Optimal Fermentation Conditions of Hyaluronidase Inhibition Activity on Asparagus cochinchinensis Merrill by Weissella cibaria.

PubMed

Kim, Minji; Kim, Won-Baek; Koo, Kyoung Yoon; Kim, Bo Ram; Kim, Doohyun; Lee, Seoyoun; Son, Hong Joo; Hwang, Dae Youn; Kim, Dong Seob; Lee, Chung Yeoul; Lee, Heeseob

2017-04-28

This study was conducted to evaluate the hyaluronidase (HAase) inhibition activity of Asparagus cochinchinesis (AC) extracts following fermentation by Weissella cibaria through response surface methodology. To optimize the HAase inhibition activity, a central composite design was introduced based on four variables: the concentration of AC extract ( X 1 : 1-5%), amount of starter culture ( X 2 : 1-5%), pH ( X 3 : 4-8), and fermentation time ( X 4 : 0-10 days). The experimental data were fitted to quadratic regression equations, the accuracy of the equations was analyzed by ANOVA, and the regression coefficients for the surface quadratic model of HAase inhibition activity in the fermented AC extract were estimated by the F test and the corresponding p values. The HAase inhibition activity indicated that fermentation time was most significant among the parameters within the conditions tested. To validate the model, two different conditions among those generated by the Design Expert program were selected. Under both conditions, predicted and experimental data agreed well. Moreover, the content of protodioscin (a well-known compound related to anti-inflammation activity) was elevated after fermentation of the AC extract at the optimized fermentation condition.

Graphical Description of Johnson-Neyman Outcomes for Linear and Quadratic Regression Surfaces.

ERIC Educational Resources Information Center

Schafer, William D.; Wang, Yuh-Yin

A modification of the usual graphical representation of heterogeneous regressions is described that can aid in interpreting significant regions for linear or quadratic surfaces. The standard Johnson-Neyman graph is a bivariate plot with the criterion variable on the ordinate and the predictor variable on the abscissa. Regression surfaces are drawn…

An Unexpected Influence on a Quadratic

ERIC Educational Resources Information Center

Davis, Jon D.

2013-01-01

Using technology to explore the coefficients of a quadratic equation can lead to an unexpected result. This article describes an investigation that involves sliders and dynamically linked representations. It guides students to notice the effect that the parameter "a" has on the graphical representation of a quadratic function in the form…

Genome-wide association study on legendre random regression coefficients for the growth and feed intake trajectory on Duroc Boars.

PubMed

Howard, Jeremy T; Jiao, Shihui; Tiezzi, Francesco; Huang, Yijian; Gray, Kent A; Maltecca, Christian

2015-05-30

Feed intake and growth are economically important traits in swine production. Previous genome wide association studies (GWAS) have utilized average daily gain or daily feed intake to identify regions that impact growth and feed intake across time. The use of longitudinal models in GWAS studies, such as random regression, allows for SNPs having a heterogeneous effect across the trajectory to be characterized. The objective of this study is therefore to conduct a single step GWAS (ssGWAS) on the animal polynomial coefficients for feed intake and growth. Corrected daily feed intake (DFI Adj) and average daily weight measurements (DBW Avg) on 8981 (n=525,240 observations) and 5643 (n=283,607 observations) animals were utilized in a random regression model using Legendre polynomials (order=2) and a relationship matrix that included genotyped and un-genotyped animals. A ssGWAS was conducted on the animal polynomials coefficients (intercept, linear and quadratic) for animals with genotypes (DFIAdj: n=855; DBWAvg: n=590). Regions were characterized based on the variance of 10-SNP sliding windows GEBV (WGEBV). A bootstrap analysis (n=1000) was conducted to declare significance. Heritability estimates for the traits trajectory ranged from 0.34-0.52 to 0.07-0.23 for DBWAvg and DFIAdj, respectively. Genetic correlations across age classes were large and positive for both DBWAvg and DFIAdj, albeit age classes at the beginning had a small to moderate genetic correlation with age classes towards the end of the trajectory for both traits. The WGEBV variance explained by significant regions (P<0.001) for each polynomial coefficient ranged from 0.2-0.9 to 0.3-1.01% for DBWAvg and DFIAdj, respectively. The WGEBV variance explained by significant regions for the trajectory was 1.54 and 1.95% for DBWAvg and DFIAdj. Both traits identified candidate genes with functions related to metabolite and energy homeostasis, glucose and insulin signaling and behavior. We have identified regions of the genome that have an impact on the intercept, linear and quadratic terms for DBWAvg and DFIAdj. These results provide preliminary evidence that individual growth and feed intake trajectories are impacted by different regions of the genome at different times.

Visualising the Complex Roots of Quadratic Equations with Real Coefficients

ERIC Educational Resources Information Center

Bardell, Nicholas S.

2012-01-01

The roots of the general quadratic equation y = ax[superscript 2] + bx + c (real a, b, c) are known to occur in the following sets: (i) real and distinct; (ii) real and coincident; and (iii) a complex conjugate pair. Case (iii), which provides the focus for this investigation, can only occur when the values of the real coefficients a, b, and c are…

Design of an all-optical fractional-order differentiator with terahertz bandwidth based on a fiber Bragg grating in transmission.

PubMed

Liu, Xin; Shu, Xuewen

2017-08-20

All-optical fractional-order temporal differentiators with bandwidths reaching terahertz (THz) values are demonstrated with transmissive fiber Bragg gratings. Since the designed fractional-order differentiator is a minimum phase function, the reflective phase of the designed function can be chosen arbitrarily. As examples, we first design several 0.5th-order differentiators with bandwidths reaching the THz range for comparison. The reflective phases of the 0.5th-order differentiators are chosen to be linear phase, quadratic phase, cubic phase, and biquadratic phase, respectively. We find that both the maximum coupling coefficient and the spatial resolution of the designed grating increase when the reflective phase varies from quadratic function to cubic function to biquadratic function. Furthermore, when the reflective phase is chosen to be a quadratic function, the obtained grating coupling coefficient and period are more likely to be achieved in practice. Then we design fractional-order differentiators with different orders when the reflective phase is chosen to be a quadratic function. We see that when the designed order of the differentiator increases, the obtained maximum coupling coefficient also increases while the oscillation of the coupling coefficient decreases. Finally, we give the numerical performance of the designed 0.5th-order differentiator by showing its temporal response and calculating its cross-correlation coefficient.

The effects of five-order nonlinear on the dynamics of dark solitons in optical fiber.

PubMed

He, Feng-Tao; Wang, Xiao-Lin; Duan, Zuo-Liang

2013-01-01

We study the influence of five-order nonlinear on the dynamic of dark soliton. Starting from the cubic-quintic nonlinear Schrodinger equation with the quadratic phase chirp term, by using a similarity transformation technique, we give the exact solution of dark soliton and calculate the precise expressions of dark soliton's width, amplitude, wave central position, and wave velocity which can describe the dynamic behavior of soliton's evolution. From two different kinds of quadratic phase chirps, we mainly analyze the effect on dark soliton's dynamics which different fiver-order nonlinear term generates. The results show the following two points with quintic nonlinearities coefficient increasing: (1) if the coefficients of the quadratic phase chirp term relate to the propagation distance, the solitary wave displays a periodic change and the soliton's width increases, while its amplitude and wave velocity reduce. (2) If the coefficients of the quadratic phase chirp term do not depend on propagation distance, the wave function only emerges in a fixed area. The soliton's width increases, while its amplitude and the wave velocity reduce.

The Effects of Five-Order Nonlinear on the Dynamics of Dark Solitons in Optical Fiber

PubMed Central

Wang, Xiao-Lin; Duan, Zuo-Liang

2013-01-01

We study the influence of five-order nonlinear on the dynamic of dark soliton. Starting from the cubic-quintic nonlinear Schrodinger equation with the quadratic phase chirp term, by using a similarity transformation technique, we give the exact solution of dark soliton and calculate the precise expressions of dark soliton's width, amplitude, wave central position, and wave velocity which can describe the dynamic behavior of soliton's evolution. From two different kinds of quadratic phase chirps, we mainly analyze the effect on dark soliton's dynamics which different fiver-order nonlinear term generates. The results show the following two points with quintic nonlinearities coefficient increasing: (1) if the coefficients of the quadratic phase chirp term relate to the propagation distance, the solitary wave displays a periodic change and the soliton's width increases, while its amplitude and wave velocity reduce. (2) If the coefficients of the quadratic phase chirp term do not depend on propagation distance, the wave function only emerges in a fixed area. The soliton's width increases, while its amplitude and the wave velocity reduce. PMID:23818814

Some Comments on the Use of de Moivre's Theorem to Solve Quadratic Equations with Real or Complex Coefficients

ERIC Educational Resources Information Center

Bardell, Nicholas S.

2014-01-01

This paper describes how a simple application of de Moivre's theorem may be used to not only find the roots of a quadratic equation with real or generally complex coefficients but also to pinpoint their location in the Argand plane. This approach is much simpler than the comprehensive analysis presented by Bardell (2012, 2014), but it does not…

On Vieta's Formulas and the Determination of a Set of Positive Integers by Their Sum and Product

ERIC Educational Resources Information Center

Valahas, Theodoros; Boukas, Andreas

2011-01-01

In Years 9 and 10 of secondary schooling students are typically introduced to quadratic expressions and functions and related modelling, algebra, and graphing. This includes work on the expansion and factorisation of quadratic expressions (typically with integer values of coefficients), graphing quadratic functions, finding the roots of quadratic…

Growth of finiteness in the third year of life: replication and predictive validity.

PubMed

Hadley, Pamela A; Rispoli, Matthew; Holt, Janet K; Fitzgerald, Colleen; Bahnsen, Alison

2014-06-01

The authors of this study investigated the validity of tense and agreement productivity (TAP) scoring in diverse sentence frames obtained during conversational language sampling as an alternative measure of finiteness for use with young children. Longitudinal language samples were used to model TAP growth from 21 to 30 months of age for 37 typically developing toddlers. Empirical Bayes (EB) linear and quadratic growth coefficients and child sex were then used to predict elicited grammar composite scores on the Test of Early Grammatical Impairment (TEGI; Rice & Wexler, 2001) at 36 months. A random-effects quadratic model with no intercept best characterized TAP growth, replicating the findings of Rispoli, Hadley, and Holt (2009). The combined regression model was significant, with the 3 variables accounting for 55.5% of the variance in the TEGI composite scores. These findings establish TAP growth as a valid metric of finiteness in the 3rd year of life. Developmental and theoretical implications are discussed.

Analysis of a Split-Plot Experimental Design Applied to a Low-Speed Wind Tunnel Investigation

NASA Technical Reports Server (NTRS)

Erickson, Gary E.

2013-01-01

A procedure to analyze a split-plot experimental design featuring two input factors, two levels of randomization, and two error structures in a low-speed wind tunnel investigation of a small-scale model of a fighter airplane configuration is described in this report. Standard commercially-available statistical software was used to analyze the test results obtained in a randomization-restricted environment often encountered in wind tunnel testing. The input factors were differential horizontal stabilizer incidence and the angle of attack. The response variables were the aerodynamic coefficients of lift, drag, and pitching moment. Using split-plot terminology, the whole plot, or difficult-to-change, factor was the differential horizontal stabilizer incidence, and the subplot, or easy-to-change, factor was the angle of attack. The whole plot and subplot factors were both tested at three levels. Degrees of freedom for the whole plot error were provided by replication in the form of three blocks, or replicates, which were intended to simulate three consecutive days of wind tunnel facility operation. The analysis was conducted in three stages, which yielded the estimated mean squares, multiple regression function coefficients, and corresponding tests of significance for all individual terms at the whole plot and subplot levels for the three aerodynamic response variables. The estimated regression functions included main effects and two-factor interaction for the lift coefficient, main effects, two-factor interaction, and quadratic effects for the drag coefficient, and only main effects for the pitching moment coefficient.

Age and mortality after injury: is the association linear?

PubMed

Friese, R S; Wynne, J; Joseph, B; Hashmi, A; Diven, C; Pandit, V; O'Keeffe, T; Zangbar, B; Kulvatunyou, N; Rhee, P

2014-10-01

Multiple studies have demonstrated a linear association between advancing age and mortality after injury. An inflection point, or an age at which outcomes begin to differ, has not been previously described. We hypothesized that the relationship between age and mortality after injury is non-linear and an inflection point exists. We performed a retrospective cohort analysis at our urban level I center from 2007 through 2009. All patients aged 65 years and older with the admission diagnosis of injury were included. Non-parametric logistic regression was used to identify the functional form between mortality and age. Multivariate logistic regression was utilized to explore the association between age and mortality. Age 65 years was used as the reference. Significance was defined as p < 0.05. A total of 1,107 patients were included in the analysis. One-third required intensive care unit (ICU) admission and 48 % had traumatic brain injury. 229 patients (20.6 %) were 84 years of age or older. The overall mortality was 7.2 %. Our model indicates that mortality is a quadratic function of age. After controlling for confounders, age is associated with mortality with a regression coefficient of 1.08 for the linear term (p = 0.02) and a regression coefficient of -0.006 for the quadratic term (p = 0.03). The model identified 84.4 years of age as the inflection point at which mortality rates begin to decline. The risk of death after injury varies linearly with age until 84 years. After 84 years of age, the mortality rates decline. These findings may reflect the varying severity of comorbidities and differences in baseline functional status in elderly trauma patients. Specifically, a proportion of our injured patient population less than 84 years old may be more frail, contributing to increased mortality after trauma, whereas a larger proportion of our injured patients over 84 years old, by virtue of reaching this advanced age, may, in fact, be less frail, contributing to less risk of death.

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…

Validation of drift and diffusion coefficients from experimental data

NASA Astrophysics Data System (ADS)

Riera, R.; Anteneodo, C.

2010-04-01

Many fluctuation phenomena, in physics and other fields, can be modeled by Fokker-Planck or stochastic differential equations whose coefficients, associated with drift and diffusion components, may be estimated directly from the observed time series. Its correct characterization is crucial to determine the system quantifiers. However, due to the finite sampling rates of real data, the empirical estimates may significantly differ from their true functional forms. In the literature, low-order corrections, or even no corrections, have been applied to the finite-time estimates. A frequent outcome consists of linear drift and quadratic diffusion coefficients. For this case, exact corrections have been recently found, from Itô-Taylor expansions. Nevertheless, model validation constitutes a necessary step before determining and applying the appropriate corrections. Here, we exploit the consequences of the exact theoretical results obtained for the linear-quadratic model. In particular, we discuss whether the observed finite-time estimates are actually a manifestation of that model. The relevance of this analysis is put into evidence by its application to two contrasting real data examples in which finite-time linear drift and quadratic diffusion coefficients are observed. In one case the linear-quadratic model is readily rejected while in the other, although the model constitutes a very good approximation, low-order corrections are inappropriate. These examples give warning signs about the proper interpretation of finite-time analysis even in more general diffusion processes.

A Maximum Likelihood Approach to Determine Sensor Radiometric Response Coefficients for NPP VIIRS Reflective Solar Bands

NASA Technical Reports Server (NTRS)

Lei, Ning; Chiang, Kwo-Fu; Oudrari, Hassan; Xiong, Xiaoxiong

2011-01-01

Optical sensors aboard Earth orbiting satellites such as the next generation Visible/Infrared Imager/Radiometer Suite (VIIRS) assume that the sensors radiometric response in the Reflective Solar Bands (RSB) is described by a quadratic polynomial, in relating the aperture spectral radiance to the sensor Digital Number (DN) readout. For VIIRS Flight Unit 1, the coefficients are to be determined before launch by an attenuation method, although the linear coefficient will be further determined on-orbit through observing the Solar Diffuser. In determining the quadratic polynomial coefficients by the attenuation method, a Maximum Likelihood approach is applied in carrying out the least-squares procedure. Crucial to the Maximum Likelihood least-squares procedure is the computation of the weight. The weight not only has a contribution from the noise of the sensor s digital count, with an important contribution from digitization error, but also is affected heavily by the mathematical expression used to predict the value of the dependent variable, because both the independent and the dependent variables contain random noise. In addition, model errors have a major impact on the uncertainties of the coefficients. The Maximum Likelihood approach demonstrates the inadequacy of the attenuation method model with a quadratic polynomial for the retrieved spectral radiance. We show that using the inadequate model dramatically increases the uncertainties of the coefficients. We compute the coefficient values and their uncertainties, considering both measurement and model errors.

Normative biometrics for fetal ocular growth using volumetric MRI reconstruction.

PubMed

Velasco-Annis, Clemente; Gholipour, Ali; Afacan, Onur; Prabhu, Sanjay P; Estroff, Judy A; Warfield, Simon K

2015-04-01

To determine normative ranges for fetal ocular biometrics between 19 and 38 weeks gestational age (GA) using volumetric MRI reconstruction. The 3D images of 114 healthy fetuses between 19 and 38 weeks GA were created using super-resolution volume reconstructions from MRI slice acquisitions. These 3D images were semi-automatically segmented to measure fetal orbit volume, binocular distance (BOD), interocular distance (IOD), and ocular diameter (OD). All biometry correlated with GA (Volume, Pearson's correlation coefficient (CC) = 0.9680; BOD, CC = 0.9552; OD, CC = 0.9445; and IOD, CC = 0.8429), and growth curves were plotted against linear and quadratic growth models. Regression analysis showed quadratic models to best fit BOD, IOD, and OD and a linear model to best fit volume. Orbital volume had the greatest correlation with GA, although BOD and OD also showed strong correlation. The normative data found in this study may be helpful for the detection of congenital fetal anomalies with more consistent measurements than are currently available. © 2015 John Wiley & Sons, Ltd. © 2015 John Wiley & Sons, Ltd.

Quadratic forms involving Green's and Robin functions

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

Dubinin, Vladimir N

2009-10-31

General inequalities for quadratic forms with coefficients depending on the values of Green's and Robin functions are obtained. These inequalities cover also the reduced moduli of strips and half-strips. Some applications of the results obtained to extremal partitioning problems and related questions of geometric function theory are discussed. Bibliography: 29 titles.

A quadratic regression modelling on paddy production in the area of Perlis

NASA Astrophysics Data System (ADS)

Goh, Aizat Hanis Annas; Ali, Zalila; Nor, Norlida Mohd; Baharum, Adam; Ahmad, Wan Muhamad Amir W.

2017-08-01

Polynomial regression models are useful in situations in which the relationship between a response variable and predictor variables is curvilinear. Polynomial regression fits the nonlinear relationship into a least squares linear regression model by decomposing the predictor variables into a kth order polynomial. The polynomial order determines the number of inflexions on the curvilinear fitted line. A second order polynomial forms a quadratic expression (parabolic curve) with either a single maximum or minimum, a third order polynomial forms a cubic expression with both a relative maximum and a minimum. This study used paddy data in the area of Perlis to model paddy production based on paddy cultivation characteristics and environmental characteristics. The results indicated that a quadratic regression model best fits the data and paddy production is affected by urea fertilizer application and the interaction between amount of average rainfall and percentage of area defected by pest and disease. Urea fertilizer application has a quadratic effect in the model which indicated that if the number of days of urea fertilizer application increased, paddy production is expected to decrease until it achieved a minimum value and paddy production is expected to increase at higher number of days of urea application. The decrease in paddy production with an increased in rainfall is greater, the higher the percentage of area defected by pest and disease.

Integration of the Quadratic Function and Generalization

ERIC Educational Resources Information Center

Mitsuma, Kunio

2011-01-01

We will first recall useful formulas in integration that simplify the calculation of certain definite integrals with the quadratic function. A main formula relies only on the coefficients of the function. We will then explore a geometric proof of one of these formulas. Finally, we will extend the formulas to more general cases. (Contains 3…

Genetic parameters for stayability to consecutive calvings in Zebu cattle.

PubMed

Silva, D O; Santana, M L; Ayres, D R; Menezes, G R O; Silva, L O C; Nobre, P R C; Pereira, R J

2017-12-22

Longer-lived cows tend to be more profitable and the stayability trait is a selection criterion correlated to longevity. An alternative to the traditional approach to evaluate stayability is its definition based on consecutive calvings, whose main advantage is the more accurate evaluation of young bulls. However, no study using this alternative approach has been conducted for Zebu breeds. Therefore, the objective of this study was to compare linear random regression models to fit stayability to consecutive calvings of Guzerá, Nelore and Tabapuã cows and to estimate genetic parameters for this trait in the respective breeds. Data up to the eighth calving were used. The models included the fixed effects of age at first calving and year-season of birth of the cow and the random effects of contemporary group, additive genetic, permanent environmental and residual. Random regressions were modeled by orthogonal Legendre polynomials of order 1 to 4 (2 to 5 coefficients) for contemporary group, additive genetic and permanent environmental effects. Using Deviance Information Criterion as the selection criterion, the model with 4 regression coefficients for each effect was the most adequate for the Nelore and Tabapuã breeds and the model with 5 coefficients is recommended for the Guzerá breed. For Guzerá, heritabilities ranged from 0.05 to 0.08, showing a quadratic trend with a peak between the fourth and sixth calving. For the Nelore and Tabapuã breeds, the estimates ranged from 0.03 to 0.07 and from 0.03 to 0.08, respectively, and increased with increasing calving number. The additive genetic correlations exhibited a similar trend among breeds and were higher for stayability between closer calvings. Even between more distant calvings (second v. eighth), stayability showed a moderate to high genetic correlation, which was 0.77, 0.57 and 0.79 for the Guzerá, Nelore and Tabapuã breeds, respectively. For Guzerá, when the models with 4 or 5 regression coefficients were compared, the rank correlations between predicted breeding values for the intercept were always higher than 0.99, indicating the possibility of practical application of the least parameterized model. In conclusion, the model with 4 random regression coefficients is recommended for the genetic evaluation of stayability to consecutive calvings in Zebu cattle.

Nonlinear response from transport theory and quantum field theory at finite temperature

NASA Astrophysics Data System (ADS)

Carrington, M. E.; Defu, Hou; Kobes, R.

2001-07-01

We study the nonlinear response in weakly coupled hot φ4 theory. We obtain an expression for a quadratic shear viscous response coefficient using two different formalisms: transport theory and response theory. The transport theory calculation is done by assuming a local equilibrium form for the distribution function and expanding in the gradient of the local four dimensional velocity field. By performing a Chapman-Enskog expansion on the Boltzmann equation we obtain a hierarchy of equations for the coefficients of the expanded distribution function. To do the response theory calculation we use Zubarev's techniques in nonequilibrium statistical mechanics to derive a generalized Kubo formula. Using this formula allows us to obtain the quadratic shear viscous response from the three-point retarded Green function of the viscous shear stress tensor. We use the closed time path formalism of real time finite temperature field theory to show that this three-point function can be calculated by writing it as an integral equation involving a four-point vertex. This four-point vertex can in turn be obtained from an integral equation which represents the resummation of an infinite series of ladder and extended-ladder diagrams. The connection between transport theory and response theory is made when we show that the integral equation for this four-point vertex has exactly the same form as the equation obtained from the Boltzmann equation for the coefficient of the quadratic term of the gradient expansion of the distribution function. We conclude that calculating the quadratic shear viscous response using transport theory and keeping terms that are quadratic in the gradient of the velocity field in the Chapman-Enskog expansion of the Boltzmann equation is equivalent to calculating the quadratic shear viscous response from response theory using the next-to-linear response Kubo formula, with a vertex given by an infinite resummation of ladder and extended-ladder diagrams.

