Nonlinear and Synchronous Dissolved Organic Matter Dynamics in Streams Across an Agriculture Land Use and Climate Setting

NASA Astrophysics Data System (ADS)

Xenopoulos, M. A.; Vogt, R. J.

2014-12-01

There is now increasing evidence that non-linearity is a common response in ecological systems to pressures caused by human activities. There is also increasing evidence that exogenous environmental drivers, such as climate, induce spatial and temporal synchrony in a wide range of ecological variables. Using Moran's I and Pearson's correlation, we quantified the synchrony of dissolved organic carbon concentration (DOC) and quality (DOM; e.g., specific UV absorbance, Fluorescence Index, PARAFAC), nutrients, discharge and temperature in 40 streams that span an agriculture gradient (0 to >70% cropland), over 10 years. We then used breakpoint regression, 2D-Kolmogorov-Smirnov test and significant zero crossings (SiZer) analyses to quantify the prevalence of nonlinearity and ecological thresholds (breakpoints) where applicable. There was a high degree of synchrony in DOM quality (r > 0.7) but not DOC (r < 0.4). The degree of synchrony was driven in part by the catchment's land use. With respect to the nonlinear analyses we found non-linearity in ~50% of bivariate datasets analyzed. Non-linearity was also driven in part by the catchment's land use. Breakpoints defined different DOM properties. Nonlinearity and synchronous behaviour in DOM are intimately linked to land use.

Genomic prediction based on data from three layer lines using non-linear regression models.

PubMed

Huang, Heyun; Windig, Jack J; Vereijken, Addie; Calus, Mario P L

2014-11-06

Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a multi-trait genomic best linear unbiased prediction (GBLUP) model that modelled trait by line combinations as separate but correlated traits and (2) non-linear models based on kernel learning. These models were compared to conventional linear models for genomic prediction for two lines of brown layer hens (B1 and B2) and one line of white hens (W1). The three lines each had 1004 to 1023 training and 238 to 240 validation animals. Prediction accuracy was evaluated by estimating the correlation between observed phenotypes and predicted breeding values. When the training dataset included only data from the evaluated line, non-linear models yielded at best a similar accuracy as linear models. In some cases, when adding a distantly related line, the linear models showed a slight decrease in performance, while non-linear models generally showed no change in accuracy. When only information from a closely related line was used for training, linear models and non-linear radial basis function (RBF) kernel models performed similarly. The multi-trait GBLUP model took advantage of the estimated genetic correlations between the lines. Combining linear and non-linear models improved the accuracy of multi-line genomic prediction. Linear models and non-linear RBF models performed very similarly for genomic prediction, despite the expectation that non-linear models could deal better with the heterogeneous multi-population data. This heterogeneity of the data can be overcome by modelling trait by line combinations as separate but correlated traits, which avoids the occasional occurrence of large negative accuracies when the evaluated line was not included in the training dataset. Furthermore, when using a multi-line training dataset, non-linear models provided information on the genotype data that was complementary to the linear models, which indicates that the underlying data distributions of the three studied lines were indeed heterogeneous.

Study of solar wind spectra by nonlinear waves interaction

NASA Astrophysics Data System (ADS)

Dwivedi, Navin; Sharma, Rampal; Narita, Yasuhito

2014-05-01

The nature of small-scale turbulent fluctuations in the solar wind (SW) turbulence is a topic that is being investigated extensively nowadays, both theoretically and observationally. Although recent observations predict the evidence of the dominance of kinetic Alfvén waves (KAW) at sub-ion scales with frequency below than ion cyclotron frequency, while other studies suggest that the KAW mode cannot carry the turbulence cascade down to electron scales and that the whistler mode is more relevant. In the present work, nonlinear interaction of kinetic Alfvén wave with whistler wave is considered as one of the possible cause responsible for the solar wind turbulence. A set of coupled dimensionless equations are derived for the intermediate beta plasmas and the nonlinear interaction between these two wave modes has been studied. As a consequence of ponderomotive nonlinearity, the pump KAW becomes filamented when its power exceeds the threshold for the filamentation instability. Whistler is considered to be weak and thus doesn't have enough intensity to initiate its own localization. It gets localized while propagating through the density channel created by KAW localization. In addition, spectral scales of power spectra of KAW and whistler are also calculated. The steeper spectra are found with scaling greater than -5/3. This type of nonlinear interaction between different wave modes and steeper spectra is one of the reasons for the solar wind turbulence and particles acceleration. This work is partially supported by DST (India) and FP7/STORM (313038)

Optimal estimation for discrete time jump processes

NASA Technical Reports Server (NTRS)

Vaca, M. V.; Tretter, S. A.

1978-01-01

Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are derived. The approach used is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. Thus a general representation is obtained for optimum estimates, and recursive equations are derived for minimum mean-squared error (MMSE) estimates. In general, MMSE estimates are nonlinear functions of the observations. The problem is considered of estimating the rate of a DTJP when the rate is a random variable with a beta probability density function and the jump amplitudes are binomially distributed. It is shown that the MMSE estimates are linear. The class of beta density functions is rather rich and explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.

Functional characterization of the beta-adrenergic receptor subtypes expressed by CA1 pyramidal cells in the rat hippocampus.

PubMed

Hillman, Kristin L; Doze, Van A; Porter, James E

2005-08-01

Recent studies have demonstrated that activation of the beta-adrenergic receptor (AR) using the selective beta-AR agonist isoproterenol (ISO) facilitates pyramidal cell long-term potentiation in the cornu ammonis 1 (CA1) region of the rat hippocampus. We have previously analyzed beta-AR genomic expression patterns of 17 CA1 pyramidal cells using single cell reverse transcription-polymerase chain reaction, demonstrating that all samples expressed the beta2-AR transcript, with four of the 17 cells additionally expressing mRNA for the beta1-AR subtype. However, it has not been determined which beta-AR subtypes are functionally expressed in CA1 for these same pyramidal neurons. Using cell-attached recordings, we tested the ability of ISO to increase pyramidal cell action potential (AP) frequency in the presence of subtype-selective beta-AR antagonists. ICI-118,551 [(+/-)-1-[2,3-(dihydro-7-methyl-1H-inden-4-yl)oxy]-3-[(1-methylethyl)amino]-2-butanol] and butoxamine [alpha-[1-(t-butylamino)ethyl]-2,5-dimethoxybenzyl alcohol) hydrochloride], agents that selectively block the beta2-AR, produced significant parallel rightward shifts in the concentration-response curves for ISO. From these curves, apparent equilibrium dissociation constant (K(b)) values of 0.3 nM for ICI-118,551 and 355 nM for butoxamine were calculated using Schild regression analysis. Conversely, effective concentrations of the selective beta1-AR antagonists CGP 20712A [(+/-)-2-hydroxy-5-[2-([2-hydroxy-3-(4-[1-methyl-4-(trifluoromethyl)-1H-imidazol-2-yl]phenoxy)propyl]amino)ethoxy]-benzamide methanesulfonate] and atenolol [4-[2'-hydroxy-3'-(isopropyl-amino)propoxy]phenylacetamide] did not significantly affect the pyramidal cell response to ISO. However, at higher concentrations, atenolol significantly decreased the potency for ISO-mediated AP frequencies. From these curves, an apparent atenolol K(b) value of 3162 nM was calculated. This pharmacological profile for subtype-selective beta-AR antagonists indicates that beta2-AR activation is mediating the increased AP frequency. Knowledge of functional AR expression in CA1 pyramidal neurons will aid future long-term potentiation studies by allowing selective manipulation of specific beta-AR subtypes.

Velocity Curve Analysis of Spectroscopic Binary Stars AI Phe, GM Dra, HD 93917 and V502 Oph by Nonlinear Regression

NASA Astrophysics Data System (ADS)

Karami, K.; Mohebi, R.

2007-08-01

We introduce a new method to derive the orbital parameters of spectroscopic binary stars by nonlinear least squares of (o-c). Using the measured radial velocity data of the four double lined spectroscopic binary systems, AI Phe, GM Dra, HD 93917 and V502 Oph, we derived both the orbital and combined spectroscopic elements of these systems. Our numerical results are in good agreement with the those obtained using the method of Lehmann-Filhé.

Error Rates Resulting From Anemia Can Be Corrected in Multiple Commonly Used Point of Care Glucometers

DTIC Science & Technology

2008-01-01

strategies, increasing the prevalence of both hypoglycemia and anemia in the ICU.14–20 The change in allogeneic blood transfusion practices occurred in...measurements in samples with low HCT levels.4,5,7,8,12 The error occurs because de- creased red blood cell causes less displacement of plasma, resulting...Nonlinear component regression was performed be- cause HCT has a nonlinear effect on accuracy of POC glucometers. A dual parameter correction factor was

PharmML in Action: an Interoperable Language for Modeling and Simulation

PubMed Central

Bizzotto, R; Smith, G; Yvon, F; Kristensen, NR; Swat, MJ

2017-01-01

PharmML1 is an XML‐based exchange format2, 3, 4 created with a focus on nonlinear mixed‐effect (NLME) models used in pharmacometrics,5, 6 but providing a very general framework that also allows describing mathematical and statistical models such as single‐subject or nonlinear and multivariate regression models. This tutorial provides an overview of the structure of this language, brief suggestions on how to work with it, and use cases demonstrating its power and flexibility. PMID:28575551

Two-dimensional advective transport in ground-water flow parameter estimation

USGS Publications Warehouse

Anderman, E.R.; Hill, M.C.; Poeter, E.P.

1996-01-01

Nonlinear regression is useful in ground-water flow parameter estimation, but problems of parameter insensitivity and correlation often exist given commonly available hydraulic-head and head-dependent flow (for example, stream and lake gain or loss) observations. To address this problem, advective-transport observations are added to the ground-water flow, parameter-estimation model MODFLOWP using particle-tracking methods. The resulting model is used to investigate the importance of advective-transport observations relative to head-dependent flow observations when either or both are used in conjunction with hydraulic-head observations in a simulation of the sewage-discharge plume at Otis Air Force Base, Cape Cod, Massachusetts, USA. The analysis procedure for evaluating the probable effect of new observations on the regression results consists of two steps: (1) parameter sensitivities and correlations calculated at initial parameter values are used to assess the model parameterization and expected relative contributions of different types of observations to the regression; and (2) optimal parameter values are estimated by nonlinear regression and evaluated. In the Cape Cod parameter-estimation model, advective-transport observations did not significantly increase the overall parameter sensitivity; however: (1) inclusion of advective-transport observations decreased parameter correlation enough for more unique parameter values to be estimated by the regression; (2) realistic uncertainties in advective-transport observations had a small effect on parameter estimates relative to the precision with which the parameters were estimated; and (3) the regression results and sensitivity analysis provided insight into the dynamics of the ground-water flow system, especially the importance of accurate boundary conditions. In this work, advective-transport observations improved the calibration of the model and the estimation of ground-water flow parameters, and use of regression and related techniques produced significant insight into the physical system.

Intimate Partner Violence Associated with Postpartum Depression, Regardless of Socioeconomic Status.

PubMed

Kothari, Catherine L; Liepman, Michael R; Shama Tareen, R; Florian, Phyllis; Charoth, Remitha M; Haas, Suzanne S; McKean, Joseph W; Moe, Angela; Wiley, James; Curtis, Amy

2016-06-01

Objective This study examined whether socioeconomic status moderated the association between intimate partner violence (IPV) and postpartum depression among a community-based sample of women. Defining the role of poverty in the risk of postpartum depression for IPV victims enables prioritization of health promotion efforts to maximize the effectiveness of existing maternal-infant resources. Methods This cross-sectional telephone-survey study interviewed 301 postpartum women 2 months after delivery, screening them for IPV and depression [using Edinburgh Postnatal Depression Scale (EPDS)]. Socioeconomic status was defined by insurance (Medicaid-paid-delivery or not). This analysis controlled for the following covariates, collected through interview and medical-record review: demographics, obstetric history, prenatal health and additional psychosocial risk factors. After adjusting for significant covariates, multiple linear regression was conducted to test whether socioeconomic status confounded or moderated IPV's relationship with EPDS-score. Results Ten percent of participants screened positive for postpartum depression, 21.3 % screened positive for current or previous adult emotional or physical abuse by a partner, and 32.2 % met poverty criteria. IPV and poverty were positively associated with each other (χ(2) (1) = 11.76, p < .001) and with EPDS score (IPV: beta 3.2 (CI 2.0, 4.5) p < .001, poverty: beta 1.3 (CI 0.2, 2.4) p = .017). In the multiple linear regression, IPV remained significantly associated, but poverty did not (IPV: adjusted beta 3.1 (CI 1.8, 4.3) p < .001, poverty: adjusted beta 0.8 (CI -0.3, 1.9) p = .141), and no statistically significant interaction between IPV and poverty was found. Conclusions Study findings illustrated that IPV was strongly associated with postpartum depression, outweighing the influence of socioeconomic status upon depression for postpartum women.

The Effect of Plan Type and Comprehensive Medication Reviews on High-Risk Medication Use.

PubMed

Almodovar, Armando Silva; Axon, David Rhys; Coleman, Ashley M; Warholak, Terri; Nahata, Milap C

2018-05-01

In 2007, the Centers for Medicare & Medicaid Services (CMS) instituted a star rating system using performance outcome measures to assess Medicare Advantage Prescription Drug (MAPD) and Prescription Drug Plan (PDP) providers. To assess the relationship between 2 performance outcome measures for Medicare insurance providers, comprehensive medication reviews (CMRs), and high-risk medication use. This cross-sectional study included Medicare Part C and Part D performance data from the 2014 and 2015 calendar years. Performance data were downloaded per Medicare contract from the CMS. We matched Medicare insurance provider performance data with the enrollment data of each contract. Mann Whitney U and Spearman rho tests and a hierarchical linear regression model assessed the relationship between provider characteristics, high-risk medication use, and CMR completion rate outcome measures. In 2014, an inverse correlation between CMR completion rate and high-risk medication use was identified among MAPD plan providers. This relationship was further strengthened in 2015. No correlation was detected between the CMR completion rate and high-risk medication use among PDP plan providers in either year. A multivariate regression found an inverse association with high-risk medication use among MAPD plan providers in comparison with PDP plan providers in 2014 (beta = -0.358, P < 0.001) and 2015 (beta = -0.350, P < 0.001), the CMR completion rate in 2015 (beta = -0.221, P < 0.001), and enrollee population size in 2015 (beta = -0.203, P = 0.001). This study found that MAPD plan providers and higher CMR completion rates were associated with lower use of high-risk medications among beneficiaries. No outside funding supported this study. Silva Almodovar reports a fellowship funded by SinfoniaRx, Tucson, Arizona, during the time of this study. The other authors have nothing to disclose.

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

Thein, S.L.; Weatherall, D.J.; Sampietro, M.

[open quotes]Heterocellular hereditary persistence of fetal hemoglobin[close quotes] (HPFH) is the term used to describe the genetically determined persistence of fetal hemoglobin (Hb F) production into adult life, in the absence of any related hematological disorder. Whereas some forms are caused by mutations in the [beta]-globin gene cluster on chromosome 11, others segregate independently. While the latter are of particular interest with respect to the regulation of globin gene switching, it has not been possible to determine their chromosomal location, mainly because their mode of inheritance is not clear, but also because several other factors are known to modify Hbmore » F production. The authors have examined a large Asian Indian pedigree which includes individuals with heterocellular HPFH associated with [beta]-thalassemia and/or [alpha]-thalassemia. Segregation analysis was conducted on the HPFH trait FC, defined to be the percentage of Hb F-containing cells (F-cells), using the class D regressive model. The results provide evidence for the presence of a major gene, dominant or codominant, which controls the FC values with residual familial correlations. The major gene was detected when the effects of genetic modifiers, notably [beta]-thalassemia and the XmnI-[sup G][gamma] polymorphism, are accounted for in this analysis. Linkage with the [beta]-globin gene cluster is excluded. The transmission of the FC values in this pedigree is informative enough to allow detection of linkage with an appropriate marker(s). The analytical approach outlined in this study, using simple regression to allow for genetic modifiers and thus allowing the mode of inheritance of a trait to be dissected out, may be useful as a model for segregation and linkage analyses of other complex phenotypes. 39 refs., 4 figs., 6 tabs.« less

Secular and Religious Social Support Better Protect Blacks than Whites against Depressive Symptoms.

PubMed

Assari, Shervin; Moghani Lankarani, Maryam

2018-05-04

Purpose: Although the protective effect of social support against depression is well known, limited information exists on racial differences in this association. The current study examined Black-White differences in the effects of religious and secular emotional social support on depressive symptoms in a national sample of older adults in the United States. Methods: With a longitudinal prospective design, the Religion, Aging and Health Survey, 2001⁻2004, followed 1493 Black ( n = 734) and White ( n = 759) elderly individuals (age 66 and older) for three years. Race, demographics (age and gender), socio-economics (education and marital status) and frequency of church attendance were measured at baseline in 2001. Secular social support, religious social support, chronic medical conditions and depressive symptoms [8- item Center for Epidemiological Studies-Depression scale (CES-D)] were measured in 2004. Multiple linear regression models were used for data analysis. In the pooled sample, secular and religious social support were both protective against depressive symptoms, net of all covariates. Race interacted with secular ( β = −0.62 for interaction) and religious ( β = −0.21 for interaction) social support on baseline depressive symptoms ( p < 0.05 for both interactions), suggesting larger protections for Blacks compared to Whites. In race-specific models, the regression weight for the effect of secular social support on depressive symptoms was larger for Blacks ( β = −0.64) than Whites ( β = −0.16). Conclusion: We found Black—White differences in the protective effects of secular and religious social support against depressive symptoms. Blacks seem to benefit more from the same level of emotional social support, regardless of its source, compared to Whites.

BIODEGRADATION PROBABILITY PROGRAM (BIODEG)

EPA Science Inventory

The Biodegradation Probability Program (BIODEG) calculates the probability that a chemical under aerobic conditions with mixed cultures of microorganisms will biodegrade rapidly or slowly. It uses fragment constants developed using multiple linear and non-linear regressions and d...

The effects of spatial autoregressive dependencies on inference in ordinary least squares: a geometric approach

NASA Astrophysics Data System (ADS)

Smith, Tony E.; Lee, Ka Lok

2012-01-01

There is a common belief that the presence of residual spatial autocorrelation in ordinary least squares (OLS) regression leads to inflated significance levels in beta coefficients and, in particular, inflated levels relative to the more efficient spatial error model (SEM). However, our simulations show that this is not always the case. Hence, the purpose of this paper is to examine this question from a geometric viewpoint. The key idea is to characterize the OLS test statistic in terms of angle cosines and examine the geometric implications of this characterization. Our first result is to show that if the explanatory variables in the regression exhibit no spatial autocorrelation, then the distribution of test statistics for individual beta coefficients in OLS is independent of any spatial autocorrelation in the error term. Hence, inferences about betas exhibit all the optimality properties of the classic uncorrelated error case. However, a second more important series of results show that if spatial autocorrelation is present in both the dependent and explanatory variables, then the conventional wisdom is correct. In particular, even when an explanatory variable is statistically independent of the dependent variable, such joint spatial dependencies tend to produce "spurious correlation" that results in over-rejection of the null hypothesis. The underlying geometric nature of this problem is clarified by illustrative examples. The paper concludes with a brief discussion of some possible remedies for this problem.

Factors associated to clinical learning in nursing students in primary health care: an analytical cross-sectional study

PubMed Central

Serrano-Gallardo, Pilar; Martínez-Marcos, Mercedes; Espejo-Matorrales, Flora; Arakawa, Tiemi; Magnabosco, Gabriela Tavares; Pinto, Ione Carvalho

2016-01-01

ABSTRACT Objective: to identify the students' perception about the quality of clinical placements and asses the influence of the different tutoring processes in clinical learning. Methods: analytical cross-sectional study on second and third year nursing students (n=122) about clinical learning in primary health care. The Clinical Placement Evaluation Tool and a synthetic index of attitudes and skills were computed to give scores to the clinical learning (scale 0-10). Univariate, bivariate and multivariate (multiple linear regression) analyses were performed. Results: the response rate was 91.8%. The most commonly identified tutoring process was "preceptor-professor" (45.2%). The clinical placement was assessed as "optimal" by 55.1%, relationship with team-preceptor was considered good by 80.4% of the cases and the average grade for clinical learning was 7.89. The multiple linear regression model with more explanatory capacity included the variables "Academic year" (beta coefficient = 1.042 for third-year students), "Primary Health Care Area (PHC)" (beta coefficient = 0.308 for Area B) and "Clinical placement perception" (beta coefficient = - 0.204 for a suboptimal perception). Conclusions: timeframe within the academic program, location and clinical placement perception were associated with students' clinical learning. Students' perceptions of setting quality were positive and a good team-preceptor relationship is a matter of relevance. PMID:27627124

Treatment of colon cancer cells using the cytosine deaminase/5-fluorocytosine suicide system induces apoptosis, modulation of the proteome, and Hsp90beta phosphorylation.

PubMed

Negroni, Luc; Samson, Michel; Guigonis, Jean-Marie; Rossi, Bernard; Pierrefite-Carle, Valérie; Baudoin, Christian

2007-10-01

The bacterial cytosine deaminase (CD) gene, associated with the 5-fluorocytosine (5FC) prodrug, is one of the most widely used suicide systems in gene therapy. Introduction of the CD gene within a tumor induces, after 5FC treatment of the animal, a local production of 5-fluorouracil resulting in intratumor chemotherapy. Destruction of the gene-modified tumor is then followed by the triggering of an antitumor immune reaction resulting in the regression of distant wild-type metastasis. The global effects of 5FC on colorectal adenocarcinoma cells expressing the CD gene were analyzed using the proteomic method. Application of 5FC induced apoptosis and 19 proteins showed a significant change in 5FC-treated cells compared with control cells. The up-regulated and down-regulated proteins include cytoskeletal proteins, chaperones, and proteins involved in protein synthesis, the antioxidative network, and detoxification. Most of these proteins are involved in resistance to anticancer drugs and resistance to apoptosis. In addition, we show that the heat shock protein Hsp90beta is phosphorylated on serine 254 upon 5FC treatment. Our results suggest that activation of Hsp90beta by phosphorylation might contribute to tumor regression and tumor immunogenicity. Our findings bring new insights into the mechanism of the anticancer effects induced by CD/5FC treatment.

Empirical prediction and validation of antibacterial inhibitory effects of various plant essential oils on common pathogenic bacteria.

PubMed

Akdemir Evrendilek, Gulsun

2015-06-02

In this study, fractional compound composition, antioxidant capacity, and phenolic substance content of 14 plant essential oils-anise (Pimpinella anisum), bay leaves (Laurus nobilis), cinnamon bark (Cinnamomum verum), clove (Eugenia caryophyllata), fennel (Foeniculum vulgare), hop (Humulus lupulus), Istanbul oregano (Origanum vulgare subsp. hirtum), Izmir oregano (Origanum onites), mint (Mentha piperita), myrtus (Myrtus communis), orange peel (Citrus sinensis), sage (Salvia officinalis), thyme (Thymbra spicata), and Turkish oregano (Origanum minutiflorum)--were related to inhibition of 10 bacteria through multiple linear or non-linear (M(N)LR) models-four Gram-positive bacteria of Listeria innocua, coagulase-negative staphylococci, Staphylococcus aureus, and Bacillus subtilis, and six Gram-negative bacteria of Yersinia enterocolitica, Salmonella Enteritidis, Salmonella Typhimurium, Proteus mirabilis, Escherichia coli O157:H7, and Klebsiella oxytoca. A total of 65 compounds with different antioxidant capacity, phenolic substance content and antibacterial properties were detected with 14 plant essential oils. The best-fit M(N)LR models indicated that relative to anise essential oil, the essential oils of oreganos, cinnamon, and thyme had consistently high inhibitory effects, while orange peel essential oil had consistently a low inhibitory effect. Regression analysis indicated that beta-bisabolene (Turkish and Istanbul oreganos), and terpinolene (thyme) were found to be the most inhibitory compounds regardless of the bacteria type tested. Copyright © 2015 Elsevier B.V. All rights reserved.