OPTOELECTRONICS, FIBER OPTICS, AND OTHER ASPECTS OF QUANTUM ELECTRONICS: Influence of the Rayleigh backscattering on the mode composition of radiation in multimode graded-index waveguides with a quadratic refractive-index profile

NASA Astrophysics Data System (ADS)

Esayan, G. L.; Krivoshlykov, S. G.

1989-08-01

A method of coherent states is used to describe the process of Rayleigh scattering in a multimode graded-index waveguide with a quadratic refractive-index profile. Explicit expressions are obtained for the coefficients representing excitation of Gaussian-Hermite backscattering modes in two cases of practical importance: excitation of a waveguide by an extended noncoherent light source and selective excitation of different modes at the entry to a waveguide. An analysis is also made of the coefficients of coupling between forward and backward modes. Explicit expressions for the coefficients representing capture of backscattered radiation by a waveguide are obtained for two special cases of excitation (extended light source and zeroth mode).

Optimization of cascade blade mistuning. I - Equations of motion and basic inherent properties

NASA Technical Reports Server (NTRS)

Nissim, E.

1985-01-01

Attention is given to the derivation of the equations of motion of mistuned compressor blades, interpolating aerodynamic coefficients by means of quadratic expressions in the reduced frequency. If the coefficients of the quadratic expressions are permitted to assume complex values, excellent accuracy is obtained and Pade rational expressions are obviated. On the basis of the resulting equations, it is shown analytically that the sum of all the real parts of the eigenvalues is independent of the mistuning introduced into the system. Blade mistuning is further treated through the aerodynamic energy approach, and the limiting vibration modes associated with alternative mistunings are identified.

Estimating chlorophyll content of spartina alterniflora at leaf level using hyper-spectral data

NASA Astrophysics Data System (ADS)

Wang, Jiapeng; Shi, Runhe; Liu, Pudong; Zhang, Chao; Chen, Maosi

2017-09-01

Spartina alterniflora, one of most successful invasive species in the world, was firstly introduced to China in 1979 to accelerate sedimentation and land formation via so-called "ecological engineering", and it is now widely distributed in coastal saltmarshes in China. A key question is how to retrieve chlorophyll content to reflect growth status, which has important implication of potential invasiveness. In this work, an estimation model of chlorophyll content of S. alterniflora was developed based on hyper-spectral data in the Dongtan Wetland, Yangtze Estuary, China. The spectral reflectance of S. alterniflora leaves and their corresponding chlorophyll contents were measured, and then the correlation analysis and regression (i.e., linear, logarithmic, quadratic, power and exponential regression) method were established. The spectral reflectance was transformed and the feature parameters (i.e., "san bian", "lv feng" and "hong gu") were extracted to retrieve the chlorophyll content of S. alterniflora . The results showed that these parameters had a large correlation coefficient with chlorophyll content. On the basis of the correlation coefficient, mathematical models were established, and the models of power and exponential based on SDb had the least RMSE and larger R2 , which had a good performance regarding the inversion of chlorophyll content of S. alterniflora.

Assessing Spurious Interaction Effects in Structural Equation Modeling

ERIC Educational Resources Information Center

Harring, Jeffrey R.; Weiss, Brandi A.; Li, Ming

2015-01-01

Several studies have stressed the importance of simultaneously estimating interaction and quadratic effects in multiple regression analyses, even if theory only suggests an interaction effect should be present. Specifically, past studies suggested that failing to simultaneously include quadratic effects when testing for interaction effects could…

Weight Vector Fluctuations in Adaptive Antenna Arrays Tuned Using the Least-Mean-Square Error Algorithm with Quadratic Constraint

NASA Astrophysics Data System (ADS)

Zimina, S. V.

2015-06-01

We present the results of statistical analysis of an adaptive antenna array tuned using the least-mean-square error algorithm with quadratic constraint on the useful-signal amplification with allowance for the weight-coefficient fluctuations. Using the perturbation theory, the expressions for the correlation function and power of the output signal of the adaptive antenna array, as well as the formula for the weight-vector covariance matrix are obtained in the first approximation. The fluctuations are shown to lead to the signal distortions at the antenna-array output. The weight-coefficient fluctuations result in the appearance of additional terms in the statistical characteristics of the antenna array. It is also shown that the weight-vector fluctuations are isotropic, i.e., identical in all directions of the weight-coefficient space.

Iterative method for in situ measurement of lens aberrations in lithographic tools using CTC-based quadratic aberration model.

PubMed

Liu, Shiyuan; Xu, Shuang; Wu, Xiaofei; Liu, Wei

2012-06-18

This paper proposes an iterative method for in situ lens aberration measurement in lithographic tools based on a quadratic aberration model (QAM) that is a natural extension of the linear model formed by taking into account interactions among individual Zernike coefficients. By introducing a generalized operator named cross triple correlation (CTC), the quadratic model can be calculated very quickly and accurately with the help of fast Fourier transform (FFT). The Zernike coefficients up to the 37th order or even higher are determined by solving an inverse problem through an iterative procedure from several through-focus aerial images of a specially designed mask pattern. The simulation work has validated the theoretical derivation and confirms that such a method is simple to implement and yields a superior quality of wavefront estimate, particularly for the case when the aberrations are relatively large. It is fully expected that this method will provide a useful practical means for the in-line monitoring of the imaging quality of lithographic tools.

Application of stochastic particle swarm optimization algorithm to determine the graded refractive index distribution in participating media

NASA Astrophysics Data System (ADS)

Wei, Lin-Yang; Qi, Hong; Ren, Ya-Tao; Ruan, Li-Ming

2016-11-01

Inverse estimation of the refractive index distribution in one-dimensional participating media with graded refractive index (GRI) is investigated. The forward radiative transfer problem is solved by the Chebyshev collocation spectral method. The stochastic particle swarm optimization (SPSO) algorithm is employed to retrieve three kinds of GRI distribution, i.e. the linear, sinusoidal and quadratic GRI distribution. The retrieval accuracy of GRI distribution with different wall emissivity, optical thickness, absorption coefficients and scattering coefficients are discussed thoroughly. To improve the retrieval accuracy of quadratic GRI distribution, a double-layer model is proposed to supply more measurement information. The influence of measurement errors upon the precision of estimated results is also investigated. Considering the GRI distribution is unknown beforehand in practice, a quadratic function is employed to retrieve the linear GRI by SPSO algorithm. All the results show that the SPSO algorithm is applicable to retrieve different GRI distributions in participating media accurately even with noisy data.

Understanding a Nonlinear Causal Relationship Between Rewards and Physicians' Contributions in Online Health Care Communities: Longitudinal Study.

PubMed

Wang, Jying-Nan; Chiu, Ya-Ling; Yu, Haiyan; Hsu, Yuan-Teng

2017-12-21

The online health care community is not just a place for the public to share physician reviews or medical knowledge, but also a physician-patient communication platform. The medical resources of developing countries are relatively inadequate, and the online health care community is a potential solution to alleviate the phenomenon of long hospital queues and the lack of medical resources in rural areas. However, the success of the online health care community depends on online contributions by physicians. The aim of this study is to examine the effect of incentive mechanisms on physician's online contribution behavior in the online health community. We addressed the following questions: (1) from which specialty area are physicians more likely to participate in online health care community activities, (2) what are the factors affecting physician online contributions, and (3) do incentive mechanisms, including psychological and material rewards, result in differences of physician online contributions? We designed a longitudinal study involving a data sample in three waves. All data were collected from the Good Doctor website, which is the largest online health care community in China. We first used descriptive statistics to investigate the physician online contribution behavior in its entirety. Then multiple linear and quadratic regression models were applied to verify the causal relationship between rewards and physician online contribution. Our sample included 40,300 physicians from 3607 different hospitals, 10 different major specialty areas, and 31 different provinces or municipalities. Based on the multiple quadratic regression model, we found that the coefficients of the control variables, past physician online contributions, doctor review rating, clinic title, hospital level, and city level, were .415, .189, -.099, -.106, and -.143, respectively. For the psychological (or material) rewards, the standardized coefficient of the main effect was 0.261 (or 0.688) and the standardized coefficient of the quadratic effect was -0.015 (or -0.049). All estimates were statistically significant (P<.001). Physicians with more past physician online contribution, with higher review ratings, coming from lower level clinics, not coming from tertiary hospitals, and not coming from big cities were more willing to participate in online health care community activities. To promote physician online contribution, it is necessary to establish an appropriate incentive mechanism including psychological and material rewards. Finally, our findings suggest two guidelines for designing a useful incentive mechanism to facilitate physician online contribution. First, material reward is more useful than psychological reward. Second, as indicated by the concave-down-increasing causal relationship between rewards and physician online contribution, although an appropriate reward is effective in encouraging willingness on the part of physicians to contribute to the online health care community, the effect of additional rewards is limited. ©Jying-Nan Wang, Ya-Ling Chiu, Haiyan Yu, Yuan-Teng Hsu. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 21.12.2017.

Understanding a Nonlinear Causal Relationship Between Rewards and Physicians’ Contributions in Online Health Care Communities: Longitudinal Study

PubMed Central

2017-01-01

Background The online health care community is not just a place for the public to share physician reviews or medical knowledge, but also a physician-patient communication platform. The medical resources of developing countries are relatively inadequate, and the online health care community is a potential solution to alleviate the phenomenon of long hospital queues and the lack of medical resources in rural areas. However, the success of the online health care community depends on online contributions by physicians. Objective The aim of this study is to examine the effect of incentive mechanisms on physician’s online contribution behavior in the online health community. We addressed the following questions: (1) from which specialty area are physicians more likely to participate in online health care community activities, (2) what are the factors affecting physician online contributions, and (3) do incentive mechanisms, including psychological and material rewards, result in differences of physician online contributions? Methods We designed a longitudinal study involving a data sample in three waves. All data were collected from the Good Doctor website, which is the largest online health care community in China. We first used descriptive statistics to investigate the physician online contribution behavior in its entirety. Then multiple linear and quadratic regression models were applied to verify the causal relationship between rewards and physician online contribution. Results Our sample included 40,300 physicians from 3607 different hospitals, 10 different major specialty areas, and 31 different provinces or municipalities. Based on the multiple quadratic regression model, we found that the coefficients of the control variables, past physician online contributions, doctor review rating, clinic title, hospital level, and city level, were .415, .189, –.099, –.106, and –.143, respectively. For the psychological (or material) rewards, the standardized coefficient of the main effect was 0.261 (or 0.688) and the standardized coefficient of the quadratic effect was –0.015 (or –0.049). All estimates were statistically significant (P<.001). Conclusions Physicians with more past physician online contribution, with higher review ratings, coming from lower level clinics, not coming from tertiary hospitals, and not coming from big cities were more willing to participate in online health care community activities. To promote physician online contribution, it is necessary to establish an appropriate incentive mechanism including psychological and material rewards. Finally, our findings suggest two guidelines for designing a useful incentive mechanism to facilitate physician online contribution. First, material reward is more useful than psychological reward. Second, as indicated by the concave-down-increasing causal relationship between rewards and physician online contribution, although an appropriate reward is effective in encouraging willingness on the part of physicians to contribute to the online health care community, the effect of additional rewards is limited. PMID:29269344

Kinematic parameters of internal waves of the second mode in the South China Sea

NASA Astrophysics Data System (ADS)

Kurkina, Oxana; Talipova, Tatyana; Soomere, Tarmo; Giniyatullin, Ayrat; Kurkin, Andrey

2017-10-01

Spatial distributions of the main properties of the mode function and kinematic and non-linear parameters of internal waves of the second mode are derived for the South China Sea for typical summer conditions in July. The calculations are based on the Generalized Digital Environmental Model (GDEM) climatology of hydrological variables, from which the local stratification is evaluated. The focus is on the phase speed of long internal waves and the coefficients at the dispersive, quadratic and cubic terms of the weakly non-linear Gardner model. Spatial distributions of these parameters, except for the coefficient at the cubic term, are qualitatively similar for waves of both modes. The dispersive term of Gardner's equation and phase speed for internal waves of the second mode are about a quarter and half, respectively, of those for waves of the first mode. Similarly to the waves of the first mode, the coefficients at the quadratic and cubic terms of Gardner's equation are practically independent of water depth. In contrast to the waves of the first mode, for waves of the second mode the quadratic term is mostly negative. The results can serve as a basis for expressing estimates of the expected parameters of internal waves for the South China Sea.

Issues in the digital implementation of control compensators. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Moroney, P.

1979-01-01

Techniques developed for the finite-precision implementation of digital filters were used, adapted, and extended for digital feedback compensators, with particular emphasis on steady state, linear-quadratic-Gaussian compensators. Topics covered include: (1) the linear-quadratic-Gaussian problem; (2) compensator structures; (3) architectural issues: serialism, parallelism, and pipelining; (4) finite wordlength effects: quantization noise, quantizing the coefficients, and limit cycles; and (5) the optimization of structures.

Random vibrations of quadratic damping systems. [optimum damping analysis for automobile suspension system

NASA Technical Reports Server (NTRS)

Sireteanu, T.

1974-01-01

An oscillating system with quadratic damping subjected to white noise excitation is replaced by a nonlinear, statistically equivalent system for which the associated Fokker-Planck equation can be exactly solved. The mean square responses are calculated and the optimum damping coefficient is determined with respect to the minimum mean square acceleration criteria. An application of these results to the optimization of automobile suspension damping is given.

Solid-state reversible quadratic nonlinear optical molecular switch with an exceptionally large contrast.

PubMed

Sun, Zhihua; Luo, Junhua; Zhang, Shuquan; Ji, Chengmin; Zhou, Lei; Li, Shenhui; Deng, Feng; Hong, Maochun

2013-08-14

Exceptional nonlinear optical (NLO) switching behavior, including an extremely large contrast (on/off) of ∼35 and high NLO coefficients, is displayed by a solid-state reversible quadratic NLO switch. The favorable results, induced by very fast molecular motion and anionic ordering, provides impetus for the design of a novel second-harmonic-generation switch involving molecular motion. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization of resistant starch formation from high amylose corn starch by microwave irradiation treatments and characterization of starch preparations.

PubMed

Mutlu, Selime; Kahraman, Kevser; Öztürk, Serpil

2017-02-01

The effects of microwave irradiation on resistant starch (RS) formation and functional properties in high-amylose corn starch, Hylon VII, by applying microwave-storing cycles and drying processes were investigated. The Response Surface Methodology (RSM) was used to optimize the reaction conditions, microwave time (2-4min) and power (20-100%), for RS formation. The starch:water (1:10) mixtures were cooked and autoclaved and then different microwave-storing cycles and drying (oven or freeze drying) processes were applied. The RS contents of the samples increased with increasing microwave-storing cycle. The highest RS (43.4%) was obtained by oven drying after 3 cycles of microwave treatment at 20% power for 2min. The F, p (<0.05) and R 2 values indicated that the selected models were consistent. Linear equations were obtained for oven-dried samples applied by 1 and 3 cycles of microwave with regression coefficients of 0.65 and 0.62, respectively. Quadratic equation was obtained for freeze-dried samples applied by 3 cycles of microwave with a regression coefficient of 0.83. The solubility, water binding capacity (WBC) and RVA viscosity values of the microwave applied samples were higher than those of native Hylon VII. The WBC and viscosity values of the freeze-dried samples were higher than those of the oven-dried ones. Copyright © 2016 Elsevier B.V. All rights reserved.

Subsonic Aircraft With Regression and Neural-Network Approximators Designed

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Hopkins, Dale A.

2004-01-01

At the NASA Glenn Research Center, NASA Langley Research Center's Flight Optimization System (FLOPS) and the design optimization testbed COMETBOARDS with regression and neural-network-analysis approximators have been coupled to obtain a preliminary aircraft design methodology. For a subsonic aircraft, the optimal design, that is the airframe-engine combination, is obtained by the simulation. The aircraft is powered by two high-bypass-ratio engines with a nominal thrust of about 35,000 lbf. It is to carry 150 passengers at a cruise speed of Mach 0.8 over a range of 3000 n mi and to operate on a 6000-ft runway. The aircraft design utilized a neural network and a regression-approximations-based analysis tool, along with a multioptimizer cascade algorithm that uses sequential linear programming, sequential quadratic programming, the method of feasible directions, and then sequential quadratic programming again. Optimal aircraft weight versus the number of design iterations is shown. The central processing unit (CPU) time to solution is given. It is shown that the regression-method-based analyzer exhibited a smoother convergence pattern than the FLOPS code. The optimum weight obtained by the approximation technique and the FLOPS code differed by 1.3 percent. Prediction by the approximation technique exhibited no error for the aircraft wing area and turbine entry temperature, whereas it was within 2 percent for most other parameters. Cascade strategy was required by FLOPS as well as the approximators. The regression method had a tendency to hug the data points, whereas the neural network exhibited a propensity to follow a mean path. The performance of the neural network and regression methods was considered adequate. It was at about the same level for small, standard, and large models with redundancy ratios (defined as the number of input-output pairs to the number of unknown coefficients) of 14, 28, and 57, respectively. In an SGI octane workstation (Silicon Graphics, Inc., Mountainview, CA), the regression training required a fraction of a CPU second, whereas neural network training was between 1 and 9 min, as given. For a single analysis cycle, the 3-sec CPU time required by the FLOPS code was reduced to milliseconds by the approximators. For design calculations, the time with the FLOPS code was 34 min. It was reduced to 2 sec with the regression method and to 4 min by the neural network technique. The performance of the regression and neural network methods was found to be satisfactory for the analysis and design optimization of the subsonic aircraft.

Role of orbital filling on nonlinear ionic Raman scattering in perovskite titanates

NASA Astrophysics Data System (ADS)

Gu, Mingqiang; Rondinelli, James M.

2017-01-01

The linear and nonlinear phononic interactions between an optically excited infrared (IR) or hyper-Raman mode and a driven Raman mode are computed for the d0 (CaTiO3) and d1 (LaTiO3) titanates within a first-principles density functional framework. We calculate the potential energy surface expanded in terms of the Ag or B1 g mode amplitudes coupled to the Au or the B3 u mode and determine the coupling coefficients for these multimode interactions. We find that the linear-quadratic coupling dominates the anharmonicities over the quadratic-quadratic interaction in the perovskite titanates. The IR and Raman modes both modify the electronic structure with the former being more significant but occurring on a different time scale; furthermore, the coupled-mode interactions lead to sizable perturbations to the valence bandwidth (˜100 meV ) and band gap (˜50 meV). By comparing the coupling coefficients of undoped CaTiO3 and LaTiO3 to those for electron-doped (CaTiO3) and hole-doped (LaTiO3) titanates, we isolate the role of orbital filling in the nonlinear coupling process. We find that with increasing occupancy of the d manifold, the linear-quadratic interaction decreases by approximately 30% with minor changes induced by the cation chemistry (that mainly affect the phonon mode frequencies) or by electron correlation. We identify the importance of the Ti-O bond stiffness, which depends on the orbital filling, in governing the lattice anharmonicitiy. This microscopic understanding can be used to increase the nonlinear coupling coefficient to facilitate more facile access of nonequilibrium structures and properties through ionic Raman scattering processes.

Determining friction and effective loading for sled sprinting.

PubMed

Cross, Matt R; Tinwala, Farhan; Lenetsky, Seth; Samozino, Pierre; Brughelli, Matt; Morin, Jean-Benoit

2017-11-01

Understanding the impact of friction in sled sprinting allows the quantification of kinetic outputs and the effective loading experienced by the athlete. This study assessed changes in the coefficient of friction (µ k ) of a sled sprint-training device with changing mass and speed to provide a means of quantifying effective loading for athletes. A common sled equipped with a load cell was towed across an athletics track using a motorised winch under variable sled mass (33.1-99.6 kg) with constant speeds (0.1 and 0.3 m · s -1 ), and with constant sled mass (55.6 kg) and varying speeds (0.1-6.0 m · s -1 ). Mean force data were analysed, with five trials performed for each condition to assess the reliability of measures. Variables were determined as reliable (ICC > 0.99, CV < 4.3%), with normal-force/friction-force and speed/coefficient of friction relationships well fitted with linear (R 2  = 0.994-0.995) and quadratic regressions (R 2  = 0.999), respectively (P < 0.001). The linearity of composite friction values determined at two speeds, and the range in values from the quadratic fit (µ k  = 0.35-0.47) suggested µ k and effective loading were dependent on instantaneous speed on athletics track surfaces. This research provides a proof-of-concept for the assessment of friction characteristics during sled towing, with a practical example of its application in determining effective loading and sled-sprinting kinetics. The results clarify effects of friction during sled sprinting and improve the accuracy of loading applications in practice and transparency of reporting in research.

Functional Data Approximation on Bounded Domains using Polygonal Finite Elements.

PubMed

Cao, Juan; Xiao, Yanyang; Chen, Zhonggui; Wang, Wenping; Bajaj, Chandrajit

2018-07-01

We construct and analyze piecewise approximations of functional data on arbitrary 2D bounded domains using generalized barycentric finite elements, and particularly quadratic serendipity elements for planar polygons. We compare approximation qualities (precision/convergence) of these partition-of-unity finite elements through numerical experiments, using Wachspress coordinates, natural neighbor coordinates, Poisson coordinates, mean value coordinates, and quadratic serendipity bases over polygonal meshes on the domain. For a convex n -sided polygon, the quadratic serendipity elements have 2 n basis functions, associated in a Lagrange-like fashion to each vertex and each edge midpoint, rather than the usual n ( n + 1)/2 basis functions to achieve quadratic convergence. Two greedy algorithms are proposed to generate Voronoi meshes for adaptive functional/scattered data approximations. Experimental results show space/accuracy advantages for these quadratic serendipity finite elements on polygonal domains versus traditional finite elements over simplicial meshes. Polygonal meshes and parameter coefficients of the quadratic serendipity finite elements obtained by our greedy algorithms can be further refined using an L 2 -optimization to improve the piecewise functional approximation. We conduct several experiments to demonstrate the efficacy of our algorithm for modeling features/discontinuities in functional data/image approximation.

Statistical optimization of medium components and growth conditions by response surface methodology to enhance phenol degradation by Pseudomonas putida.