Treatment of amyloidosis.

PubMed

Tan, S Y; Pepys, M B; Hawkins, P N

1995-08-01

Amyloidosis is the extracellular deposition of normally soluble autologous protein in a characteristic abnormal fibrillar form. Systemic amyloidosis and some local forms are progressive, cause major morbidity, and are often fatal. No treatment specifically causes the resolution of amyloid deposits, but therapy that reduces the supply of amyloid fibril precursor proteins can improve survival and preserve organ function. Major regression of amyloid occurs in at least a proportion of such cases, suggesting that the clinical improvement reflects mobilization of amyloid. The clearest evidence for regression of amyloid has been obtained in juvenile rheumatoid arthritis patients with AA amyloidosis treated with chlorambucil. This drug suppresses the acute phase production of serum amyloid A protein, the precursor of AA amyloid fibrils, and is associated with remission of proteinuria and greatly improved survival. In many such patients, scintigraphy with serum amyloid P component shows major regression of amyloid over 12 to 36 months and frequently reveals a discrepancy between the local amyloid load and organ dysfunction. Measurement of target organ function is therefore not an adequate method for monitoring treatment aimed at promoting the resolution of amyloid. In monoclonal immunoglobulin light chain (AL) amyloidosis the aim of treatment is to suppress the underlying B-cell clone and, therefore, production of the amyloid fibril precursor protein. This can be difficult to achieve or sustain and, since the prognosis is so poor, many patients die before benefits of therapy are realized. A recent development has been the introduction of liver transplantation as treatment for familial amyloid polyneuropathy caused by transthyretin gene mutations. This leads to the disappearance of variant transthyretin from the plasma and halts progression of the neurologic disease. Features of autonomic neuropathy frequently ameliorate, and improvement in peripheral motor nerve function has been recently reported. Serum amyloid P component scans show regression of associated visceral amyloidosis. This surgical form of gene therapy holds much promise for patients with familial amyloid polyneuropathy and has been widely adopted. The only other form of amyloidosis in which the supply of the fibril precursor protein can be sharply reduced is beta 2M amyloidosis in long-term hemodialysis patients. Renal transplantation lowers the plasma concentration of beta 2M to normal levels and is associated with rapid improvement of the osteoarticular symptoms. Preliminary observations suggest that the beta 2M amyloid deposits also can regress in some patients.(ABSTRACT TRUNCATED AT 400 WORDS)

Bias and uncertainty in regression-calibrated models of groundwater flow in heterogeneous media

USGS Publications Warehouse

Cooley, R.L.; Christensen, S.

2006-01-01

Groundwater models need to account for detailed but generally unknown spatial variability (heterogeneity) of the hydrogeologic model inputs. To address this problem we replace the large, m-dimensional stochastic vector ?? that reflects both small and large scales of heterogeneity in the inputs by a lumped or smoothed m-dimensional approximation ????*, where ?? is an interpolation matrix and ??* is a stochastic vector of parameters. Vector ??* has small enough dimension to allow its estimation with the available data. The consequence of the replacement is that model function f(????*) written in terms of the approximate inputs is in error with respect to the same model function written in terms of ??, ??,f(??), which is assumed to be nearly exact. The difference f(??) - f(????*), termed model error, is spatially correlated, generates prediction biases, and causes standard confidence and prediction intervals to be too small. Model error is accounted for in the weighted nonlinear regression methodology developed to estimate ??* and assess model uncertainties by incorporating the second-moment matrix of the model errors into the weight matrix. Techniques developed by statisticians to analyze classical nonlinear regression methods are extended to analyze the revised method. The analysis develops analytical expressions for bias terms reflecting the interaction of model nonlinearity and model error, for correction factors needed to adjust the sizes of confidence and prediction intervals for this interaction, and for correction factors needed to adjust the sizes of confidence and prediction intervals for possible use of a diagonal weight matrix in place of the correct one. If terms expressing the degree of intrinsic nonlinearity for f(??) and f(????*) are small, then most of the biases are small and the correction factors are reduced in magnitude. Biases, correction factors, and confidence and prediction intervals were obtained for a test problem for which model error is large to test robustness of the methodology. Numerical results conform with the theoretical analysis. ?? 2005 Elsevier Ltd. All rights reserved.

Relationship between age and elite marathon race time in world single age records from 5 to 93 years

PubMed Central

2014-01-01

Background The aims of the study were (i) to investigate the relationship between elite marathon race times and age in 1-year intervals by using the world single age records in marathon running from 5 to 93 years and (ii) to evaluate the sex difference in elite marathon running performance with advancing age. Methods World single age records in marathon running in 1-year intervals for women and men were analysed regarding changes across age for both men and women using linear and non-linear regression analyses for each age for women and men. Results The relationship between elite marathon race time and age was non-linear (i.e. polynomial regression 4th degree) for women and men. The curve was U-shaped where performance improved from 5 to ~20 years. From 5 years to ~15 years, boys and girls performed very similar. Between ~20 and ~35 years, performance was quite linear, but started to decrease at the age of ~35 years in a curvilinear manner with increasing age in both women and men. The sex difference increased non-linearly (i.e. polynomial regression 7th degree) from 5 to ~20 years, remained unchanged at ~20 min from ~20 to ~50 years and increased thereafter. The sex difference was lowest (7.5%, 10.5 min) at the age of 49 years. Conclusion Elite marathon race times improved from 5 to ~20 years, remained linear between ~20 and ~35 years, and started to increase at the age of ~35 years in a curvilinear manner with increasing age in both women and men. The sex difference in elite marathon race time increased non-linearly and was lowest at the age of ~49 years. PMID:25120915

Beta-blocker usage after malignant melanoma diagnosis and survival: a population-based nested case-control study.

PubMed

McCourt, C; Coleman, H G; Murray, L J; Cantwell, M M; Dolan, O; Powe, D G; Cardwell, C R

2014-04-01

Beta-blockers have potential antiangiogenic and antimigratory activity. Studies have demonstrated a survival benefit in patients with malignant melanoma treated with beta-blockers. To investigate the association between postdiagnostic beta-blocker usage and risk of melanoma-specific mortality in a population-based cohort of patients with malignant melanoma. Patients with incident malignant melanoma diagnosed between 1998 and 2010 were identified within the U.K. Clinical Practice Research Datalink and confirmed using cancer registry data. Patients with malignant melanoma with a melanoma-specific death (cases) recorded by the Office of National Statistics were matched on year of diagnosis, age and sex to four malignant melanoma controls (who lived at least as long after diagnosis as their matched case). A nested case-control approach was used to investigate the association between postdiagnostic beta-blocker usage and melanoma-specific death and all-cause mortality. Conditional logistic regression was applied to generate odds ratios (ORs) and 95% confidence intervals (CIs) for beta-blocker use determined from general practitioner prescribing. Beta-blocker medications were prescribed after malignant melanoma diagnosis to 20·2% of 242 patients who died from malignant melanoma (cases) and 20·3% of 886 matched controls. Consequently, there was no association between beta-blocker use postdiagnosis and cancer-specific death (OR 0·99, 95% CI 0·68-1·42), which did not markedly alter after adjustment for confounders including stage (OR 0·87, 95% CI 0·56-1·34). No significant associations were detected for individual beta-blocker types, by defined daily doses of use or for all-cause mortality. Contrary to some previous studies, beta-blocker use after malignant melanoma diagnosis was not associated with reduced risk of death from melanoma in this U.K. population-based study. © 2014 British Association of Dermatologists.

Pressure-anisotropy-induced nonlinearities in the kinetic magnetorotational instability

NASA Astrophysics Data System (ADS)

Squire, J.; Quataert, E.; Kunz, M. W.

2017-12-01

In collisionless and weakly collisional plasmas, such as hot accretion flows onto compact objects, the magnetorotational instability (MRI) can differ significantly from the standard (collisional) MRI. In particular, pressure anisotropy with respect to the local magnetic-field direction can both change the linear MRI dispersion relation and cause nonlinear modifications to the mode structure and growth rate, even when the field and flow perturbations are very small. This work studies these pressure-anisotropy-induced nonlinearities in the weakly nonlinear, high-ion-beta regime, before the MRI saturates into strong turbulence. Our goal is to better understand how the saturation of the MRI in a low-collisionality plasma might differ from that in the collisional regime. We focus on two key effects: (i) the direct impact of self-induced pressure-anisotropy nonlinearities on the evolution of an MRI mode, and (ii) the influence of pressure anisotropy on the `parasitic instabilities' that are suspected to cause the mode to break up into turbulence. Our main conclusions are: (i) The mirror instability regulates the pressure anisotropy in such a way that the linear MRI in a collisionless plasma is an approximate nonlinear solution once the mode amplitude becomes larger than the background field (just as in magnetohyrodynamics). This implies that differences between the collisionless and collisional MRI become unimportant at large amplitudes. (ii) The break up of large-amplitude MRI modes into turbulence via parasitic instabilities is similar in collisionless and collisional plasmas. Together, these conclusions suggest that the route to magnetorotational turbulence in a collisionless plasma may well be similar to that in a collisional plasma, as suggested by recent kinetic simulations. As a supplement to these findings, we offer guidance for the design of future kinetic simulations of magnetorotational turbulence.

Beta-2 adrenoceptor genotype and progress in term and late preterm active labor

PubMed Central

MILLER, Russell S.; SMILEY, Richard M.; DANIEL, Danette; WENG, Chunhua; EMALA, Charles W.; BLOUIN, Jean-Louis; FLOOD, Pamela D.

2011-01-01

OBJECTIVE To evaluate whether beta-2 adrenoceptor genotype at a functional polymorphic site encoding for amino acid residue 16 influences rate of cervical dilatation in term and late preterm active labor. STUDY DESIGN Subjects that underwent vaginal delivery at 34 or greater weeks gestational age between May, 2006, and August, 2007, were identified. Each subject had provided venous blood from which DNA was extracted for beta-2 adrenoceptor genotyping. Digital cervical examinations with paired examination times were collected from intrapartum records. Rate of cervical dilatation in active labor was determined using linear regression and rates were compared between genotype groups. RESULTS Among 401 subjects with satisfactory genotype and intrapartum data, overall rate of active labor was 0.76+/−0.01 cm/hr. When labor was compared by genotype, homozygous Arg/Arg16 subjects progressed at a slower rate (0.64+/−0.03 cm/hr) than all other pooled genotypes (0.8+/−0.02 cm/hr). CONCLUSION Homozygous beta-2 adrenoceptor genotype encoding for Arg/Arg16 was associated with slower progress in active labor. PMID:21600547

Endocrine regulation of gonadotropin and growth hormone gene transcription in fish.

PubMed

Melamed, P; Rosenfeld, H; Elizur, A; Yaron, Z

1998-06-01

The pituitary of a number of teleosts contains two gonadotropins (GtHs) which are produced in distinct populations of cells; the beta subunit of the GtH I being found in close proximity to the somatotrophs, while the II beta cells are more peripheral. In several species the GtH beta subunits are expressed at varying levels throughout the reproductive cycle, the I beta dominating in early maturing fish, after which the II beta becomes predominant. This suggests differential control of the beta subunit synthesis which may be regulated by both hypothalamic hormones and gonadal steroids. At ovulation and spawning, changes also occur in the somatotrophs, which become markedly more active, while plasma growth hormone (GH) levels increase. In a number of species, GnRH elevates either the I beta or the II beta mRNA levels, depending on the reproductive state of the fish. In tilapia, the GnRH effect on the II beta appears to be mediated through both cAMP-PKA and PKC pathways. GnRH also stimulates GH release in both goldfish and tilapia, but it increases the GH transcript levels only in goldfish; both GnRH and direct activation of PKC are ineffective in altering GH mRNA in tilapia pituitary cells. Dopamine (DA) does not alter II beta transcript levels in cultured tilapia pituitary cells, but increases GH mRNA levels in both rainbow trout and tilapia, in a PKA-dependent manner. This effect appears to be through interactions with Pit-1 and also by stabilizing the mRNA. Somatostatin (SRIF) does not alter GH transcript levels in either tilapia or rainbow trout, although it may alter GH synthesis by modulation of translation. Gonadal steroids appear to have differential effects on the transcription of the beta subunits. In tilapia, testosterone (T) elevates I beta mRNA levels in cells from immature or early maturing fish (in low doses), but depresses them in cells from late maturing fish and is ineffective in cells from regressed fish. Similar results were seen in early recrudescing male coho salmon injected with T or E2. T or E2 administered in vivo has dramatic stimulatory effects on the II beta transcript levels in immature fish of a number of species, while less powerful effects are seen in vitro. A response is also seen in cells from early maturing rainbow trout or tilapia, or regressed tilapia, but not in cells from late maturing or spawning fish. These results are substantiated by the finding that the promoter of the salmon II beta gene contains several estrogen responsive elements (EREs) which react and interact differently when exposed to varying levels of E2. In addition, activator protein-1 (AP-1) and steroidogenic factor-1 (SF-1) response elements are also found in the salmon II beta promoter; the AP-1 site is located close to a half ERE, while the SF-1 acts synergistically with the E2 receptor. The mRNA levels of both AP-1 and SP-1 are elevated, at least in mammals, by GnRH, suggesting possible sites for cross-talk between GnRH and steroid activated pathways. Reports of the effects of T or E2 on GH transcription differ. No effect is seen in vitro in pituitaries of tilapia, juvenile rainbow trout or common carp, but T does increase the transcript levels in pituitaries of both immature and mature goldfish. Reasons for these discrepancies are unclear, but other systemic hormones may be more instrumental than the gonadal steroids in regulating GH transcription. These include T3 which increases both GH mRNA levels and de novo synthesis (in tilapia and common carp) and insulin-like growth factor-I (IGF-I) which reduces GH transcript levels as well as inhibiting GH release.

Parameter estimation of Monod model by the Least-Squares method for microalgae Botryococcus Braunii sp

NASA Astrophysics Data System (ADS)

See, J. J.; Jamaian, S. S.; Salleh, R. M.; Nor, M. E.; Aman, F.

2018-04-01

This research aims to estimate the parameters of Monod model of microalgae Botryococcus Braunii sp growth by the Least-Squares method. Monod equation is a non-linear equation which can be transformed into a linear equation form and it is solved by implementing the Least-Squares linear regression method. Meanwhile, Gauss-Newton method is an alternative method to solve the non-linear Least-Squares problem with the aim to obtain the parameters value of Monod model by minimizing the sum of square error ( SSE). As the result, the parameters of the Monod model for microalgae Botryococcus Braunii sp can be estimated by the Least-Squares method. However, the estimated parameters value obtained by the non-linear Least-Squares method are more accurate compared to the linear Least-Squares method since the SSE of the non-linear Least-Squares method is less than the linear Least-Squares method.

Entropy-based financial asset pricing.

PubMed

Ormos, Mihály; Zibriczky, Dávid

2014-01-01

We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return-entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy.

Entropy-Based Financial Asset Pricing

PubMed Central

Ormos, Mihály; Zibriczky, Dávid

2014-01-01

We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return – entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy. PMID:25545668

Method development estimating ambient mercury concentration from monitored mercury wet deposition

NASA Astrophysics Data System (ADS)

Chen, S. M.; Qiu, X.; Zhang, L.; Yang, F.; Blanchard, P.

2013-05-01

Speciated atmospheric mercury data have recently been monitored at multiple locations in North America; but the spatial coverage is far less than the long-established mercury wet deposition network. The present study describes a first attempt linking ambient concentration with wet deposition using Beta distribution fitting of a ratio estimate. The mean, median, mode, standard deviation, and skewness of the fitted Beta distribution parameters were generated using data collected in 2009 at 11 monitoring stations. Comparing the normalized histogram and the fitted density function, the empirical and fitted Beta distribution of the ratio shows a close fit. The estimated ambient mercury concentration was further partitioned into reactive gaseous mercury and particulate bound mercury using linear regression model developed by Amos et al. (2012). The method presented here can be used to roughly estimate mercury ambient concentration at locations and/or times where such measurement is not available but where wet deposition is monitored.

Anuglar distribution of shower particles produced in the collisions of 20-GeV/c and 300-GeV negative pions with emulsion nuclei

NASA Technical Reports Server (NTRS)

Kim, C. O.; Kim, S. N.; Park, I. G.; Yoon, C. S.

1983-01-01

For 435 accelerator produced antipions jets of 20 GeV/c and 300 GeV, in nuclear emulsion, eta(theta)'s have been individually calculated for each jet, where eta(theta) is a kinematic parameter introduced in order to approximate the LS (laboratory system) rapidity, eta = arctan h (beta cos theta). By taking further averages by dividing the samples into groupings of the LS energy E sub pi = m cos h eta sub pi N sub h, the number of heavy prongs with LS velocity beta 0.7, and n , the number of charged shower particles with LS velocity beta 0.7, much less than eta (theta) much greater than are obtained. By use of the KNO (Koba-Nielsen-Olesen) scaling variable, xi = n sub s/,n sub s. good fit is found of data to regression function.

Effect of ascorbic acid on the stability of beta-carotene and capsanthin in paprika (Capsicum annuum) powder.

PubMed

Morais, H; Rodrigues, P; Ramos, C; Forgács, E; Cserháti, T; Oliveira, J

2002-10-01

The effect of ascorbic acid, light, and storage on the stability of the pigments beta-carotene and capsanthin in red pepper (Capsicum annuum) powder has been elucidated by determining the amount of pigment in samples treated by various concentrations of ascorbic acid. Determination of pigment concentration has been performed after different storage times using high-performance liquid chromatography. The dependence of the concentration of pigments on the concentration of ascorbic acid, presence of light and the storage time has been assessed by stepwise regression analysis. The concentration of pigments decreased at longer storage time and increased at higher concentration of ascorbic acid, beta-carotene being more sensitive towards storage time and concentration of ascorbic acid than capsanthin. Interaction between the effects of light and storage time, and light and concentration of ascorbic acid has been established.

A PHARMACOKINETIC PROGRAM (PKFIT) FOR R

EPA Science Inventory

The purpose of this study was to create a nonlinear regression (including a genetic algorithm) program (R script) to deal with data fitting for pharmacokinetics (PK) in R environment using its available packages. We call this tool as PKfit.

The Relationship between Bullying and Social Skills in Primary School Students

ERIC Educational Resources Information Center

Larke, Ian D.; Beran, Tanya N.

2006-01-01

In this study we examined the relationship between children's social skills and bullying behaviours. Teachers rated social skills and indirect and direct physical bullying behaviours of 120 students in elementary school. Hierarchical regression analyses indicated that social skills are inversely related to both direct physical bullying (beta =…

Understanding the Determinants of Debt Burden among College Graduates

ERIC Educational Resources Information Center

Chen, Rong; Wiederspan, Mark

2014-01-01

This article examines debt burden among college graduates and contributes to previous research by incorporating institutional and state characteristics. Utilizing a combination of national datasets and zero-one inflated beta regression, we find several major themes. First, family income and college experiences are strongly associated with the…

Experimental validation of a coupled neutron-photon inverse radiation transport solver

NASA Astrophysics Data System (ADS)

Mattingly, John; Mitchell, Dean J.; Harding, Lee T.

2011-10-01

Sandia National Laboratories has developed an inverse radiation transport solver that applies nonlinear regression to coupled neutron-photon deterministic transport models. The inverse solver uses nonlinear regression to fit a radiation transport model to gamma spectrometry and neutron multiplicity counting measurements. The subject of this paper is the experimental validation of that solver. This paper describes a series of experiments conducted with a 4.5 kg sphere of α-phase, weapons-grade plutonium. The source was measured bare and reflected by high-density polyethylene (HDPE) spherical shells with total thicknesses between 1.27 and 15.24 cm. Neutron and photon emissions from the source were measured using three instruments: a gross neutron counter, a portable neutron multiplicity counter, and a high-resolution gamma spectrometer. These measurements were used as input to the inverse radiation transport solver to evaluate the solver's ability to correctly infer the configuration of the source from its measured radiation signatures.

Nonlinear least squares regression for single image scanning electron microscope signal-to-noise ratio estimation.

PubMed

Sim, K S; Norhisham, S

2016-11-01

A new method based on nonlinear least squares regression (NLLSR) is formulated to estimate signal-to-noise ratio (SNR) of scanning electron microscope (SEM) images. The estimation of SNR value based on NLLSR method is compared with the three existing methods of nearest neighbourhood, first-order interpolation and the combination of both nearest neighbourhood and first-order interpolation. Samples of SEM images with different textures, contrasts and edges were used to test the performance of NLLSR method in estimating the SNR values of the SEM images. It is shown that the NLLSR method is able to produce better estimation accuracy as compared to the other three existing methods. According to the SNR results obtained from the experiment, the NLLSR method is able to produce approximately less than 1% of SNR error difference as compared to the other three existing methods. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Non-linear quantitative structure-activity relationship for adenine derivatives as competitive inhibitors of adenosine deaminase

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

Sadat Hayatshahi, Sayyed Hamed; Abdolmaleki, Parviz; Safarian, Shahrokh

2005-12-16

Logistic regression and artificial neural networks have been developed as two non-linear models to establish quantitative structure-activity relationships between structural descriptors and biochemical activity of adenosine based competitive inhibitors, toward adenosine deaminase. The training set included 24 compounds with known k {sub i} values. The models were trained to solve two-class problems. Unlike the previous work in which multiple linear regression was used, the highest of positive charge on the molecules was recognized to be in close relation with their inhibition activity, while the electric charge on atom N1 of adenosine was found to be a poor descriptor. Consequently, themore » previously developed equation was improved and the newly formed one could predict the class of 91.66% of compounds correctly. Also optimized 2-3-1 and 3-4-1 neural networks could increase this rate to 95.83%.« less

Linear and nonlinear models for predicting fish bioconcentration factors for pesticides.

PubMed

Yuan, Jintao; Xie, Chun; Zhang, Ting; Sun, Jinfang; Yuan, Xuejie; Yu, Shuling; Zhang, Yingbiao; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu

2016-08-01

This work is devoted to the applications of the multiple linear regression (MLR), multilayer perceptron neural network (MLP NN) and projection pursuit regression (PPR) to quantitative structure-property relationship analysis of bioconcentration factors (BCFs) of pesticides tested on Bluegill (Lepomis macrochirus). Molecular descriptors of a total of 107 pesticides were calculated with the DRAGON Software and selected by inverse enhanced replacement method. Based on the selected DRAGON descriptors, a linear model was built by MLR, nonlinear models were developed using MLP NN and PPR. The robustness of the obtained models was assessed by cross-validation and external validation using test set. Outliers were also examined and deleted to improve predictive power. Comparative results revealed that PPR achieved the most accurate predictions. This study offers useful models and information for BCF prediction, risk assessment, and pesticide formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

The presence of betapapillomavirus antibodies around transplantation predicts the development of keratinocyte carcinoma in organ transplant recipients: a cohort study.

PubMed

Genders, Roel E; Mazlom, Hadi; Michel, Angelika; Plasmeijer, Elsemieke I; Quint, Koen D; Pawlita, Michael; van der Meijden, Els; Waterboer, Tim; de Fijter, Hans; Claas, Frans H; Wolterbeek, Ron; Feltkamp, Mariet C W; Bouwes Bavinck, Jan Nico

2015-05-01

Organ transplant recipients (OTRs) have an increased risk of developing keratinocyte carcinomas (KCs). The aim of this study was to correlate infection with human papillomaviruses (HPVs) belonging to the beta genus (Beta-papillomavirus (Beta-PV)) at transplantation with later development of KCs. In a cohort study, sera collected between 1 year before and 1 year after transplantation of OTRs transplanted between 1990 and 2006 were tested for antibody responses against the L1 capsid antigen of Beta-PV and other HPV genera (Gamma-, Mu-, Nu-, and Alpha-PV) using multiplex serology. The OTRs were followed for a maximum of 22 years. Cox regression models with KC, squamous cell carcinoma (SCC), and basal cell carcinoma (BCC) as outcome variables were used. Out of 445 OTRs, 60 had developed KC: 14 developed only SCC, 24 only BCC, and 22 both types of KC. The time-dependent hazard ratio (HR) to develop either or both types of KC, adjusted for age, sex, and transplanted organ, in tested Beta-PV-seropositive OTR around the time of transplantation compared with Beta-PV-seronegative OTR was 2.9 (95% confidence interval (CI) 1.3-6.4). The HR for SCC was 2.9 (95% CI 0.99-8.5) and for BCC it was 3.1 (95% CI 1.2-8.0). There was also an association between Mu-PV seropositivity and KC, but there were no significant associations between other HPV genera tested and KC. A positive seroresponse for Beta-PV around transplantation significantly predicted the development of KC in OTRs up to 22 years later, providing additional evidence that infection with Beta-PV has a role in KC carcinogenesis.

Topical Beta-Blockers and Cardiovascular Mortality: Systematic Review and Meta-Analysis with Data from the EPIC-Norfolk Cohort Study

PubMed Central

Pinnock, Claude; Yip, Jennifer L. Y.; Khawaja, Anthony P.; Luben, Robert; Hayat, Shabina; Broadway, David C.; Foster, Paul J.; Khaw, Kay-Tee; Wareham, Nick

2016-01-01

ABSTRACT Purpose: To determine if topical beta-blocker use is associated with increased cardiovascular mortality, particularly among people with self-reported glaucoma. Methods: All participants who participated in the first health check (N = 25,639) of the European Prospective Investigation into Cancer (EPIC) Norfolk cohort (1993–2013) were included in this prospective cohort study, with a median follow-up of 17.0 years. We determined use of topical beta-blockers at baseline through a self-reported questionnaire and prescription check at the first clinical visit. Cardiovascular mortality was ascertained through data linkage with the Office for National Statistics mortality database. Hazard ratios (HRs) were estimated using multivariable Cox regression models. Meta-analysis of the present study’s results together with other identified literature was performed using a random effects model. Results: We did not find an association between the use of topical beta-blockers and cardiovascular mortality (HR 0.93, 95% confidence interval, CI, 0.67–1.30). In the 514 participants with self-reported glaucoma, no association was found between the use of topical beta-blockers and cardiovascular mortality (HR 0.89, 95% CI 0.56–1.40). In the primary meta-analysis of four publications, there was no evidence of an association between the use of topical beta-blockers and cardiovascular mortality (pooled HR estimate 1.10, 95% CI 0.84–1.36). Conclusion: Topical beta-blockers do not appear to be associated with excess cardiovascular mortality. This evidence does not indicate that a change in current practice is warranted, although clinicians should continue to assess individual patients and their cardiovascular risk prior to commencing topical beta-blockers. PMID:27551956

On a nonlinear state of the electromagnetic ion/ion cyclotron instability

NASA Astrophysics Data System (ADS)

Cremer, M.; Scholer, M.

We have investigated the nonlinear properties of the electromagnetic ion/ion cyclotron instability (EMIIC) by means of hybrid simulations (macroparticle ions, massless electron fluid). The instability is driven by the relative (super-Alfvénic) streaming of two field-aligned ion beams in a low beta plasma (ion thermal pressure to magnetic field pressure) and may be of importance in the plasma sheet boundary layer. As shown in previously reported simulations the waves propagate obliquely to the magnetic field and heat the ions in the perpendicular direction as the relative beam velocity decreases. By running the simulation to large times it can be shown that the large temperature anisotropy leads to the ion cyclotron instability (IC) with parallel propagating Alfvén ion cyclotron waves. This is confirmed by numerically solving the electromagnetic dispersion relation. An application of this property to the plasma sheet boundary layer is discussed.

A new equation in two dimensional fast magnetoacoustic shock waves in electron-positron-ion plasmas

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

Masood, W.; Jehan, Nusrat; Mirza, Arshad M.

2010-03-15

Nonlinear properties of the two dimensional fast magnetoacoustic waves are studied in a three-component plasma comprising of electrons, positrons, and ions. In this regard, Kadomtsev-Petviashvili-Burger (KPB) equation is derived using the small amplitude perturbation expansion method. Under the condition that the electron and positron inertia are ignored, Burger-Kadomtsev-Petviashvili (Burger-KP) for a fast magnetoacoustic wave is derived for the first time, to the best of author's knowledge. The solutions of both KPB and Burger-KP equations are obtained using the tangent hyperbolic method. The effects of positron concentration, kinematic viscosity, and plasma beta are explored both for the KPB and the Burger-KPmore » shock waves and the differences between the two are highlighted. The present investigation may have relevance in the study of nonlinear electromagnetic shock waves both in laboratory and astrophysical plasmas.« less

Particle-in-cell Simulations of Continuously Driven Mirror and Ion Cyclotron Instabilities in High Beta Astrophysical and Heliospheric Plasmas

NASA Astrophysics Data System (ADS)

Riquelme, Mario A.; Quataert, Eliot; Verscharen, Daniel

2015-02-01

We use particle-in-cell simulations to study the nonlinear evolution of ion velocity space instabilities in an idealized problem in which a background velocity shear continuously amplifies the magnetic field. We simulate the astrophysically relevant regime where the shear timescale is long compared to the ion cyclotron period, and the plasma beta is β ~ 1-100. The background field amplification in our calculation is meant to mimic processes such as turbulent fluctuations or MHD-scale instabilities. The field amplification continuously drives a pressure anisotropy with p > p ∥ and the plasma becomes unstable to the mirror and ion cyclotron instabilities. In all cases, the nonlinear state is dominated by the mirror instability, not the ion cyclotron instability, and the plasma pressure anisotropy saturates near the threshold for the linear mirror instability. The magnetic field fluctuations initially undergo exponential growth but saturate in a secular phase in which the fluctuations grow on the same timescale as the background magnetic field (with δB ~ 0.3 langBrang in the secular phase). At early times, the ion magnetic moment is well-conserved but once the fluctuation amplitudes exceed δB ~ 0.1 langBrang, the magnetic moment is no longer conserved but instead changes on a timescale comparable to that of the mean magnetic field. We discuss the implications of our results for low-collisionality astrophysical plasmas, including the near-Earth solar wind and low-luminosity accretion disks around black holes.

Binding kinetics of five drugs to beta2-adrenoceptor using peak profiling method and nonlinear chromatography.

PubMed

Liang, Yuan; Wang, Jing; Fei, Fuhuan; Sun, Huanmei; Liu, Ting; Li, Qian; Zhao, Xinfeng; Zheng, Xiaohui

2018-02-23

Investigations of drug-protein interactions have advanced our knowledge of ways to design more rational drugs. In addition to extensive thermodynamic studies, ongoing works are needed to enhance the exploration of drug-protein binding kinetics. In this work, the beta2-adrenoceptor (β 2 -AR) was immobilized on N, N'-carbonyldiimidazole activated amino polystyrene microspheres to prepare an affinity column (4.6 mm × 5.0 cm, 8 μm). The β 2 -AR column was utilized to determine the binding kinetics of five drugs to the receptor. Introducing peak profiling method into this receptor chromatographic analysis, we determined the dissociation rate constants (k d ) of salbutamol, terbutaline, methoxyphenamine, isoprenaline hydrochloride and ephedrine hydrochloride to β 2 -AR to be 15 (±1), 22 (±1), 3.3 (±0.2), 2.3 (±0.2) and 2.1 (±0.1) s -1 , respectively. The employment of nonlinear chromatography (NLC) in this case exhibited the same rank order of k d values for the five drugs bound to β 2 -AR. We confirmed that both the peak profiling method and NLC were capable of routine measurement of receptor-drug binding kinetics. Compared with the peak profiling method, NLC was advantageous in the simultaneous assessment of the kinetic and apparent thermodynamic parameters. It will become a powerful method for high throughput drug-receptor interaction analysis. Copyright © 2018 Elsevier B.V. All rights reserved.

Gray matter network disruptions and amyloid beta in cognitively normal adults.

PubMed

Tijms, Betty M; Kate, Mara Ten; Wink, Alle Meije; Visser, Pieter Jelle; Ecay, Mirian; Clerigue, Montserrat; Estanga, Ainara; Garcia Sebastian, Maite; Izagirre, Andrea; Villanua, Jorge; Martinez Lage, Pablo; van der Flier, Wiesje M; Scheltens, Philip; Sanz Arigita, Ernesto; Barkhof, Frederik

2016-01-01

Gray matter networks are disrupted in Alzheimer's disease (AD). It is unclear when these disruptions start during the development of AD. Amyloid beta 1-42 (Aβ42) is among the earliest changes in AD. We studied, in cognitively healthy adults, the relationship between Aβ42 levels in cerebrospinal fluid (CSF) and single-subject cortical gray matter network measures. Single-subject gray matter networks were extracted from structural magnetic resonance imaging scans in a sample of cognitively healthy adults (N = 185; age range 39-79, mini-mental state examination >25, N = 12 showed abnormal Aβ42 < 550 pg/mL). Degree, clustering coefficient, and path length were computed at whole brain level and for 90 anatomical areas. Associations between continuous Aβ42 CSF levels and single-subject cortical gray matter network measures were tested. Smoothing splines were used to determine whether a linear or nonlinear relationship gave a better fit to the data. Lower Aβ42 CSF levels were linearly associated at whole brain level with lower connectivity density, and nonlinearly with lower clustering values and higher path length values, which is indicative of a less-efficient network organization. These relationships were specific to medial temporal areas, precuneus, and the middle frontal gyrus (all p < 0.05). These results suggest that mostly within the normal spectrum of amyloid, lower Aβ42 levels can be related to gray matter networks disruptions. Copyright © 2016 Elsevier Inc. All rights reserved.

Aircraft noise annoyance in recreational areas after changes in noise exposure: comments on Krog and Engdahl (2004).

PubMed

Klaeboe, Ronny

2005-09-01

When Gardermoen replaced Fornebu as the main airport for Oslo, aircraft noise levels increased in recreational areas near Gardermoen and decreased in areas near Fornebu. Krog and Engdahl [J. Acoust. Soc. Am. 116, 323-333 (2004)] estimate that recreationists' annoyance from aircraft noise in these areas changed more than would be anticipated from the actual noise changes. However, the sizes of their estimated "situation" effects are not credible. One possible reason for the anomalous results is that standard regression assumptions become violated when motivational factors are inserted into the regression model. Standardized regression coefficients (beta values) should also not be utilized for comparisons across equations.

Critical validation studies of neurofeedback.

PubMed

Gruzelier, John; Egner, Tobias

2005-01-01

The field of neurofeedback training has proceeded largely without validation. In this article the authors review studies directed at validating sensory motor rhythm, beta and alpha-theta protocols for improving attention, memory, and music performance in healthy participants. Importantly, benefits were demonstrable with cognitive and neurophysiologic measures that were predicted on the basis of regression models of learning to enhance sensory motor rhythm and beta activity. The first evidence of operant control over the alpha-theta ratio is provided, together with remarkable improvements in artistic aspects of music performance equivalent to two class grades in conservatory students. These are initial steps in providing a much needed scientific basis to neurofeedback.

Correlation and simple linear regression.

PubMed

Zou, Kelly H; Tuncali, Kemal; Silverman, Stuart G

2003-06-01

In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.

The relationship of exposure to air pollutants in pregnancy with surrogate markers of endothelial dysfunction in umbilical cord.

PubMed

Poursafa, Parinaz; Baradaran-Mahdavi, Sadegh; Moradi, Bita; Haghjooy Javanmard, Shaghayegh; Tajadini, Mohammadhasan; Mehrabian, Ferdous; Kelishadi, Roya

2016-04-01

This study aims to investigate the association of exposure to ambient air pollution during pregnancy with cord blood concentrations of surrogate markers of endothelial dysfunction. This population-based cohort was conducted from March 2014 to March 2015 among 250 mother-neonate pairs in urban areas of Isfahan, the second large and air-polluted city in Iran. We analyzed the association between the ambient carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), particular matter 10 (PM10), and air quality index (AQI) with cord blood levels of endothelin-1, vascular adhesion molecule (VCAM), and intercellular adhesion molecule (ICAM). Multiple regression analysis was conducted after adjustment for potential confounding factors and covariates. The regression coefficient (beta), standard error of the estimate (SE), and 95% confidence intervals for each regression coefficient (95% CI) are reported. Data of 233 mother-neonate pairs were complete, and included in the analysis. Multiple regression analyses showed that AQI, CO and O3 had significant correlation with cord blood ICAM-1 [Beta (SE), 95%CI: 2.93 (0.72), 1.33,5.54; 2.28(1.44), 1.56,5.12; and 2.02(0.01), 1.03,2.04, respectively] as well as with VCAM-1 [2.78(0.91), 1.69,4.57; 2.47(1.47), 1.43,5.37; and 2.01(0.01),1.07,2.04, respectively]. AQI, PM10, and SO2 were significantly associated with Endothelin-1 concentrations [Beta (SE), 95%CI: 10.16(5.08),7.61,14.28; 9.70(3.46), 2.88,16.52; and 1.07(0.02), 1.03,2.11, respectively]. The significant associations of air pollutants with markers of endothelial dysfunction during fetal period may provide another evidence on the adverse health effects of air pollutants on early stages of atherosclerosis from fetal period. Our findings underscore the importance of considering environmental factors in primordial prevention of chronic diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

ICU Acquisition Rate, Risk Factors, and Clinical Significance of Digestive Tract Colonization With Extended-Spectrum Beta-Lactamase-Producing Enterobacteriaceae: A Systematic Review and Meta-Analysis.

PubMed

Detsis, Marios; Karanika, Styliani; Mylonakis, Eleftherios

2017-04-01

To evaluate the acquisition rate, identify risk factors, and estimate the risk for subsequent infection, associated with the colonization of the digestive tract with extended-spectrum beta-lactamase-producing Enterobacteriaceae during ICU-hospitalization. PubMed, EMBASE, and reference lists of all eligible articles. Included studies provided data on ICU-acquired colonization with extended-spectrum beta-lactamase-producing Enterobacteriaceae in previously noncolonized and noninfected patients and used the double disk synergy test for extended-spectrum beta-lactamase-producing Enterobacteriaceae phenotypic confirmation. Studies reporting extended-spectrum beta-lactamase-producing Enterobacteriaceae outbreaks or data on pediatric population were excluded. Two authors independently assessed study eligibility and performed data extraction. Thirteen studies (with 15,045 ICUs-patients) were evaluated using a random-effect model and a meta-regression analysis. The acquisition rate of digestive tract colonization during ICU stay was 7% (95% CI, 5-10) and it varies from 3% (95% CI, 2-4) and 4% (95% CI, 2-6) in the Americas and Europe to 21% (95% CI, 9-35) in the Western Pacific region. Previous hospitalization (risk ratio, 1.57 [95% CI, 1.07-2.31]) or antibiotic use (risk ratio, 1.65 [95% CI, 1.15-2.37]) and exposure to beta-lactams/beta-lactamase inhibitors (risk ratio, 1.78 [95% CI, 1.24-2.56]) and carbapenems (risk ratio, 2.13 [95% CI, 1.49-3.06]) during the ICU stay were independent risk factors for ICU-acquired colonization. Importantly, colonized patients were more likely to develop an extended-spectrum beta-lactamase-producing Enterobacteriaceae infection (risk ratio, 49.62 [95% CI, 20.42-120.58]). The sensitivity and specificity of prior colonization to predict subsequent extended-spectrum beta-lactamase-producing Enterobacteriaceae infection were 95.1% (95% CI, 54.7-99.7) and 89.2% (95% CI, 77.2-95.3), respectively. The ICU acquisition rate of extended-spectrum beta-lactamase-producing Enterobacteriaceae ranged from 5% to 10%. Previous use of beta-lactam/beta-lactamase or carbapenems and recent hospitalization were independent risk factors for extended-spectrum beta-lactamase-producing Enterobacteriaceae colonization, and colonization was associated with significantly higher frequency of extended-spectrum beta-lactamase-producing Enterobacteriaceae subsequent infection and increased mortality.

On neural networks in identification and control of dynamic systems

NASA Technical Reports Server (NTRS)

Phan, Minh; Juang, Jer-Nan; Hyland, David C.

1993-01-01

This paper presents a discussion of the applicability of neural networks in the identification and control of dynamic systems. Emphasis is placed on the understanding of how the neural networks handle linear systems and how the new approach is related to conventional system identification and control methods. Extensions of the approach to nonlinear systems are then made. The paper explains the fundamental concepts of neural networks in their simplest terms. Among the topics discussed are feed forward and recurrent networks in relation to the standard state-space and observer models, linear and nonlinear auto-regressive models, linear, predictors, one-step ahead control, and model reference adaptive control for linear and nonlinear systems. Numerical examples are presented to illustrate the application of these important concepts.

Considerations on the calibration of small thermoluminescent dosimeters used for measurement of beta particle absorbed doses in liquid environments.

PubMed

Demidecki, A J; Williams, L E; Wong, J Y; Wessels, B W; Yorke, E D; Strandh, M; Strand, S E

1993-01-01

An investigation has been carried out on the factors which affect the absolute calibration of thermoluminescent dosimeters (TLDs) used in beta particle absorbed dose evaluations. Four effects on light output (LO) were considered: decay of detector sensitivity with time, finite TLD volume, dose linearity, and energy dependence. Most important of these was the decay of LO with time in culture medium, muscle tissue, and gels. This permanent loss of sensitivity was as large as an order of magnitude over a 21-day interval for the nominally 20-microns-thick disc-shaped CaSO4(Dy) TLDs in gel. Associated leaching of the dosimeter crystals out of the Teflon matrix was observed using scanning electron microscopy. Large channels leading from the outside environment into the TLDs were identified using SEM images. A possibility of batch dependence of fading was indicated. The second most important effect was the apparent reduction of light output due to finite size and increased specific gravity of the dosimeter (volume effect). We estimated this term by calculations as 10% in standard "mini" rods for beta particles from 90Y, but nearly a factor of 3 for 131I beta particles in the same geometry. No significant nonlinearity of the log (light output) with log (absorbed dose) over the range 0.05-20.00 Gy was discovered. Energy dependence of the LO was found to be not detectable, within measurement errors, over the range of 0.60-6.0 MeV mean energy electrons. With careful understanding of these effects, calibration via gel phantom would appear to be an acceptable strategy for mini TLDs used in beta absorbed dose evaluations in media.(ABSTRACT TRUNCATED AT 250 WORDS)

Method and Excel VBA Algorithm for Modeling Master Recession Curve Using Trigonometry Approach.

PubMed

Posavec, Kristijan; Giacopetti, Marco; Materazzi, Marco; Birk, Steffen

2017-11-01

A new method was developed and implemented into an Excel Visual Basic for Applications (VBAs) algorithm utilizing trigonometry laws in an innovative way to overlap recession segments of time series and create master recession curves (MRCs). Based on a trigonometry approach, the algorithm horizontally translates succeeding recession segments of time series, placing their vertex, that is, the highest recorded value of each recession segment, directly onto the appropriate connection line defined by measurement points of a preceding recession segment. The new method and algorithm continues the development of methods and algorithms for the generation of MRC, where the first published method was based on a multiple linear/nonlinear regression model approach (Posavec et al. 2006). The newly developed trigonometry-based method was tested on real case study examples and compared with the previously published multiple linear/nonlinear regression model-based method. The results show that in some cases, that is, for some time series, the trigonometry-based method creates narrower overlaps of the recession segments, resulting in higher coefficients of determination R 2 , while in other cases the multiple linear/nonlinear regression model-based method remains superior. The Excel VBA algorithm for modeling MRC using the trigonometry approach is implemented into a spreadsheet tool (MRCTools v3.0 written by and available from Kristijan Posavec, Zagreb, Croatia) containing the previously published VBA algorithms for MRC generation and separation. All algorithms within the MRCTools v3.0 are open access and available free of charge, supporting the idea of running science on available, open, and free of charge software. © 2017, National Ground Water Association.

Foot and hip contributions to high frontal plane knee projection angle in athletes: a classification and regression tree approach.

PubMed

Bittencourt, Natalia F N; Ocarino, Juliana M; Mendonça, Luciana D M; Hewett, Timothy E; Fonseca, Sergio T

2012-12-01

Cross-sectional. To investigate predictors of increased frontal plane knee projection angle (FPKPA) in athletes. The underlying mechanisms that lead to increased FPKPA are likely multifactorial and depend on how the musculoskeletal system adapts to the possible interactions between its distal and proximal segments. Bivariate and linear analyses traditionally employed to analyze the occurrence of increased FPKPA are not sufficiently robust to capture complex relationships among predictors. The investigation of nonlinear interactions among biomechanical factors is necessary to further our understanding of the interdependence of lower-limb segments and resultant dynamic knee alignment. The FPKPA was assessed in 101 athletes during a single-leg squat and in 72 athletes at the moment of landing from a jump. The investigated predictors were sex, hip abductor isometric torque, passive range of motion (ROM) of hip internal rotation (IR), and shank-forefoot alignment. Classification and regression trees were used to investigate nonlinear interactions among predictors and their influence on the occurrence of increased FPKPA. During single-leg squatting, the occurrence of high FPKPA was predicted by the interaction between hip abductor isometric torque and passive hip IR ROM. At the moment of landing, the shank-forefoot alignment, abductor isometric torque, and passive hip IR ROM were predictors of high FPKPA. In addition, the classification and regression trees established cutoff points that could be used in clinical practice to identify athletes who are at potential risk for excessive FPKPA. The models captured nonlinear interactions between hip abductor isometric torque, passive hip IR ROM, and shank-forefoot alignment.

Learning Inverse Rig Mappings by Nonlinear Regression.

PubMed

Holden, Daniel; Saito, Jun; Komura, Taku

2017-03-01

We present a framework to design inverse rig-functions-functions that map low level representations of a character's pose such as joint positions or surface geometry to the representation used by animators called the animation rig. Animators design scenes using an animation rig, a framework widely adopted in animation production which allows animators to design character poses and geometry via intuitive parameters and interfaces. Yet most state-of-the-art computer animation techniques control characters through raw, low level representations such as joint angles, joint positions, or vertex coordinates. This difference often stops the adoption of state-of-the-art techniques in animation production. Our framework solves this issue by learning a mapping between the low level representations of the pose and the animation rig. We use nonlinear regression techniques, learning from example animation sequences designed by the animators. When new motions are provided in the skeleton space, the learned mapping is used to estimate the rig controls that reproduce such a motion. We introduce two nonlinear functions for producing such a mapping: Gaussian process regression and feedforward neural networks. The appropriate solution depends on the nature of the rig and the amount of data available for training. We show our framework applied to various examples including articulated biped characters, quadruped characters, facial animation rigs, and deformable characters. With our system, animators have the freedom to apply any motion synthesis algorithm to arbitrary rigging and animation pipelines for immediate editing. This greatly improves the productivity of 3D animation, while retaining the flexibility and creativity of artistic input.

Does the presence or location of graphic markers affect untrained listeners' ratings of severity of dysphonia?