PubMed

Annadurai, Gurusamy; Ling, Lai Yi; Lee, Jiunn-Fwu

2008-02-28

In this work, a four-level Box-Behnken factorial design was employed combining with response surface methodology (RSM) to optimize the medium composition for the degradation of phenol by pseudomonas putida (ATCC 31800). A mathematical model was then developed to show the effect of each medium composition and their interactions on the biodegradation of phenol. Response surface method was using four levels like glucose, yeast extract, ammonium sulfate and sodium chloride, which also enabled the identification of significant effects of interactions for the batch studies. The biodegradation of phenol on Pseudomonas putida (ATCC 31800) was determined to be pH-dependent and the maximum degradation capacity of microorganism at 30 degrees C when the phenol concentration was 0.2 g/L and the pH of the solution was 7.0. Second order polynomial regression model was used for analysis of the experiment. Cubic and quadratic terms were incorporated into the regression model through variable selection procedures. The experimental values are in good agreement with predicted values and the correlation coefficient was found to be 0.9980.

Response surface methodological approach for the decolorization of simulated dye effluent using Aspergillus fumigatus fresenius.

PubMed

Sharma, Praveen; Singh, Lakhvinder; Dilbaghi, Neeraj

2009-01-30

The aim of our research was to study, effect of temperature, pH and initial dye concentration on decolorization of diazo dye Acid Red 151 (AR 151) from simulated dye solution using a fungal isolate Aspergillus fumigatus fresenius have been investigated. The central composite design matrix and response surface methodology (RSM) have been applied to design the experiments to evaluate the interactive effects of three most important operating variables: temperature (25-35 degrees C), pH (4.0-7.0), and initial dye concentration (100-200 mg/L) on the biodegradation of AR 151. The total 20 experiments were conducted in the present study towards the construction of a quadratic model. Very high regression coefficient between the variables and the response (R(2)=0.9934) indicated excellent evaluation of experimental data by second-order polynomial regression model. The RSM indicated that initial dye concentration of 150 mg/L, pH 5.5 and a temperature of 30 degrees C were optimal for maximum % decolorization of AR 151 in simulated dye solution, and 84.8% decolorization of AR 151 was observed at optimum growth conditions.

Simultaneous effect of dissolved organic carbon, surfactant, and organic acid on the desorption of pesticides investigated by response surface methodology.

PubMed

Trinh, Ha Thu; Duong, Hanh Thi; Ta, Thao Thi; Van Cao, Hoang; Strobel, Bjarne W; Le, Giang Truong

2017-08-01

Desorption of pesticides (fenobucarb, endosulfan, and dichlorodiphenyltrichloroethane (DDT)) from soil to aqueous solution with the simultaneous presence of dissolved organic carbon (DOC), sodium dodecyl sulfate (SDS), and sodium oxalate (Oxa) was investigated in batch test by applying a full factorial design and the Box-Behnken response surface methodology (RSM). Five concentration levels of DOC (8 to 92 mg L -1 ), SDS (0 to 6.4 critical micelle concentration (CMC)), and Oxa (0 to 0.15 M) were used for the experiments with a rice field topsoil. The results of RSM analysis and analysis of variance (ANOVA) have shown that the experimental data could be well described by quadratic regression equations with determination coefficients (R 2 ) of 0.990, 0.976, and 0.984 for desorption of fenobucarb, endosulfan, and DDT, respectively. The individual effects and interaction of DOC, SDS, and Oxa were evaluated through quadratic regression equations. When the aqueous solution includes 50 mg L -1 DOC, 3.75 CMC SDS, and 0.1 M Oxa, the maximum desorption concentrations of fenobucarb, endosulfan, and DDT were 96, 80, and 75 μg L -1 , respectively. The lowest concentration of SDS, DOC, and Oxa caused the minimum desorption. This point at conditions of concern for flooding water is high content of organic compounds causing potentially high contamination by desorption, and the remarkably lower desorption at organic matter-free conditions. The suspended organic matter is one of the common characteristics of flooding and irrigation water in rice fields, and surfactants from pollution increase the problem with desorption of legacy pesticides in the rice fields.

A bivariate rational interpolation with a bi-quadratic denominator

NASA Astrophysics Data System (ADS)

Duan, Qi; Zhang, Huanling; Liu, Aikui; Li, Huaigu

2006-10-01

In this paper a new rational interpolation with a bi-quadratic denominator is developed to create a space surface using only values of the function being interpolated. The interpolation function has a simple and explicit rational mathematical representation. When the knots are equally spaced, the interpolating function can be expressed in matrix form, and this form has a symmetric property. The concept of integral weights coefficients of the interpolation is given, which describes the "weight" of the interpolation points in the local interpolating region.

Design of Linear Quadratic Regulators and Kalman Filters

NASA Technical Reports Server (NTRS)

Lehtinen, B.; Geyser, L.

1986-01-01

AESOP solves problems associated with design of controls and state estimators for linear time-invariant systems. Systems considered are modeled in state-variable form by set of linear differential and algebraic equations with constant coefficients. Two key problems solved by AESOP are linear quadratic regulator (LQR) design problem and steady-state Kalman filter design problem. AESOP is interactive. User solves design problems and analyzes solutions in single interactive session. Both numerical and graphical information available to user during the session.

Polynomials with Restricted Coefficients and Their Applications

DTIC Science & Technology

1987-01-01

sums of exponentials of quadratics, he reduced such ýzums to exponentials of linears (geometric sums!) by simplg multiplying by their conjugates...n, the same algebraic manipulations as before lead to rn V`-~ v ie ? --8-- el4V’ .fk ts with 𔄃 = a+(2r+l)t, A = a+(2r+2m+l)t. To estimate the right...coefficients. These random polynomials represent the deviation in frequency response of a linear , equispaced antenna array cauised by coefficient

Piece-wise quadratic approximations of arbitrary error functions for fast and robust machine learning.

PubMed

Gorban, A N; Mirkes, E M; Zinovyev, A

2016-12-01

Most of machine learning approaches have stemmed from the application of minimizing the mean squared distance principle, based on the computationally efficient quadratic optimization methods. However, when faced with high-dimensional and noisy data, the quadratic error functionals demonstrated many weaknesses including high sensitivity to contaminating factors and dimensionality curse. Therefore, a lot of recent applications in machine learning exploited properties of non-quadratic error functionals based on L 1 norm or even sub-linear potentials corresponding to quasinorms L p (0

Slip and Slide Method of Factoring Trinomials with Integer Coefficients over the Integers

ERIC Educational Resources Information Center

Donnell, William A.

2012-01-01

In intermediate and college algebra courses there are a number of methods for factoring quadratic trinomials with integer coefficients over the integers. Some of these methods have been given names, such as trial and error, reversing FOIL, AC method, middle term splitting method and slip and slide method. The purpose of this article is to discuss…

Cellulose microfibril orientation of Picea abies and its variability at the micron-level determined by Raman imaging.

PubMed

Gierlinger, Notburga; Luss, Saskia; König, Christian; Konnerth, Johannes; Eder, Michaela; Fratzl, Peter

2010-01-01

The functional characteristics of plant cell walls depend on the composition of the cell wall polymers, as well as on their highly ordered architecture at scales from a few nanometres to several microns. Raman spectra of wood acquired with linear polarized laser light include information about polymer composition as well as the alignment of cellulose microfibrils with respect to the fibre axis (microfibril angle). By changing the laser polarization direction in 3 degrees steps, the dependency between cellulose and laser orientation direction was investigated. Orientation-dependent changes of band height ratios and spectra were described by quadratic linear regression and partial least square regressions, respectively. Using the models and regressions with high coefficients of determination (R(2) > 0.99) microfibril orientation was predicted in the S1 and S2 layers distinguished by the Raman imaging approach in cross-sections of spruce normal, opposite, and compression wood. The determined microfibril angle (MFA) in the different S2 layers ranged from 0 degrees to 49.9 degrees and was in coincidence with X-ray diffraction determination. With the prerequisite of geometric sample and laser alignment, exact MFA prediction can complete the picture of the chemical cell wall design gained by the Raman imaging approach at the micron level in all plant tissues.

Second-order rogue wave breathers in the nonlinear Schrödinger equation with quadratic potential modulated by a spatially-varying diffraction coefficient.

PubMed

Zhong, Wei-Ping; Belić, Milivoj; Zhang, Yiqi

2015-02-09

Nonlinear Schrödinger equation with simple quadratic potential modulated by a spatially-varying diffraction coefficient is investigated theoretically. Second-order rogue wave breather solutions of the model are constructed by using the similarity transformation. A modal quantum number is introduced, useful for classifying and controlling the solutions. From the solutions obtained, the behavior of second order Kuznetsov-Ma breathers (KMBs), Akhmediev breathers (ABs), and Peregrine solitons is analyzed in particular, by selecting different modulation frequencies and quantum modal parameter. We show how to generate interesting second order breathers and related hybrid rogue waves. The emergence of true rogue waves - single giant waves that are generated in the interaction of KMBs, ABs, and Peregrine solitons - is explicitly displayed in our analytical solutions.

Statistical distribution sampling

NASA Technical Reports Server (NTRS)

Johnson, E. S.

1975-01-01

Determining the distribution of statistics by sampling was investigated. Characteristic functions, the quadratic regression problem, and the differential equations for the characteristic functions are analyzed.

Physical evaluation of a maize-based extruded snack with curry powder.

PubMed

Christofides, Vassilis; Ainsworth, Paul; Ibanoğlu, Senol; Gomes, Frances

2004-02-01

Response surface methodology was used to analyze the effect of screw speed (200-280 rpm), feed moisture (13.0-17.0%, wet basis), and curry powder (6.0-9.0%) on the bulk density, lateral expansion, and firmness of maize-based extruded snack with curry powder. Regression equations describing the effect of each variable on the responses were obtained. Responses were most affected by changes in feed moisture followed by screw speed and curry powder (p < 0.05). Lateral expansion increased linearly as the amount of curry powder added was increased whereas a quadratic increase was obtained in lateral expansion with decreasing feed moisture. The firmness of samples was increased with an increase in feed moisture. The bulk density of samples was increased with increasing feed moisture and screw speeds. Radial expansion was found to be a better index to measure the physical properties of the extruded product indicated by a higher correlation coefficient.

Enzymatic catalysis treatment method of meat industry wastewater using lacasse.

PubMed

Thirugnanasambandham, K; Sivakumar, V

2015-01-01

The process of meat industry produces in a large amount of wastewater that contains high levels of colour and chemical oxygen demand (COD). So they must be pretreated before their discharge into the ecological system. In this paper, enzymatic catalysis (EC) was adopted to treat the meat wastewater. Box-Behnken design (BBD), an experimental design for response surface methodology (RSM), was used to create a set of 29 experimental runs needed for optimizing of the operating conditions. Quadratic regression models with estimated coefficients were developed to describe the colour and COD removals. The experimental results show that EC could effectively reduce colour (95 %) and COD (86 %) at the optimum conditions of enzyme dose of 110 U/L, incubation time of 100 min, pH of 7 and temperature of 40 °C. RSM could be effectively adopted to optimize the operating multifactors in complex EC process.

Quadratic Electro-optic Effect in a Novel Nonconjugated Conductive Polymer, iodine-doped Polynorbornene

NASA Astrophysics Data System (ADS)

Narayanan, Ananthakrishnan; Thakur, Mrinal

2009-03-01

Quadratic electro-optic effect in a novel nonconjugated conductive polymer, iodine-doped polynorbornene has been measured using field-induced birefringence at 633 nm. The electrical conductivity^1 of polynorbornene increases by twelve orders of magnitude to about 0.01 S/cm upon doping with iodine. The electro-optic measurement has been made in a film doped at the medium doping-level. The electro-optic modulation signal was recorded using a lock-in amplifier for various applied ac voltages (4 kHz) and the quadratic dependence of the modulation on the applied voltage was observed. A modulation of about 0.01% was observed for an applied electric field of 3 V/micron for a 100 nm thick film The Kerr coefficient as determined is about 1.77x10-11m/V^2. This exceptionally large quadratic electro-optic effect has been attributed to the confinement of this charge-transfer system within a sub-nanometer dimension. 1. A. Narayanan, A. Palthi and M. Thakur, J. Macromol. Sci. -- PAC, accepted.

Silicon and Manganese Partition Between Slag and Metal Phases and Their Activities Pertinent to Ferromanganese and Silicomanganese Production

NASA Astrophysics Data System (ADS)

Cengizler, Hakan; Eric, R. Hurman

Equilibrium between MnO-CaO-MgO-SiO2-Al2O3 slags and carbon saturated Mn-Si-Fe-C alloys was investigated under CO at 1500oC. Manganese and silicon activities were obtained by using the present data and the previously determined MnO and SiO2 activities of the slag. Quadratic multi-coefficient regression equations were developed for activity coefficients of manganese and silicon. The conclusions of this work are:(i)increase in the basicity and the CaO/Al2O3 ratios decreases the Mn distribution ratio,(ii)increase in the silica concentration and the MgO/CaO ratio increases the Mn distribution ratio, iii)carbon and manganese as well as carbon and silicon of the metal phase are inversely proportional,(iv)as Mn/Fe and Mn/Si ratio increases in the metal the carbon solubility increases,(v)decrease in the basicity increases the silicon content of the metal and (vi)increase in the silica content of the slag increases the silicon content of the metal and this effect is more pronounced at the higher Mn/Fe and Mn/Si ratios.

Career Preparedness and School Achievement of Portuguese Children: Longitudinal Trend Articulations

PubMed Central

Oliveira, Íris M.; Taveira, Maria do Céu; Porfeli, Erik J.

2017-01-01

Social Cognitive Career Theory suggests that students' preparedness for the school-to-work transition is a developmental process. Middle school children explore various careers, obtain feedback about their academic progress, and develop career self-efficacy and outcome expectations. These processes advance provisional educational/occupational goals. The literature has suggested articulations between career and academic development and how both vary across demographic characteristics, but longitudinal studies linking these processes are scarce. This study tested articulations between career preparedness and academic achievement during middle school years and employed gender and geographical location as potential moderators affecting the linkage between career and school domains. Participants included 429 children (47.8% girls) from northern (69.5%) and central Portugal (30.5%) followed across four occasions of measurement (MageWave1 = 10.23, SD = 0.50). Data was collected with school records, the Multidimensional Scales of Perceived Self-Efficacy, Career Exploratory Outcome Expectations Scale, Childhood Career Exploration Inventory and Childhood Career Development Scale. Average and orthnormalized linear, quadratic and cubic trends were computed. Pearson correlation coefficients suggested positive and statistically significant associations between career exploratory outcome expectations and academic achievement average trends. Career planning and self-efficacy expectations were negatively associated with academic achievement quadratic trends. Multiple linear regression models suggested that career exploratory outcome expectations and career planning were respectively statistically significant predictors of the average and quadratic trends of academic achievement. Gender moderated the association between the career variables and academic achievement linear trends as well as the relation of career planning and self-efficacy with academic achievement cubic trends. Additionally, the geographical location moderated the association between the average trend of career exploratory outcome expectations and academic achievement as well as tended to moderate the relation between the career variables and academic achievement quadratic trends. Future research could seek to explore the role of context in shaping the trajectories and linkages between career and academic progress with a more representative sample of participants from a broader array of geographical locations. This study advances extant literature by affirming the longitudinal relationship between the school and work domains in youth, which might sustain practices aimed at fostering students' career preparedness and academic achievement. PMID:28484413

Career Preparedness and School Achievement of Portuguese Children: Longitudinal Trend Articulations.

PubMed

Oliveira, Íris M; Taveira, Maria do Céu; Porfeli, Erik J

2017-01-01

Social Cognitive Career Theory suggests that students' preparedness for the school-to-work transition is a developmental process. Middle school children explore various careers, obtain feedback about their academic progress, and develop career self-efficacy and outcome expectations. These processes advance provisional educational/occupational goals. The literature has suggested articulations between career and academic development and how both vary across demographic characteristics, but longitudinal studies linking these processes are scarce. This study tested articulations between career preparedness and academic achievement during middle school years and employed gender and geographical location as potential moderators affecting the linkage between career and school domains. Participants included 429 children (47.8% girls) from northern (69.5%) and central Portugal (30.5%) followed across four occasions of measurement ( M ageWave1 = 10.23, SD = 0.50). Data was collected with school records, the Multidimensional Scales of Perceived Self-Efficacy, Career Exploratory Outcome Expectations Scale, Childhood Career Exploration Inventory and Childhood Career Development Scale. Average and orthnormalized linear, quadratic and cubic trends were computed. Pearson correlation coefficients suggested positive and statistically significant associations between career exploratory outcome expectations and academic achievement average trends. Career planning and self-efficacy expectations were negatively associated with academic achievement quadratic trends. Multiple linear regression models suggested that career exploratory outcome expectations and career planning were respectively statistically significant predictors of the average and quadratic trends of academic achievement. Gender moderated the association between the career variables and academic achievement linear trends as well as the relation of career planning and self-efficacy with academic achievement cubic trends. Additionally, the geographical location moderated the association between the average trend of career exploratory outcome expectations and academic achievement as well as tended to moderate the relation between the career variables and academic achievement quadratic trends. Future research could seek to explore the role of context in shaping the trajectories and linkages between career and academic progress with a more representative sample of participants from a broader array of geographical locations. This study advances extant literature by affirming the longitudinal relationship between the school and work domains in youth, which might sustain practices aimed at fostering students' career preparedness and academic achievement.

Detecting sea-level hazards: Simple regression-based methods for calculating the acceleration of sea level

USGS Publications Warehouse

Doran, Kara S.; Howd, Peter A.; Sallenger,, Asbury H.

2016-01-04

Recent studies, and most of their predecessors, use tide gage data to quantify SL acceleration, ASL(t). In the current study, three techniques were used to calculate acceleration from tide gage data, and of those examined, it was determined that the two techniques based on sliding a regression window through the time series are more robust compared to the technique that fits a single quadratic form to the entire time series, particularly if there is temporal variation in the magnitude of the acceleration. The single-fit quadratic regression method has been the most commonly used technique in determining acceleration in tide gage data. The inability of the single-fit method to account for time-varying acceleration may explain some of the inconsistent findings between investigators. Properly quantifying ASL(t) from field measurements is of particular importance in evaluating numerical models of past, present, and future SLR resulting from anticipated climate change.

A comparative analysis of predictive models of morbidity in intensive care unit after cardiac surgery - part II: an illustrative example.

PubMed

Cevenini, Gabriele; Barbini, Emanuela; Scolletta, Sabino; Biagioli, Bonizella; Giomarelli, Pierpaolo; Barbini, Paolo

2007-11-22

Popular predictive models for estimating morbidity probability after heart surgery are compared critically in a unitary framework. The study is divided into two parts. In the first part modelling techniques and intrinsic strengths and weaknesses of different approaches were discussed from a theoretical point of view. In this second part the performances of the same models are evaluated in an illustrative example. Eight models were developed: Bayes linear and quadratic models, k-nearest neighbour model, logistic regression model, Higgins and direct scoring systems and two feed-forward artificial neural networks with one and two layers. Cardiovascular, respiratory, neurological, renal, infectious and hemorrhagic complications were defined as morbidity. Training and testing sets each of 545 cases were used. The optimal set of predictors was chosen among a collection of 78 preoperative, intraoperative and postoperative variables by a stepwise procedure. Discrimination and calibration were evaluated by the area under the receiver operating characteristic curve and Hosmer-Lemeshow goodness-of-fit test, respectively. Scoring systems and the logistic regression model required the largest set of predictors, while Bayesian and k-nearest neighbour models were much more parsimonious. In testing data, all models showed acceptable discrimination capacities, however the Bayes quadratic model, using only three predictors, provided the best performance. All models showed satisfactory generalization ability: again the Bayes quadratic model exhibited the best generalization, while artificial neural networks and scoring systems gave the worst results. Finally, poor calibration was obtained when using scoring systems, k-nearest neighbour model and artificial neural networks, while Bayes (after recalibration) and logistic regression models gave adequate results. Although all the predictive models showed acceptable discrimination performance in the example considered, the Bayes and logistic regression models seemed better than the others, because they also had good generalization and calibration. The Bayes quadratic model seemed to be a convincing alternative to the much more usual Bayes linear and logistic regression models. It showed its capacity to identify a minimum core of predictors generally recognized as essential to pragmatically evaluate the risk of developing morbidity after heart surgery.

Random regression analyses using B-splines functions to model growth from birth to adult age in Canchim cattle.

PubMed

Baldi, F; Alencar, M M; Albuquerque, L G

2010-12-01

The objective of this work was to estimate covariance functions using random regression models on B-splines functions of animal age, for weights from birth to adult age in Canchim cattle. Data comprised 49,011 records on 2435 females. The model of analysis included fixed effects of contemporary groups, age of dam as quadratic covariable and the population mean trend taken into account by a cubic regression on orthogonal polynomials of animal age. Residual variances were modelled through a step function with four classes. The direct and maternal additive genetic effects, and animal and maternal permanent environmental effects were included as random effects in the model. A total of seventeen analyses, considering linear, quadratic and cubic B-splines functions and up to seven knots, were carried out. B-spline functions of the same order were considered for all random effects. Random regression models on B-splines functions were compared to a random regression model on Legendre polynomials and with a multitrait model. Results from different models of analyses were compared using the REML form of the Akaike Information criterion and Schwarz' Bayesian Information criterion. In addition, the variance components and genetic parameters estimated for each random regression model were also used as criteria to choose the most adequate model to describe the covariance structure of the data. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most adequate to describe the covariance structure of the data. Random regression models using B-spline functions as base functions fitted the data better than Legendre polynomials, especially at mature ages, but higher number of parameters need to be estimated with B-splines functions. © 2010 Blackwell Verlag GmbH.

Meta-Regression Approximations to Reduce Publication Selection Bias

ERIC Educational Resources Information Center

Stanley, T. D.; Doucouliagos, Hristos

2014-01-01

Publication selection bias is a serious challenge to the integrity of all empirical sciences. We derive meta-regression approximations to reduce this bias. Our approach employs Taylor polynomial approximations to the conditional mean of a truncated distribution. A quadratic approximation without a linear term, precision-effect estimate with…

Optimization of process variables for decolorization of Disperse Yellow 211 by Bacillus subtilis using Box-Behnken design.

PubMed

Sharma, Praveen; Singh, Lakhvinder; Dilbaghi, Neeraj

2009-05-30

Decolorization of textile azo dye Disperse Yellow 211 (DY 211) was carried out from simulated aqueous solution by bacterial strain Bacillus subtilis. Response surface methodology (RSM), involving Box-Behnken design matrix in three most important operating variables; temperature, pH and initial dye concentration was successfully employed for the study and optimization of decolorization process. The total 17 experiments were conducted in the study towards the construction of a quadratic model. According to analysis of variance (ANOVA) results, the proposed model can be used to navigate the design space. Under optimized conditions the bacterial strain was able to decolorize DY 211 up to 80%. Model indicated that initial dye concentration of 100 mgl(-1), pH 7 and a temperature of 32.5 degrees C were found optimum for maximum % decolorization. Very high regression coefficient between the variables and the response (R(2)=0.9930) indicated excellent evaluation of experimental data by polynomial regression model. The combination of the three variables predicted through RSM was confirmed through confirmatory experiments, hence the bacterial strain holds a great potential for the treatment of colored textile effluents.