PubMed

Nagle, Kathy F; Helou, Leah B; Solomon, Nancy P; Eadie, Tanya L

2014-07-01

To determine the effect of presence and location of severity labels for different types of visual analog scales (VAS) on overall severity (OS) ratings in dysphonic speech. Experimental, between group comparisons. Dysphonic and normal voice samples from male and female speakers were presented to inexperienced listeners for judgments of OS. To rate samples, listeners used an undifferentiated 100-mm VAS labeled at the extremes, a VAS with nonlinearly distributed labels as in the "beta" version of the Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V), or a VAS with symmetrically distributed labels as in the "official" version of the CAPE-V. Overall, mean OS ratings did not differ significantly across scale types, although ratings using the nonlinearly marked VAS were generally lower than those from other scales. This effect was significant for female speakers whose samples tended toward moderate OS. The ratings distribution, when compiled into 10-mm bins, differed significantly by scale type, with users of the nonlinearly marked scales skewing their ratings toward normal. The presence and placement of labels on VAS did not significantly affect OS ratings overall, but values were significantly lower when rating female voices with the nonlinearly labeled VAS. Results indicate that professionals should specify the scale type used for rating OS and use scales consistently when comparing voices. Copyright © 2014 The Voice Foundation. All rights reserved.

Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal.

PubMed

Hosseinifard, Behshad; Moradi, Mohammad Hassan; Rostami, Reza

2013-03-01

Diagnosing depression in the early curable stages is very important and may even save the life of a patient. In this paper, we study nonlinear analysis of EEG signal for discriminating depression patients and normal controls. Forty-five unmedicated depressed patients and 45 normal subjects were participated in this study. Power of four EEG bands and four nonlinear features including detrended fluctuation analysis (DFA), higuchi fractal, correlation dimension and lyapunov exponent were extracted from EEG signal. For discriminating the two groups, k-nearest neighbor, linear discriminant analysis and logistic regression as the classifiers are then used. Highest classification accuracy of 83.3% is obtained by correlation dimension and LR classifier among other nonlinear features. For further improvement, all nonlinear features are combined and applied to classifiers. A classification accuracy of 90% is achieved by all nonlinear features and LR classifier. In all experiments, genetic algorithm is employed to select the most important features. The proposed technique is compared and contrasted with the other reported methods and it is demonstrated that by combining nonlinear features, the performance is enhanced. This study shows that nonlinear analysis of EEG can be a useful method for discriminating depressed patients and normal subjects. It is suggested that this analysis may be a complementary tool to help psychiatrists for diagnosing depressed patients. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Thermohydrogen processing (THP) of titanium alloy and titanium-aluminum alloys

NASA Astrophysics Data System (ADS)

Qazi, Javaid Iqbal

The microstructures, phases and phase transformations occurring in cast and Hot Isostatic Pressed (HIP'd) Ti-6Al-4V-H and the blended elemental (BE) TiAl-H systems were investigated. In this work, the existing Ti-6Al-4V-H phase diagram was revised and the time-temperature-transformation (TTT) diagrams for beta-phase (isothermal) and martensite (quench plus aging) decomposition were determined at different hydrogen concentrations. Alloying with hydrogen decreases the nose temperatures for the start of both the beta/martensite decompositions in a linear fashion and increases the nose times for both of these in a non-linear fashion. During aging at temperatures below the beta transus temperature, the martensite decomposes into alpha+betaM (metastable beta) and on quenching, from the aging temperature, the betaM transforms to martensite + beta R (residual beta) with the amount of latter increasing with increasing hydrogen content. Microstructures varying from alpha-lamellar laths to fine equiaxed alpha-grains were produced in the Ti-6Al-4V alloy, by using different thermohydrogen processing (THP) treatments. A microstructure consisting of mixed equiaxed and elongated alpha-grains were only produced in samples containing 30at.%H after the complete decomposition of the beta/martensite below a critical temperature (Tc), followed by dehydrogenation. A mixture consisting of partially equiaxed alpha-grains thus produced by THP, increased the tensile strength from 841MPa (starting Ti-6Al-4V) to 965MPa after THP and also increased the % elongation from 7.5% to 10.5%. In addition to other THP parameters, the final microstructure also depends on the starting microstructure and recommendations are made for future work in this regard. Initial results of temperature cycling treatments, which involved heat treating of Ti-6Al-4V samples containing 30at.%H at 680°C for 5 minutes followed by water quenching and repetition of the same treatment for 10 cycles, did not show a decrease in the average prior beta grain size; recommendations have been made for future work in this area. Fully dense hydrogenated nano-crystalline TiAl compacts were produced from BE powders. HIP'ing of the mechanically alloyed hydrogenated powders at 850°C resulted in a homogenous microstructure, whereas prior powder particle boundaries were visible in the samples produced from non-hydrogenated powders. The hydrogen was removed by vacuum annealing resulting in nano-size gamma-TiAl.

Down syndrome's brain dynamics: analysis of fractality in resting state.

PubMed

Hemmati, Sahel; Ahmadlou, Mehran; Gharib, Masoud; Vameghi, Roshanak; Sajedi, Firoozeh

2013-08-01

To the best knowledge of the authors there is no study on nonlinear brain dynamics of down syndrome (DS) patients, whereas brain is a highly complex and nonlinear system. In this study, fractal dimension of EEG, as a key characteristic of brain dynamics, showing irregularity and complexity of brain dynamics, was used for evaluation of the dynamical changes in the DS brain. The results showed higher fractality of the DS brain in almost all regions compared to the normal brain, which indicates less centrality and higher irregular or random functioning of the DS brain regions. Also, laterality analysis of the frontal lobe showed that the normal brain had a right frontal laterality of complexity whereas the DS brain had an inverse pattern (left frontal laterality). Furthermore, the high accuracy of 95.8 % obtained by enhanced probabilistic neural network classifier showed the potential of nonlinear dynamic analysis of the brain for diagnosis of DS patients. Moreover, the results showed that the higher EEG fractality in DS is associated with the higher fractality in the low frequencies (delta and theta), in broad regions of the brain, and the high frequencies (beta and gamma), majorly in the frontal regions.

Comparing magnetic fluctuation dynamics in nonlinear MHD simulations of low-aspect-ratio RFPs to RELAX experiments

NASA Astrophysics Data System (ADS)

McCollam, K. J.; den Hartog, D. J.; Jacobson, C. M.; Sovinec, C. R.; Masamune, S.; Sanpei, A.

2017-10-01

We present comparisons of magnetic tearing fluctuation activity between RFP experiments on the low-aspect-ratio RELAX device (R / a 2) and nonlinear simulations of zero-beta, single-fluid MHD using the NIMROD code in both cylindrical and toroidal geometries at a Lundquist number of S =104 , nearly as high as experimental values. Time-average fluctuation amplitudes observed in the simulations are similar to those from the experiments, but more rigorous comparisons versus spectral mode numbers are in progress. We also focus on how the spatiotemporal dynamics of the fluctuations vary with RFP equilibrium parameters. Interestingly, at shallow reversal, cylindrical simulations show a relatively uncoupled spectrum of nearly quiescent modes periodically varying in time, whereas the corresponding toroidal cases show a fully chaotic spectrum of strongly nonlinearly interacting modes. We ascribe this to the geometric m = 1 coupling present in the toroidal but not the cylindrical case. We present initial results from convergence studies with increased spatial resolution for both geometries. Simulations at higher S are planned. This work is supported by the U.S. DOE and by the Japan Society for the Promotion of Science.

Effects of structure distortion on optical phonon properties of crystalline beta-BaTeMo{sub 2}O{sub 9}—A novel nonlinear optical material: Infrared and Raman spectra as well as first-principles calculations

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

Zhou, S. T.; Huang, Y.; Qiu, W. Y.

2013-12-21

The infrared dielectric property of monoclinic BaTeMo{sub 2}O{sub 9} single crystals is studied by polarized IR reflectance spectra from 20 to 1800 cm{sup −1}. Based on the modified Lorentz model, the frequencies, strengths, and dampings of TO modes as well as the orientations of the dipole momenta are determined, agreeing well with Raman spectra and results from First-principles calculation. The observed modes are visually assigned to the specific atoms' motions in the primitive cell based on the theory calculations. A large shift of the internal modes of the anion groups relative to free anion co-ordination polyhedra is observed, which can bemore » used to indicate the distortions of co-ordination polyhedra related to the nonlinear optical properties. Further, the experimental results of the strengths of the oscillators support the elimination and splitting of degenerate modes in free regular polyhedrons. These results offer a way to evaluate the nonlinear optical properties by use of traditional IR reflectivity spectra.« less

Flexible link functions in nonparametric binary regression with Gaussian process priors.

PubMed

Li, Dan; Wang, Xia; Lin, Lizhen; Dey, Dipak K

2016-09-01

In many scientific fields, it is a common practice to collect a sequence of 0-1 binary responses from a subject across time, space, or a collection of covariates. Researchers are interested in finding out how the expected binary outcome is related to covariates, and aim at better prediction in the future 0-1 outcomes. Gaussian processes have been widely used to model nonlinear systems; in particular to model the latent structure in a binary regression model allowing nonlinear functional relationship between covariates and the expectation of binary outcomes. A critical issue in modeling binary response data is the appropriate choice of link functions. Commonly adopted link functions such as probit or logit links have fixed skewness and lack the flexibility to allow the data to determine the degree of the skewness. To address this limitation, we propose a flexible binary regression model which combines a generalized extreme value link function with a Gaussian process prior on the latent structure. Bayesian computation is employed in model estimation. Posterior consistency of the resulting posterior distribution is demonstrated. The flexibility and gains of the proposed model are illustrated through detailed simulation studies and two real data examples. Empirical results show that the proposed model outperforms a set of alternative models, which only have either a Gaussian process prior on the latent regression function or a Dirichlet prior on the link function. © 2015, The International Biometric Society.

Flexible Link Functions in Nonparametric Binary Regression with Gaussian Process Priors

PubMed Central

Li, Dan; Lin, Lizhen; Dey, Dipak K.

2015-01-01

Summary In many scientific fields, it is a common practice to collect a sequence of 0-1 binary responses from a subject across time, space, or a collection of covariates. Researchers are interested in finding out how the expected binary outcome is related to covariates, and aim at better prediction in the future 0-1 outcomes. Gaussian processes have been widely used to model nonlinear systems; in particular to model the latent structure in a binary regression model allowing nonlinear functional relationship between covariates and the expectation of binary outcomes. A critical issue in modeling binary response data is the appropriate choice of link functions. Commonly adopted link functions such as probit or logit links have fixed skewness and lack the flexibility to allow the data to determine the degree of the skewness. To address this limitation, we propose a flexible binary regression model which combines a generalized extreme value link function with a Gaussian process prior on the latent structure. Bayesian computation is employed in model estimation. Posterior consistency of the resulting posterior distribution is demonstrated. The flexibility and gains of the proposed model are illustrated through detailed simulation studies and two real data examples. Empirical results show that the proposed model outperforms a set of alternative models, which only have either a Gaussian process prior on the latent regression function or a Dirichlet prior on the link function. PMID:26686333

The allometry of coarse root biomass: log-transformed linear regression or nonlinear regression?

PubMed

Lai, Jiangshan; Yang, Bo; Lin, Dunmei; Kerkhoff, Andrew J; Ma, Keping

2013-01-01

Precise estimation of root biomass is important for understanding carbon stocks and dynamics in forests. Traditionally, biomass estimates are based on allometric scaling relationships between stem diameter and coarse root biomass calculated using linear regression (LR) on log-transformed data. Recently, it has been suggested that nonlinear regression (NLR) is a preferable fitting method for scaling relationships. But while this claim has been contested on both theoretical and empirical grounds, and statistical methods have been developed to aid in choosing between the two methods in particular cases, few studies have examined the ramifications of erroneously applying NLR. Here, we use direct measurements of 159 trees belonging to three locally dominant species in east China to compare the LR and NLR models of diameter-root biomass allometry. We then contrast model predictions by estimating stand coarse root biomass based on census data from the nearby 24-ha Gutianshan forest plot and by testing the ability of the models to predict known root biomass values measured on multiple tropical species at the Pasoh Forest Reserve in Malaysia. Based on likelihood estimates for model error distributions, as well as the accuracy of extrapolative predictions, we find that LR on log-transformed data is superior to NLR for fitting diameter-root biomass scaling models. More importantly, inappropriately using NLR leads to grossly inaccurate stand biomass estimates, especially for stands dominated by smaller trees.

Optimizing separate phase light hydrocarbon recovery from contaminated unconfined aquifers

NASA Astrophysics Data System (ADS)

Cooper, Grant S.; Peralta, Richard C.; Kaluarachchi, Jagath J.

A modeling approach is presented that optimizes separate phase recovery of light non-aqueous phase liquids (LNAPL) for a single dual-extraction well in a homogeneous, isotropic unconfined aquifer. A simulation/regression/optimization (S/R/O) model is developed to predict, analyze, and optimize the oil recovery process. The approach combines detailed simulation, nonlinear regression, and optimization. The S/R/O model utilizes nonlinear regression equations describing system response to time-varying water pumping and oil skimming. Regression equations are developed for residual oil volume and free oil volume. The S/R/O model determines optimized time-varying (stepwise) pumping rates which minimize residual oil volume and maximize free oil recovery while causing free oil volume to decrease a specified amount. This S/R/O modeling approach implicitly immobilizes the free product plume by reversing the water table gradient while achieving containment. Application to a simple representative problem illustrates the S/R/O model utility for problem analysis and remediation design. When compared with the best steady pumping strategies, the optimal stepwise pumping strategy improves free oil recovery by 11.5% and reduces the amount of residual oil left in the system due to pumping by 15%. The S/R/O model approach offers promise for enhancing the design of free phase LNAPL recovery systems and to help in making cost-effective operation and management decisions for hydrogeologists, engineers, and regulators.

Evaluation of laser cutting process with auxiliary gas pressure by soft computing approach

NASA Astrophysics Data System (ADS)

Lazov, Lyubomir; Nikolić, Vlastimir; Jovic, Srdjan; Milovančević, Miloš; Deneva, Heristina; Teirumenieka, Erika; Arsic, Nebojsa

2018-06-01

Evaluation of the optimal laser cutting parameters is very important for the high cut quality. This is highly nonlinear process with different parameters which is the main challenge in the optimization process. Data mining methodology is one of most versatile method which can be used laser cutting process optimization. Support vector regression (SVR) procedure is implemented since it is a versatile and robust technique for very nonlinear data regression. The goal in this study was to determine the optimal laser cutting parameters to ensure robust condition for minimization of average surface roughness. Three cutting parameters, the cutting speed, the laser power, and the assist gas pressure, were used in the investigation. As a laser type TruLaser 1030 technological system was used. Nitrogen as an assisted gas was used in the laser cutting process. As the data mining method, support vector regression procedure was used. Data mining prediction accuracy was very high according the coefficient (R2) of determination and root mean square error (RMSE): R2 = 0.9975 and RMSE = 0.0337. Therefore the data mining approach could be used effectively for determination of the optimal conditions of the laser cutting process.

INNOVATIVE INSTRUMENTATION AND ANALYSIS OF THE TEMPERATURE MEASUREMENT FOR HIGH TEMPERATURE GASIFICATION

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

Seong W. Lee

During this reporting period, the literature survey including the gasifier temperature measurement literature, the ultrasonic application and its background study in cleaning application, and spray coating process are completed. The gasifier simulator (cold model) testing has been successfully conducted. Four factors (blower voltage, ultrasonic application, injection time intervals, particle weight) were considered as significant factors that affect the temperature measurement. The Analysis of Variance (ANOVA) was applied to analyze the test data. The analysis shows that all four factors are significant to the temperature measurements in the gasifier simulator (cold model). The regression analysis for the case with the normalizedmore » room temperature shows that linear model fits the temperature data with 82% accuracy (18% error). The regression analysis for the case without the normalized room temperature shows 72.5% accuracy (27.5% error). The nonlinear regression analysis indicates a better fit than that of the linear regression. The nonlinear regression model's accuracy is 88.7% (11.3% error) for normalized room temperature case, which is better than the linear regression analysis. The hot model thermocouple sleeve design and fabrication are completed. The gasifier simulator (hot model) design and the fabrication are completed. The system tests of the gasifier simulator (hot model) have been conducted and some modifications have been made. Based on the system tests and results analysis, the gasifier simulator (hot model) has met the proposed design requirement and the ready for system test. The ultrasonic cleaning method is under evaluation and will be further studied for the gasifier simulator (hot model) application. The progress of this project has been on schedule.« less

Adherence to the Mediterranean Diet Is not Related to Beta-Amyloid Deposition: Data from the Women's Healthy Ageing Project.

PubMed

Hill, E; Szoeke, C; Dennerstein, L; Campbell, S; Clifton, P

2018-01-01

Research has indicated the neuroprotective potential of the Mediterranean diet. Adherence to the Mediterranean diet has shown preventative potential for Alzheimer's disease incidence and prevalence, yet few studies have investigated the impact of Mediterranean diet adherence on the hallmark protein; beta-amyloid. To investigate the association between Mediterranean diet adherence and beta-amyloid deposition in a cohort of healthy older Australian women. This study was a cross-sectional investigation of participants from the longitudinal, epidemiologically sourced Women's Healthy Ageing Project which is a follow-up of the Melbourne Women's Midlife Health Project. Assessments were conducted at the Centre for Medical Research, Royal Melbourne Hospital in Melbourne, Australia. F-18 Florbetaben positron emission tomography scanning was conducted at the Austin Centre for PET in Victoria, Australia. One hundred and eleven Women's Healthy Ageing Project participants were included in the study. Mediterranean diet adherence scores for all participants were calculated from the administration of a validated food frequency questionnaire constructed by the Cancer Council of Victoria. Beta-amyloid deposition was measured using positron emission tomography standardised uptake value ratios. Gamma regression analysis displayed no association between Mediterranean diet adherence and beta-amyloid deposition. This result was consistent across APOE-ε4 +/- cohorts and with the inclusion of covariates such as age, education, body mass index and cognition. This study found no association between adherence to the Mediterranean diet and beta-amyloid deposition in a cohort of healthy Australian women.

Predictors of Physical Activity among Adolescent Girl Students Based on the Social Cognitive Theory.

PubMed

Ardestani, Monasadat; Niknami, Shamsaddin; Hidarnia, Alireza; Hajizadeh, Ebrahim

2015-01-01

The importance of increasing adolescence girl's level of physical activity is recognized as a priority for having a healthy lifestyle. However, adolescent girls especially Iranian, are at high risk for physical inactivity. Social Cognitive Theory (SCT) is a successful theory to explain physical activity behavior. The aim of this study was to determine the predictors of physical activity based on the SCT. This cross-sectional study was conducted among 400 adolescent girls (15-16 yr old) in Tehran, Iran (2013). The participants were randomly chosen with multistage sampling. The SCT constructs consisted of self-efficacy, self-regulation, social support, outcome expectancy, and self-efficacy to overcoming impediments. Statistical analysis was carried out applying SPSS: 16, LISREL 8.8. Stepwise regression was used to test predictors of behavior. Pearson correlation was assessed. Self efficacy to overcoming impediments was the main construct to predict physical activity (Beta=0.37). Other determinants were self-efficacy (Beta=0.29), family support (beta=0.14), outcome expectancy (beta=0.13), friend support (beta=0.12), and self-regulation (beta=0.11), respectively. In general, the SCT questionnaire determined 0.85 variation of physical activity behavior. All of the constructs had direct significant relation to physical activity behavior (P<0.001). The constructs of SCT provide a suitable framework to perform promoting physical activity programs and self-efficacy to overcoming impediments and self-efficacy are the best predictors of physical activity in adolescent girls.

Nonselective Beta-Blockers Do Not Affect Survival in Cirrhotic Patients with Ascites.

PubMed

Facciorusso, Antonio; Roy, Sunil; Livadas, Sarantis; Fevrier-Paul, Adwalia; Wekesa, Clara; Kilic, Ismail Dogu; Chaurasia, Amit Kumar; Sadeq, Mina; Muscatiello, Nicola

2018-05-03

The role of nonselective beta-blockers in cirrhotic patients with ascites has been recently questioned; however, definitive evidence in this regard is still lacking. To analyze published data on the influence of nonselective beta-blockers as compared to control group on survival of cirrhotic patients with ascites. Computerized bibliographic search on the main databases was performed. Hazard ratios from Kaplan-Meier curves were extracted in order to perform an unbiased comparison of survival estimates. Secondary outcomes were mortality in patients with refractory ascites, pooled rate of nonselective beta-blockers interruption, spontaneous bacterial peritonitis and hepato-renal syndrome incidence. Three randomized controlled trials and 13 observational studies with 8279 patients were included. Overall survival was comparable between the two groups (hazard ratio = 0.86, 0.71-1.03, p = 0.11). Study design resulted as the main source of heterogeneity in sensitivity analysis and meta-regression. Mortality in refractory ascites patients was similar in the two groups (odds ratio = 0.90, 0.45-1.79; p = 0.76). No difference in spontaneous bacterial peritonitis (odds ratio = 0.78, 0.47-1.29, p = 0.33) and hepato-renal syndrome incidence (odds ratio = 1.22, 0.48-3.09; p = 0.67) was observed. Pooled rate of nonselective beta-blockers interruption was 18.6% (5.2-32.1%). Based on our findings, nonselective beta-blockers should not be routinely withheld in patients with cirrhosis and ascites, even if refractory.

Linear and nonlinear stiffness and friction in biological rhythmic movements.

PubMed

Beek, P J; Schmidt, R C; Morris, A W; Sim, M Y; Turvey, M T

1995-11-01

Biological rhythmic movements can be viewed as instances of self-sustained oscillators. Auto-oscillatory phenomena must involve a nonlinear friction function, and usually involve a nonlinear elastic function. With respect to rhythmic movements, the question is: What kinds of nonlinear friction and elastic functions are involved? The nonlinear friction functions of the kind identified by Rayleigh (involving terms such as theta3) and van der Pol (involving terms such as theta2theta), and the nonlinear elastic functions identified by Duffing (involving terms such as theta3), constitute elementary nonlinear components for the assembling of self-sustained oscillators, Recently, additional elementary nonlinear friction and stiffness functions expressed, respectively, through terms such as theta2theta3 and thetatheta2, and a methodology for evaluating the contribution of the elementary components to any given cyclic activity have been identified. The methodology uses a quantification of the continuous deviation of oscillatory motion from ideal (harmonic) motion. Multiple regression of this quantity on the elementary linear and nonlinear terms reveals the individual contribution of each term to the oscillator's non-harmonic behavior. In the present article the methodology was applied to the data from three experiments in which human subjects produced pendular rhythmic movements under manipulations of rotational inertia (experiment 1), rotational inertia and frequency (experiment 2), and rotational inertia and amplitude (experiment 3). The analysis revealed that the pendular oscillators assembled in the three experiments were compositionally rich, braiding linear and nonlinear friction and elastic functions in a manner that depended on the nature of the task.