Electrochemical reduction of carbon fluorine bond in 4-fluorobenzonitrile Mechanistic analysis employing Marcus Hush quadratic activation-driving force relation

NASA Astrophysics Data System (ADS)

Muthukrishnan, A.; Sangaranarayanan, M. V.

2007-10-01

The reduction of carbon-fluorine bond in 4-fluorobenzonitrile in acetonitrile as the solvent, is analyzed using convolution potential sweep voltammetry and the dependence of the transfer coefficient on potential is investigated within the framework of Marcus-Hush quadratic activation-driving force theory. The validity of stepwise mechanism is inferred from solvent reorganization energy estimates as well as bond length calculations using B3LYP/6-31g(d) method. A novel method of estimating the standard reduction potential of the 4-fluorobenzonitrile in acetonitrile is proposed.

Orientation of doubly rotated quartz plates.

PubMed

Sherman, J R

1989-01-01

A derivation from classical spherical trigonometry of equations to compute the orientation of doubly-rotated quartz blanks from Bragg X-ray data is discussed. These are usually derived by compact and efficient vector methods, which are reviewed briefly. They are solved by generating a quadratic equation with numerical coefficients. Two methods exist for performing the computation from measurements against two planes: a direct solution by a quadratic equation and a process of convergent iteration. Both have a spurious solution. Measurement against three lattice planes yields a set of three linear equations the solution of which is an unambiguous result.

Cellulose microfibril orientation of Picea abies and its variability at the micron-level determined by Raman imaging

PubMed Central

Gierlinger, Notburga; Luss, Saskia; König, Christian; Konnerth, Johannes; Eder, Michaela; Fratzl, Peter

2010-01-01

The functional characteristics of plant cell walls depend on the composition of the cell wall polymers, as well as on their highly ordered architecture at scales from a few nanometres to several microns. Raman spectra of wood acquired with linear polarized laser light include information about polymer composition as well as the alignment of cellulose microfibrils with respect to the fibre axis (microfibril angle). By changing the laser polarization direction in 3° steps, the dependency between cellulose and laser orientation direction was investigated. Orientation-dependent changes of band height ratios and spectra were described by quadratic linear regression and partial least square regressions, respectively. Using the models and regressions with high coefficients of determination (R2 > 0.99) microfibril orientation was predicted in the S1 and S2 layers distinguished by the Raman imaging approach in cross-sections of spruce normal, opposite, and compression wood. The determined microfibril angle (MFA) in the different S2 layers ranged from 0° to 49.9° and was in coincidence with X-ray diffraction determination. With the prerequisite of geometric sample and laser alignment, exact MFA prediction can complete the picture of the chemical cell wall design gained by the Raman imaging approach at the micron level in all plant tissues. PMID:20007198

Modified Regression Correlation Coefficient for Poisson Regression Model

NASA Astrophysics Data System (ADS)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

Effects of the bottom boundary condition in numerical investigations of dense water cascading on a slope

NASA Astrophysics Data System (ADS)

Berntsen, Jarle; Alendal, Guttorm; Avlesen, Helge; Thiem, Øyvind

2018-05-01

The flow of dense water along continental slopes is considered. There is a large literature on the topic based on observations and laboratory experiments. In addition, there are many analytical and numerical studies of dense water flows. In particular, there is a sequence of numerical investigations using the dynamics of overflow mixing and entrainment (DOME) setup. In these papers, the sensitivity of the solutions to numerical parameters such as grid size and numerical viscosity coefficients and to the choices of methods and models is investigated. In earlier DOME studies, three different bottom boundary conditions and a range of vertical grid sizes are applied. In other parts of the literature on numerical studies of oceanic gravity currents, there are statements that appear to contradict choices made on bottom boundary conditions in some of the DOME papers. In the present study, we therefore address the effects of the bottom boundary condition and vertical resolution in numerical investigations of dense water cascading on a slope. The main finding of the present paper is that it is feasible to capture the bottom Ekman layer dynamics adequately and cost efficiently by using a terrain-following model system using a quadratic drag law with a drag coefficient computed to give near-bottom velocity profiles in agreement with the logarithmic law of the wall. Many studies of dense water flows are performed with a quadratic bottom drag law and a constant drag coefficient. It is shown that when using this bottom boundary condition, Ekman drainage will not be adequately represented. In other studies of gravity flow, a no-slip bottom boundary condition is applied. With no-slip and a very fine resolution near the seabed, the solutions are essentially equal to the solutions obtained with a quadratic drag law and a drag coefficient computed to produce velocity profiles matching the logarithmic law of the wall. However, with coarser resolution near the seabed, there may be a substantial artificial blocking effect when using no-slip.

Investigating bias in squared regression structure coefficients

PubMed Central

Nimon, Kim F.; Zientek, Linda R.; Thompson, Bruce

2015-01-01

The importance of structure coefficients and analogs of regression weights for analysis within the general linear model (GLM) has been well-documented. The purpose of this study was to investigate bias in squared structure coefficients in the context of multiple regression and to determine if a formula that had been shown to correct for bias in squared Pearson correlation coefficients and coefficients of determination could be used to correct for bias in squared regression structure coefficients. Using data from a Monte Carlo simulation, this study found that squared regression structure coefficients corrected with Pratt's formula produced less biased estimates and might be more accurate and stable estimates of population squared regression structure coefficients than estimates with no such corrections. While our findings are in line with prior literature that identified multicollinearity as a predictor of bias in squared regression structure coefficients but not coefficients of determination, the findings from this study are unique in that the level of predictive power, number of predictors, and sample size were also observed to contribute bias in squared regression structure coefficients. PMID:26217273

Identify Secretory Protein of Malaria Parasite with Modified Quadratic Discriminant Algorithm and Amino Acid Composition.

PubMed

Feng, Yong-E

2016-06-01

Malaria parasite secretes various proteins in infected red blood cell for its growth and survival. Thus identification of these secretory proteins is important for developing vaccine or drug against malaria. In this study, the modified method of quadratic discriminant analysis is presented for predicting the secretory proteins. Firstly, 20 amino acids are divided into five types according to the physical and chemical characteristics of amino acids. Then, we used five types of amino acids compositions as inputs of the modified quadratic discriminant algorithm. Finally, the best prediction performance is obtained by using 20 amino acid compositions, the sensitivity of 96 %, the specificity of 92 % with 0.88 of Mathew's correlation coefficient in fivefold cross-validation test. The results are also compared with those of existing prediction methods. The compared results shown our method are prominent in the prediction of secretory proteins.

Quantized Algebra I Texts

NASA Astrophysics Data System (ADS)

DeBuvitz, William

2014-03-01

I am a volunteer reader at the Princeton unit of "Learning Ally" (formerly "Recording for the Blind & Dyslexic") and I recently discovered that high school students are introduced to the concept of quantization well before they take chemistry and physics. For the past few months I have been reading onto computer files a popular Algebra I textbook, and I was surprised and dismayed by how it treated simultaneous equations and quadratic equations. The coefficients are always simple integers in examples and exercises, even when they are related to physics. This is probably a good idea when these topics are first presented to the students. It makes it easy to solve simultaneous equations by the method of elimination of a variable. And it makes it easy to solve some quadratic equations by factoring. The textbook also discusses the method of substitution for linear equations and the use of the quadratic formula, but only with simple integers.

Engineering quadratic nonlinear photonic crystals for frequency conversion of lasers

NASA Astrophysics Data System (ADS)

Chen, Baoqin; Hong, Lihong; Hu, Chenyang; Zhang, Chao; Liu, Rongjuan; Li, Zhiyuan

2018-03-01

Nonlinear frequency conversion offers an effective way to extend the laser wavelength range. Quadratic nonlinear photonic crystals (NPCs) are artificial materials composed of domain-inversion structures whose sign of nonlinear coefficients are modulated with desire to implement quasi-phase matching (QPM) required for nonlinear frequency conversion. These structures can offer various reciprocal lattice vectors (RLVs) to compensate the phase-mismatching during the quadratic nonlinear optical processes, including second-harmonic generation (SHG), sum-frequency generation and the cascaded third-harmonic generation (THG). The modulation pattern of the nonlinear coefficients is flexible, which can be one-dimensional or two-dimensional (2D), be periodic, quasi-periodic, aperiodic, chirped, or super-periodic. As a result, these NPCs offer very flexible QPM scheme to satisfy various nonlinear optics and laser frequency conversion problems via design of the modulation patterns and RLV spectra. In particular, we introduce the electric poling technique for fabricating QPM structures, a simple effective nonlinear coefficient model for efficiently and precisely evaluating the performance of QPM structures, the concept of super-QPM and super-periodically poled lithium niobate for finely tuning nonlinear optical interactions, the design of 2D ellipse QPM NPC structures enabling continuous tunability of SHG in a broad bandwidth by simply changing the transport direction of pump light, and chirped QPM structures that exhibit broadband RLVs and allow for simultaneous radiation of broadband SHG, THG, HHG and thus coherent white laser from a single crystal. All these technical, theoretical, and physical studies on QPM NPCs can help to gain a deeper insight on the mechanisms, approaches, and routes for flexibly controlling the interaction of lasers with various QPM NPCs for high-efficiency frequency conversion and creation of novel lasers.

An Evaluation of Residual Feed Intake Estimates Obtained with Computer Models Versus Empirical Regression

USDA-ARS?s Scientific Manuscript database

Data on individual daily feed intake, bi-weekly BW, and carcass composition were obtained on 1,212 crossbred steers, in Cycle VII of the Germplasm Evaluation Project at the U.S. Meat Animal Research Center. Within animal regressions of cumulative feed intake and BW on linear and quadratic days on fe...

Reduction of shock induced noise in imperfectly expanded supersonic jets using convex optimization

NASA Astrophysics Data System (ADS)

Adhikari, Sam

2007-11-01

Imperfectly expanded jets generate screech noise. The imbalance between the backpressure and the exit pressure of the imperfectly expanded jets produce shock cells and expansion or compression waves from the nozzle. The instability waves and the shock cells interact to generate the screech sound. The mathematical model consists of cylindrical coordinate based full Navier-Stokes equations and large-eddy-simulation turbulence modeling. Analytical and computational analysis of the three-dimensional helical effects provide a model that relates several parameters with shock cell patterns, screech frequency and distribution of shock generation locations. Convex optimization techniques minimize the shock cell patterns and the instability waves. The objective functions are (convex) quadratic and the constraint functions are affine. In the quadratic optimization programs, minimization of the quadratic functions over a set of polyhedrons provides the optimal result. Various industry standard methods like regression analysis, distance between polyhedra, bounding variance, Markowitz optimization, and second order cone programming is used for Quadratic Optimization.

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

Sano, Yukio; Sano, Tomokazu

A quadratic equation for the temperature-independent Grueneisen coefficient {gamma} was derived by a method in which the Walsh-Christian and Mie-Grueneisen equations are combined. Some previously existing ab initio temperature Hugoniots for hexagonal close-packed solid Fe are inaccurate because the constant-volume specific heats on the Hugoniots CVH, which are related uniquely to the solutions of the quadratic equation, have values that are too small. A CVH distribution in the solid phase range was demonstrated to agree approximately with a previous ab initio distribution. In contrast, the corresponding {gamma} distribution was significantly different from the ab initio distribution in the lower pressuremore » region. The causes of these disagreements are clarified.« less

Weak interspecific interactions in a sagebrush steppe? Conflicting evidence from observations and experiments.

PubMed

Adler, Peter B; Kleinhesselink, Andrew; Giles, Hooker; Taylor, J Bret; Teller, Brittany; Ellner, Stephen P

2018-04-28

Stable coexistence requires intraspecific limitations to be stronger than interspecific limitations. The greater the difference between intra- and interspecific limitations, the more stable the coexistence, and the weaker the competitive release any species should experience following removal of competitors. We conducted a removal experiment to test whether a previously estimated model, showing surprisingly weak interspecific competition for four dominant species in a sagebrush steppe, accurately predicts competitive release. Our treatments were 1) removal of all perennial grasses and 2) removal of the dominant shrub, Artemisia tripartita. We regressed survival, growth and recruitment on the locations, sizes, and species identities of neighboring plants, along with an indicator variable for removal treatment. If our "baseline" regression model, which accounts for local plant-plant interactions, accurately explains the observed responses to removals, then the removal coefficient should be non-significant. For survival, the removal coefficients were never significantly different from zero, and only A. tripartita showed a (negative) response to removals at the recruitment stage. For growth, the removal treatment effect was significant and positive for two species, Poa secunda and Pseudoroegneria spicata, indicating that the baseline model underestimated interspecific competition. For all three grass species, population models based on the vital rate regressions that included removal effects projected 1.4 to 3-fold increases in equilibrium population size relative to the baseline model (no removal effects). However, we found no evidence of higher response to removal in quadrats with higher pretreatment cover of A. tripartita, or by plants experiencing higher pre-treatment crowding by A. tripartita, raising questions about the mechanisms driving the positive response to removal. While our results show the value of combining observations with a simple removal experiment, more tightly controlled experiments focused on underlying mechanisms may be required to conclusively validate or reject predictions from phenomenological models. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

A new approach to synthesis of benzyl cinnamate: Optimization by response surface methodology.

PubMed

Zhang, Dong-Hao; Zhang, Jiang-Yan; Che, Wen-Cai; Wang, Yun

2016-09-01

In this work, the new approach to synthesis of benzyl cinnamate by enzymatic esterification of cinnamic acid with benzyl alcohol is optimized by response surface methodology. The effects of various reaction conditions, including temperature, enzyme loading, substrate molar ratio of benzyl alcohol to cinnamic acid, and reaction time, are investigated. A 5-level-4-factor central composite design is employed to search for the optimal yield of benzyl cinnamate. A quadratic polynomial regression model is used to analyze the experimental data at a 95% confidence level (P<0.05). The coefficient of determination of this model is found to be 0.9851. Three sets of optimum reaction conditions are established, and the verified experimental trials are performed for validating the optimum points. Under the optimum conditions (40°C, 31mg/mL enzyme loading, 2.6:1 molar ratio, 27h), the yield reaches 97.7%, which provides an efficient processes for industrial production of benzyl cinnamate. Copyright © 2016 Elsevier Ltd. All rights reserved.

Response Surface Methodology for the Optimization of Preparation of Biocomposites Based on Poly(lactic acid) and Durian Peel Cellulose

PubMed Central

Penjumras, Patpen; Abdul Rahman, Russly; Talib, Rosnita A.; Abdan, Khalina

2015-01-01

Response surface methodology was used to optimize preparation of biocomposites based on poly(lactic acid) and durian peel cellulose. The effects of cellulose loading, mixing temperature, and mixing time on tensile strength and impact strength were investigated. A central composite design was employed to determine the optimum preparation condition of the biocomposites to obtain the highest tensile strength and impact strength. A second-order polynomial model was developed for predicting the tensile strength and impact strength based on the composite design. It was found that composites were best fit by a quadratic regression model with high coefficient of determination (R 2) value. The selected optimum condition was 35 wt.% cellulose loading at 165°C and 15 min of mixing, leading to a desirability of 94.6%. Under the optimum condition, the tensile strength and impact strength of the biocomposites were 46.207 MPa and 2.931 kJ/m2, respectively. PMID:26167523

Standards for Standardized Logistic Regression Coefficients

ERIC Educational Resources Information Center

Menard, Scott

2011-01-01

Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

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...

Spectral Properties of Limit-Periodic Schrödinger Operators (PhD Thesis)

NASA Astrophysics Data System (ADS)

Gideonse, Hendrik David, XIX

The Acoustic Ramp is a wedge-shaped, number-theoretical quadratic-residue-type acoustic diffuser. Since the late 1970's, several methodologies for the testing and analysis of diffusers have been developed including, the ISO Scattering Coefficient and the AES Diffusion Coefficient. These coefficients are the source of some controversy today and this paper makes the attempt to investigate the benefits and weaknesses of these tools by using them to research and test the Acoustic Ramp. Several issues are exposed in using the coefficients, the most important of which being the validity of the comparison of the diffuser's behavior to that of a like sized flat panel. Further issues comprise of an intuitive disconnect between the perceived merits of polar plots and the numerical value of coefficients derived from the plots.

Scalable Track Initiation for Optical Space Surveillance

DTIC Science & Technology

2012-09-01

orbital elements. Descartes ’ rule of signs tells us the number of positive real roots. If the third coefficient in the quadratic form (3) is...specified intervals of the orbital elements. Assuming that we have real roots in equation (8), we use Descartes ’ rule of signs to determine the number

On Partial Fraction Decompositions by Repeated Polynomial Divisions

ERIC Educational Resources Information Center

Man, Yiu-Kwong

2017-01-01

We present a method for finding partial fraction decompositions of rational functions with linear or quadratic factors in the denominators by means of repeated polynomial divisions. This method does not involve differentiation or solving linear equations for obtaining the unknown partial fraction coefficients, which is very suitable for either…

About the Atlantic RTOFS

Science.gov Websites

Quadratic bottom friction coefficient: 0.003 Bottom boundary layer thickness: 10 m EMC/MMAB Information . Provide seamless boundary and initial conditions to regional ocean physical and biogeochemical models RTOFS. Their report is available here (pdf). Model Configuration The dynamical model is HYCOM. The model

Modelling the breeding of Aedes Albopictus species in an urban area in Pulau Pinang using polynomial regression

NASA Astrophysics Data System (ADS)

Salleh, Nur Hanim Mohd; Ali, Zalila; Noor, Norlida Mohd.; Baharum, Adam; Saad, Ahmad Ramli; Sulaiman, Husna Mahirah; Ahmad, Wan Muhamad Amir W.

2014-07-01

Polynomial regression is used to model a curvilinear relationship between a response variable and one or more predictor variables. It is a form of a least squares linear regression model that predicts a single response variable by decomposing the predictor variables into an nth order polynomial. In a curvilinear relationship, each curve has a number of extreme points equal to the highest order term in the polynomial. A quadratic model will have either a single maximum or minimum, whereas a cubic model has both a relative maximum and a minimum. This study used quadratic modeling techniques to analyze the effects of environmental factors: temperature, relative humidity, and rainfall distribution on the breeding of Aedes albopictus, a type of Aedes mosquito. Data were collected at an urban area in south-west Penang from September 2010 until January 2011. The results indicated that the breeding of Aedes albopictus in the urban area is influenced by all three environmental characteristics. The number of mosquito eggs is estimated to reach a maximum value at a medium temperature, a medium relative humidity and a high rainfall distribution.

Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs. NBER Working Paper No. 20405

ERIC Educational Resources Information Center

Gelman, Andrew; Imbens, Guido

2014-01-01

It is common in regression discontinuity analysis to control for high order (third, fourth, or higher) polynomials of the forcing variable. We argue that estimators for causal effects based on such methods can be misleading, and we recommend researchers do not use them, and instead use estimators based on local linear or quadratic polynomials or…

Influence of salinity and temperature on acute toxicity of cadmium to Mysidopsis bahia molenock

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

Voyer, R.A.; Modica, G.

1990-01-01

Acute toxicity tests were conducted to compare estimates of toxicity, as modified by salinity and temperature, based on response surface techniques with those derived using conventional test methods, and to compare effect of a single episodic exposure to cadmium as a function of salinity with that of continuous exposure. Regression analysis indicated that mortality following continuous 96-hr exposure is related to linear and quadratic effects of salinity and cadmium at 20 C, and to the linear and quadratic effects of cadmium only at 25C. LC50s decreased with increases in temperature and decreases in salinity. Based on the regression model developed,more » 96-hr LC50s ranged from 15.5 to 28.0 micro Cd/L at 10 and 30% salinities, respectively, at 25C; and from 47 to 85 microgram Cd/L at these salinities at 20C.« less

Retrieve polarization aberration from image degradation: a new measurement method in DUV lithography

NASA Astrophysics Data System (ADS)

Xiang, Zhongbo; Li, Yanqiu

2017-10-01

Detailed knowledge of polarization aberration (PA) of projection lens in higher-NA DUV lithographic imaging is necessary due to its impact to imaging degradations, and precise measurement of PA is conductive to computational lithography techniques such as RET and OPC. Current in situ measurement method of PA thorough the detection of degradations of aerial images need to do linear approximation and apply the assumption of 3-beam/2-beam interference condition. The former approximation neglects the coupling effect of the PA coefficients, which would significantly influence the accuracy of PA retrieving. The latter assumption restricts the feasible pitch of test masks in higher-NA system, conflicts with the Kirhhoff diffraction model of test mask used in retrieving model, and introduces 3D mask effect as a source of retrieving error. In this paper, a new in situ measurement method of PA is proposed. It establishes the analytical quadratic relation between the PA coefficients and the degradations of aerial images of one-dimensional dense lines in coherent illumination through vector aerial imaging, which does not rely on the assumption of 3-beam/2- beam interference and linear approximation. In this case, the retrieval of PA from image degradation can be convert from the nonlinear system of m-quadratic equations to a multi-objective quadratic optimization problem, and finally be solved by nonlinear least square method. Some preliminary simulation results are given to demonstrate the correctness and accuracy of the new PA retrieving model.

Application of Statistic Experimental Design to Assess the Effect of Gammairradiation Pre-Treatment on the Drying Characteristics and Qualities of Wheat

NASA Astrophysics Data System (ADS)

Yu, Yong; Wang, Jun

Wheat, pretreated by 60Co gamma irradiation, was dried by hot-air with irradiation dosage 0-3 kGy, drying temperature 40-60 °C, and initial moisture contents 19-25% (drying basis). The drying characteristics and dried qualities of wheat were evaluated based on drying time, average dehydration rate, wet gluten content (WGC), moisture content of wet gluten (MCWG)and titratable acidity (TA). A quadratic rotation-orthogonal composite experimental design, with three variables (at five levels) and five response functions, and analysis method were employed to study the effect of three variables on the individual response functions. The five response functions (drying time, average dehydration rate, WGC, MCWG, TA) correlated with these variables by second order polynomials consisting of linear, quadratic and interaction terms. A high correlation coefficient indicated the suitability of the second order polynomial to predict these response functions. The linear, interaction and quadratic effects of three variables on the five response functions were all studied.

de la Vallée-Poussin means of Fourier series for the quadratic spectrum and for spectra with power-like density

NASA Astrophysics Data System (ADS)

Bochkarev, S. V.