Turbulent Convection in an Anelastic Rotating Sphere: A Model for the Circulation on the Giant Planets

DTIC Science & Technology

2008-06-01

exterior weather layer, using a quasigeostrophic two layer channel model on a beta plane , where the colum- nar interior is therefore represented by a...116 5.4 The evolution of the ’it’ field in the weakly nonlinear run ........ .. 117 5.5 The zonal mean zonal velocity on the equatorial plane in...turbulence on a 8 plane . These two approaches have been in debate ever since. 1.3.1 Shallow Models The first to apply the "shallow" approach to

A new linear least squares method for T1 estimation from SPGR signals with multiple TRs

NASA Astrophysics Data System (ADS)

Chang, Lin-Ching; Koay, Cheng Guan; Basser, Peter J.; Pierpaoli, Carlo

2009-02-01

The longitudinal relaxation time, T1, can be estimated from two or more spoiled gradient recalled echo x (SPGR) images with two or more flip angles and one or more repetition times (TRs). The function relating signal intensity and the parameters are nonlinear; T1 maps can be computed from SPGR signals using nonlinear least squares regression. A widely-used linear method transforms the nonlinear model by assuming a fixed TR in SPGR images. This constraint is not desirable since multiple TRs are a clinically practical way to reduce the total acquisition time, to satisfy the required resolution, and/or to combine SPGR data acquired at different times. A new linear least squares method is proposed using the first order Taylor expansion. Monte Carlo simulations of SPGR experiments are used to evaluate the accuracy and precision of the estimated T1 from the proposed linear and the nonlinear methods. We show that the new linear least squares method provides T1 estimates comparable in both precision and accuracy to those from the nonlinear method, allowing multiple TRs and reducing computation time significantly.

Developing a predictive tropospheric ozone model for Tabriz

NASA Astrophysics Data System (ADS)

Khatibi, Rahman; Naghipour, Leila; Ghorbani, Mohammad A.; Smith, Michael S.; Karimi, Vahid; Farhoudi, Reza; Delafrouz, Hadi; Arvanaghi, Hadi

2013-04-01

Predictive ozone models are becoming indispensable tools by providing a capability for pollution alerts to serve people who are vulnerable to the risks. We have developed a tropospheric ozone prediction capability for Tabriz, Iran, by using the following five modeling strategies: three regression-type methods: Multiple Linear Regression (MLR), Artificial Neural Networks (ANNs), and Gene Expression Programming (GEP); and two auto-regression-type models: Nonlinear Local Prediction (NLP) to implement chaos theory and Auto-Regressive Integrated Moving Average (ARIMA) models. The regression-type modeling strategies explain the data in terms of: temperature, solar radiation, dew point temperature, and wind speed, by regressing present ozone values to their past values. The ozone time series are available at various time intervals, including hourly intervals, from August 2010 to March 2011. The results for MLR, ANN and GEP models are not overly good but those produced by NLP and ARIMA are promising for the establishing a forecasting capability.

Mixed and Mixture Regression Models for Continuous Bounded Responses Using the Beta Distribution

ERIC Educational Resources Information Center

Verkuilen, Jay; Smithson, Michael

2012-01-01

Doubly bounded continuous data are common in the social and behavioral sciences. Examples include judged probabilities, confidence ratings, derived proportions such as percent time on task, and bounded scale scores. Dependent variables of this kind are often difficult to analyze using normal theory models because their distributions may be quite…

The Use of Structure Coefficients to Address Multicollinearity in Sport and Exercise Science

ERIC Educational Resources Information Center

Yeatts, Paul E.; Barton, Mitch; Henson, Robin K.; Martin, Scott B.

2017-01-01

A common practice in general linear model (GLM) analyses is to interpret regression coefficients (e.g., standardized ß weights) as indicators of variable importance. However, focusing solely on standardized beta weights may provide limited or erroneous information. For example, ß weights become increasingly unreliable when predictor variables are…

Is serum zinc level associated with prediabetes and diabetes?: a cross-sectional study from Bangladesh.

PubMed

Islam, Md Rafiqul; Arslan, Iqbal; Attia, John; McEvoy, Mark; McElduff, Patrick; Basher, Ariful; Rahman, Waliur; Peel, Roseanne; Akhter, Ayesha; Akter, Shahnaz; Vashum, Khanrin P; Milton, Abul Hasnat

2013-01-01

To determine serum zinc level and other relevant biological markers in normal, prediabetic and diabetic individuals and their association with Homeostasis Model Assessment (HOMA) parameters. This cross-sectional study was conducted between March and December 2009. Any patient aged ≥ 30 years attending the medicine outpatient department of a medical university hospital in Dhaka, Bangladesh and who had a blood glucose level ordered by a physician was eligible to participate. A total of 280 participants were analysed. On fasting blood sugar results, 51% were normal, 13% had prediabetes and 36% had diabetes. Mean serum zinc level was lowest in prediabetic compared to normal and diabetic participants (mean differences were approximately 65 ppb/L and 33 ppb/L, respectively). In multiple linear regression, serum zinc level was found to be significantly lower in prediabetes than in those with normoglycemia. Beta cell function was significantly lower in prediabetes than normal participants. Adjusted linear regression for HOMA parameters did not show a statistically significant association between serum zinc level, beta cell function (P = 0.07) and insulin resistance (P = 0.08). Low serum zinc accentuated the increase in insulin resistance seen with increasing BMI. Participants with prediabetes have lower zinc levels than controls and zinc is significantly associated with beta cell function and insulin resistance. Further longitudinal population based studies are warranted and controlled trials would be valuable for establishing whether zinc supplementation in prediabetes could be a useful strategy in preventing progression to Type 2 diabetes.

Abdominal Subcutaneous Fat: A Favorable or Nonfunctional Fat Depot for Glucose Metabolism in Chinese Adults?

PubMed

Hou, Xuhong; Chen, Peizhu; Hu, Gang; Wei, Li; Jiao, Lei; Wang, Hongmei; Liang, Yebei; Bao, Yuqian; Jia, Weiping

2018-06-01

The objective of this study was to assess the associations of abdominal visceral and subcutaneous adipose tissue with blood glucose and beta-cell function. In this study, 11,223 participants without known diabetes were selected for this cross-sectional analysis. Visceral and subcutaneous fat area (VFA and SFA) were measured by magnetic resonance imaging. An oral glucose tolerance test was conducted, and beta-cell function was evaluated. Men had significantly larger VFA but smaller SFA than women. After controlling for age, linear regression showed that SFA was adversely associated with 0-minute, 30-minute, and 2-hour plasma glucose (PG) and early-, first- and second-phase disposition indices (DIs). After further adjustment for BMI and VFA, some associations of SFA with PG indices and DIs disappeared, while the other associations became significantly weaker in men (2-hour PG: 0.05 and DI 2nd : -0.05) or were reversed in women (0-minute, 30-minute, and 2-hour PG: from -0.07 to -0.04; DI 1st : 0.04, P < 0.05). After adjustment for age, BMI, and SFA, VFA was significantly and adversely associated with PG indices and DIs, with the largest standardized regression coefficients with 2-hour PG. The associations of SFA with blood glucose and beta-cell function were clinically insignificant in Chinese adults. VFA had the strongest association with 2-hour PG. © 2018 The Obesity Society.

Systematic review of the evidence relating FEV1 decline to giving up smoking

PubMed Central

2010-01-01

Background The rate of forced expiratory volume in 1 second (FEV1) decline ("beta") is a marker of chronic obstructive pulmonary disease risk. The reduction in beta after quitting smoking is an upper limit for the reduction achievable from switching to novel nicotine delivery products. We review available evidence to estimate this reduction and quantify the relationship of smoking to beta. Methods Studies were identified, in healthy individuals or patients with respiratory disease, that provided data on beta over at least 2 years of follow-up, separately for those who gave up smoking and other smoking groups. Publications to June 2010 were considered. Independent beta estimates were derived for four main smoking groups: never smokers, ex-smokers (before baseline), quitters (during follow-up) and continuing smokers. Unweighted and inverse variance-weighted regression analyses compared betas in the smoking groups, and in continuing smokers by amount smoked, and estimated whether beta or beta differences between smoking groups varied by age, sex and other factors. Results Forty-seven studies had relevant data, 28 for both sexes and 19 for males. Sixteen studies started before 1970. Mean follow-up was 11 years. On the basis of weighted analysis of 303 betas for the four smoking groups, never smokers had a beta 10.8 mL/yr (95% confidence interval (CI), 8.9 to 12.8) less than continuing smokers. Betas for ex-smokers were 12.4 mL/yr (95% CI, 10.1 to 14.7) less than for continuing smokers, and for quitters, 8.5 mL/yr (95% CI, 5.6 to 11.4) less. These betas were similar to that for never smokers. In continuing smokers, beta increased 0.33 mL/yr per cigarette/day. Beta differences between continuing smokers and those who gave up were greater in patients with respiratory disease or with reduced baseline lung function, but were not clearly related to age or sex. Conclusion The available data have numerous limitations, but clearly show that continuing smokers have a beta that is dose-related and over 10 mL/yr greater than in never smokers, ex-smokers or quitters. The greater decline in those with respiratory disease or reduced lung function is consistent with some smokers having a more rapid rate of FEV1 decline. These results help in designing studies comparing continuing smokers of conventional cigarettes and switchers to novel products. PMID:21156048

Two-Stage Residual Inclusion Estimation in Health Services Research and Health Economics.

PubMed

Terza, Joseph V

2018-06-01

Empirical analyses in health services research and health economics often require implementation of nonlinear models whose regressors include one or more endogenous variables-regressors that are correlated with the unobserved random component of the model. In such cases, implementation of conventional regression methods that ignore endogeneity will likely produce results that are biased and not causally interpretable. Terza et al. (2008) discuss a relatively simple estimation method that avoids endogeneity bias and is applicable in a wide variety of nonlinear regression contexts. They call this method two-stage residual inclusion (2SRI). In the present paper, I offer a 2SRI how-to guide for practitioners and a step-by-step protocol that can be implemented with any of the popular statistical or econometric software packages. We introduce the protocol and its Stata implementation in the context of a real data example. Implementation of 2SRI for a very broad class of nonlinear models is then discussed. Additional examples are given. We analyze cigarette smoking as a determinant of infant birthweight using data from Mullahy (1997). It is hoped that the discussion will serve as a practical guide to implementation of the 2SRI protocol for applied researchers. © Health Research and Educational Trust.

Fouling resistance prediction using artificial neural network nonlinear auto-regressive with exogenous input model based on operating conditions and fluid properties correlations

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

Biyanto, Totok R.

Fouling in a heat exchanger in Crude Preheat Train (CPT) refinery is an unsolved problem that reduces the plant efficiency, increases fuel consumption and CO{sub 2} emission. The fouling resistance behavior is very complex. It is difficult to develop a model using first principle equation to predict the fouling resistance due to different operating conditions and different crude blends. In this paper, Artificial Neural Networks (ANN) MultiLayer Perceptron (MLP) with input structure using Nonlinear Auto-Regressive with eXogenous (NARX) is utilized to build the fouling resistance model in shell and tube heat exchanger (STHX). The input data of the model aremore » flow rates and temperatures of the streams of the heat exchanger, physical properties of product and crude blend data. This model serves as a predicting tool to optimize operating conditions and preventive maintenance of STHX. The results show that the model can capture the complexity of fouling characteristics in heat exchanger due to thermodynamic conditions and variations in crude oil properties (blends). It was found that the Root Mean Square Error (RMSE) are suitable to capture the nonlinearity and complexity of the STHX fouling resistance during phases of training and validation.« less

Estimating mono- and bi-phasic regression parameters using a mixture piecewise linear Bayesian hierarchical model

PubMed Central

Zhao, Rui; Catalano, Paul; DeGruttola, Victor G.; Michor, Franziska

2017-01-01

The dynamics of tumor burden, secreted proteins or other biomarkers over time, is often used to evaluate the effectiveness of therapy and to predict outcomes for patients. Many methods have been proposed to investigate longitudinal trends to better characterize patients and to understand disease progression. However, most approaches assume a homogeneous patient population and a uniform response trajectory over time and across patients. Here, we present a mixture piecewise linear Bayesian hierarchical model, which takes into account both population heterogeneity and nonlinear relationships between biomarkers and time. Simulation results show that our method was able to classify subjects according to their patterns of treatment response with greater than 80% accuracy in the three scenarios tested. We then applied our model to a large randomized controlled phase III clinical trial of multiple myeloma patients. Analysis results suggest that the longitudinal tumor burden trajectories in multiple myeloma patients are heterogeneous and nonlinear, even among patients assigned to the same treatment cohort. In addition, between cohorts, there are distinct differences in terms of the regression parameters and the distributions among categories in the mixture. Those results imply that longitudinal data from clinical trials may harbor unobserved subgroups and nonlinear relationships; accounting for both may be important for analyzing longitudinal data. PMID:28723910

An Experimental Study in Determining Energy Expenditure from Treadmill Walking using Hip-Worn Inertial Sensors

PubMed Central

Vathsangam, Harshvardhan; Emken, Adar; Schroeder, E. Todd; Spruijt-Metz, Donna; Sukhatme, Gaurav S.

2011-01-01

This paper describes an experimental study in estimating energy expenditure from treadmill walking using a single hip-mounted triaxial inertial sensor comprised of a triaxial accelerometer and a triaxial gyroscope. Typical physical activity characterization using accelerometer generated counts suffers from two drawbacks - imprecison (due to proprietary counts) and incompleteness (due to incomplete movement description). We address these problems in the context of steady state walking by directly estimating energy expenditure with data from a hip-mounted inertial sensor. We represent the cyclic nature of walking with a Fourier transform of sensor streams and show how one can map this representation to energy expenditure (as measured by V O2 consumption, mL/min) using three regression techniques - Least Squares Regression (LSR), Bayesian Linear Regression (BLR) and Gaussian Process Regression (GPR). We perform a comparative analysis of the accuracy of sensor streams in predicting energy expenditure (measured by RMS prediction accuracy). Triaxial information is more accurate than uniaxial information. LSR based approaches are prone to outlier sensitivity and overfitting. Gyroscopic information showed equivalent if not better prediction accuracy as compared to accelerometers. Combining accelerometer and gyroscopic information provided better accuracy than using either sensor alone. We also analyze the best algorithmic approach among linear and nonlinear methods as measured by RMS prediction accuracy and run time. Nonlinear regression methods showed better prediction accuracy but required an order of magnitude of run time. This paper emphasizes the role of probabilistic techniques in conjunction with joint modeling of triaxial accelerations and rotational rates to improve energy expenditure prediction for steady-state treadmill walking. PMID:21690001

Piezoelectric Response of Aligned Electrospun Polyvinylidene Fluoride/Carbon Nanotube Nanofibrous Membranes.

PubMed

Wu, Chang-Mou; Chou, Min-Hui; Zeng, Wun-Yuan

2018-06-10

Polyvinylidene fluoride (PVDF) shows piezoelectricity related to its β-phase content and mechanical and electrical properties influenced by its morphology and crystallinity. Electrospinning (ES) can produce ultrafine and well-aligned PVDF nanofibers. In this study, the effects of the presence of carbon nanotubes (CNT) and optimized ES parameters on the crystal structures and piezoelectric properties of aligned PVDF/CNT nanofibrous membranes were examined. The optimal β content and piezoelectric coefficient (d 33 ) of the aligned electrospun PVDF reached 88% and 27.4 pC/N; CNT addition increased the β-phase content to 89% and d 33 to 31.3 pC/N. The output voltages of piezoelectric units with aligned electrospun PVDF/CNT membranes increased linearly with applied loading and showed good stability during cyclic dynamic compression and tension. The sensitivities of the piezoelectric units with the membranes under dynamic compression and tension were 2.26 mV/N and 4.29 mV/%, respectively. In bending tests, the output voltage increased nonlinearly with bending angle because complicated forces were involved. The output of the aligned membrane-based piezoelectric unit with CNT was 1.89 V at the bending angle of 100°. The high electric outputs indicate that the aligned electrospun PVDF/CNT membranes are potentially effective for flexible wearable sensor application with high sensitivity.

A nonlinear cointegration approach with applications to structural health monitoring

NASA Astrophysics Data System (ADS)

Shi, H.; Worden, K.; Cross, E. J.

2016-09-01

One major obstacle to the implementation of structural health monitoring (SHM) is the effect of operational and environmental variabilities, which may corrupt the signal of structural degradation. Recently, an approach inspired from the community of econometrics, called cointegration, has been employed to eliminate the adverse influence from operational and environmental changes and still maintain sensitivity to structural damage. However, the linear nature of cointegration may limit its application when confronting nonlinear relations between system responses. This paper proposes a nonlinear cointegration method based on Gaussian process regression (GPR); the method is constructed under the Engle-Granger framework, and tests for unit root processes are conducted both before and after the GPR is applied. The proposed approach is examined with real engineering data from the monitoring of the Z24 Bridge.

On structure-exploiting trust-region regularized nonlinear least squares algorithms for neural-network learning.

PubMed

Mizutani, Eiji; Demmel, James W

2003-01-01

This paper briefly introduces our numerical linear algebra approaches for solving structured nonlinear least squares problems arising from 'multiple-output' neural-network (NN) models. Our algorithms feature trust-region regularization, and exploit sparsity of either the 'block-angular' residual Jacobian matrix or the 'block-arrow' Gauss-Newton Hessian (or Fisher information matrix in statistical sense) depending on problem scale so as to render a large class of NN-learning algorithms 'efficient' in both memory and operation costs. Using a relatively large real-world nonlinear regression application, we shall explain algorithmic strengths and weaknesses, analyzing simulation results obtained by both direct and iterative trust-region algorithms with two distinct NN models: 'multilayer perceptrons' (MLP) and 'complementary mixtures of MLP-experts' (or neuro-fuzzy modular networks).

[Correlates of change in cognitive function during a two-year follow-up period in a comprehensive health examination for the community-dwelling elderly for the prevention of geriatric syndromes and bed-ridden state].

PubMed

Iwasa, Hajime; Suzuki, Takao; Yoshida, Yuko; Kwon, Jinhee; Yoshida, Hideyo; Kim, Hunkyung; Sugiura, Miho; Furuna, Taketo

2006-11-01

We explored correlates of change in cognitive function during a two-year follow-up period among the community-dwelling elderly in Japan, using a population-based prospective approach. The participants analyzed in the present study were 260 men and 222 women aged 70 to 84 years at baseline, living in an urban Japanese community. Data such as change in cognitive function during two years (calculated by subtracting baseline Mini-Mental State Examination [MMSE] score from follow-up MMSE score: a negative value means a decrease in MMSE scores during the two-year period) as an outcome variable, age, education, hearing and vision problems, IADL deficit (measured by the Tokyo Metropolitan Institute of Gerontology of Index of Competence), problems related to memory complaint, living alone, hemoglobin level, as explanatory variables, and the baseline MMSE score, depressive status (measured by the Mini-International Neuropsychiatric Interview), chronic conditions (hypertension, stroke, and diabetes mellitus) as covariates, were collected during a comprehensive health examination survey for the elderly. We conducted multivariate regression analysis by genders to explore correlates of change in cognitive function. The results showed that higher age (beta = -0.18), presence of hearing problem (beta = -0.21), presence of IADL deficit (beta = -0.15), and memory complaint (beta = -0.20) in men, and higher age (beta = -0.27), low education level (beta = -0.25) and lower hemoglobin level (beta = 0.16) in women, were significantly associated with change in cognitive function when adjusting for the potential confounders. These factors may be reliable predictors for cognitive decline.

Evidence for Increased Beta-Adrenoreceptor Responsiveness Induced by 14 Days of Simulated Microgravity in Humans

NASA Technical Reports Server (NTRS)

Convertino, Victor A.; Polet, Jill L.; Engelke, Keith A.; Hoffler, G. W.; Lane, Lynda D.

1996-01-01

We studied hemodynamic responses to alpha and beta receptor agonists in 8 healthy men ( 38+- 2 yrs) before and after 14 days of 6 degree head-down tilt (HDT) to test the hypothesis that increased adrenergic responsiveness is induced by prolonged exposure to microgravity. Immediately following a 30-min baseline period, a steady-state infusion of isoproterenol (ISO) was used to assess beta 1- and beta 2-adrenergic responsiveness. ISO was infused at three graded constant rates of 0.005, 0.01 and 0.02 ug/kg/min. After heart rate and blood pressure had been allowed to return to baseline levels following ISO infusion graded infusion of phenylephrine (PE) was used to assess responsiveness of alpha I-vascular receptors. PE was infused at three graded constant rates of 0.25, 0.50 and 1.00 ug/kg/min. Each infusion interval for both drugs was 9 min. During the infusions, constant monitoring of beat-to-beat blood pressure and heart rate was performed and leg blood flow was measured with occlusion plethysmography at each infusion level. The slopes calculated from linear regressions between ISO and PE doses and changes in heart rate, blood pressure, and leg vascular resistance for each subject were used to represent alpha- and beta- adrenoreceptor responsiveness. Fourteen days HDT increased the slopes of heart rate (1056 +- 107 to 1553 +- 83 beats/ug/kg/min; P= 0.014) and vasodilation (-469ft +- 111 to -l446 +- 309 PRU/ug/kg/min; P =0.0224) to ISO infusion. There was no alteration in blood pressure or vascular resistance responses to PE infusion after HDT. Our results provide evidence that microgravity causes selective increases in beta 1- and beta 2-adrenergic responsiveness without affecting alpha 1-vascular responses.

Beta-carotene Antioxidant Use During Radiation Therapy and Prostate Cancer Outcome in the Physicians' Health Study

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

Margalit, Danielle N., E-mail: dmargalit@lroc.harvard.edu; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts; Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts

2012-05-01

Purpose: The safety of antioxidant supplementation during radiation therapy (RT) for cancer is controversial. Antioxidants could potentially counteract the pro-oxidant effects of RT and compromise therapeutic efficacy. We performed a prospective study nested within the Physicians' Health Study (PHS) randomized trial to determine if supplemental antioxidant use during RT for prostate cancer is associated with an increased risk of prostate cancer death or metastases. Methods and Materials: PHS participants (383) received RT for prostate cancer while randomized to receive beta-carotene (50 mg on alternate days) or placebo. The primary endpoint was time from RT to lethal prostate cancer, defined asmore » prostate cancer death or bone metastases. The Kaplan-Meier method was used to estimate survival probabilities and the log-rank test to compare groups. Cox proportional hazards regression was used to estimate the effect of beta-carotene compared with that of placebo during RT. Results: With a median follow-up of 10.5 years, there was no significant difference between risk of lethal prostate cancer with the use of beta-carotene during RT compared with that of placebo (hazard ratio = 0.72; 95% confidence interval [CI], 0.42-1.24; p = 0.24). After we adjusted for age at RT, prostate-specific antigen serum level, Gleason score, and clinical stage, the difference remained nonsignificant. The 10-year freedom from lethal prostate cancer was 92% (95% CI, 87-95%) in the beta-carotene group and 89% (95% CI, 84-93%) in the placebo group. Conclusion: The use of supplemental antioxidant beta-carotene during RT was not associated with an increased risk of prostate cancer death or metastases. This study suggests a lack of harm from supplemental beta-carotene during RT for prostate cancer.« less

Anxiety and beta-adrenergic receptor function in a normal population.

PubMed

Kang, Eun-Ho; Yu, Bum-Hee

2005-06-01

Many studies have shown a close relationship between anxiety and beta-adrenergic receptor function in patients with anxiety disorders. This study examined the relationship between beta-adrenergic receptor function and anxiety levels in a normal population. Subjects for this study included 36 men and 44 women between the ages of 20 and 40 years whose Body Mass Index (BMI) was between 18 and 26. All of them were healthy subjects who had no previous history of medical or psychiatric illnesses. The authors measured the Spielberger State-Trait Anxiety Inventory (STAI), Beck Depression Inventory (BDI), and Chronotropic 25 Dose (CD25) of isoproterenol, previously developed to assess in vivo beta-adrenergic receptor sensitivity. We also examined correlations between log normalized CD25 and mood states. The mean of CD25 was 2.64+/-1.37 mug and the mean of CD25 in men was significantly higher (i.e., lower beta-adrenergic receptor sensitivity) than that of women (3.26+/-1.35 vs. 2.14+/-1.17 microg; t = 3.99, p < 0.001). CD25 showed negative correlations with STAI state anxiety (r = -0.344, p = 0.002), trait anxiety (r = -0.331, p = 0.003), and BDI (r = -0.283, p = 0.011). CD25 was positively correlated with BMI (r = 0.423, p < 0.001) and age (r = 0.271, p = 0.015). In stepwise multiple regression analyses, 34% of the variance in CD25 was accounted for by sex, state anxiety, and BMI. The sensitivity of beta-adrenergic receptors increased as anxiety levels became higher in a normal population. Thus, the relationship between anxiety and beta-adrenergic receptor function in healthy subjects may be different from that of patients with anxiety disorders.

A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels.

PubMed

Heino, Jani; Melo, Adriano S; Bini, Luis Mauricio; Altermatt, Florian; Al-Shami, Salman A; Angeler, David G; Bonada, Núria; Brand, Cecilia; Callisto, Marcos; Cottenie, Karl; Dangles, Olivier; Dudgeon, David; Encalada, Andrea; Göthe, Emma; Grönroos, Mira; Hamada, Neusa; Jacobsen, Dean; Landeiro, Victor L; Ligeiro, Raphael; Martins, Renato T; Miserendino, María Laura; Md Rawi, Che Salmah; Rodrigues, Marciel E; Roque, Fabio de Oliveira; Sandin, Leonard; Schmera, Denes; Sgarbi, Luciano F; Simaika, John P; Siqueira, Tadeu; Thompson, Ross M; Townsend, Colin R

2015-03-01

The hypotheses that beta diversity should increase with decreasing latitude and increase with spatial extent of a region have rarely been tested based on a comparative analysis of multiple datasets, and no such study has focused on stream insects. We first assessed how well variability in beta diversity of stream insect metacommunities is predicted by insect group, latitude, spatial extent, altitudinal range, and dataset properties across multiple drainage basins throughout the world. Second, we assessed the relative roles of environmental and spatial factors in driving variation in assemblage composition within each drainage basin. Our analyses were based on a dataset of 95 stream insect metacommunities from 31 drainage basins distributed around the world. We used dissimilarity-based indices to quantify beta diversity for each metacommunity and, subsequently, regressed beta diversity on insect group, latitude, spatial extent, altitudinal range, and dataset properties (e.g., number of sites and percentage of presences). Within each metacommunity, we used a combination of spatial eigenfunction analyses and partial redundancy analysis to partition variation in assemblage structure into environmental, shared, spatial, and unexplained fractions. We found that dataset properties were more important predictors of beta diversity than ecological and geographical factors across multiple drainage basins. In the within-basin analyses, environmental and spatial variables were generally poor predictors of variation in assemblage composition. Our results revealed deviation from general biodiversity patterns because beta diversity did not show the expected decreasing trend with latitude. Our results also call for reconsideration of just how predictable stream assemblages are along ecological gradients, with implications for environmental assessment and conservation decisions. Our findings may also be applicable to other dynamic systems where predictability is low.

A local basal area adjustment for crown width prediction

Treesearch

Don C. Bragg

2001-01-01

Nonlinear crown width regressive equations were developed for 24 species common to the upper Lake States of Michigan, Minnesota, and Wisconsin. Of the species surveyed, 15 produced statistically significant (P 0.05) local basal area effect coefficients showing a reduction in crown...

Accelerated test design

NASA Technical Reports Server (NTRS)

Mcdermott, P. P.

1980-01-01

The design of an accelerated life test program for electric batteries is discussed. A number of observations and suggestions on the procedures and objectives for conducting an accelerated life test program are presented. Equations based on nonlinear regression analysis for predicting the accelerated life test parameters are discussed.

Correlates of Physical Activity in Latino Preschool Children Attending Head Start.

PubMed

Dawson-Hahn, Elizabeth Erin; Fesinmeyer, Megan D; Mendoza, Jason A

2015-08-01

Physical activity is associated with long-term benefits for health and tracks from early childhood into later adolescence. Limited information exists about factors influencing physical activity among Latino preschoolers. We aimed to identify correlates of objectively measured light-to-vigorous-intensity physical activity as a proportion of wear time (% PA) in Latino 3-5 year olds. Latino preschoolers (n = 96) were recruited from Head Start centers in Houston, TX, USA, from 2009 to 2010. Sociodemographics, anthropometrics, acculturation, neighborhood disorder, and TV viewing were measured. Actigraph GT1M accelerometers measured physical activity. Block linear regression was used with % PA as the dependent variable. Children achieved 285.7 ± 58.0 min/day of PA. In the final adjusted-model, child age, parental education and neighborhood disorder were positively associated with % PA (beta = 0.33, p = .002; beta = 0.25, p = .038; beta = 0.22, p = .039, respectively). TV viewing was inversely associated with % PA (beta=-0.23, p = .027). The majority of Latino preschoolers in our study exceeded US national and international guidelines of physical activity duration. Future interventions to sustain physical activity should focus on the influence of age, socioeconomic status, neighborhood disorder, and TV viewing on Latino preschoolers' attainment of physical activity.

The relationships among racial identity, self-esteem, sociodemographics, and health-promoting lifestyles.

PubMed

Johnson, Rolanda L

2002-01-01

The purpose of this study was to explore the relationships between racial identity, self-esteem, sociodemographic factors, and health-promoting lifestyles in a sample of African Americans. African American mortality rates are disproportionately high. These rates are associated with health behaviors that are driven by many factors including lifestyle practices. Other factors may be self-esteem and racial identity. Research shows gender differences in health behaviors, but no studies have explored a racial identity and gender interaction. Exploring these relationships may lead to the improved health status of African Americans. A convenience sample of 224 was recruited consisting of 48% males (n = 108). The mean age was 37.2 years (SD = 12.6). Regression analyses demonstrated that the internalization racial identity stage (beta = .12; p < .001) and self-esteem (beta = .50; p < .001) contributed to the variance in health-promoting lifestyles. Self-esteem did not mediate the relationship between immersion and health-promoting lifestyle scores (beta = -.16; p = .03). The full model Beta values show that racial identity remains significant with sociodemographics and interactions controlled, but moderators do not. Racial identity, while not a strong predictor, has some impact on health-promoting lifestyles regardless of sociodemographics.

Dehydroepiandrosterone and dehydroepiandrosterone sulfate: anabolic, neuroprotective, and neuroexcitatory properties in military men.

PubMed

Taylor, Marcus K

2013-01-01

Evidence links dehydroepiandrosterone (DHEA) and dehydroepiandrosterone sulfate (DHEAS) to crucial military health issues, including operational stress, resilience, and traumatic brain injury. This study evaluated the anabolic, neuroprotective, and neuroexcitatory properties of DHEA(S) in healthy military men. A salivary sample was obtained from 42 men and assayed for DHEA(S), testosterone, nerve growth factor (NGF; which supports nerve cell proliferation), and salivary alpha amylase (sAA; a proxy of sympathetic nervous system function). Separate regression analyses were conducted with DHEA and DHEAS as independent variables, and testosterone, NGF, and sAA as dependent variables, respectively. The models explained 23.4% of variance in testosterone (p < 0.01), 17.2% of variance in NGF (p < 0.01), and 7.4% of variance in sAA (p = 0.09). Standardized beta coefficients revealed that DHEA independently influenced testosterone (beta = 0.40, p < 0.01), whereas DHEAS independently influenced NGF (beta = 0.48, p < 0.01) and sAA (beta = 0.36, p < 0.05). DHEA demonstrated anabolic properties, whereas DHEAS demonstrated neuroprotective and neuroexcitatory properties in military men. This area of study has broad implications for stress inoculation, traumatic brain injury rehabilitation, and regenerative medicine in military personnel.

Impact of family abuse on running away, deviance, and street victimization among homeless rural and urban youth.

PubMed

Thrane, Lisa E; Hoyt, Danny R; Whitbeck, Les B; Yoder, Kevin A

2006-10-01

Various demographic and familial risk factors have been linked to runaway behavior. To date, there has not been a systematic investigation of the impact of size of community on runaway behavior. This study will compare runaways from smaller cities and rural areas to their urban counterparts. A convenience sample of 602 adolescents was interviewed between 1995 and August of 1996 in Missouri, Iowa, Nebraska, and Kansas, USA. Multiple regression was used to examine the association between gender, neglect, sexual abuse, physical abuse, geographic and family structure change, and community size of first runaway to predict age at first runaway, deviant subsistence strategies, and street victimization. Findings indicate that adolescents exposed to neglect (beta=-.20) and sexual abuse (beta=-.16) ran away sooner and were more likely to be victimized on the street. Rural adolescents who experienced higher levels of physical abuse relied more heavily on deviant subsistence strategies (beta=.15) and remained in abusive homes longer (beta=.15) than their similarly situated urban counterparts. Rural youth who have been subjected to elevated levels of familial abuse are at greater risk of deviant subsistence strategies, which increase the likelihood of street victimization.

Determinants of satisfaction with health care provider interactions at health centres in central Ethiopia: a cross sectional study.

PubMed

Birhanu, Zewdie; Assefa, Tsion; Woldie, Mirkuzie; Morankar, Sudhakar

2010-03-24

In primary health care, provider-patient interaction is fundamental platform and critically affects service delivery. Nevertheless, it is often ignored in medical research and practice and it is infrequently subjected to scientific inquiry, particularly in Ethiopia. This study aimed to assess patient satisfaction with health care provider interactions and its influencing factors among out-patients at health centers in West Shoa, Central Ethiopia. A cross sectional facility based study was conducted on 768 out-patients of six health centers in West Shoa Zone, Central Ethiopia. The total sample size was allocated to each of the six health centers based on patient flow during the ten days prior to the start of data collection. Pre-tested instruments were used for data collection and the data were analyzed using SPSS version 16.0 statistical software. Factor score was computed for the items identified to represent the satisfaction scale by varimax rotation method. Using this regression factor score, multivariate linear regression analysis was performed and the effect of independent variables on the regression factor score was quantified. Seventy three percent of the respondents perceived that provider's empathy was good and 35% complained that providers were not technically competent enough. In addition, 82% of the respondents rated non-verbal communication by the providers to be good, very good or excellent on a five-point ordinal scale. Regardless of the process, only 34.1% of the patients implied that the consultations made a difference in understanding their illness and coping with it. Generally speaking, 62.6% of the patients reported that they have been satisfied with their visit. Perceived empathy, perceived technical competency, non-verbal communication, patient enablement, being told the name of once illness, type and frequency of visit, knowing the providers and educational status were main independent predictors of patient satisfaction in this study. Furthermore, very good empathy (Beta = -4.323), fair non-verbal communication (Beta = -0.188), fewer expectations met (Beta = -0.169) and disagreement to technical competency (Beta = -0.156) had greater negative influence on patient satisfaction. On the other hand, excellent non-verbal communication (Beta = 0.114) and being told the name of once illness (0.109) had pronounced positive influence on patient satisfaction. The present study showed that interpersonal processes including perceived empathy, perceived technical competency, non-verbal communication and patient enablement significantly influence patient satisfaction. Therefore, health care providers should work towards improving the communication skill of their professionals along with having technically competent workers which could possibly affect the perception of the patient about all of the variables identified as independent predictors of patient satisfaction in this study.

Human ovarian cancer xenografts in nude mice: chemotherapy trials with paclitaxel, cisplatin, vinorelbine and titanocene dichloride.

PubMed

Villena-Heinsen, C; Friedrich, M; Ertan, A K; Farnhammer, C; Schmidt, W

1998-07-01

The new cytostatics titanocene dichloride and vinorelbine were compared to cisplatin and paclitaxel using a human ovarian cancer xenografts model. Biopsy material from a native human ovarian carcinoma was expanded and transplanted into 96 nude mice. The animals were divided into six treatment groups: cisplatin 3 x 4 mg/kg, paclitaxel 5 x 26 mg/kg, vinorelbine 1 x 20 mg/kg, titanocene dichloride 3 x 30 mg/kg, titanocene dichloride 3 x 40 mg/kg and a control group treated with 0.9% saline. Each experiment was repeated with eight mice in each treatment group. Treatment groups were evaluated in terms of average daily increase in tumor volume and average daily body weight increase of nude mice based on slopes of least-square regressions performed on individual animals. The slope factors alpha and beta of the body weight (alpha) and tumor volume changes (beta) within each group during the course of an experiment were calculated. Both a statistically significant decrease (p<0.05) in the body weight of the experimental animals (cisplatin: alpha = -0.5163, vinorelbine: alpha = -0.6598, paclitaxel: alpha = -0.6746, titanocene dichloride 3 x 30 mg/kg: alpha = -0.6259, titanocene dichloride 3 x 40 mg/kg: alpha = -0.7758) and a significant reduction (p<0.05) of the increase in tumor volume (cisplatin: beta = 12.049, vinorelbine: beta = 0.504, paclitaxel: beta = -1.636, titanocene dichloride 3 x 30 mg/kg: beta = 6.212, titanocene dichloride 3 x 40 mg/kg: beta= -0.685) was shown in all treated groups compared to the control group (alpha = -0.1398; beta = 23.056). No significant weight changes were observed between the individually treated groups. A statistically significant reduction of the tumor growth occured under paclitaxel (beta = -1.636), vinorelbine (beta = 0.504) and titanocene dichloride medication 3 x 40 mg/kg (beta = -0.685), as compared to the group treated with cisplatin (beta = 12.049). We found titanocene dichloride to be as effective as paclitaxel and more effective than cisplatin. Vinorelbine seems to be a very effective antineoplastic agent exhibiting a significant higher cytostatic effect than cisplatin. Both titanocene dichloride and vinorelbine provide new therapeutic options in women with ovarian carcinoma not responding to standard chemotherapy.

[Predicting the outcome in severe injuries: an analysis of 2069 patients from the trauma register of the German Society of Traumatology (DGU)].

PubMed

Rixen, D; Raum, M; Bouillon, B; Schlosser, L E; Neugebauer, E

2001-03-01

On hospital admission numerous variables are documented from multiple trauma patients. The value of these variables to predict outcome are discussed controversially. The aim was the ability to initially determine the probability of death of multiple trauma patients. Thus, a multivariate probability model was developed based on data obtained from the trauma registry of the Deutsche Gesellschaft für Unfallchirurgie (DGU). On hospital admission the DGU trauma registry collects more than 30 variables prospectively. In the first step of analysis those variables were selected, that were assumed to be clinical predictors for outcome from literature. In a second step a univariate analysis of these variables was performed. For all primary variables with univariate significance in outcome prediction a multivariate logistic regression was performed in the third step and a multivariate prognostic model was developed. 2069 patients from 20 hospitals were prospectively included in the trauma registry from 01.01.1993-31.12.1997 (age 39 +/- 19 years; 70.0% males; ISS 22 +/- 13; 18.6% lethality). From more than 30 initially documented variables, the age, the GCS, the ISS, the base excess (BE) and the prothrombin time were the most important prognostic factors to predict the probability of death (P(death)). The following prognostic model was developed: P(death) = 1/1 + e(-[k + beta 1(age) + beta 2(GCS) + beta 3(ISS) + beta 4(BE) + beta 5(prothrombin time)]) where: k = -0.1551, beta 1 = 0.0438 with p < 0.0001, beta 2 = -0.2067 with p < 0.0001, beta 3 = 0.0252 with p = 0.0071, beta 4 = -0.0840 with p < 0.0001 and beta 5 = -0.0359 with p < 0.0001. Each of the five variables contributed significantly to the multifactorial model. These data show that the age, GCS, ISS, base excess and prothrombin time are potentially important predictors to initially identify multiple trauma patients with a high risk of lethality. With the base excess and prothrombin time value, as only variables of this multifactorial model that can be therapeutically influenced, it might be possible to better guide early and aggressive therapy.

QUAGMIRE v1.3: a quasi-geostrophic model for investigating rotating fluids experiments

NASA Astrophysics Data System (ADS)

Williams, P. D.; Haine, T. W. N.; Read, P. L.; Lewis, S. R.; Yamazaki, Y. H.

2008-09-01

QUAGMIRE is a quasi-geostrophic numerical model for performing fast, high-resolution simulations of multi-layer rotating annulus laboratory experiments on a desktop personal computer. The model uses a hybrid finite-difference/spectral approach to numerically integrate the coupled nonlinear partial differential equations of motion in cylindrical geometry in each layer. Version 1.3 implements the special case of two fluid layers of equal resting depths. The flow is forced either by a differentially rotating lid, or by relaxation to specified streamfunction or potential vorticity fields, or both. Dissipation is achieved through Ekman layer pumping and suction at the horizontal boundaries, including the internal interface. The effects of weak interfacial tension are included, as well as the linear topographic beta-effect and the quadratic centripetal beta-effect. Stochastic forcing may optionally be activated, to represent approximately the effects of random unresolved features. A leapfrog time stepping scheme is used, with a Robert filter. Flows simulated by the model agree well with those observed in the corresponding laboratory experiments.

QUAGMIRE v1.3: a quasi-geostrophic model for investigating rotating fluids experiments

NASA Astrophysics Data System (ADS)

Williams, P. D.; Haine, T. W. N.; Read, P. L.; Lewis, S. R.; Yamazaki, Y. H.

2009-02-01

QUAGMIRE is a quasi-geostrophic numerical model for performing fast, high-resolution simulations of multi-layer rotating annulus laboratory experiments on a desktop personal computer. The model uses a hybrid finite-difference/spectral approach to numerically integrate the coupled nonlinear partial differential equations of motion in cylindrical geometry in each layer. Version 1.3 implements the special case of two fluid layers of equal resting depths. The flow is forced either by a differentially rotating lid, or by relaxation to specified streamfunction or potential vorticity fields, or both. Dissipation is achieved through Ekman layer pumping and suction at the horizontal boundaries, including the internal interface. The effects of weak interfacial tension are included, as well as the linear topographic beta-effect and the quadratic centripetal beta-effect. Stochastic forcing may optionally be activated, to represent approximately the effects of random unresolved features. A leapfrog time stepping scheme is used, with a Robert filter. Flows simulated by the model agree well with those observed in the corresponding laboratory experiments.

Stress assessment based on EEG univariate features and functional connectivity measures.

PubMed

Alonso, J F; Romero, S; Ballester, M R; Antonijoan, R M; Mañanas, M A

2015-07-01

The biological response to stress originates in the brain but involves different biochemical and physiological effects. Many common clinical methods to assess stress are based on the presence of specific hormones and on features extracted from different signals, including electrocardiogram, blood pressure, skin temperature, or galvanic skin response. The aim of this paper was to assess stress using EEG-based variables obtained from univariate analysis and functional connectivity evaluation. Two different stressors, the Stroop test and sleep deprivation, were applied to 30 volunteers to find common EEG patterns related to stress effects. Results showed a decrease of the high alpha power (11 to 12 Hz), an increase in the high beta band (23 to 36 Hz, considered a busy brain indicator), and a decrease in the approximate entropy. Moreover, connectivity showed that the high beta coherence and the interhemispheric nonlinear couplings, measured by the cross mutual information function, increased significantly for both stressors, suggesting that useful stress indexes may be obtained from EEG-based features.

Three wave mixing test of hyperelasticity in highly nonlinear solids: sedimentary rocks.

PubMed

D'Angelo, R M; Winkler, K W; Johnson, D L

2008-02-01

Measurements of three-wave mixing amplitudes on solids whose third order elastic constants have also been measured by means of the elasto-acoustic effect are reported. Because attenuation and diffraction are important aspects of the measurement technique results are analyzed using a frequency domain version of the KZK equation, modified to accommodate an arbitrary frequency dependence to the attenuation. It is found that the value of beta so deduced for poly(methylmethacrylate) (PMMA) agrees quite well with that predicted from the stress-dependent sound speed measurements, establishing that PMMA may be considered a hyperelastic solid, in this context. The beta values of sedimentary rocks, though they are typically two orders of magnitude larger than, e.g., PMMA's, are still a factor of 3-10 less than those predicted from the elasto-acoustic effect. Moreover, these samples exhibit significant heterogeneity on a centimeter scale, which heterogeneity is not apparent from a measurement of the position dependent sound speed.

Design Considerations for Proposed Fermilab Integrable RCS

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

Eldred, Jeffrey; Valishev, Alexander

2017-03-02

Integrable optics is an innovation in particle accelerator design that provides strong nonlinear focusing while avoiding parametric resonances. One promising application of integrable optics is to overcome the traditional limits on accelerator intensity imposed by betatron tune-spread and collective instabilities. The efficacy of high-intensity integrable accelerators will be undergo comprehensive testing over the next several years at the Fermilab Integrable Optics Test Accelerator (IOTA) and the University of Maryland Electron Ring (UMER). We propose an integrable Rapid-Cycling Synchrotron (iRCS) as a replacement for the Fermilab Booster to achieve multi-MW beam power for the Fermilab high-energy neutrino program. We provide amore » overview of the machine parameters and discuss an approach to lattice optimization. Integrable optics requires arcs with integer-pi phase advance followed by drifts with matched beta functions. We provide an example integrable lattice with features of a modern RCS - long dispersion-free drifts, low momentum compaction, superperiodicity, chromaticity correction, separate-function magnets, and bounded beta functions.« less

Quasi-Axially Symmetric Stellarators with 3 Field Periods

NASA Astrophysics Data System (ADS)

Garabedian, Paul; Ku, Long-Poe

1998-11-01

Compact hybrid configurations with 2 field periods have been studied recently as candidates for a proof of principle experiment at PPPL, cf. A. Reiman et al., Physics design of a high beta quasi-axially symmetric stellarator, J. Plas. Fus. Res. SERIES 1, 429(1998). This enterprise has led us to the discovery of a family of quasi-axially symmetric stellarators with 3 field periods that seem to have significant advantages, although their aspect ratios are a little larger. They have reversed shear and perform better in a local analysis of ballooning modes. Nonlinear equilibrium and stability calculations predict that the average beta limit may be as high as 6% if the bootstrap current turns out to be as big as that expected in comparable tokamaks. The concept relies on a combination of helical fields and bootstrap current to achieve adequate rotational transform at low aspect ratio. A detailed manuscript describing some of this work will be published soon, cf. P.R. Garabedian, Quasi-axially symmetric stellarators, Proc. Natl. Acad. Sci. USA 95 (1998).

Cell kill by megavoltage protons with high LET.

PubMed

Kuperman, Vadim Y

2016-07-21

The aim of the current study is to develop a radiobiological model which describes the effect of linear energy transfer (LET) on cell survival and relative biological effectiveness (RBE) of megavoltage protons. By assuming the existence of critical sites within a cell, analytical expression for cell survival S as a function of LET is derived. The obtained results indicate that in cases where dose per fraction is small, [Formula: see text] is a linear-quadratic (LQ) function of dose while both alpha and beta radio-sensitivities are non-linearly dependent on LET. In particular, in the current model alpha increases with increasing LET while beta decreases. Conversely, in the case of large dose per fraction, the LQ dependence of [Formula: see text] on dose is invalid. The proposed radiobiological model predicts cell survival probability and RBE which, in general, deviate from the results obtained by using conventional LQ formalism. The differences between the LQ model and that described in the current study are reflected in the calculated RBE of protons.

Physicians' reactions to uncertainty in the context of shared decision making.