2014-02-01

A new method is proposed and elaborated for investigating complex or real trigonometric series with various spectra. It is based on new multiplicative inequalities which give a lower bound for the integral norm of the de la Vallée-Poussin means and are themselves based on results establishing corresponding analogues of the Littlewood-Paley theorem in the BMO, Hardy, and Lorentz spaces. For spectra with power-like density a description of the class of absolute values of coefficients such that the corresponding complex or real trigonometric series are Fourier series is found which depends on the arithmetic characteristics of the spectrum and is sharp in limiting cases. Furthermore, for the quadratic spectrum some results of Hardy and Littlewood on elliptic theta functions are generalized and refined. For the quadratic spectrum and power-like spectra with non-integer exponents new lower bounds are found for the integral norms of exponential sums. Bibliography: 41 titles.

Quadratic Electro-optic Effect in a Novel Nano-optical Polymer (iodine-doped polyisoprene)

NASA Astrophysics Data System (ADS)

Swamy, Rajendra; Titus, Jitto; Thakur, Mrinal

2004-03-01

In this report, exceptionally large quadratic electro-optic effect in a novel nano-optical polymer will be discussed. The material involved is cis-1,4-polyisoprene or natural rubber which is a nonconjugated conductive polymer[1,2].Upon doping with an acceptor such as iodine, an electron is transferred from its isolated double bond to the dopant leading to a charge-transfer complex. The positive charge (hole) thus created is localized around the double-bond site, within a nanometer dimension - thus, forming a nano-optical material. The quadratic electro-optic measurement on the doped polyisoprene film was made using field-induced birefringence method. The measured Kerr coefficient is about sixty six times that of nitrobenzene at 632 nm. Significant electroabsorption was also observed in this material at 632 nm. 1. M. Thakur, J. Macromol. Sci. - PAC, 2001, A38(12), 1337. 2. M. Thakur, S. Khatavkar and E.J. Parish, J. Macromol. Sci. - PAC, 2003, A40 (12), 1397.

Nutrient Digestibility and Metabolizable Energy Content of Mucuna pruriens Whole Pods Fed to Growing Pelibuey Lambs.

PubMed

Loyra-Tzab, Enrique; Sarmiento-Franco, Luis Armando; Sandoval-Castro, Carlos Alfredo; Santos-Ricalde, Ronald Herve

2013-07-01

The nutrient digestibility, nitrogen balance and in vivo metabolizable energy supply of Mucuna pruriens whole pods fed to growing Pelibuey lambs was investigated. Eight Pelibuey sheep housed in metabolic crates were fed increasing levels of Mucuna pruriens pods: 0 (control), 100 (Mucuna100), 200 (Mucuna200) and 300 (Mucuna300) g/kg dry matter. A quadratic (p<0.002) effect was observed for dry matter (DM), neutral detergent fibre (aNDF), nitrogen (N) and gross energy (GE) intakes with higher intakes in the Mucuna100 and Mucuna200 treatments. Increasing M. pruriens in the diets had no effect (p>0.05) on DM and GE apparent digestibility (p<0.05). A linear reduction in N digestibility and N retention was observed with increasing mucuna pod level. This effect was accompanied by a quadratic effect (p<0.05) on fecal-N and N-balance which were higher in the Mucuna100 and Mucuna200 treatments. Urine-N excretion, GE retention and dietary estimated nutrient supply (metabolizable protein and metabolizable energy) were not affected (p>0.05). DM, N and GE apparent digestibility coefficient of M. pruriens whole pods obtained through multiple regression equations were 0.692, 0.457, 0.654 respectively. In vivo DE and ME content of mucuna whole pod were estimated in 11.0 and 9.7 MJ/kg DM. It was concluded that whole pods from M. pruriens did not affect nutrient utilization when included in an mixed diet up to 200 g/kg DM. This is the first in vivo estimation of mucuna whole pod ME value for ruminants.

Polynomials to model the growth of young bulls in performance tests.

PubMed

Scalez, D C B; Fragomeni, B O; Passafaro, T L; Pereira, I G; Toral, F L B

2014-03-01

The use of polynomial functions to describe the average growth trajectory and covariance functions of Nellore and MA (21/32 Charolais+11/32 Nellore) young bulls in performance tests was studied. The average growth trajectories and additive genetic and permanent environmental covariance functions were fit with Legendre (linear through quintic) and quadratic B-spline (with two to four intervals) polynomials. In general, the Legendre and quadratic B-spline models that included more covariance parameters provided a better fit with the data. When comparing models with the same number of parameters, the quadratic B-spline provided a better fit than the Legendre polynomials. The quadratic B-spline with four intervals provided the best fit for the Nellore and MA groups. The fitting of random regression models with different types of polynomials (Legendre polynomials or B-spline) affected neither the genetic parameters estimates nor the ranking of the Nellore young bulls. However, fitting different type of polynomials affected the genetic parameters estimates and the ranking of the MA young bulls. Parsimonious Legendre or quadratic B-spline models could be used for genetic evaluation of body weight of Nellore young bulls in performance tests, whereas these parsimonious models were less efficient for animals of the MA genetic group owing to limited data at the extreme ages.

The National Tumor Association Foundation (ANT): A 30 year old model of home palliative care

PubMed Central

2010-01-01

Background Models of palliative care delivery develop within a social, cultural, and political context. This paper describes the 30-year history of the National Tumor Association (ANT), a palliative care organization founded in the Italian province of Bologna, focusing on this model of home care for palliative cancer patients and on its evaluation. Methods Data were collected from the 1986-2008 ANT archives and documents from the Emilia-Romagna Region Health Department, Italy. Outcomes of interest were changed in: number of patients served, performance status at admission (Karnofsky Performance Status score [KPS]), length of participation in the program (days of care provided), place of death (home vs. hospital/hospice), and satisfaction with care. Statistical methods included linear and quadratic regressions. A linear and a quadratic regressions were generated; the independent variable was the year, while the dependent one was the number of patients from 1986 to 2008. Two linear regressions were generated for patients died at home and in the hospital, respectively. For each regression, the R square, the unstandardized and standardized coefficients and related P-values were estimated. Results The number of patients served by ANT has increased continuously from 131 (1986) to a cumulative total of 69,336 patients (2008), at a steady rate of approximately 121 additional patients per year and with no significant gender difference. The annual number of home visits increased from 6,357 (1985) to 904,782 (2008). More ANT patients died at home than in hospice or hospital; this proportion increased from 60% (1987) to 80% (2007). The rate of growth in the number of patients dying in hospital/hospice was approximately 40 patients/year (p < 0.01), vs. approximately 177 patients/year for patients who died at home. The percentage of patients with KPS < 40 at admission decreased from 70% (2003) to 30% (2008); the percentage of patients with KPS > 40 increased. Mean days of care for patients with KPS > 40 exceeded mean days for patients with KPS < 40 (p < 0.001). Patients and caregivers reported high satisfaction with care in each year of assessment; in 2008, among 187 interviewed caregivers, 95% judged the quality of doctors' assistance, and 91% judged the quality of nurses' assistance, to be "optimal." Conclusions The ANT home care model of palliative care delivery has been well-received, with progressively growing numbers of patients served. It has resulted in a greater proportion of home deaths and in patients' accessing palliative care at an earlier point in the disease trajectory. Changes in ANT chronicle palliative care trends in general. PMID:20529310

Measurement of true ileal phosphorus digestibility in meat and bone meal for broiler chickens.

PubMed

Mutucumarana, R K; Ravindran, V; Ravindran, G; Cowieson, A J

2015-07-01

An experiment was conducted to estimate true ileal phosphorus (P:) digestibility of 3 meat and bone meal samples (MBM-1, MBM-2: , and MBM-3:) for broiler chickens. Four semipurified diets were formulated from each sample to contain graded concentrations of P. The experiment was conducted as a completely randomized design with 6 replicates (6 birds per replicate) per dietary treatment. A total of 432 Ross 308 broilers were assigned at 21 d of age to the 12 test diets. The apparent ileal digestibility coefficient of P was determined by the indicator method, and the linear regression method was used to determine the true P digestibility coefficient. The apparent ileal digestibility coefficient of P in birds fed diets containing MBM-1 and MBM-2 was unaffected by increasing dietary concentrations of P (P > 0.05). The apparent ileal digestibility coefficient of P in birds fed the MBM-3 diets decreased with increasing P concentrations (linear, P < 0.001; quadratic, P < 0. 01). In birds fed the MBM-1 and MBM-2 diets, ileal endogenous P losses were estimated to be 0.049 and 0.142 g/kg DM intake (DMI:), respectively. In birds fed the MBM-3 diets, endogenous P loss was estimated to be negative (-0.370 g/kg DMI). True ileal P digestibility of MBM-1, MBM-2, and MBM-3 was determined to be 0.693, 0.608, and 0.420, respectively. True ileal P digestibility coefficients determined for MBM-1 and MBM-2 were similar (P < 0.05), but were higher (P < 0.05) than that for MBM-3. Total P and true digestible P contents of MBM-1, MBM-2, and MBM-3 were determined to be 37.5 and 26.0; 60.2 and 36.6; and 59.8 and 25.1 g/kg, respectively, on an as-fed basis. © 2015 Poultry Science Association Inc.

Ridge: a computer program for calculating ridge regression estimates

Treesearch

Donald E. Hilt; Donald W. Seegrist

1977-01-01

Least-squares coefficients for multiple-regression models may be unstable when the independent variables are highly correlated. Ridge regression is a biased estimation procedure that produces stable estimates of the coefficients. Ridge regression is discussed, and a computer program for calculating the ridge coefficients is presented.

Arbitrary-order corrections for finite-time drift and diffusion coefficients

NASA Astrophysics Data System (ADS)

Anteneodo, C.; Riera, R.

2009-09-01

We address a standard class of diffusion processes with linear drift and quadratic diffusion coefficients. These contributions to dynamic equations can be directly drawn from data time series. However, real data are constrained to finite sampling rates and therefore it is crucial to establish a suitable mathematical description of the required finite-time corrections. Based on Itô-Taylor expansions, we present the exact corrections to the finite-time drift and diffusion coefficients. These results allow to reconstruct the real hidden coefficients from the empirical estimates. We also derive higher-order finite-time expressions for the third and fourth conditional moments that furnish extra theoretical checks for this class of diffusion models. The analytical predictions are compared with the numerical outcomes of representative artificial time series.

Non-ideal Solution Thermodynamics of Cytoplasm

PubMed Central

Ross-Rodriguez, Lisa U.; McGann, Locksley E.

2012-01-01

Quantitative description of the non-ideal solution thermodynamics of the cytoplasm of a living mammalian cell is critically necessary in mathematical modeling of cryobiology and desiccation and other fields where the passive osmotic response of a cell plays a role. In the solution thermodynamics osmotic virial equation, the quadratic correction to the linear ideal, dilute solution theory is described by the second osmotic virial coefficient. Herein we report, for the first time, intracellular solution second osmotic virial coefficients for four cell types [TF-1 hematopoietic stem cells, human umbilical vein endothelial cells (HUVEC), porcine hepatocytes, and porcine chondrocytes] and further report second osmotic virial coefficients indistinguishable from zero (for the concentration range studied) for human hepatocytes and mouse oocytes. PMID:23840923

Phase lag control of tidally reversing mega-ripple geometry and bed stress in tidal inlets

NASA Astrophysics Data System (ADS)

Traykovski, P.

2016-02-01

Recent observations in the Columbia River Mouth, New River Inlet, and Wasque Shoals have shown that tidally reversing mega-ripples are an ubiquitous bedform morphology in energetic tidal inlets. As the name implies, these bedforms reverse asymmetry and migration direction in each half tidal cycle. With wavelengths of 2 to 5 m and heights of 0.2 to 0.5 m, these bedforms are larger than current formed ripples, but smaller than dunes. Unlike dunes which have a depth dependent geometry, observations indicate the tidally reversing mega-ripples geometry is related to the time dependent tidal flow and independent of depth. Previous empirical relations for predicting the geometry of ripples or dunes do not successfully predict the geometry of these features. A time dependent geometric model was developed that accounts for the reversal of migration and asymmetry to successfully predict bedform geometry. The model requires sufficient sediment transport in each half tidal cycle to reverse the asymmetry before the bedforms begin to grow. Both the observations and model indicate that the complete reversal of asymmetry and development of a steep lee face occurs near or after maximum flow in each half tidal cycle. This phase lag in bedform response to tidal forcing also has important implications for bed stress in tidal inlets. Observations of frictional drag in the Columbia River mouth based on a tidal momentum balance of surface slope over 10 km regressed against quadratic near bed velocity show drag coefficients that fall off as CD U-1.4. Reynolds stress measurements performed using the dual ADV differencing technique show similar relations. The Reynolds stress measurements also show a dramatic asymmetry between accelerating flows and decelerating flows with a factor of 5 increase during deceleration. Pulse coherent Doppler profiles of near bed turbulence indicate that the turbulence is dominated by energetic fluctuations in separation zones downstream of steep lee faces. The phase lag of the bedform evolution, whereby steep lee faces are only present in the decelerating phase of the tidal cycle, provides an explanation for the asymmetry and non-quadratic behavior of the drag coefficients.

Implicit Wiener series analysis of epileptic seizure recordings.

PubMed

Barbero, Alvaro; Franz, Matthias; van Drongelen, Wim; Dorronsoro, José R; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2009-01-01

Implicit Wiener series are a powerful tool to build Volterra representations of time series with any degree of non-linearity. A natural question is then whether higher order representations yield more useful models. In this work we shall study this question for ECoG data channel relationships in epileptic seizure recordings, considering whether quadratic representations yield more accurate classifiers than linear ones. To do so we first show how to derive statistical information on the Volterra coefficient distribution and how to construct seizure classification patterns over that information. As our results illustrate, a quadratic model seems to provide no advantages over a linear one. Nevertheless, we shall also show that the interpretability of the implicit Wiener series provides insights into the inter-channel relationships of the recordings.

Rate of convergence of k-step Newton estimators to efficient likelihood estimators

Treesearch

Steve Verrill

2007-01-01

We make use of Cramer conditions together with the well-known local quadratic convergence of Newton?s method to establish the asymptotic closeness of k-step Newton estimators to efficient likelihood estimators. In Verrill and Johnson [2007. Confidence bounds and hypothesis tests for normal distribution coefficients of variation. USDA Forest Products Laboratory Research...

Modeling parameters that characterize pacing of elite female 800-m freestyle swimmers.

PubMed

Lipińska, Patrycja; Allen, Sian V; Hopkins, Will G

2016-01-01

Pacing offers a potential avenue for enhancement of endurance performance. We report here a novel method for characterizing pacing in 800-m freestyle swimming. Websites provided 50-m lap and race times for 192 swims of 20 elite female swimmers between 2000 and 2013. Pacing for each swim was characterized with five parameters derived from a linear model: linear and quadratic coefficients for effect of lap number, reductions from predicted time for first and last laps, and lap-time variability (standard error of the estimate). Race-to-race consistency of the parameters was expressed as intraclass correlation coefficients (ICCs). The average swim was a shallow negative quadratic with slowest time in the eleventh lap. First and last laps were faster by 6.4% and 3.6%, and lap-time variability was ±0.64%. Consistency between swimmers ranged from low-moderate for the linear and quadratic parameters (ICC = 0.29 and 0.36) to high for the last-lap parameter (ICC = 0.62), while consistency for race time was very high (ICC = 0.80). Only ~15% of swimmers had enough swims (~15 or more) to provide reasonable evidence of optimum parameter values in plots of race time vs. each parameter. The modest consistency of most of the pacing parameters and lack of relationships between parameters and performance suggest that swimmers usually compensated for changes in one parameter with changes in another. In conclusion, pacing in 800-m elite female swimmers can be characterized with five parameters, but identifying an optimal pacing profile is generally impractical.

Measurement of pediatric regional cerebral blood flow from 6 months to 15 years of age in a clinical population.

PubMed

Carsin-Vu, Aline; Corouge, Isabelle; Commowick, Olivier; Bouzillé, Guillaume; Barillot, Christian; Ferré, Jean-Christophe; Proisy, Maia

2018-04-01

To investigate changes in cerebral blood flow (CBF) in gray matter (GM) between 6 months and 15 years of age and to provide CBF values for the brain, GM, white matter (WM), hemispheres and lobes. Between 2013 and 2016, we retrospectively included all clinical MRI examinations with arterial spin labeling (ASL). We excluded subjects with a condition potentially affecting brain perfusion. For each subject, mean values of CBF in the brain, GM, WM, hemispheres and lobes were calculated. GM CBF was fitted using linear, quadratic and cubic polynomial regression against age. Regression models were compared with Akaike's information criterion (AIC), and Likelihood Ratio tests. 84 children were included (44 females/40 males). Mean CBF values were 64.2 ± 13.8 mL/100 g/min in GM, and 29.3 ± 10.0 mL/100 g/min in WM. The best-fit model of brain perfusion was the cubic polynomial function (AIC = 672.7, versus respectively AIC = 673.9 and AIC = 674.1 with the linear negative function and the quadratic polynomial function). A statistically significant difference between the tested models demonstrating the superiority of the quadratic (p = 0.18) or cubic polynomial model (p = 0.06), over the negative linear regression model was not found. No effect of general anesthesia (p = 0.34) or of gender (p = 0.16) was found. we provided values for ASL CBF in the brain, GM, WM, hemispheres, and lobes over a wide pediatric age range, approximately showing inverted U-shaped changes in GM perfusion over the course of childhood. Copyright © 2018 Elsevier B.V. All rights reserved.

Quadratic Polynomial Regression using Serial Observation Processing:Implementation within DART

NASA Astrophysics Data System (ADS)

Hodyss, D.; Anderson, J. L.; Collins, N.; Campbell, W. F.; Reinecke, P. A.

2017-12-01

Many Ensemble-Based Kalman ltering (EBKF) algorithms process the observations serially. Serial observation processing views the data assimilation process as an iterative sequence of scalar update equations. What is useful about this data assimilation algorithm is that it has very low memory requirements and does not need complex methods to perform the typical high-dimensional inverse calculation of many other algorithms. Recently, the push has been towards the prediction, and therefore the assimilation of observations, for regions and phenomena for which high-resolution is required and/or highly nonlinear physical processes are operating. For these situations, a basic hypothesis is that the use of the EBKF is sub-optimal and performance gains could be achieved by accounting for aspects of the non-Gaussianty. To this end, we develop here a new component of the Data Assimilation Research Testbed [DART] to allow for a wide-variety of users to test this hypothesis. This new version of DART allows one to run several variants of the EBKF as well as several variants of the quadratic polynomial lter using the same forecast model and observations. Dierences between the results of the two systems will then highlight the degree of non-Gaussianity in the system being examined. We will illustrate in this work the differences between the performance of linear versus quadratic polynomial regression in a hierarchy of models from Lorenz-63 to a simple general circulation model.

Sex-specific nonlinear associations between serum lipids and different domains of cognitive function in middle to older age individuals.

PubMed

Lu, Yanhui; An, Yu; Yu, Huanling; Che, Fengyuan; Zhang, Xiaona; Rong, Hongguo; Xi, Yuandi; Xiao, Rong

2017-08-01

To examine how serum lipids relates to specific cognitive ability domains between the men and women in Chinese middle to older age individuals. A complete lipid panel was obtained from 1444 individuals, ages 50-65, who also underwent a selection of cognitive tests. Participants were 584 men and 860 women from Linyi city, Shandong province. Multiple linear regression analyses examined serum lipids level as quadratic predictors of sex-specific measure of performance in different cognitive domains, which were adjusted for sociodemographic and lifestyle characteristics. In men, a significant quadratic effect of total cholesterol (TC) was identified for Digit Symbol (B = -0.081, P = 0.044) and also quadratic effect of low density lipoprotein-cholesterol (LDL-C) was identified for Trail Making Test B (B = -0.082, P = 0.045). Differently in women, there were significant quadratic associations between high density lipoprotein-cholesterol (HDL-C) and multiple neuropsychological tests. The nonlinear lipid-cognition associations differed between men and women and were specific to certain cognitive domains and might be of potential relevance for prevention and therapy of cognitive decline.

A comparison of two gears for quantifying abundance of lotic-dwelling crayfish

USGS Publications Warehouse

Williams, Kristi; Brewer, Shannon K.; Ellersieck, Mark R.

2014-01-01

Crayfish (saddlebacked crayfish, Orconectes medius) catch was compared using a kick seine applied two different ways with a 1-m2 quadrat sampler (with known efficiency and bias in riffles) from three small streams in the Missouri Ozarks. Triplicate samples (one of each technique) were taken from two creeks and one headwater stream (n=69 sites) over a two-year period. General linear mixed models showed the number of crayfish collected using the quadrat sampler was greater than the number collected using either of the two seine techniques. However, there was no significant interaction with gear suggesting year, stream size, and channel unit type did not relate to different catches of crayfish by gear type. Variation in catch among gears was similar, as was the proportion of young-of-year individuals across samples taken with different gears or techniques. Negative binomial linear regression provided the appropriate relation between the gears which allows correction factors to be applied, if necessary, to relate catches by the kick seine to those of the quadrat sampler. The kick seine appears to be a reasonable substitute to the quadrat sampler in these shallow streams, with the advantage of ease of use and shorter time required per sample.

Biophysical characterization of a swimmer with a unilateral arm amputation: a case study.

PubMed

Figueiredo, Pedro; Willig, Renata; Alves, Francisco; Vilas-Boas, João Paulo; Fernandes, Ricardo J

2014-11-01

To examine the effect of swimming speed (v) on the biomechanical and physiological responses of a trained front-crawl swimmer with a unilateral arm amputation. A 13-y-old girl with a unilateral arm amputation (level of the elbow) was tested for stroke length (SL, horizontal displacement cover with each stroke cycle), stroke frequency (SF, inverse of the time to complete each stroke cycle), adapted index of coordination (IdCadapt, lag time between propulsive phases), intracycle velocity variation (IVV, coefficient of variation of the instantaneous velocity-time data), active drag (D, hydrodynamic resistance), and energy cost (C, ratio of metabolic power to speed) during trials of increasing v. Swimmer data showed a positive relationship between v and SF (R² = 1, P < .001), IVV (R² = .98, P = .002), D (R² = .98, P < .001), and C (R² = .95, P = .001) and a negative relationship with the SL (R² = .99, P = .001). No relation was found between v and IdCadapt (R² = .35, P = .22). A quadratic regression best fitted the relationship between v and general kinematical parameters (SL and SF); a cubic relationship fit the IVV best. The relationship between v and D was best expressed by a power regression, and the linear regression fit the C and IdCadapt best. The subject's adaptation to increased v was different from able-bodied swimmers, mainly on interarm coordination, maintaining the lag time between propulsive phases, which influence the magnitude of the other parameters. These results might be useful to develop specific training and enhance swimming performance in swimmers with amputations.