PubMed

Politi, Mary C; Légaré, France

2010-08-01

Physicians' reactions towards uncertainty may influence their willingness to engage in shared decision making (SDM). This study aimed to identify variables associated with physician's anxiety from uncertainty and reluctance to disclose uncertainty to patients. We conducted a cross-sectional secondary analysis of longitudinal data of an implementation study of SDM among primary care professionals (n=122). Outcomes were anxiety from uncertainty and reluctance to disclose uncertainty to patients. Hypothesized factors that would be associated with outcomes included attitude, social norm, perceived behavioral control, intention to implement SDM in practice, and socio-demographics. Stepwise linear regression was used to identify predictors of anxiety from uncertainty and reluctance to disclose uncertainty to patients. In multivariate analyses, anxiety from uncertainty was influenced by female gender (beta=0.483; p=0.0039), residency status (1st year: beta=0.600; p=0.001; 2nd year: beta=0.972; p<0.001), and number of hours worked per week (beta=-0.012; p=0.048). Reluctance to disclose uncertainty to patients was influenced by having more years in formal education (beta=-1.996; p=0.012). Variables associated with anxiety from uncertainty differ from those associated with reluctance to disclose uncertainty to patients. Given the importance of communicating uncertainty during SDM, measuring physicians' reactions to uncertainty is essential in SDM implementation studies. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

Catchments as non-linear filters: evaluating data-driven approaches for spatio-temporal predictions in ungauged basins

NASA Astrophysics Data System (ADS)

Bellugi, D. G.; Tennant, C.; Larsen, L.

2016-12-01

Catchment and climate heterogeneity complicate prediction of runoff across time and space, and resulting parameter uncertainty can lead to large accumulated errors in hydrologic models, particularly in ungauged basins. Recently, data-driven modeling approaches have been shown to avoid the accumulated uncertainty associated with many physically-based models, providing an appealing alternative for hydrologic prediction. However, the effectiveness of different methods in hydrologically and geomorphically distinct catchments, and the robustness of these methods to changing climate and changing hydrologic processes remain to be tested. Here, we evaluate the use of machine learning techniques to predict daily runoff across time and space using only essential climatic forcing (e.g. precipitation, temperature, and potential evapotranspiration) time series as model input. Model training and testing was done using a high quality dataset of daily runoff and climate forcing data for 25+ years for 600+ minimally-disturbed catchments (drainage area range 5-25,000 km2, median size 336 km2) that cover a wide range of climatic and physical characteristics. Preliminary results using Support Vector Regression (SVR) suggest that in some catchments this nonlinear-based regression technique can accurately predict daily runoff, while the same approach fails in other catchments, indicating that the representation of climate inputs and/or catchment filter characteristics in the model structure need further refinement to increase performance. We bolster this analysis by using Sparse Identification of Nonlinear Dynamics (a sparse symbolic regression technique) to uncover the governing equations that describe runoff processes in catchments where SVR performed well and for ones where it performed poorly, thereby enabling inference about governing processes. This provides a robust means of examining how catchment complexity influences runoff prediction skill, and represents a contribution towards the integration of data-driven inference and physically-based models.

Development of Ensemble Model Based Water Demand Forecasting Model

NASA Astrophysics Data System (ADS)

Kwon, Hyun-Han; So, Byung-Jin; Kim, Seong-Hyeon; Kim, Byung-Seop

2014-05-01

In recent years, Smart Water Grid (SWG) concept has globally emerged over the last decade and also gained significant recognition in South Korea. Especially, there has been growing interest in water demand forecast and optimal pump operation and this has led to various studies regarding energy saving and improvement of water supply reliability. Existing water demand forecasting models are categorized into two groups in view of modeling and predicting their behavior in time series. One is to consider embedded patterns such as seasonality, periodicity and trends, and the other one is an autoregressive model that is using short memory Markovian processes (Emmanuel et al., 2012). The main disadvantage of the abovementioned model is that there is a limit to predictability of water demands of about sub-daily scale because the system is nonlinear. In this regard, this study aims to develop a nonlinear ensemble model for hourly water demand forecasting which allow us to estimate uncertainties across different model classes. The proposed model is consist of two parts. One is a multi-model scheme that is based on combination of independent prediction model. The other one is a cross validation scheme named Bagging approach introduced by Brieman (1996) to derive weighting factors corresponding to individual models. Individual forecasting models that used in this study are linear regression analysis model, polynomial regression, multivariate adaptive regression splines(MARS), SVM(support vector machine). The concepts are demonstrated through application to observed from water plant at several locations in the South Korea. Keywords: water demand, non-linear model, the ensemble forecasting model, uncertainty. Acknowledgements This subject is supported by Korea Ministry of Environment as "Projects for Developing Eco-Innovation Technologies (GT-11-G-02-001-6)

A deep belief network with PLSR for nonlinear system modeling.

PubMed

Qiao, Junfei; Wang, Gongming; Li, Wenjing; Li, Xiaoli

2018-08-01

Nonlinear system modeling plays an important role in practical engineering, and deep learning-based deep belief network (DBN) is now popular in nonlinear system modeling and identification because of the strong learning ability. However, the existing weights optimization for DBN is based on gradient, which always leads to a local optimum and a poor training result. In this paper, a DBN with partial least square regression (PLSR-DBN) is proposed for nonlinear system modeling, which focuses on the problem of weights optimization for DBN using PLSR. Firstly, unsupervised contrastive divergence (CD) algorithm is used in weights initialization. Secondly, initial weights derived from CD algorithm are optimized through layer-by-layer PLSR modeling from top layer to bottom layer. Instead of gradient method, PLSR-DBN can determine the optimal weights using several PLSR models, so that a better performance of PLSR-DBN is achieved. Then, the analysis of convergence is theoretically given to guarantee the effectiveness of the proposed PLSR-DBN model. Finally, the proposed PLSR-DBN is tested on two benchmark nonlinear systems and an actual wastewater treatment system as well as a handwritten digit recognition (nonlinear mapping and modeling) with high-dimension input data. The experiment results show that the proposed PLSR-DBN has better performances of time and accuracy on nonlinear system modeling than that of other methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

PRESS-based EFOR algorithm for the dynamic parametrical modeling of nonlinear MDOF systems

NASA Astrophysics Data System (ADS)

Liu, Haopeng; Zhu, Yunpeng; Luo, Zhong; Han, Qingkai

2017-09-01

In response to the identification problem concerning multi-degree of freedom (MDOF) nonlinear systems, this study presents the extended forward orthogonal regression (EFOR) based on predicted residual sums of squares (PRESS) to construct a nonlinear dynamic parametrical model. The proposed parametrical model is based on the non-linear autoregressive with exogenous inputs (NARX) model and aims to explicitly reveal the physical design parameters of the system. The PRESS-based EFOR algorithm is proposed to identify such a model for MDOF systems. By using the algorithm, we built a common-structured model based on the fundamental concept of evaluating its generalization capability through cross-validation. The resulting model aims to prevent over-fitting with poor generalization performance caused by the average error reduction ratio (AERR)-based EFOR algorithm. Then, a functional relationship is established between the coefficients of the terms and the design parameters of the unified model. Moreover, a 5-DOF nonlinear system is taken as a case to illustrate the modeling of the proposed algorithm. Finally, a dynamic parametrical model of a cantilever beam is constructed from experimental data. Results indicate that the dynamic parametrical model of nonlinear systems, which depends on the PRESS-based EFOR, can accurately predict the output response, thus providing a theoretical basis for the optimal design of modeling methods for MDOF nonlinear systems.

Nonlinear analysis of pupillary dynamics.

PubMed

Onorati, Francesco; Mainardi, Luca Tommaso; Sirca, Fabiola; Russo, Vincenzo; Barbieri, Riccardo

2016-02-01

Pupil size reflects autonomic response to different environmental and behavioral stimuli, and its dynamics have been linked to other autonomic correlates such as cardiac and respiratory rhythms. The aim of this study is to assess the nonlinear characteristics of pupil size of 25 normal subjects who participated in a psychophysiological experimental protocol with four experimental conditions, namely “baseline”, “anger”, “joy”, and “sadness”. Nonlinear measures, such as sample entropy, correlation dimension, and largest Lyapunov exponent, were computed on reconstructed signals of spontaneous fluctuations of pupil dilation. Nonparametric statistical tests were performed on surrogate data to verify that the nonlinear measures are an intrinsic characteristic of the signals. We then developed and applied a piecewise linear regression model to detrended fluctuation analysis (DFA). Two joinpoints and three scaling intervals were identified: slope α0, at slow time scales, represents a persistent nonstationary long-range correlation, whereas α1 and α2, at middle and fast time scales, respectively, represent long-range power-law correlations, similarly to DFA applied to heart rate variability signals. Of the computed complexity measures, α0 showed statistically significant differences among experimental conditions (p<0.001). Our results suggest that (a) pupil size at constant light condition is characterized by nonlinear dynamics, (b) three well-defined and distinct long-memory processes exist at different time scales, and (c) autonomic stimulation is partially reflected in nonlinear dynamics. (c) autonomic stimulation is partially reflected in nonlinear dynamics.

Frequency, pressure and strain dependence of nonlinear elasticity in Berea Sandstone

DOE PAGES

Riviere, Jacques; Johnson, Paul Allan; Marone, Chris; ...

2016-04-14

Acoustoelasticity measurements in a sample of room dry Berea sandstone are conducted at various loading frequencies to explore the transition between the quasi-static ( f → 0) and dynamic (few kilohertz) nonlinear elastic response. We carry out these measurements at multiple confining pressures and perform a multivariate regression analysis to quantify the dependence of the harmonic content on strain amplitude, frequency, and pressure. The modulus softening (equivalent to the harmonic at 0f) increases by a factor 2–3 over 3 orders of magnitude increase in frequency. Harmonics at 2f, 4f, and 6f exhibit similar behaviors. In contrast, the harmonic at 1fmore » appears frequency independent. This result corroborates previous studies showing that the nonlinear elasticity of rocks can be described with a minimum of two physical mechanisms. This study provides quantitative data that describes the rate dependency of nonlinear elasticity. Furthermore, these findings can be used to improve theories relating the macroscopic elastic response to microstructural features.« less

Analysis of Binary Adherence Data in the Setting of Polypharmacy: A Comparison of Different Approaches

PubMed Central

Esserman, Denise A.; Moore, Charity G.; Roth, Mary T.

2009-01-01

Older community dwelling adults often take multiple medications for numerous chronic diseases. Non-adherence to these medications can have a large public health impact. Therefore, the measurement and modeling of medication adherence in the setting of polypharmacy is an important area of research. We apply a variety of different modeling techniques (standard linear regression; weighted linear regression; adjusted linear regression; naïve logistic regression; beta-binomial (BB) regression; generalized estimating equations (GEE)) to binary medication adherence data from a study in a North Carolina based population of older adults, where each medication an individual was taking was classified as adherent or non-adherent. In addition, through simulation we compare these different methods based on Type I error rates, bias, power, empirical 95% coverage, and goodness of fit. We find that estimation and inference using GEE is robust to a wide variety of scenarios and we recommend using this in the setting of polypharmacy when adherence is dichotomously measured for multiple medications per person. PMID:20414358

Impact of Social Processes in Online Health Communities on Patient Empowerment in Relationship With the Physician: Emergence of Functional and Dysfunctional Empowerment.

PubMed

Petrič, Gregor; Atanasova, Sara; Kamin, Tanja

2017-03-13

Substantial research demonstrates the importance of online health communities (OHCs) for patient empowerment, although the impact on the patient-physician relationship is understudied. Patient empowerment also occurs in relationship with the physician, but studies of OHCs mostly disregard this. The question also remains about the nature and consequences of this empowerment, as it might be based on the limited validity of some information in OHCs. The main purpose of this study was to examine the impact of social processes in OHCs (information exchange with users and health professional moderators, social support, finding meaning, and self-expressing) on functional and dysfunctional patient empowerment in relationship with the physician (PERP). This impact was investigated by taking into account moderating role of eHealth literacy and physician's paternalism. An email list-based Web survey on a simple random sample of 25,000 registered users of the most popular general OHC in Slovenia was conducted. A total of 1572 respondents completed the survey. The analyses were conducted on a subsample of 591 regular users, who had visited a physician at least once in the past 2 years. To estimate the impact of social processes in OHC on functional and dysfunctional PERP, we performed a series of hierarchical regression analyses. To determine the moderating role of eHealth literacy and the perceived physician characteristics, interactions were included in the regression analyses. The mean age of the respondents in the sample was 37.6 years (SD 10.3) and 83.3% were females. Factor analyses of the PERP revealed a five-factor structure with acceptable fit (root-mean-square error of approximation =.06). Most important results are that functional self-efficacy is positively predicted by information exchange with health professional moderators (beta=.12, P=.02), information exchange with users (beta=.12, P=.05), and giving social support (beta=.13, P=.02), but negatively predicted with receiving social support (beta=-.21, P<.001). Functional control is also predicted by information exchange with health professional moderators (beta=.16, P=.005). Dysfunctional control and competence are inhibited by information exchanges with health professionals (beta=-.12, P=.03), whereas dysfunctional self-efficacy is inhibited by self-expressing (beta=-.12, P=.05). The process of finding meaning likely leads to the development of dysfunctional competences and control if the physician is perceived to be paternalistic (beta=.14, P=.03). Under the condition of high eHealth literacy, the process of finding meaning will inhibit the development of dysfunctional competences and control (beta=-.17, P=.01). Social processes in OHCs do not have a uniform impact on PERP. This impact is moderated by eHealth literacy and physician paternalism. Exchanging information with health professional moderators in OHCs is the most important factor for stimulating functional PERP as well as diminishing dysfunctional PERP. Social support in OHCs plays an ambiguous role, often making patients behave in a strategic, uncooperative way toward physicians. ©Gregor Petrič, Sara Atanasova, Tanja Kamin. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 13.03.2017.

Impact of Social Processes in Online Health Communities on Patient Empowerment in Relationship With the Physician: Emergence of Functional and Dysfunctional Empowerment

PubMed Central

Atanasova, Sara; Kamin, Tanja

2017-01-01

Background Substantial research demonstrates the importance of online health communities (OHCs) for patient empowerment, although the impact on the patient-physician relationship is understudied. Patient empowerment also occurs in relationship with the physician, but studies of OHCs mostly disregard this. The question also remains about the nature and consequences of this empowerment, as it might be based on the limited validity of some information in OHCs. Objective The main purpose of this study was to examine the impact of social processes in OHCs (information exchange with users and health professional moderators, social support, finding meaning, and self-expressing) on functional and dysfunctional patient empowerment in relationship with the physician (PERP). This impact was investigated by taking into account moderating role of eHealth literacy and physician’s paternalism. Method An email list–based Web survey on a simple random sample of 25,000 registered users of the most popular general OHC in Slovenia was conducted. A total of 1572 respondents completed the survey. The analyses were conducted on a subsample of 591 regular users, who had visited a physician at least once in the past 2 years. To estimate the impact of social processes in OHC on functional and dysfunctional PERP, we performed a series of hierarchical regression analyses. To determine the moderating role of eHealth literacy and the perceived physician characteristics, interactions were included in the regression analyses. Results The mean age of the respondents in the sample was 37.6 years (SD 10.3) and 83.3% were females. Factor analyses of the PERP revealed a five-factor structure with acceptable fit (root-mean-square error of approximation =.06). Most important results are that functional self-efficacy is positively predicted by information exchange with health professional moderators (beta=.12, P=.02), information exchange with users (beta=.12, P=.05), and giving social support (beta=.13, P=.02), but negatively predicted with receiving social support (beta=−.21, P<.001). Functional control is also predicted by information exchange with health professional moderators (beta=.16, P=.005). Dysfunctional control and competence are inhibited by information exchanges with health professionals (beta=−.12, P=.03), whereas dysfunctional self-efficacy is inhibited by self-expressing (beta=−.12, P=.05). The process of finding meaning likely leads to the development of dysfunctional competences and control if the physician is perceived to be paternalistic (beta=.14, P=.03). Under the condition of high eHealth literacy, the process of finding meaning will inhibit the development of dysfunctional competences and control (beta=−.17, P=.01). Conclusions Social processes in OHCs do not have a uniform impact on PERP. This impact is moderated by eHealth literacy and physician paternalism. Exchanging information with health professional moderators in OHCs is the most important factor for stimulating functional PERP as well as diminishing dysfunctional PERP. Social support in OHCs plays an ambiguous role, often making patients behave in a strategic, uncooperative way toward physicians. PMID:28288953

A data-driven approach for modeling post-fire debris-flow volumes and their uncertainty

USGS Publications Warehouse

Friedel, Michael J.

2011-01-01

This study demonstrates the novel application of genetic programming to evolve nonlinear post-fire debris-flow volume equations from variables associated with a data-driven conceptual model of the western United States. The search space is constrained using a multi-component objective function that simultaneously minimizes root-mean squared and unit errors for the evolution of fittest equations. An optimization technique is then used to estimate the limits of nonlinear prediction uncertainty associated with the debris-flow equations. In contrast to a published multiple linear regression three-variable equation, linking basin area with slopes greater or equal to 30 percent, burn severity characterized as area burned moderate plus high, and total storm rainfall, the data-driven approach discovers many nonlinear and several dimensionally consistent equations that are unbiased and have less prediction uncertainty. Of the nonlinear equations, the best performance (lowest prediction uncertainty) is achieved when using three variables: average basin slope, total burned area, and total storm rainfall. Further reduction in uncertainty is possible for the nonlinear equations when dimensional consistency is not a priority and by subsequently applying a gradient solver to the fittest solutions. The data-driven modeling approach can be applied to nonlinear multivariate problems in all fields of study.

Turnover of plant lineages shapes herbivore phylogenetic beta diversity along ecological gradients.

PubMed

Pellissier, Loïc; Ndiribe, Charlotte; Dubuis, Anne; Pradervand, Jean-Nicolas; Salamin, Nicolas; Guisan, Antoine; Rasmann, Sergio

2013-05-01

Understanding drivers of biodiversity patterns is of prime importance in this era of severe environmental crisis. More diverse plant communities have been postulated to represent a larger functional trait-space, more likely to sustain a diverse assembly of herbivore species. Here, we expand this hypothesis to integrate environmental, functional and phylogenetic variation of plant communities as factors explaining the diversity of lepidopteran assemblages along elevation gradients in the Swiss Western Alps. According to expectations, we found that the association between butterflies and their host plants is highly phylogenetically structured. Multiple regression analyses showed the combined effect of climate, functional traits and phylogenetic diversity in structuring butterfly communities. Furthermore, we provide the first evidence that plant phylogenetic beta diversity is the major driver explaining butterfly phylogenetic beta diversity. Along ecological gradients, the bottom up control of herbivore diversity is thus driven by phylogenetically structured turnover of plant traits as well as environmental variables. © 2013 Blackwell Publishing Ltd/CNRS.

Self-determination theory and physical activity among breast cancer survivors.

PubMed

Milne, Helen M; Wallman, Karen E; Guilfoyle, Andrew; Gordon, Sandy; Corneya, Kerry S

2008-02-01

The study aim was to examine constructs of autonomy support and competence as well as the motivation continuum from the self-determination theory (SDT) as a framework for understanding physical activity (PA) motivation and behavior in breast cancer survivors. Questionnaires assessing demographics, medical factors, PA, motivation continuum, perceived autonomy support, and competence were completed by 558 breast cancer survivors. Results showed that lymphedema (chi2 = 7.9, p < .01) (chi2 = 4.6, p < .05) were associated with meeting PA guidelines. Moreover, survivors meeting PA guidelines reported more identified regulations and intrinsic motivation (p < .01), autonomy support (p < .01), and competence (p < .01). Forced entry hierarchical regression analysis showed that SDT constructs explained 20.2% (p < .01) of the PA variance. Significant independent SDT predictors included identified regulation (Beta = .14, p < .05) and competence (Beta = .23, p < .01), with autonomy support approaching significance (Beta = .9, p = .057). SDT may be a useful model for understanding PA motivation and behavior in breast cancer survivors.

Risk Score Algorithm for Treatment of Persistent Apical Periodontitis

PubMed Central

Yu, V.S.; Khin, L.W.; Hsu, C.S.; Yee, R.; Messer, H.H.

2014-01-01

Persistent apical periodontitis related to a nonvital tooth that does not resolve following root canal treatment may be compatible with health and may not require further intervention. This research aimed to develop a Deterioration Risk Score (DRS) to differentiate lesions requiring further intervention from lesions likely to be compatible with health. In this cross-sectional study, patient records (2003-2008) were screened for root-filled teeth with periapical radiolucency visible on periapical radiographs taken at treatment and at recruitment at least 4 yr later. The final sample consisted of 228 lesions in 182 patients. Potential demographic and treatment risk factors were screened against 3 categorical outcomes (improved/unchanged/deteriorated), and a multivariate independent multinomial probit regression model was built. A 5-level DRS was constructed by summing values of adjusted regression coefficients in the model, based on predicted probabilities of deterioration. Most lesions (127, 55.7%) had improved over time, while 32 (14.0%) remained unchanged, and 69 (30.3%) had deteriorated. Significant predictors of deterioration were as follows: time since treatment (relative risk [RR]: 1.11, 95% confidence interval [CI]: 1.01-1.22, p = .030, rounded beta value = 1, for every year increase after 4 yr), current pain (RR: 3.79, 95% CI: 1.48-9.70, p = .005, rounded beta value = 13), sinus tract present (RR: 4.13, 95% CI: 1.11-15.29, p = .034, rounded beta value = 14), and lesion size (RR: 7.20, 95% CI: 3.70-14.02, p < .001, rounded beta value = 20). Persistent apical periodontitis with DRS <15 represented very low risk; 15-20, low risk; 21-30, moderate risk; 31-40, high risk; and >40, very high risk. DRS could help the clinician identify persistent apical periodontitis at low risk for deterioration, and it would not require intervention. When validated, this tool could reduce the risk of overtreatment and contribute toward targeted care and better efficiency in the timely management of disease. PMID:25190267

Feasibility of using near infrared spectroscopy to detect and quantify an adulterant in high quality sandalwood oil.

PubMed

Kuriakose, Saji; Joe, I Hubert

2013-11-01

Determination of the authenticity of essential oils has become more significant, in recent years, following some illegal adulteration and contamination scandals. The present investigative study focuses on the application of near infrared spectroscopy to detect sample authenticity and quantify economic adulteration of sandalwood oils. Several data pre-treatments are investigated for calibration and prediction using partial least square regression (PLSR). The quantitative data analysis is done using a new spectral approach - full spectrum or sequential spectrum. The optimum number of PLS components is obtained according to the lowest root mean square error of calibration (RMSEC=0.00009% v/v). The lowest root mean square error of prediction (RMSEP=0.00016% v/v) in the test set and the highest coefficient of determination (R(2)=0.99989) are used as the evaluation tools for the best model. A nonlinear method, locally weighted regression (LWR), is added to extract nonlinear information and to compare with the linear PLSR model. Copyright © 2013 Elsevier B.V. All rights reserved.

Nonlinear least-squares data fitting in Excel spreadsheets.

PubMed

Kemmer, Gerdi; Keller, Sandro

2010-02-01

We describe an intuitive and rapid procedure for analyzing experimental data by nonlinear least-squares fitting (NLSF) in the most widely used spreadsheet program. Experimental data in x/y form and data calculated from a regression equation are inputted and plotted in a Microsoft Excel worksheet, and the sum of squared residuals is computed and minimized using the Solver add-in to obtain the set of parameter values that best describes the experimental data. The confidence of best-fit values is then visualized and assessed in a generally applicable and easily comprehensible way. Every user familiar with the most basic functions of Excel will be able to implement this protocol, without previous experience in data fitting or programming and without additional costs for specialist software. The application of this tool is exemplified using the well-known Michaelis-Menten equation characterizing simple enzyme kinetics. Only slight modifications are required to adapt the protocol to virtually any other kind of dataset or regression equation. The entire protocol takes approximately 1 h.

A non-linear regression analysis program for describing electrophysiological data with multiple functions using Microsoft Excel.