Photocatalytic water splitting over titania supported copper and nickel oxide in photoelectrochemical cell; optimization of photoconversion efficiency

NASA Astrophysics Data System (ADS)

Muti Mohamed, Norani; Bashiri, Robabeh; Kait, Chong Fai; Sufian, Suriati

2018-04-01

we investigated the influence of fluctuating the preparation variables of TiO2 on the efficiency of photocatalytic water splitting in photoelectrochemical (PEC) cell. Hydrothermal associated sol-gel technique was applied to synthesis modified TiO2 with nickel and copper oxide. The variation of water (mL), acid (mL) and total metal loading (%) were mathematically modelled using central composite design (CCD) from the response surface method (RSM) to explore the single and combined effects of parameters on the system performance. The experimental data were fitted using quadratic polynomial regression model from analysis of variance (ANOVA). The coefficient of determination value of 98% confirms the linear relationship between the experimental and predicted values. The amount of water had maximum effect on the photoconversion efficiency due to a direct effect on the crystalline and the number of defects on the surface of photocatalyst. The optimal parameter ratios with maximum photoconversion efficiency were 16 mL, 3 mL and 5 % for water, acid and total metal loading, respectively.

Neural Modeling of Fuzzy Controllers for Maximum Power Point Tracking in Photovoltaic Energy Systems

NASA Astrophysics Data System (ADS)

Lopez-Guede, Jose Manuel; Ramos-Hernanz, Josean; Altın, Necmi; Ozdemir, Saban; Kurt, Erol; Azkune, Gorka

2018-06-01

One field in which electronic materials have an important role is energy generation, especially within the scope of photovoltaic energy. This paper deals with one of the most relevant enabling technologies within that scope, i.e, the algorithms for maximum power point tracking implemented in the direct current to direct current converters and its modeling through artificial neural networks (ANNs). More specifically, as a proof of concept, we have addressed the problem of modeling a fuzzy logic controller that has shown its performance in previous works, and more specifically the dimensionless duty cycle signal that controls a quadratic boost converter. We achieved a very accurate model since the obtained medium squared error is 3.47 × 10-6, the maximum error is 16.32 × 10-3 and the regression coefficient R is 0.99992, all for the test dataset. This neural implementation has obvious advantages such as a higher fault tolerance and a simpler implementation, dispensing with all the complex elements needed to run a fuzzy controller (fuzzifier, defuzzifier, inference engine and knowledge base) because, ultimately, ANNs are sums and products.

Mortality trends due to chronic obstructive pulmonary disease in Brazil.

PubMed

Graudenz, Gustavo Silveira; Gazotto, Gabriel Pereira

2014-01-01

The purpose of this study was to update and analyze data on mortality trend due to chronic obstructive pulmonary disease (COPD) in Brazil. Initially, the specific COPD mortality rates were calculated from 1989 to 2009 using data collected from DATASUS (Departamento de Informática do SUS - Brazilian Health System Database). Then, the polynomial regression models from the observed functional relation were estimated based on mortality coefficients and study years. We verified that the general mortality rates due to COPD in Brazil showed an increasing trend from 1989 to 2004, and then decreased. Both genders showed the same increasing tendencies until 2004 and decreased thereafter. The age group under 35 years old showed a linear decreasing trend. All other age groups showed quadratic tendencies, with increases until the years of 1998-1999 and then decreasing. The South and Southeast regions showed the highest COPD mortality rates with increasing trends until the years 2001-2002 and then decreased. The North, Northeast and Central-West regions showed lower mortality rates but increasing trend. This is the first report of COPD mortality stabilization in Brazil since 1980.

The impact of dietary protein levels on nutrient digestibility and water and nitrogen balances in eventing horses.

PubMed

Oliveira, C A A; Azevedo, J F; Martins, J A; Barreto, M P; Silva, V P; Julliand, V; Almeida, F Q

2015-01-01

This study was performed to evaluate the impact of dietary protein levels on nutrient digestibility and water and nitrogen balances in conditioning eventing horses. Twenty-four Brazilian Sport Horses, male and female (8.0 to 15.0 yr; 488 ± 32 kg BW), were used in a randomized design with 4 levels of CP diets: 7.5%, 9.0%, 11.0%, and 13.0%. A digestion assay was performed with partial feces collection over 4 d, followed by 1 d of total urine collection. Data were submitted to regression analysis and adjusted to linear and quadratic models (P < 0.05). No differences were observed in the intake of DM, OM, EE, ADF, and NDF as a function of dietary protein levels. Dry matter intake average was 1.7% of BW. CP and N intake showed a linear increase as a function of increasing protein level in diets. A quadratic response (P < 0.05) was observed on the CP and NDF digestibility coefficients, with the maximum estimated level of digestibility at 11.6% and 11.4% CP in the diet, respectively. There was a linear effect on ADF digestibility coefficients, digestible DM and protein intake, and CP/DE ratio according to dietary protein levels. There was no impact of dietary protein levels on daily water intake, total water intake, or fecal water excretion. Urinary excretion values showed a linear increase in response to increased dietary protein levels, but no impact was observed on water balance, with an average of 8.4 L/d. Nitrogen intake (NI), N absorption (NA), and urinary N increased linearly as a function of increasing dietary protein levels. There was no impact of dietary protein levels on N retention (NR), with an average of 7.5 g N/d. Nitrogen retention as a percentage of NI or NA showed no significant changes in the function of dietary protein levels. There was an impact of dietary protein levels on the digestibility coefficient of CP, NDF, ADF, and digestible protein intake on conditioning eventing horses. The 11.6% CP level in the diet provided an intake of 2.25 g CP/kg BW and 0.37 g N/kg BW, and this intake was the most appropriate for the conditioning of intensely exercised horses, considering the responses related to NI, NA, and the estimated NR to NA ratio. The NDF and ADF responses indicated that dietary fiber was more digested with an increased amount of N in the digestive tract.

Support Vector Machine algorithm for regression and classification

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

Yu, Chenggang; Zavaljevski, Nela

2001-08-01

The software is an implementation of the Support Vector Machine (SVM) algorithm that was invented and developed by Vladimir Vapnik and his co-workers at AT&T Bell Laboratories. The specific implementation reported here is an Active Set method for solving a quadratic optimization problem that forms the major part of any SVM program. The implementation is tuned to specific constraints generated in the SVM learning. Thus, it is more efficient than general-purpose quadratic optimization programs. A decomposition method has been implemented in the software that enables processing large data sets. The size of the learning data is virtually unlimited by themore » capacity of the computer physical memory. The software is flexible and extensible. Two upper bounds are implemented to regulate the SVM learning for classification, which allow users to adjust the false positive and false negative rates. The software can be used either as a standalone, general-purpose SVM regression or classification program, or be embedded into a larger software system.« less

[Effects of fundamental frequency and speech rate on impression formation].

PubMed

Uchida, Teruhisa; Nakaune, Naoko

2004-12-01

This study investigated the systematic relationship between nonverbal features of speech and personality trait ratings of the speaker. In Study 1, fundamental frequency (F0) in original speech was converted into five levels from 64% to 156.25%. Then 132 undergraduates rated each of the converted speeches in terms of personality traits. In Study 2 134 undergraduates similarly rated the speech stimuli, which had five speech rate levels as well as two F0 levels. Results showed that listener ratings along Big Five dimensions were mostly independent. Each dimension had a slightly different change profile over the five levels of F0 and speech rate. A quadratic regression equation provided a good approximation for each rating as a function of F0 or speech rate. The quadratic regression equations put together would provide us with a rough estimate of personality trait impression as a function of prosodic features. The functional relationship among F0, speech rate, and trait ratings was shown as a curved surface in the three-dimensional space.

Fractional-order Fourier analysis for ultrashort pulse characterization.

PubMed

Brunel, Marc; Coetmellec, Sébastien; Lelek, Mickael; Louradour, Frédéric

2007-06-01

We report what we believe to be the first experimental demonstration of ultrashort pulse characterization using fractional-order Fourier analysis. The analysis is applied to the interpretation of spectral interferometry resolved in time (SPIRIT) traces [which are spectral phase interferometry for direct electric field reconstruction (SPIDER)-like interferograms]. First, the fractional-order Fourier transformation is shown to naturally allow the determination of the cubic spectral phase coefficient of pulses to be analyzed. A simultaneous determination of both cubic and quadratic spectral phase coefficients of the pulses using the fractional-order Fourier series expansion is further demonstrated. This latter technique consists of localizing relative maxima in a 2D cartography representing decomposition coefficients. It is further used to reconstruct or filter SPIRIT traces.

The Power Coefficient in the Theory of Energy Extraction from Tidal Channels

NASA Astrophysics Data System (ADS)

Cummins, P. F.

2014-12-01

The maximum average power available from a fence of turbines deployed in a tidal channel is given by the simple formula, Ρ=γρgaQmax, where ρga is the amplitude of pressure difference across ends of the channel, Qmax is the maximum volume flux through the channel in the undisturbed state (i.e., before turbines are deployed), and γ is a numerical coefficient. The latter depends only weakly on the underlying dynamical balance of the channel. This is shown to be consequence of quadratic drag and changes to the natural impedance of the channel as deployment of turbines impedes the flow. Additionally, it is shown that the power coefficient γ is relatively insensitive to the form of the turbine drag.

Nutrient Digestibility and Metabolizable Energy Content of Mucuna pruriens Whole Pods Fed to Growing Pelibuey Lambs

PubMed Central

Loyra-Tzab, Enrique; Sarmiento-Franco, Luis Armando; Sandoval-Castro, Carlos Alfredo; Santos-Ricalde, Ronald Herve

2013-01-01

The nutrient digestibility, nitrogen balance and in vivo metabolizable energy supply of Mucuna pruriens whole pods fed to growing Pelibuey lambs was investigated. Eight Pelibuey sheep housed in metabolic crates were fed increasing levels of Mucuna pruriens pods: 0 (control), 100 (Mucuna100), 200 (Mucuna200) and 300 (Mucuna300) g/kg dry matter. A quadratic (p<0.002) effect was observed for dry matter (DM), neutral detergent fibre (aNDF), nitrogen (N) and gross energy (GE) intakes with higher intakes in the Mucuna100 and Mucuna200 treatments. Increasing M. pruriens in the diets had no effect (p>0.05) on DM and GE apparent digestibility (p<0.05). A linear reduction in N digestibility and N retention was observed with increasing mucuna pod level. This effect was accompanied by a quadratic effect (p<0.05) on fecal-N and N-balance which were higher in the Mucuna100 and Mucuna200 treatments. Urine-N excretion, GE retention and dietary estimated nutrient supply (metabolizable protein and metabolizable energy) were not affected (p>0.05). DM, N and GE apparent digestibility coefficient of M. pruriens whole pods obtained through multiple regression equations were 0.692, 0.457, 0.654 respectively. In vivo DE and ME content of mucuna whole pod were estimated in 11.0 and 9.7 MJ/kg DM. It was concluded that whole pods from M. pruriens did not affect nutrient utilization when included in an mixed diet up to 200 g/kg DM. This is the first in vivo estimation of mucuna whole pod ME value for ruminants. PMID:25049876

The critical proportion of immune individuals needed to control hepatitis B

NASA Astrophysics Data System (ADS)

Ospina, Juan; Hincapié-Palacio, Doracelly

2016-05-01

We estimate the critical proportion of immunity (Pc) to control hepatitis B in Medellin - Colombia, based on a random population survey of 2077 individuals of 6-64 years of age. The force of infection (Fi) was estimated according to empirical data of susceptibility by age S(a), assuming a quadratic expression. Parameters were estimated by adjusting data to a nonlinear regression. Fi was defined by -(ds(a)/da)/s(a) and according to the form of the empirical curve S(a) we assume a quadratic expression given by S(a)= Ea2+Ba+C. Then we have the explicit expression for the accumulated Fi by age given by F(a) = -a(Ea+B)/c. The expression of average infection age A is obtained as A = L + EL3/(3C)+BL2/(2C) and the basic reproductive number R0 is obtained as R0 = 1 + 6C/(6C+2EL2+3BL). From the las result we obtain the Pc given by Pc= 6C/(12C+2EL2+3BL). Numerical simulations were performed with the age-susceptibility proportion and initial values (a=0.02, b=20, c=100), obtaining an adjusted coefficient of multiple determination of 64.83%. According to the best estimate, the algebraic expressions for S(a) and the Fi were derived. Using the result of Fi, we obtain A = 30, L =85; R0 CI 95%: 1.42 - 1.64 and Pc: 0-0.29. These results indicate that at the worst case, to maintain control of the disease should be immunes at least 30% of susceptible individuals. Similar results were obtained by sex and residential area.

Estimating biomass of shrubs and forbs in central Washington Douglas-fir stands.

Treesearch

Craig M. Olson; Robert E. Martin

1981-01-01

Understory plants in closed 70-year-old even-aged Douglas-fir stands in north central Washington were destructively sampled to determine the relationship of ground cover and height to dry weight. Weight of plant material can be estimated from the product of plant height and percentage of ground cover on 50- x 100-centimeter (cm) quadrats. Correlation coefficients for...

A study of a diffusive model of asset returns and an empirical analysis of financial markets

NASA Astrophysics Data System (ADS)

Alejandro Quinones, Angel Luis

A diffusive model for market dynamics is studied and the predictions of the model are compared to real financial markets. The model has a non-constant diffusion coefficient which depends both on the asset value and the time. A general solution for the distribution of returns is obtained and shown to match the results of computer simulations for two simple cases, piecewise linear and quadratic diffusion. The effects of discreteness in the market dynamics on the model are also studied. For the quadratic diffusion case, a type of phase transition leading to fat tails is observed as the discrete distribution approaches the continuum limit. It is also found that the model captures some of the empirical stylized facts observed in real markets, including fat-tails and scaling behavior in the distribution of returns. An analysis of empirical data for the EUR/USD currency exchange rate and the S&P 500 index is performed. Both markets show time scaling behavior consistent with a value of 1/2 for the Hurst exponent. Finally, the results show that the distribution of returns for the two markets is well fitted by the model, and the corresponding empirical diffusion coefficients are determined.

LQG control of a deformable mirror adaptive optics system with time-delayed measurements

NASA Astrophysics Data System (ADS)

Anderson, David J.

1991-12-01

This thesis proposes a linear quadratic Gaussian (LQG) control law for a ground-based deformable mirror adaptive optics system. The incoming image wavefront is distorted, primarily in phase, due to the turbulent effects of the earth's atmosphere. The adaptive optics system attempts to compensate for the distortion with a deformable mirror. A Hartman wavefront sensor measures the degree of distortion in the image wavefront. The measurements are input to a Kalman filter which estimates the system states. The state estimates are processed by a linear quadratic regulator which generates the appropriate control voltages to apply to the deformable mirror actuators. The dynamics model for the atmospheric phase distortion consists of 14 Zernike coefficient states; each modeled as a first-order linear time-invariant shaping filter driven by zero-mean white Gaussian noise. The dynamics of the deformable mirror are also model as 14 Zernike coefficients with first-order deterministic dynamics. A significant reduction in total wavefront phase distortion is achieved in the presence of time-delayed measurements. Wavefront sensor sampling rate is the major factor limiting system performance. The Multimode Simulation for Optimal Filter Evaluation (MSOFE) software is the performance evaluation tool of choice for this research.

A contracting-interval program for the Danilewski method. Ph.D. Thesis - Va. Univ.

NASA Technical Reports Server (NTRS)

Harris, J. D.

1971-01-01

The concept of contracting-interval programs is applied to finding the eigenvalues of a matrix. The development is a three-step process in which (1) a program is developed for the reduction of a matrix to Hessenberg form, (2) a program is developed for the reduction of a Hessenberg matrix to colleague form, and (3) the characteristic polynomial with interval coefficients is readily obtained from the interval of colleague matrices. This interval polynomial is then factored into quadratic factors so that the eigenvalues may be obtained. To develop a contracting-interval program for factoring this polynomial with interval coefficients it is necessary to have an iteration method which converges even in the presence of controlled rounding errors. A theorem is stated giving sufficient conditions for the convergence of Newton's method when both the function and its Jacobian cannot be evaluated exactly but errors can be made proportional to the square of the norm of the difference between the previous two iterates. This theorem is applied to prove the convergence of the generalization of the Newton-Bairstow method that is used to obtain quadratic factors of the characteristic polynomial.

A Note on the Relationship between the Number of Indicators and Their Reliability in Detecting Regression Coefficients in Latent Regression Analysis

ERIC Educational Resources Information Center

Dolan, Conor V.; Wicherts, Jelte M.; Molenaar, Peter C. M.

2004-01-01

We consider the question of how variation in the number and reliability of indicators affects the power to reject the hypothesis that the regression coefficients are zero in latent linear regression analysis. We show that power remains constant as long as the coefficient of determination remains unchanged. Any increase in the number of indicators…

A graphical method to evaluate spectral preprocessing in multivariate regression calibrations: example with Savitzky-Golay filters and partial least squares regression.

PubMed

Delwiche, Stephen R; Reeves, James B

2010-01-01

In multivariate regression analysis of spectroscopy data, spectral preprocessing is often performed to reduce unwanted background information (offsets, sloped baselines) or accentuate absorption features in intrinsically overlapping bands. These procedures, also known as pretreatments, are commonly smoothing operations or derivatives. While such operations are often useful in reducing the number of latent variables of the actual decomposition and lowering residual error, they also run the risk of misleading the practitioner into accepting calibration equations that are poorly adapted to samples outside of the calibration. The current study developed a graphical method to examine this effect on partial least squares (PLS) regression calibrations of near-infrared (NIR) reflection spectra of ground wheat meal with two analytes, protein content and sodium dodecyl sulfate sedimentation (SDS) volume (an indicator of the quantity of the gluten proteins that contribute to strong doughs). These two properties were chosen because of their differing abilities to be modeled by NIR spectroscopy: excellent for protein content, fair for SDS sedimentation volume. To further demonstrate the potential pitfalls of preprocessing, an artificial component, a randomly generated value, was included in PLS regression trials. Savitzky-Golay (digital filter) smoothing, first-derivative, and second-derivative preprocess functions (5 to 25 centrally symmetric convolution points, derived from quadratic polynomials) were applied to PLS calibrations of 1 to 15 factors. The results demonstrated the danger of an over reliance on preprocessing when (1) the number of samples used in a multivariate calibration is low (<50), (2) the spectral response of the analyte is weak, and (3) the goodness of the calibration is based on the coefficient of determination (R(2)) rather than a term based on residual error. The graphical method has application to the evaluation of other preprocess functions and various types of spectroscopy data.

Phonation threshold pressure across the pitch range: preliminary test of a model.

PubMed

Solomon, Nancy Pearl; Ramanathan, Pradeep; Makashay, Matthew J

2007-09-01

This study sought to examine the specific relationship between phonation threshold pressure (PTP) and voice fundamental frequency (F(0)) across the pitch range. A published theoretical model of this relationship described a quadratic equation, with PTP increasing exponentially with F(0). Prospective data from eight adults with normal, untrained voices were collected. Subjects produced their quietest phonation at 10 randomly ordered pitches from 5% to 95% of their semitone pitch range at 10% intervals. Analysis included curve fitting for individual and group data, as well as comparisons to the previous model. The group data fit a quadratic function similar to that proposed previously, but the specific quadratic coefficient and constant values differed. Four of the individual subjects' data were best fit by quartic functions, two by quadratic functions, and one by a linear function. This preliminary study indicates that PTP may be minimal at a "comfortable" pitch rather than the lowest pitch tested, and that, for some individuals, PTP may be slightly elevated during the passaggio between modal and falsetto vocal registers. These data support the general form of the theoretical PTP-F(0) function for these speakers, and indicate the possibility of potential refinements to the model. Future studies with larger groups of male and female subjects across a wider age range may eventually reveal the specific nature of the function.

A General Method for Solving Systems of Non-Linear Equations

NASA Technical Reports Server (NTRS)

Nachtsheim, Philip R.; Deiss, Ron (Technical Monitor)

1995-01-01

The method of steepest descent is modified so that accelerated convergence is achieved near a root. It is assumed that the function of interest can be approximated near a root by a quadratic form. An eigenvector of the quadratic form is found by evaluating the function and its gradient at an arbitrary point and another suitably selected point. The terminal point of the eigenvector is chosen to lie on the line segment joining the two points. The terminal point found lies on an axis of the quadratic form. The selection of a suitable step size at this point leads directly to the root in the direction of steepest descent in a single step. Newton's root finding method not infrequently diverges if the starting point is far from the root. However, the current method in these regions merely reverts to the method of steepest descent with an adaptive step size. The current method's performance should match that of the Levenberg-Marquardt root finding method since they both share the ability to converge from a starting point far from the root and both exhibit quadratic convergence near a root. The Levenberg-Marquardt method requires storage for coefficients of linear equations. The current method which does not require the solution of linear equations requires more time for additional function and gradient evaluations. The classic trade off of time for space separates the two methods.

Demonstration of an all-optical feed-forward delay line buffer using the quadratic Stark effect and two-photon absorption in an SOA.

PubMed

Soto, Horacio; Tong, Miriam A; Domínguez, Juan C; Muraoka, Ramón

2017-09-04

We have inserted into an unbiased semiconductor optical amplifier (SOA) a powerful control beam, with photon energy slightly smaller than that of the band-gap of its active region, for exciting two-photon absorption and the quadratic Stark effect. For the available SOA, we estimated these phenomena generated a nonlinear absorption coefficient β= -865 cm/GW and induced an appreciable birefringence inside the amplifier waveguide, which significantly modified the polarization-state of a probe beam. Based on these effects, we have experimentally demonstrated the operation of an all-optical buffer, using an 80 Gb/s optical pulse comb, as well as an unbiased SOA, which was therefore, devoid of amplified spontaneous emission and pattern effects.

DQM: Decentralized Quadratically Approximated Alternating Direction Method of Multipliers

NASA Astrophysics Data System (ADS)

Mokhtari, Aryan; Shi, Wei; Ling, Qing; Ribeiro, Alejandro

2016-10-01

This paper considers decentralized consensus optimization problems where nodes of a network have access to different summands of a global objective function. Nodes cooperate to minimize the global objective by exchanging information with neighbors only. A decentralized version of the alternating directions method of multipliers (DADMM) is a common method for solving this category of problems. DADMM exhibits linear convergence rate to the optimal objective but its implementation requires solving a convex optimization problem at each iteration. This can be computationally costly and may result in large overall convergence times. The decentralized quadratically approximated ADMM algorithm (DQM), which minimizes a quadratic approximation of the objective function that DADMM minimizes at each iteration, is proposed here. The consequent reduction in computational time is shown to have minimal effect on convergence properties. Convergence still proceeds at a linear rate with a guaranteed constant that is asymptotically equivalent to the DADMM linear convergence rate constant. Numerical results demonstrate advantages of DQM relative to DADMM and other alternatives in a logistic regression problem.