PubMed

Brown, Angus M

2006-04-01

The objective of this present study was to demonstrate a method for fitting complex electrophysiological data with multiple functions using the SOLVER add-in of the ubiquitous spreadsheet Microsoft Excel. SOLVER minimizes the difference between the sum of the squares of the data to be fit and the function(s) describing the data using an iterative generalized reduced gradient method. While it is a straightforward procedure to fit data with linear functions, and we have previously demonstrated a method of non-linear regression analysis of experimental data based upon a single function, it is more complex to fit data with multiple functions, usually requiring specialized expensive computer software. In this paper we describe an easily understood program for fitting experimentally acquired data, in this case the stimulus-evoked compound action potential from the mouse optic nerve, with multiple Gaussian functions. The program is flexible and can be applied to describe data with a wide variety of user-input functions.

Macrocell path loss prediction using artificial intelligence techniques

NASA Astrophysics Data System (ADS)

Usman, Abraham U.; Okereke, Okpo U.; Omizegba, Elijah E.

2014-04-01

The prediction of propagation loss is a practical non-linear function approximation problem which linear regression or auto-regression models are limited in their ability to handle. However, some computational Intelligence techniques such as artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFISs) have been shown to have great ability to handle non-linear function approximation and prediction problems. In this study, the multiple layer perceptron neural network (MLP-NN), radial basis function neural network (RBF-NN) and an ANFIS network were trained using actual signal strength measurement taken at certain suburban areas of Bauchi metropolis, Nigeria. The trained networks were then used to predict propagation losses at the stated areas under differing conditions. The predictions were compared with the prediction accuracy of the popular Hata model. It was observed that ANFIS model gave a better fit in all cases having higher R2 values in each case and on average is more robust than MLP and RBF models as it generalises better to a different data.

Applications of Monte Carlo method to nonlinear regression of rheological data

NASA Astrophysics Data System (ADS)

Kim, Sangmo; Lee, Junghaeng; Kim, Sihyun; Cho, Kwang Soo

2018-02-01

In rheological study, it is often to determine the parameters of rheological models from experimental data. Since both rheological data and values of the parameters vary in logarithmic scale and the number of the parameters is quite large, conventional method of nonlinear regression such as Levenberg-Marquardt (LM) method is usually ineffective. The gradient-based method such as LM is apt to be caught in local minima which give unphysical values of the parameters whenever the initial guess of the parameters is far from the global optimum. Although this problem could be solved by simulated annealing (SA), the Monte Carlo (MC) method needs adjustable parameter which could be determined in ad hoc manner. We suggest a simplified version of SA, a kind of MC methods which results in effective values of the parameters of most complicated rheological models such as the Carreau-Yasuda model of steady shear viscosity, discrete relaxation spectrum and zero-shear viscosity as a function of concentration and molecular weight.

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time‐to‐Event Analysis

PubMed Central

Gong, Xiajing; Hu, Meng

2018-01-01

Abstract Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time‐to‐event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high‐dimensional data featured by a large number of predictor variables. Our results showed that ML‐based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high‐dimensional data. The prediction performances of ML‐based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML‐based methods provide a powerful tool for time‐to‐event analysis, with a built‐in capacity for high‐dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. PMID:29536640

Missing-value estimation using linear and non-linear regression with Bayesian gene selection.

PubMed

Zhou, Xiaobo; Wang, Xiaodong; Dougherty, Edward R

2003-11-22

Data from microarray experiments are usually in the form of large matrices of expression levels of genes under different experimental conditions. Owing to various reasons, there are frequently missing values. Estimating these missing values is important because they affect downstream analysis, such as clustering, classification and network design. Several methods of missing-value estimation are in use. The problem has two parts: (1) selection of genes for estimation and (2) design of an estimation rule. We propose Bayesian variable selection to obtain genes to be used for estimation, and employ both linear and nonlinear regression for the estimation rule itself. Fast implementation issues for these methods are discussed, including the use of QR decomposition for parameter estimation. The proposed methods are tested on data sets arising from hereditary breast cancer and small round blue-cell tumors. The results compare very favorably with currently used methods based on the normalized root-mean-square error. The appendix is available from http://gspsnap.tamu.edu/gspweb/zxb/missing_zxb/ (user: gspweb; passwd: gsplab).

Critical Analysis of Dual-Probe Heat-Pulse Technique Applied to Measuring Thermal Diffusivity

NASA Astrophysics Data System (ADS)

Bovesecchi, G.; Coppa, P.; Corasaniti, S.; Potenza, M.

2018-07-01

The paper presents an analysis of the experimental parameters involved in application of the dual-probe heat pulse technique, followed by a critical review of methods for processing thermal response data (e.g., maximum detection and nonlinear least square regression) and the consequent obtainable uncertainty. Glycerol was selected as testing liquid, and its thermal diffusivity was evaluated over the temperature range from - 20 °C to 60 °C. In addition, Monte Carlo simulation was used to assess the uncertainty propagation for maximum detection. It was concluded that maximum detection approach to process thermal response data gives the closest results to the reference data inasmuch nonlinear regression results are affected by major uncertainties due to partial correlation between the evaluated parameters. Besides, the interpolation of temperature data with a polynomial to find the maximum leads to a systematic difference between measured and reference data, as put into evidence by the Monte Carlo simulations; through its correction, this systematic error can be reduced to a negligible value, about 0.8 %.

Feasibility of using near infrared spectroscopy to detect and quantify an adulterant in high quality sandalwood oil

NASA Astrophysics Data System (ADS)

Kuriakose, Saji; Joe, I. Hubert

2013-11-01

Determination of the authenticity of essential oils has become more significant, in recent years, following some illegal adulteration and contamination scandals. The present investigative study focuses on the application of near infrared spectroscopy to detect sample authenticity and quantify economic adulteration of sandalwood oils. Several data pre-treatments are investigated for calibration and prediction using partial least square regression (PLSR). The quantitative data analysis is done using a new spectral approach - full spectrum or sequential spectrum. The optimum number of PLS components is obtained according to the lowest root mean square error of calibration (RMSEC = 0.00009% v/v). The lowest root mean square error of prediction (RMSEP = 0.00016% v/v) in the test set and the highest coefficient of determination (R2 = 0.99989) are used as the evaluation tools for the best model. A nonlinear method, locally weighted regression (LWR), is added to extract nonlinear information and to compare with the linear PLSR model.

PharmML in Action: an Interoperable Language for Modeling and Simulation.

PubMed

Bizzotto, R; Comets, E; Smith, G; Yvon, F; Kristensen, N R; Swat, M J

2017-10-01

PharmML is an XML-based exchange format created with a focus on nonlinear mixed-effect (NLME) models used in pharmacometrics, but providing a very general framework that also allows describing mathematical and statistical models such as single-subject or nonlinear and multivariate regression models. This tutorial provides an overview of the structure of this language, brief suggestions on how to work with it, and use cases demonstrating its power and flexibility. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Efficacy of beta-blockade after isolated blunt head injury: does race matter?

PubMed

Bukur, Marko; Mohseni, Shahin; Mosheni, Shahin; Ley, Eric; Salim, Ali; Margulies, Daniel; Talving, Peep; Demetriades, Demetrios; Inaba, Kenji

2012-04-01

Several retrospective clinical studies and recent prospective animal models demonstrate improved outcomes with beta-blocker administration after isolated blunt head injury. However, no investigations to date have examined the influence of race on the potential therapeutic effectiveness of these medications. Our hypothesis was that mortality benefits associated with beta-blocker exposure after isolated blunt head injury varies based on ethnicity. The trauma registry and the surgical intensive care unit (ICU) databases of an academic Level I trauma center were used to identify all patients sustaining blunt head injury requiring ICU admission from July 1998 to December 2009. Patients sustaining major associated extracranial injuries (Abbreviated Injury Scale [AIS] score ≥ 3 in any body region) were excluded. Patient demographics, injury profile, Injury Severity Score, and beta-blocker exposure were abstracted. The primary outcome evaluated was in-hospital mortality stratified by ethnicity. During the 11-year study period, 3,750 patients were admitted to the Los Angeles County + University of Southern California Medical Center trauma ICU because of blunt trauma. Of these, 65% (n = 2,446) had an "isolated" head injury. When stratified by race, most patients were Hispanics (60%), followed by Whites (21%), Asians (11%), and African Americans (8%). After adjusting for confounding variables with multivariate regression, only those of Asian and Hispanic descent demonstrated significantly improved outcomes associated with beta-blocker administration. Our results indicate that beta-blockade after traumatic brain injury may not benefit all races equally. Further prospective research is necessary to assess this discrepancy in treatment benefit and explore other possible therapeutic interventions.

Predictors of hospital CEO affiliation with a professional association.

PubMed

Khaliq, Amir A; Walston, Stephen L

2012-01-01

Based on a 2008 cross-sectional survey of 582 hospital CEOs in the United States, this study reports the findings of two logistic regression models designed to identify CEO and hospital characteristics associated with Member and Fellow status in the American College of Healthcare Executives (ACHE). The purpose of the study was to understand the personal and organizational characteristics of those CEOs who choose to be Members and Fellows of a professional association such as ACHE. The results showed that most (74 percent) of the respondents considered ACHE to be their primary professional association. The results also revealed that a master's degree in health administration [beta = .88, t(427) = 5.35, p < .0001], male gender [beta = .59, t(427) = 3.01, p = .002], and financial incentives provided by the parent hospital [beta = .25, t(427) = 2.73, p = .006] were statistically positively linked with Member status in ACHE. A master's degree in health administration [beta = .81, t(424) = 5.79, p < .0001], male gender [beta = .39, t(424) = 2.25, p = .02], and age [beta = .02, t(424) 2.32, p = .02] were also statistically positively associated with Fellow status in ACHE. Notably, organizational factors such as size, geographic location, for-profit status, and financial strength of the hospital do not seem to play an important role in the CEOs' decision to become a Member or Fellow of ACHE. The implication of these findings is that membership and fellowship at a professional association are influenced by characteristics of the individual, and incentives provided by employers can encourage employees to get involved with their professional associations.

Vitamin A and cancer prevention II: comparison of the effects of retinol and beta-carotene.

PubMed

de Klerk, N H; Musk, A W; Ambrosini, G L; Eccles, J L; Hansen, J; Olsen, N; Watts, V L; Lund, H G; Pang, S C; Beilby, J; Hobbs, M S

1998-01-30

Former blue asbestos workers known to be at high risk of asbestos-related diseases, particularly malignant mesothelioma and lung cancer, were enrolled in a chemo-prevention program using vitamin A. Our aims were to compare rates of disease and death in subjects randomly assigned to beta-carotene or retinol. Subjects were assigned randomly to take 30 mg/day beta-carotene (512 subjects) or 25,000 IU/day retinol (512 subjects) and followed up through death and cancer registries from the start of the study in June 1990 till May 1995. Comparison between groups was by Cox regression in both intention-to-treat analyses and efficacy analyses based on treatment actually taken. Median follow-up time was 232 weeks. Four cases of lung cancer and 3 cases of mesothelioma were observed in subjects randomised to retinol and 6 cases of lung cancer and 12 cases of mesothelioma in subjects randomised to beta-carotene. The relative rate of mesothelioma (the most common single cause of death in our study) for those on retinol compared with those on beta-carotene was 0.24 (95% CI 0.07-0.86). In the retinol group, there was also a significantly lower rate for death from all causes but a higher rate of ischaemic heart disease mortality. Similar results were found with efficacy analyses. Our results confirm other findings of a lack of any benefit from administration of large doses of synthetic beta-carotene. The finding of significantly lower rates of mesothelioma among subjects assigned to retinol requires further investigation.

Lower limb muscle strength is associated with poor balance in middle-aged women: linear and nonlinear analyses.

PubMed

Wu, F; Callisaya, M; Laslett, L L; Wills, K; Zhou, Y; Jones, G; Winzenberg, T

2016-07-01

This was the first study investigating both linear associations between lower limb muscle strength and balance in middle-aged women and the potential for thresholds for the associations. There was strong evidence that even in middle-aged women, poorer LMS was associated with reduced balance. However, no evidence was found for thresholds. Decline in balance begins in middle age, yet, the role of muscle strength in balance is rarely examined in this age group. We aimed to determine the association between lower limb muscle strength (LMS) and balance in middle-aged women and investigate whether cut-points of LMS exist that might identify women at risk of poorer balance. Cross-sectional analysis of 345 women aged 36-57 years was done. Associations between LMS and balance tests (timed up and go (TUG), step test (ST), functional reach test (FRT), and lateral reach test (LRT)) were assessed using linear regression. Nonlinear associations were explored using locally weighted regression smoothing (LOWESS) and potential cut-points identified using nonlinear least-squares estimation. Segmented regression was used to estimate associations above and below the identified cut-points. Weaker LMS was associated with poorer performance on the TUG (β -0.008 (95 % CI: -0.010, -0.005) second/kg), ST (β 0.031 (0.011, 0.051) step/kg), FRT (β 0.071 (0.047, 0.096) cm/kg), and LRT (β 0.028 (0.011, 0.044) cm/kg), independent of confounders. Potential nonlinear associations were evident from LOWESS results; significant cut-points of LMS were identified for all balance tests (29-50 kg). However, excepting ST, cut-points did not persist after excluding potentially influential data points. In middle-aged women, poorer LMS is associated with reduced balance. Therefore, improving muscle strength in middle-age may be a useful strategy to improve balance and reduce falls risk in later life. Middle-aged women with low muscle strength may be an effective target group for future randomized controlled trials. Australian New Zealand Clinical Trials Registry (ANZCTR) NCT00273260.

Respiratory effect of beta-blockers in people with asthma and cardiovascular disease: population-based nested case control study.

PubMed

Morales, Daniel R; Lipworth, Brian J; Donnan, Peter T; Jackson, Cathy; Guthrie, Bruce

2017-01-27

Cardiovascular disease (CVD) is a common comorbidity in people with asthma. However, safety concerns have caused heterogeneity in clinical guideline recommendations over the use of cardioselective beta-blockers in people with asthma and CVD, partly because risk in the general population has been poorly quantified. The aim of this study was to measure the risk of asthma exacerbations with beta-blockers prescribed to a general population with asthma and CVD. Linked data from the UK Clinical Practice Research Datalink was used to perform nested case-control studies among people with asthma and CVD matched on age, sex and calendar time. Adjusted incidence rate ratios (IRR) were calculated for the association between oral beta-blocker use and moderate asthma exacerbations (rescue oral steroids) or severe asthma exacerbations (hospitalisation or death) using conditional logistic regression. The cohort consisted of 35,502 people identified with active asthma and CVD, of which 14.1% and 1.2% were prescribed cardioselective and non-selective beta-blockers, respectively, during follow-up. Cardioselective beta-blocker use was not associated with a significantly increased risk of moderate or severe asthma exacerbations. Consistent results were obtained following sensitivity analyses and a self-controlled case series approach. In contrast, non-selective beta-blockers were associated with a significantly increased risk of moderate asthma exacerbations when initiated at low to moderate doses (IRR 5.16, 95% CI 1.83-14.54, P = 0.002), and both moderate and severe exacerbations when prescribed chronically at high dose (IRR 2.68, 95% CI 1.08-6.64, P = 0.033 and IRR 12.11, 95% CI 1.02-144.11, P = 0.048, respectively). Cardioselective beta-blockers prescribed to people with asthma and CVD were not associated with a significantly increased risk of moderate or severe asthma exacerbations and potentially could be used more widely when strongly indicated.

Footprint and imprint: an ecologic time-trend analysis of cardiovascular publications in general and specialty journals.

PubMed

Baldridge, Abigail S; Huffman, Mark D; Bloomfield, Gerald S; Prabhakaran, Dorairaj

2014-06-01

Studies have demonstrated strong associations between publication source and citations, as well as investigatory analysis of collaboration effects, in general and medical literature, but are limited to specific journals or short duration of time. This study sought to analyze time trends in cardiovascular research publications in leading general and specialty journals and to determine the association between collaboration and citation index. Cardiovascular publications were retrieved from Web of Knowledge by a cardiovascular bibliometric filter, and annual publication volumes in 8 general and specialty journals were compared. Univariable linear regression models were used to determine global and journal-specific trends for overall publication, cardiovascular publication, proportion of cardiovascular publication, collaboration, and citations. Cardiovascular publications increased (1999 to 2008) by 36% and number of sources by 74%. Volume increased in European Heart Journal (beta: 18.4, 95% confidence interval [CI]: 10.6 to 26.3) and decreased in Circulation (beta: -42.9, 95% CI: -79.3 to -6.5), Annals of Internal Medicine (beta: -1.9, 95% CI: -3.5 to -0.3), and Lancet (beta: -11.2, 95% CI: -14.7 to -7.8). Number of contributing countries increased in 3 journals: BMJ (beta: 0.8, 95% CI: 0.2 to 1.5), European Heart Journal (beta: -1.2, 95% CI: 0.8 to 1.7), and New England Journal of Medicine (beta: 1.6, 95% CI: 0.6 to 2.7). Fraction of collaborative publications increased (beta: 1.1 to 2.9) in all but Annals of Internal Medicine. Collaboration was associated with a higher median actual citation index (p < 0.0001). We found increasing trends in collaboration and citation in both general and specialty journals. Contribution by country in selected journals was disproportionate and under-represents total cardiovascular research in low- and middle-income countries. Copyright © 2014 World Heart Federation (Geneva). Published by Elsevier B.V. All rights reserved.

Beta2-adrenergic receptor genotype affects the renin-angiotensin-aldosterone system response to the Dietary Approaches to Stop Hypertension (DASH) dietary pattern.

PubMed

Sun, Bei; Williams, Jonathan S; Svetkey, Laura P; Kolatkar, Nikheel S; Conlin, Paul R

2010-08-01

Beta(2)-adrenergic receptor (beta2-AR) is a susceptibility locus for hypertension, and polymorphisms at this site relate to salt sensitivity and low plasma renin activity (PRA). The Dietary Approaches to Stop Hypertension (DASH) dietary pattern lowers blood pressure and appears to interact with the renin-angiotensin-aldosterone system (RAAS). We hypothesized that the DASH diet associates with increased RAAS activity, and genotype status at beta2-AR G46A modifies this response. We genotyped participants in the DASH-Sodium study (n = 372) at beta2-AR G46A to determine the association with blood pressure, RAAS components, and consumption of the DASH diet. We used 2-way mixed linear regression and an additive model for all primary analyses. Mean (+/-SEM) PRA was significantly higher in participants in the DASH group than in participants in the control group (0.68 +/- 0.03 compared with 0.54 +/- 0.03 ng x mL(-1) x h(-1), P = 0.002). Serum aldosterone, urinary aldosterone, and urinary potassium concentrations were also significantly higher in the DASH group (P < 0.01 for all). We observed significant gene-diet interactions for changes in systolic blood pressure (SBP) and concentrations of aldosterone and urinary potassium (P for interaction = 0.048, 0.017, and 0.001 for SBP and aldosterone and urinary potassium concentrations, respectively). There was an association between the A allele of beta2-AR G46A and greater blood pressure reduction and blunted aldosterone and PRA responses to the DASH diet. Our results indicate that the DASH diet lowers blood pressure and increases PRA and aldosterone concentrations. There is an association between the G46A polymorphism of beta2-AR and blood pressure and RAAS responses to the DASH diet, which suggests that beta2-AR may be a genetic modifier of DASH-diet responsiveness. This trial was registered at clinicaltrials.gov as NCT00000608.

Rhinal-hippocampal interactions during déjà vu.

PubMed

Bartolomei, Fabrice; Barbeau, Emmanuel J; Nguyen, Trung; McGonigal, Aileen; Régis, Jean; Chauvel, Patrick; Wendling, Fabrice

2012-03-01

The phenomenon of 'déjà vu' is caused by acute disturbance of mnemonic systems of the medial temporal lobe (MTL). In epileptic patients investigated with intracerebral electrodes, déjà vu can be more readily induced by stimulation of the rhinal cortices (RCs) than the hippocampus (H). Whether déjà vu results from acute dysfunction of the familiarity system alone (sustained by RC) or from more extensive involvement of the MTL region (including H) is debatable. We analysed the synchronisation of intracerebral electroencephalography (EEG) signals recorded from RC, H and amygdala (A) in epileptic patients in whom déjà vu was induced by electrical stimulation. EEG signal correlations (between signals from RC, A and H) were evaluated using a nonlinear regression. In comparison with RC stimulations that did not lead to déjà vu (DV-), stimulations triggering déjà vu (DV+) were associated with increased broadband EEG correlation (p=0.01). Changes in correlations were significantly different in the theta band for RC-A (p=0.007) and RC-H (p=0.01) and in the beta band for RC-H (p=0.001) interactions. Déjà vu is associated with increased EEG signal correlation between MTL structures. Results are in favour of a mechanism involving transient co-operation between various MTL structures, not limited to RC alone. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

A novel model incorporating two variability sources for describing motor evoked potentials

PubMed Central

Goetz, Stefan M.; Luber, Bruce; Lisanby, Sarah H.; Peterchev, Angel V.

2014-01-01

Objective Motor evoked potentials (MEPs) play a pivotal role in transcranial magnetic stimulation (TMS), e.g., for determining the motor threshold and probing cortical excitability. Sampled across the range of stimulation strengths, MEPs outline an input–output (IO) curve, which is often used to characterize the corticospinal tract. More detailed understanding of the signal generation and variability of MEPs would provide insight into the underlying physiology and aid correct statistical treatment of MEP data. Methods A novel regression model is tested using measured IO data of twelve subjects. The model splits MEP variability into two independent contributions, acting on both sides of a strong sigmoidal nonlinearity that represents neural recruitment. Traditional sigmoidal regression with a single variability source after the nonlinearity is used for comparison. Results The distribution of MEP amplitudes varied across different stimulation strengths, violating statistical assumptions in traditional regression models. In contrast to the conventional regression model, the dual variability source model better described the IO characteristics including phenomena such as changing distribution spread and skewness along the IO curve. Conclusions MEP variability is best described by two sources that most likely separate variability in the initial excitation process from effects occurring later on. The new model enables more accurate and sensitive estimation of the IO curve characteristics, enhancing its power as a detection tool, and may apply to other brain stimulation modalities. Furthermore, it extracts new information from the IO data concerning the neural variability—information that has previously been treated as noise. PMID:24794287

Elbow joint angle and elbow movement velocity estimation using NARX-multiple layer perceptron neural network model with surface EMG time domain parameters.

PubMed

Raj, Retheep; Sivanandan, K S

2017-01-01

Estimation of elbow dynamics has been the object of numerous investigations. In this work a solution is proposed for estimating elbow movement velocity and elbow joint angle from Surface Electromyography (SEMG) signals. Here the Surface Electromyography signals are acquired from the biceps brachii muscle of human hand. Two time-domain parameters, Integrated EMG (IEMG) and Zero Crossing (ZC), are extracted from the Surface Electromyography signal. The relationship between the time domain parameters, IEMG and ZC with elbow angular displacement and elbow angular velocity during extension and flexion of the elbow are studied. A multiple input-multiple output model is derived for identifying the kinematics of elbow. A Nonlinear Auto Regressive with eXogenous inputs (NARX) structure based multiple layer perceptron neural network (MLPNN) model is proposed for the estimation of elbow joint angle and elbow angular velocity. The proposed NARX MLPNN model is trained using Levenberg-marquardt based algorithm. The proposed model is estimating the elbow joint angle and elbow movement angular velocity with appreciable accuracy. The model is validated using regression coefficient value (R). The average regression coefficient value (R) obtained for elbow angular displacement prediction is 0.9641 and for the elbow anglular velocity prediction is 0.9347. The Nonlinear Auto Regressive with eXogenous inputs (NARX) structure based multiple layer perceptron neural networks (MLPNN) model can be used for the estimation of angular displacement and movement angular velocity of the elbow with good accuracy.