Estimation of diffusion coefficients from voltammetric signals by support vector and gaussian process regression

PubMed Central

2014-01-01

Background Support vector regression (SVR) and Gaussian process regression (GPR) were used for the analysis of electroanalytical experimental data to estimate diffusion coefficients. Results For simulated cyclic voltammograms based on the EC, Eqr, and EqrC mechanisms these regression algorithms in combination with nonlinear kernel/covariance functions yielded diffusion coefficients with higher accuracy as compared to the standard approach of calculating diffusion coefficients relying on the Nicholson-Shain equation. The level of accuracy achieved by SVR and GPR is virtually independent of the rate constants governing the respective reaction steps. Further, the reduction of high-dimensional voltammetric signals by manual selection of typical voltammetric peak features decreased the performance of both regression algorithms compared to a reduction by downsampling or principal component analysis. After training on simulated data sets, diffusion coefficients were estimated by the regression algorithms for experimental data comprising voltammetric signals for three organometallic complexes. Conclusions Estimated diffusion coefficients closely matched the values determined by the parameter fitting method, but reduced the required computational time considerably for one of the reaction mechanisms. The automated processing of voltammograms according to the regression algorithms yields better results than the conventional analysis of peak-related data. PMID:24987463

Prediction of random-regression coefficient for daily milk yield after 305 days in milk by using the regression-coefficient estimates from the first 305 days.

PubMed

Yamazaki, Takeshi; Takeda, Hisato; Hagiya, Koichi; Yamaguchi, Satoshi; Sasaki, Osamu

2018-03-13

Because lactation periods in dairy cows lengthen with increasing total milk production, it is important to predict individual productivities after 305 days in milk (DIM) to determine the optimal lactation period. We therefore examined whether the random regression (RR) coefficient from 306 to 450 DIM (M2) can be predicted from those during the first 305 DIM (M1) by using a random regression model. We analyzed test-day milk records from 85690 Holstein cows in their first lactations and 131727 cows in their later (second to fifth) lactations. Data in M1 and M2 were analyzed separately by using different single-trait RR animal models. We then performed a multiple regression analysis of the RR coefficients of M2 on those of M1 during the first and later lactations. The first-order Legendre polynomials were practical covariates of random regression for the milk yields of M2. All RR coefficients for the additive genetic (AG) effect and the intercept for the permanent environmental (PE) effect of M2 had moderate to strong correlations with the intercept for the AG effect of M1. The coefficients of determination for multiple regression of the combined intercepts for the AG and PE effects of M2 on the coefficients for the AG effect of M1 were moderate to high. The daily milk yields of M2 predicted by using the RR coefficients for the AG effect of M1 were highly correlated with those obtained by using the coefficients of M2. Milk production after 305 DIM can be predicted by using the RR coefficient estimates of the AG effect during the first 305 DIM.

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…

Biases and Standard Errors of Standardized Regression Coefficients

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Chan, Wai

2011-01-01

The paper obtains consistent standard errors (SE) and biases of order O(1/n) for the sample standardized regression coefficients with both random and given predictors. Analytical results indicate that the formulas for SEs given in popular text books are consistent only when the population value of the regression coefficient is zero. The sample…

A dual two dimensional electronic portal imaging device transit dosimetry model based on an empirical quadratic formalism

PubMed Central

Metwaly, M; Glegg, M; Baggarley, S P; Elliott, A

2015-01-01

Objective: This study describes a two dimensional electronic portal imaging device (EPID) transit dosimetry model that can predict either: (1) in-phantom exit dose, or (2) EPID transit dose, for treatment verification. Methods: The model was based on a quadratic equation that relates the reduction in intensity to the equivalent path length (EPL) of the attenuator. In this study, two sets of quadratic equation coefficients were derived from calibration dose planes measured with EPID and ionization chamber in water under reference conditions. With two sets of coefficients, EPL can be calculated from either EPID or treatment planning system (TPS) dose planes. Consequently, either the in-phantom exit dose or the EPID transit dose can be predicted from the EPL. The model was tested with two open, five wedge and seven sliding window prostate and head and neck intensity-modulated radiation therapy (IMRT) fields on phantoms. Results were analysed using absolute gamma analysis (3%/3 mm). Results: The open fields gamma pass rates were >96.8% for all comparisons. For wedge and IMRT fields, comparisons between predicted and TPS-computed in-phantom exit dose resulted in mean gamma pass rate of 97.4% (range, 92.3–100%). As for the comparisons between predicted and measured EPID transit dose, the mean gamma pass rate was 97.5% (range, 92.6–100%). Conclusion: An EPID transit dosimetry model that can predict in-phantom exit dose and EPID transit dose was described and proven to be valid. Advances in knowledge: The described model is practical, generic and flexible to encourage widespread implementation of EPID dosimetry for the improvement of patients' safety in radiotherapy. PMID:25969867

Data-driven quantification of the effect of wind on athletics performance.

PubMed

Moinat, M; Fabius, O; Emanuel, K S

2018-06-11

So far, the relationship between wind and athletics performance has been studied mainly for 100 m sprint, based on simulation of biomechanical models, requiring several assumptions. In this study, this relationship is quantified empirically for all five horizontal jump and sprint events where wind is measured, with freely available competition results. After systematic scraping several elite and sub-elite results sites, the obtained results (n = 150,169) were filtered and matched to athletes. A quadratic mixed effects model with athlete and season as random effects was applied to express the influence of wind velocity on performance in each event. Whether this effect differs with performance level was investigated by applying the model on subgroups based on performance level. In the fitted quadratic model, the linear coefficients were significant (p < .001) for all events; the quadratic coefficients were significant for all events (p < .001) except long jump (p = .138). A 2.0 m s -1 tail wind provides an average advantage of 0.125, 0.140 and 0.146-s for the 100, 200 and 100/110 m hurdles, respectively, and an advantage of 0.058 and 0.102 m for long jump and triple jump, respectively. Performance level had a significant effect on the wind influence only for 100 m (p < .001). Amateur athletes (∼13 s) benefit 69% more from a 2.0 m s -1 tail wind than elite athletes (∼10 s). Practical formulas are presented for each event. These can easily be used correct results for wind speed, allowing better talent scouting and championship selection. This study demonstrates the efficacy of answering scientific questions empirically, through freely available data.

Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet

2010-05-01

This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross application model yields reasonable results which can be used for preliminary landslide hazard mapping.

Comprehensive analysis of the optical Kerr coefficient of graphene

DOE PAGES

Soh, Daniel B. S.; Hamerly, Ryan; Mabuchi, Hideo

2016-08-25

We present a comprehensive analysis of the nonlinear optical Kerr effect in graphene. We directly solve the S-matrix element to calculate the absorption rate, utilizing the Volkov-Keldysh-type crystal wave functions. We then convert to the nonlinear refractive index coefficients through the Kramers-Kronig relation. In this formalism, the source of Kerr nonlinearity is the interplay of optical fields that cooperatively drive the transition from valence to conduction band. This formalism makes it possible to identify and compute the rates of distinct nonlinear processes that contribute to the Kerr nonlinear refractive index coefficient. The four identified mechanisms are two-photon absorption, Raman transition,more » self-coupling, and quadratic ac Stark effect. As a result, we present a comparison of our theory with recent experimental and theoretical results.« less

Random regression analyses using B-splines to model growth of Australian Angus cattle

PubMed Central

Meyer, Karin

2005-01-01

Regression on the basis function of B-splines has been advocated as an alternative to orthogonal polynomials in random regression analyses. Basic theory of splines in mixed model analyses is reviewed, and estimates from analyses of weights of Australian Angus cattle from birth to 820 days of age are presented. Data comprised 84 533 records on 20 731 animals in 43 herds, with a high proportion of animals with 4 or more weights recorded. Changes in weights with age were modelled through B-splines of age at recording. A total of thirteen analyses, considering different combinations of linear, quadratic and cubic B-splines and up to six knots, were carried out. Results showed good agreement for all ages with many records, but fluctuated where data were sparse. On the whole, analyses using B-splines appeared more robust against "end-of-range" problems and yielded more consistent and accurate estimates of the first eigenfunctions than previous, polynomial analyses. A model fitting quadratic B-splines, with knots at 0, 200, 400, 600 and 821 days and a total of 91 covariance components, appeared to be a good compromise between detailedness of the model, number of parameters to be estimated, plausibility of results, and fit, measured as residual mean square error. PMID:16093011

On the Occurrence of Standardized Regression Coefficients Greater than One.

ERIC Educational Resources Information Center

Deegan, John, Jr.

1978-01-01

It is demonstrated here that standardized regression coefficients greater than one can legitimately occur. Furthermore, the relationship between the occurrence of such coefficients and the extent of multicollinearity present among the set of predictor variables in an equation is examined. Comments on the interpretation of these coefficients are…

Estimating regression coefficients from clustered samples: Sampling errors and optimum sample allocation

NASA Technical Reports Server (NTRS)

Kalton, G.

1983-01-01

A number of surveys were conducted to study the relationship between the level of aircraft or traffic noise exposure experienced by people living in a particular area and their annoyance with it. These surveys generally employ a clustered sample design which affects the precision of the survey estimates. Regression analysis of annoyance on noise measures and other variables is often an important component of the survey analysis. Formulae are presented for estimating the standard errors of regression coefficients and ratio of regression coefficients that are applicable with a two- or three-stage clustered sample design. Using a simple cost function, they also determine the optimum allocation of the sample across the stages of the sample design for the estimation of a regression coefficient.

The Outlier Detection for Ordinal Data Using Scalling Technique of Regression Coefficients

NASA Astrophysics Data System (ADS)

Adnan, Arisman; Sugiarto, Sigit

2017-06-01

The aims of this study is to detect the outliers by using coefficients of Ordinal Logistic Regression (OLR) for the case of k category responses where the score from 1 (the best) to 8 (the worst). We detect them by using the sum of moduli of the ordinal regression coefficients calculated by jackknife technique. This technique is improved by scalling the regression coefficients to their means. R language has been used on a set of ordinal data from reference distribution. Furthermore, we compare this approach by using studentised residual plots of jackknife technique for ANOVA (Analysis of Variance) and OLR. This study shows that the jackknifing technique along with the proper scaling may lead us to reveal outliers in ordinal regression reasonably well.

Random regression analyses using B-spline functions to model growth of Nellore cattle.

PubMed

Boligon, A A; Mercadante, M E Z; Lôbo, R B; Baldi, F; Albuquerque, L G

2012-02-01

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Correlation of Tc and coefficient of T 2 resistivity term of Fe-based pnictide & chalcogenide superconductors

NASA Astrophysics Data System (ADS)

Castro, P. B.; Ferreira, J. L.; Silva Neto, M. B.; ElMassalami, M.

2018-03-01

Normal-state of many Fe-based pnictides and chalcogenides superconductors exhibit a quadratic-in-temperature, ρtot – ρo – ρ ph = AT 2, over wide ranges of temperature and pressure. Moreover, these systems exhibit a correlation between their T c and A, namely ln(Tc /θ)∝ A ‑1/2(θ is an energy scale parameter), even when a control parameter such as pressure is widely varied. This manifestation, as well as that of \\frac{1}{{T}c}{≤ft(-\\frac{d{H}c2}{dT}\\right)}{Tc}\\propto \\frac{A}{n} [Phys. Rev. B 89, 220509 (2014), n is charge density, H c2 is the upper critical field] suggests a common Landau Fermi Liquid scenario for both superconductivity and quadratic-in-T contribution.

TWSVR: Regression via Twin Support Vector Machine.

PubMed

Khemchandani, Reshma; Goyal, Keshav; Chandra, Suresh

2016-02-01

Taking motivation from Twin Support Vector Machine (TWSVM) formulation, Peng (2010) attempted to propose Twin Support Vector Regression (TSVR) where the regressor is obtained via solving a pair of quadratic programming problems (QPPs). In this paper we argue that TSVR formulation is not in the true spirit of TWSVM. Further, taking motivation from Bi and Bennett (2003), we propose an alternative approach to find a formulation for Twin Support Vector Regression (TWSVR) which is in the true spirit of TWSVM. We show that our proposed TWSVR can be derived from TWSVM for an appropriately constructed classification problem. To check the efficacy of our proposed TWSVR we compare its performance with TSVR and classical Support Vector Regression(SVR) on various regression datasets. Copyright © 2015 Elsevier Ltd. All rights reserved.

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 isochrones in murine left ventricular pressure-volume loops: how well does the time-varying elastance concept hold?

PubMed

Claessens, T E; Georgakopoulos, D; Afanasyeva, M; Vermeersch, S J; Millar, H D; Stergiopulos, N; Westerhof, N; Verdonck, P R; Segers, P

2006-04-01

The linear time-varying elastance theory is frequently used to describe the change in ventricular stiffness during the cardiac cycle. The concept assumes that all isochrones (i.e., curves that connect pressure-volume data occurring at the same time) are linear and have a common volume intercept. Of specific interest is the steepest isochrone, the end-systolic pressure-volume relationship (ESPVR), of which the slope serves as an index for cardiac contractile function. Pressure-volume measurements, achieved with a combined pressure-conductance catheter in the left ventricle of 13 open-chest anesthetized mice, showed a marked curvilinearity of the isochrones. We therefore analyzed the shape of the isochrones by using six regression algorithms (two linear, two quadratic, and two logarithmic, each with a fixed or time-varying intercept) and discussed the consequences for the elastance concept. Our main observations were 1) the volume intercept varies considerably with time; 2) isochrones are equally well described by using quadratic or logarithmic regression; 3) linear regression with a fixed intercept shows poor correlation (R(2) < 0.75) during isovolumic relaxation and early filling; and 4) logarithmic regression is superior in estimating the fixed volume intercept of the ESPVR. In conclusion, the linear time-varying elastance fails to provide a sufficiently robust model to account for changes in pressure and volume during the cardiac cycle in the mouse ventricle. A new framework accounting for the nonlinear shape of the isochrones needs to be developed.

[Application of GIS and integrated mathematic models on estimating forest land wood productiveness and solar energy use efficiency].

PubMed

Xing, Shihe; Lin, Dexi; Shen, Jinquan; Cao, Rongbin

2005-10-01

Based on the meteorological elements observation and mountain soil survey in Fujian Province, this paper approached the application of geographic information system (GIS) and integrated mathematic models on estimating the grid wood productiveness and solar energy use efficiency (SEUE) of regional forest land. The results showed that there was a significant quadratic correlation of annual mean temperature, precipitation and total solar radiation energy(TSRE) with longitude, latitude and altitude, and their multiple correlation coefficients ranged from 0.692 to 0.981. The regional annual mean TSRE, temperature and precipitation could be well estimated by GIS and integrated models of quadratic tendency curve, and linear, quadratic and quartic inverse distance weighted interpolation. These annual means estimated by the models did not differ greatly from observed data, and the t test values were 1.29, 0.12 and 0.06, respectively. The grid wood productiveness and SEUE of regional forest land in Fujian could also be well estimated with the aid of GIS and integrated models, which ranged from 2.32 m3 x hm(-2) yr(-1) to 18.61 m3 x hm(-2) yr(-1) and from 0.11% to 0.91%, respectively.

Functional Form of the Radiometric Equation for the SNPP VIIRS Reflective Solar Bands: An Initial Study

NASA Technical Reports Server (NTRS)

Lei, Ning; Xiong, Xiaoxiong

2016-01-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite is a passive scanning radiometer and an imager, observing radiative energy from the Earth in 22 spectral bands from 0.41 to 12 microns which include 14 reflective solar bands (RSBs). Extending the formula used by the Moderate Resolution Imaging Spectroradiometer instruments, currently the VIIRS determines the sensor aperture spectral radiance through a quadratic polynomial of its detector digital count. It has been known that for the RSBs the quadratic polynomial is not adequate in the design specified spectral radiance region and using a quadratic polynomial could drastically increase the errors in the polynomial coefficients, leading to possible large errors in the determined aperture spectral radiance. In addition, it is very desirable to be able to extend the radiance calculation formula to correctly retrieve the aperture spectral radiance with the level beyond the design specified range. In order to more accurately determine the aperture spectral radiance from the observed digital count, we examine a few polynomials of the detector digital count to calculate the sensor aperture spectral radiance.

SU-G-IeP3-11: On the Utility of Pixel Variance to Characterize Noise for Image Receptors of Digital Radiography Systems

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

Finley, C; Dave, J

Purpose: To characterize noise for image receptors of digital radiography systems based on pixel variance. Methods: Nine calibrated digital image receptors associated with nine new portable digital radiography systems (Carestream Health, Inc., Rochester, NY) were used in this study. For each image receptor, thirteen images were acquired with RQA5 beam conditions for input detector air kerma ranging from 0 to 110 µGy, and linearized ‘For Processing’ images were extracted. Mean pixel value (MPV), standard deviation (SD) and relative noise (SD/MPV) were obtained from each image using ROI sizes varying from 2.5×2.5 to 20×20 mm{sup 2}. Variance (SD{sup 2}) was plottedmore » as a function of input detector air kerma and the coefficients of the quadratic fit were used to derive structured, quantum and electronic noise coefficients. Relative noise was also fitted as a function of input detector air kerma to identify noise sources. The fitting functions used least-squares approach. Results: The coefficient of variation values obtained using different ROI sizes was less than 1% for all the images. The structured, quantum and electronic coefficients obtained from the quadratic fit of variance (r>0.97) were 0.43±0.10, 3.95±0.27 and 2.89±0.74 (mean ± standard deviation), respectively, indicating that overall the quantum noise was the dominant noise source. However, for one system electronic noise coefficient (3.91) was greater than quantum noise coefficient (3.56) indicating electronic noise to be dominant. Using relative noise values, the power parameter of the fitting equation (|r|>0.93) showed a mean and standard deviation of 0.46±0.02. A 0.50 value for this power parameter indicates quantum noise to be the dominant noise source whereas values around 0.50 indicate presence of other noise sources. Conclusion: Characterizing noise from pixel variance assists in identifying contributions from various noise sources that, eventually, may affect image quality. This approach may be integrated during periodic quality assessments of digital image receptors.« less

Application of Biological Simulation Models in Estimating Feed Efficiency of Finishing Steers

USDA-ARS?s Scientific Manuscript database

Data on individual daily feed intake, bi-weekly BW, and carcass composition were obtained on 1,212 crossbred steers. Within animal regressions of cumulative feed intake and BW on linear and quadratic days on feed were used to quantify initial and ending BW, average daily feed intake (OFI) and ADG o...

The Inverted Student Density and Test Scores.

ERIC Educational Resources Information Center

Boldt, Robert F.

The inverted density is one whose contour lines are spheroidal as in the normal distribution, but whose moments differ from those of the normal in that its conditional arrays are not homoscedastic, being quadratic functions of the values of the linear regression functions. It is also platykurtic, its measure of kurtosis ranging from that of the…

Bicycles, Birds, Bats and Balloons: New Applications for Algebra Classes.

ERIC Educational Resources Information Center

Yoshiwara, Bruce; Yoshiwara, Kathy

This collection of activities is intended to enhance the teaching of college algebra through the use of modeling. The problems use real data and involve the representation and interpretation of the data. The concepts addressed include rates of change, linear and quadratic regression, and functions. The collection consists of eight problems, four…

Deriving the Quadratic Regression Equation Using Algebra

ERIC Educational Resources Information Center

Gordon, Sheldon P.; Gordon, Florence S.

2004-01-01

In discussions with leading educators from many different fields, MAA's CRAFTY (Curriculum Renewal Across the First Two Years) committee found that one of the most common mathematical themes in those other disciplines is the idea of fitting a function to a set of data in the least squares sense. The representatives of those partner disciplines…

Bayesian Estimation of Multivariate Latent Regression Models: Gauss versus Laplace

ERIC Educational Resources Information Center

Culpepper, Steven Andrew; Park, Trevor

2017-01-01

A latent multivariate regression model is developed that employs a generalized asymmetric Laplace (GAL) prior distribution for regression coefficients. The model is designed for high-dimensional applications where an approximate sparsity condition is satisfied, such that many regression coefficients are near zero after accounting for all the model…

Viability estimation of pepper seeds using time-resolved photothermal signal characterization

NASA Astrophysics Data System (ADS)

Kim, Ghiseok; Kim, Geon-Hee; Lohumi, Santosh; Kang, Jum-Soon; Cho, Byoung-Kwan

2014-11-01

We used infrared thermal signal measurement system and photothermal signal and image reconstruction techniques for viability estimation of pepper seeds. Photothermal signals from healthy and aged seeds were measured for seven periods (24, 48, 72, 96, 120, 144, and 168 h) using an infrared camera and analyzed by a regression method. The photothermal signals were regressed using a two-term exponential decay curve with two amplitudes and two time variables (lifetime) as regression coefficients. The regression coefficients of the fitted curve showed significant differences for each seed groups, depending on the aging times. In addition, the viability of a single seed was estimated by imaging of its regression coefficient, which was reconstructed from the measured photothermal signals. The time-resolved photothermal characteristics, along with the regression coefficient images, can be used to discriminate the aged or dead pepper seeds from the healthy seeds.

Cheetah: Starspot modeling code

NASA Astrophysics Data System (ADS)

Walkowicz, Lucianne; Thomas, Michael; Finkestein, Adam

2014-12-01

Cheetah models starspots in photometric data (lightcurves) by calculating the modulation of a light curve due to starspots. The main parameters of the program are the linear and quadratic limb darkening coefficients, stellar inclination, spot locations and sizes, and the intensity ratio of the spots to the stellar photosphere. Cheetah uses uniform spot contrast and the minimum number of spots needed to produce a good fit and ignores bright regions for the sake of simplicity.

Interpersonal Problems and Developmental Trajectories of Binge Eating Disorder

PubMed Central

Blomquist, Kerstin K.; Ansell, Emily B.; White, Marney A.; Masheb, Robin M.; Grilo, Carlos M.

2012-01-01

Objective To explore associations between specific interpersonal constructs and the developmental progression of behaviors leading to binge eating disorder (BED). Method Eighty-four consecutively evaluated, treatment-seeking obese (BMI ≥ 30) men and women with BED were assessed with structured diagnostic and clinical interviews and completed a battery of established measures to assess the current and developmental eating- and weight-related variables as well as interpersonal functioning. Results Using the interpersonal circumplex structural summary method, amplitude, elevation, the affiliation dimension, and the quadratic coefficient for the dominance dimension were associated with eating and weight-related developmental variables. The amplitude coefficient and more extreme interpersonal problems on the dominance dimension (quadratic)—i.e., problems with being extremely high (domineering) or low in dominance (submissive)—were significantly associated with ayounger age at onset of binge eating, BED, and overweight as well as accounted for significant variance in age at binge eating, BED, and overweight onset. Greater interpersonal problems with having an overly affiliative interpersonal style were significantly associated with, and accounted for significant variance in, ayounger age at diet onset. Discussion Findings provide further support for the importance of interpersonal problems among adults with BED and converge with recent work highlighting the importance of specific types of interpersonal problems for understanding heterogeneity and different developmental trajectories of individuals with BED. PMID:22727087

Does competition improve financial stability of the banking sector in ASEAN countries? An empirical analysis.

PubMed

Noman, Abu Hanifa Md; Gee, Chan Sok; Isa, Che Ruhana

2017-01-01

This study examines the influence of competition on the financial stability of the commercial banks of Association of Southeast Asian Nation (ASEAN) over the 1990 to 2014 period. Panzar-Rosse H-statistic, Lerner index and Herfindahl-Hirschman Index (HHI) are used as measures of competition, while Z-score, non-performing loan (NPL) ratio and equity ratio are used as measures of financial stability. Two-step system Generalized Method of Moments (GMM) estimates demonstrate that competition measured by H-statistic is positively related to Z-score and equity ratio, and negatively related to non-performing loan ratio. Conversely, market power measured by Lerner index is negatively related to Z-score and equity ratio and positively related to NPL ratio. These results strongly support the competition-stability view for ASEAN banks. We also capture the non-linear relationship between competition and financial stability by incorporating a quadratic term of competition in our models. The results show that the coefficient of the quadratic term of H-statistic is negative for the Z-score model given a positive coefficient of the linear term in the same model. These results support the non-linear relationship between competition and financial stability of the banking sector. The study contains significant policy implications for improving the financial stability of the commercial banks.

Does competition improve financial stability of the banking sector in ASEAN countries? An empirical analysis

PubMed Central

Gee, Chan Sok; Isa, Che Ruhana

2017-01-01

This study examines the influence of competition on the financial stability of the commercial banks of Association of Southeast Asian Nation (ASEAN) over the 1990 to 2014 period. Panzar-Rosse H-statistic, Lerner index and Herfindahl-Hirschman Index (HHI) are used as measures of competition, while Z-score, non-performing loan (NPL) ratio and equity ratio are used as measures of financial stability. Two-step system Generalized Method of Moments (GMM) estimates demonstrate that competition measured by H-statistic is positively related to Z-score and equity ratio, and negatively related to non-performing loan ratio. Conversely, market power measured by Lerner index is negatively related to Z-score and equity ratio and positively related to NPL ratio. These results strongly support the competition-stability view for ASEAN banks. We also capture the non-linear relationship between competition and financial stability by incorporating a quadratic term of competition in our models. The results show that the coefficient of the quadratic term of H-statistic is negative for the Z-score model given a positive coefficient of the linear term in the same model. These results support the non-linear relationship between competition and financial stability of the banking sector. The study contains significant policy implications for improving the financial stability of the commercial banks. PMID:28486548

An analytical model of capped turbulent oscillatory bottom boundary layers

NASA Astrophysics Data System (ADS)

Shimizu, Kenji

2010-03-01

An analytical model of capped turbulent oscillatory bottom boundary layers (BBLs) is proposed using eddy viscosity of a quadratic form. The common definition of friction velocity based on maximum bottom shear stress is found unsatisfactory for BBLs under rotating flows, and a possible extension based on turbulent kinetic energy balance is proposed. The model solutions show that the flow may slip at the top of the boundary layer due to capping by the water surface or stratification, reducing the bottom shear stress, and that the Earth's rotation induces current and bottom shear stress components perpendicular to the interior flow with a phase lag (or lead). Comparisons with field and numerical experiments indicate that the model predicts the essential characteristics of the velocity profiles, although the agreement is rather qualitative due to assumptions of quadratic eddy viscosity with time-independent friction velocity and a well-mixed boundary layer. On the other hand, the predicted linear friction coefficients, phase lead, and veering angle at the bottom agreed with available data with an error of 3%-10%, 5°-10°, and 5°-10°, respectively. As an application of the model, the friction coefficients are used to calculate e-folding decay distances of progressive internal waves with a semidiurnal frequency.

Plausibility assessment of a 2-state self-paced mental task-based BCI using the no-control performance analysis.

PubMed

Faradji, Farhad; Ward, Rabab K; Birch, Gary E

2009-06-15

The feasibility of having a self-paced brain-computer interface (BCI) based on mental tasks is investigated. The EEG signals of four subjects performing five mental tasks each are used in the design of a 2-state self-paced BCI. The output of the BCI should only be activated when the subject performs a specific mental task and should remain inactive otherwise. For each subject and each task, the feature coefficient and the classifier that yield the best performance are selected, using the autoregressive coefficients as the features. The classifier with a zero false positive rate and the highest true positive rate is selected as the best classifier. The classifiers tested include: linear discriminant analysis, quadratic discriminant analysis, Mahalanobis discriminant analysis, support vector machine, and radial basis function neural network. The results show that: (1) some classifiers obtained the desired zero false positive rate; (2) the linear discriminant analysis classifier does not yield acceptable performance; (3) the quadratic discriminant analysis classifier outperforms the Mahalanobis discriminant analysis classifier and performs almost as well as the radial basis function neural network; and (4) the support vector machine classifier has the highest true positive rates but unfortunately has nonzero false positive rates in most cases.

Resolvent estimates in homogenisation of periodic problems of fractional elasticity

NASA Astrophysics Data System (ADS)

Cherednichenko, Kirill; Waurick, Marcus

2018-03-01

We provide operator-norm convergence estimates for solutions to a time-dependent equation of fractional elasticity in one spatial dimension, with rapidly oscillating coefficients that represent the material properties of a viscoelastic composite medium. Assuming periodicity in the coefficients, we prove operator-norm convergence estimates for an operator fibre decomposition obtained by applying to the original fractional elasticity problem the Fourier-Laplace transform in time and Gelfand transform in space. We obtain estimates on each fibre that are uniform in the quasimomentum of the decomposition and in the period of oscillations of the coefficients as well as quadratic with respect to the spectral variable. On the basis of these uniform estimates we derive operator-norm-type convergence estimates for the original fractional elasticity problem, for a class of sufficiently smooth densities of applied forces.

Ground-Support Algorithms for Simulation, Processing, and Calibration of Barnes Static Earth Sensor Measurements: Applications to Tropical Rainfall Measuring Mission Observatory

NASA Technical Reports Server (NTRS)

Natanson, G. A.

1997-01-01

New algorithms are described covering the simulation, processing, and calibration of penetration angles of the Barnes static Earth sensor assembly (SESA) as implemented in the Goddard Space Flight Center Flight Dynamics Division ground support system for the Tropical Rainfall Measuring Mission (TRMM) Observatory. The new treatment involves a detailed analysis of the measurements by individual quadrants. It is shown that, to a good approximation, individual quadrant misalignments can be treated simply as penetration angle biases. Simple formulas suitable for real-time applications are introduced for computing quadrant-dependent effects. The simulator generates penetration angles by solving a quadratic equation with coefficients uniquely determined by the spacecraft's position and the quadrant's orientation in GeoCentric Inertial (GCI) coordinates. Measurement processing for attitude determination is based on linearized equations obtained by expanding the coefficients of the aforementioned quadratic equation as a Taylor series in both the Earth oblateness coefficient (alpha approx. 1/150) and the angle between the pointing axis and the geodetic nadir vector. A simple formula relating a measured value of the penetration angle to the deviation of the Earth-pointed axis from the geodetic nadir vector is derived. It is shown that even near the very edge of the quadrant's Field Of View (FOV), attitude errors resulting from quadratic effects are a few hundredths of a degree, which is small compared to the attitude determination accuracy requirement (0.18 degree, 3 sigma) of TRMM. Calibration of SESA measurements is complicated by a first-order filtering used in the TRMM onboard algorithm to compute penetration angles from raw voltages. A simple calibration scheme is introduced where these complications are avoided by treating penetration angles as the primary raw measurements, which are adjusted using biases and scale factors. In addition to three misalignment parameters, the calibration state vector contains only two average penetration angle biases (one per each pair of opposite quadrants) since, because of the very narrow sensor FOV (+/- 2.6 degrees), differences between biases of the penetration angles measured by opposite quadrants cannot be distinguished from roll and pitch sensor misalignments. After calibration, the estimated misalignments and average penetration angle biases are converted to the four penetration angle biases and to the yaw misalignment angle. The resultant biases and the estimated scale factors are finally used to update the coefficients necessary for onboard computations of penetration angles from measured voltages.

Determination of water pH using absorption-based optical sensors: evaluation of different calculation methods

NASA Astrophysics Data System (ADS)

Wang, Hongliang; Liu, Baohua; Ding, Zhongjun; Wang, Xiangxin

2017-02-01

Absorption-based optical sensors have been developed for the determination of water pH. In this paper, based on the preparation of a transparent sol-gel thin film with a phenol red (PR) indicator, several calculation methods, including simple linear regression analysis, quadratic regression analysis and dual-wavelength absorbance ratio analysis, were used to calculate water pH. Results of MSSRR show that dual-wavelength absorbance ratio analysis can improve the calculation accuracy of water pH in long-term measurement.

Evaluating the efficiency of a one-square-meter quadrat sampler for riffle-dwelling fish

USGS Publications Warehouse

Peterson, J.T.; Rabeni, C.F.

2001-01-01

We evaluated the efficacy of a 1-m2 quadrat sampler for collecting riffle-dwelling fishes in an Ozark stream. We used a dual-gear approach to evaluate sampler efficiency in relation to species, fish size, and habitat variables. Quasi-likelihood regression showed sampling efficiency to differ significantly (P 0.05). Sampling efficiency was significantly influenced by physical habitat characteristics. Mean current velocity negatively influenced sampling efficiencies for Cyprinidae (P = 0.009), Cottidae (P = 0.006), and Percidae (P < 0.001), and the amount of cobble substrate negatively influenced sampling efficiencies for Cyprinidae (P = 0.025), Ictaluridae (P < 0.001), and Percidae (P < 0.001). Water temperature negatively influenced sampling efficiency for Cyprinidae (P = 0.009) and Ictaluridae (P = 0.006). Species-richness efficiency was positively influenced (P = 0.002) by percentage of riffle sampled. Under average habitat conditions encountered in stream riffles, the 1-m2 quadrat sampler was most efficient at estimating the densities of Cyprinidae (84%) and Cottidae (80%) and least efficient for Percidae (57%) and Ictaluridae (31%).

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

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

Enhancement of docosahexaenoic acid production by Schizochytrium SW1 using response surface methodology

NASA Astrophysics Data System (ADS)

Nazir, Mohd Yusuf Mohd; Al-Shorgani, Najeeb Kaid Nasser; Kalil, Mohd Sahaid; Hamid, Aidil Abdul

2015-09-01

In this study, three factors (fructose concentration, agitation speed and monosodium glutamate (MSG) concentration) were optimized to enhance DHA production by Schizochytrium SW1 using response surface methodology (RSM). Central composite design was applied as the experimental design and analysis of variance (ANOVA) was used to analyze the data. The experiments were conducted using 500 mL flask with 100 mL working volume at 30°C for 96 hours. ANOVA analysis revealed that the process was adequately represented significantly by the quadratic model (p<0.0001) and two of the factors namely agitation speed and MSG concentration significantly affect DHA production (p<0.005). Level of influence for each variable and quadratic polynomial equation were obtained for DHA production by multiple regression analyses. The estimated optimum conditions for maximizing DHA production by SW1 were 70 g/L fructose, 250 rpm agitation speed and 12 g/L MSG. Consequently, the quadratic model was validated by applying of the estimated optimum conditions, which confirmed the model validity and 52.86% of DHA was produced.

Penalized spline estimation for functional coefficient regression models.

PubMed

Cao, Yanrong; Lin, Haiqun; Wu, Tracy Z; Yu, Yan

2010-04-01

The functional coefficient regression models assume that the regression coefficients vary with some "threshold" variable, providing appreciable flexibility in capturing the underlying dynamics in data and avoiding the so-called "curse of dimensionality" in multivariate nonparametric estimation. We first investigate the estimation, inference, and forecasting for the functional coefficient regression models with dependent observations via penalized splines. The P-spline approach, as a direct ridge regression shrinkage type global smoothing method, is computationally efficient and stable. With established fixed-knot asymptotics, inference is readily available. Exact inference can be obtained for fixed smoothing parameter λ, which is most appealing for finite samples. Our penalized spline approach gives an explicit model expression, which also enables multi-step-ahead forecasting via simulations. Furthermore, we examine different methods of choosing the important smoothing parameter λ: modified multi-fold cross-validation (MCV), generalized cross-validation (GCV), and an extension of empirical bias bandwidth selection (EBBS) to P-splines. In addition, we implement smoothing parameter selection using mixed model framework through restricted maximum likelihood (REML) for P-spline functional coefficient regression models with independent observations. The P-spline approach also easily allows different smoothness for different functional coefficients, which is enabled by assigning different penalty λ accordingly. We demonstrate the proposed approach by both simulation examples and a real data application.

Batch versus column modes for the adsorption of radioactive metal onto rice husk waste: conditions optimization through response surface methodology.

PubMed

Kausar, Abida; Bhatti, Haq Nawaz; Iqbal, Munawar; Ashraf, Aisha

2017-09-01

Batch and column adsorption modes were compared for the adsorption of U(VI) ions using rice husk waste biomass (RHWB). Response surface methodology was employed for the optimization of process variables, i.e., (pH (A), adsorbent dose (B), initial ion concentration (C)) in batch mode. The B, C and C 2 affected the U(VI) adsorption significantly in batch mode. The developed quadratic model was found to be validated on the basis of regression coefficient as well as analysis of variance. The predicted and actual values were found to be correlated well, with negligible residual value, and B, C and C 2 were significant terms. The column study was performed considering bed height, flow rate and initial metal ion concentration, and adsorption efficiency was evaluated through breakthrough curves and bed depth service time and Thomas models. Adsorption was found to be dependent on bed height and initial U(VI) ion concentration, and flow rate decreased the adsorption capacity. Thomas models fitted well to the U(VI) adsorption onto RHWB. Results revealed that RHWB has potential to remove U(VI) ions and batch adsorption was found to be efficient versus column mode.

Optimization of Acid Orange 7 Degradation in Heterogeneous Fenton-like Reaction Using Fe3-xCoxO4 Catalyst

NASA Astrophysics Data System (ADS)

Ibrahim, M. Z.; Alrozi, R.; Zubir, N. A.; Bashah, N. A.; Ali, S. A. Md; Ibrahim, N.

2018-05-01

The oxidation process such as heterogeneous Fenton and/or Fenton-like reactions is considered as an effective and efficient method for treatment of dye degradation. In this study, the degradation of Acid Orange 7 (AO7) was investigated by using Fe3-xCoxO4 as a heterogeneous Fenton-like catalyst. Response surface methodology (RSM) was used to optimize the operational parameters condition and the interaction of two or more parameters. The parameter studies were catalyst dosage (X1 ), pH (X2 ) and H2O2 concentration (X3 ) towards AO7 degradation. Based on analysis of variance (ANOVA), the derived quadratic polynomial model was significant whereby the predicted values matched the experimental values with regression coefficient of R2 = 0.9399. The optimum condition for AO7 degradation was obtained at catalyst dosage of 0.84 g/L, pH of 3 and H2O2 concentration of 46.70 mM which resulted in 86.30% removal of AO7 dye. These findings present new insights into the influence of operational parameters in the heterogeneous Fenton-like oxidation of AO7 using Fe3-xCoxO4 catalyst.

Diagnostic accuracy of a mathematical model to predict apnea-hypopnea index using nighttime pulse oximetry

NASA Astrophysics Data System (ADS)

Ebben, Matthew R.; Krieger, Ana C.

2016-03-01

The intent of this study is to develop a predictive model to convert an oxygen desaturation index (ODI) to an apnea-hypopnea index (AHI). This model will then be compared to actual AHI to determine its precision. One thousand four hundred and sixty-seven subjects given polysomnograms with concurrent pulse oximetry between April 14, 2010, and February 7, 2012, were divided into model development (n=733) and verification groups (n=734) in order to develop a predictive model of AHI using ODI. Quadratic regression was used for model development. The coefficient of determination (r2) between the actual AHI and the predicted AHI (PredAHI) was 0.80 (r=0.90), which was significant at a p<0.001. The areas under the receiver operating characteristic curve ranged from 0.96 for AHI thresholds of ≥10 and ≥15/h to 0.97 for thresholds of ≥5 and ≥30/h. The algorithm described in this paper provides a convenient and accurate way to convert ODI to a predicted AHI. This tool makes it easier for clinicians to understand oximetry data in the context of traditional measures of sleep apnea.

Optimisation of the supercritical extraction of toxic elements in fish oil.

PubMed

Hajeb, P; Jinap, S; Shakibazadeh, Sh; Afsah-Hejri, L; Mohebbi, G H; Zaidul, I S M

2014-01-01

This study aims to optimise the operating conditions for the supercritical fluid extraction (SFE) of toxic elements from fish oil. The SFE operating parameters of pressure, temperature, CO2 flow rate and extraction time were optimised using a central composite design (CCD) of response surface methodology (RSM). High coefficients of determination (R²) (0.897-0.988) for the predicted response surface models confirmed a satisfactory adjustment of the polynomial regression models with the operation conditions. The results showed that the linear and quadratic terms of pressure and temperature were the most significant (p < 0.05) variables affecting the overall responses. The optimum conditions for the simultaneous elimination of toxic elements comprised a pressure of 61 MPa, a temperature of 39.8ºC, a CO₂ flow rate of 3.7 ml min⁻¹ and an extraction time of 4 h. These optimised SFE conditions were able to produce fish oil with the contents of lead, cadmium, arsenic and mercury reduced by up to 98.3%, 96.1%, 94.9% and 93.7%, respectively. The fish oil extracted under the optimised SFE operating conditions was of good quality in terms of its fatty acid constituents.

The study of correlation among different scattering parameters in an aggregate dust model

NASA Astrophysics Data System (ADS)

Mazarbhuiya, A. M.; Das, H. S.

2017-09-01

We study the light scattering properties of aggregate particles in a wide range of complex refractive indices (m = n + i k, where 1.4 ≤ n ≤ 2.0, 0.001 ≤ k ≤1.0) and wavelengths (0.45 ≤ λ≤1.25 μ m) to investigate the correlation among different parameters e.g., the positive polarization maximum (P_{max}), the amplitude of the negative polarization (P_{min}), geometric albedo (A), (n,k) and λ. Numerical computations are performed by the Superposition T-matrix code with Ballistic Cluster-Cluster Aggregate (BCCA) particles of 128 monomers and Ballistic Aggregates (BA) particles of 512 monomers, where monomer's radius of aggregates is considered to be 0.1 μm. At a fixed value of k, P_{max} and n are correlated via a quadratic regression equation and this nature is observed at all wavelengths. Further, P_{max} and k are found to be related via a polynomial regression equation when n is taken to be fixed. The degree of the equation depends on the wavelength, higher the wavelength lower is the degree. We find that A and P_{max} are correlated via a cubic regression at λ= 0.45 μ m whereas this correlation is quadratic at higher wavelengths. We notice that |P_{min}| increases with the decrease of P_{max} and a strong linear correlation between them is observed when n is fixed at some value and k is changed from higher to lower value. Further, at a fix value of k, P_{min} and P_{max} can be fitted well via a quartic regression equation when n is changed from higher to lower value. We also find that P_{max} increases with λ and they are correlated via a quartic regression.

Estimation of stature from sternum - Exploring the quadratic models.

PubMed

Saraf, Ashish; Kanchan, Tanuj; Krishan, Kewal; Ateriya, Navneet; Setia, Puneet

2018-04-14

Identification of the dead is significant in examination of unknown, decomposed and mutilated human remains. Establishing the biological profile is the central issue in such a scenario, and stature estimation remains one of the important criteria in this regard. The present study was undertaken to estimate stature from different parts of the sternum. A sample of 100 sterna was obtained from individuals during the medicolegal autopsies. Length of the deceased and various measurements of the sternum were measured. Student's t-test was performed to find the sex differences in stature and sternal measurements included in the study. Correlation between stature and sternal measurements were analysed using Karl Pearson's correlation, and linear and quadratic regression models were derived. All the measurements were found to be significantly larger in males than females. Stature correlated best with the combined length of sternum, among males (R = 0.894), females (R = 0.859), and for the total sample (R = 0.891). The study showed that the models derived for stature estimation from combined length of sternum are likely to give the most accurate estimates of stature in forensic case work when compared to manubrium and mesosternum. Accuracy of stature estimation further increased with quadratic models derived for the mesosternum among males and combined length of sternum among males and females when compared to linear regression models. Future studies in different geographical locations and a larger sample size are proposed to confirm the study observations. Copyright © 2018 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Sex differences of anthropometric indices of obesity by age among Iranian adults in northern Iran: A predictive regression model.

PubMed

Hajian-Tilaki, Karimollah; Heidari, Behzad

2015-01-01

The biological variation of body mass index (BMI) and waist circumference (WC) with age may vary by gender. The objective of this study was to investigate the functional relationship of anthropometric measures with age and sex. The data were collected from a population-based cross-sectional study of 1800 men and 1800 women aged 20-70 years in northern Iran. The linear and quadratic pattern of age on weight, height, BMI and WC and WHR were tested statistically and the interaction effect of age and gender was also formally tested. The quadratic model (age(2)) provided a significantly better fit than simple linear model for weight, BMI and WC. BMI, WC and weight explained a greater variance using quadratic form for women compared with men (for BMI, R(2)=0.18, p<0.001 vs R(2)=0.059, p<0.001 and for WC, R(2)=0.17, p<0.001 vs R(2)=0.047, p<0.001). For height, there is an inverse linear relationship while for WHR, a positive linear association was apparent by aging, the quadratic form did not add to better fit. These findings indicate the different patterns of weight gain, fat accumulation for visceral adiposity and loss of muscle mass between men and women in the early and middle adulthood.

Thermal expansion behavior study of Co nanowire array with in situ x-ray diffraction and x-ray absorption fine structure techniques

NASA Astrophysics Data System (ADS)

Mo, Guang; Cai, Quan; Jiang, Longsheng; Wang, Wei; Zhang, Kunhao; Cheng, Weidong; Xing, Xueqing; Chen, Zhongjun; Wu, Zhonghua

2008-10-01

In situ x-ray diffraction and x-ray absorption fine structure techniques were used to study the structural change of ordered Co nanowire array with temperature. The results show that the Co nanowires are polycrystalline with hexagonal close packed structure without phase change up until 700 °C. A nonlinear thermal expansion behavior has been found and can be well described by a quadratic equation with the first-order thermal expansion coefficient of 4.3×10-6/°C and the second-order thermal expansion coefficient of 5.9×10-9/°C. The mechanism of this nonlinear thermal expansion behavior is discussed.

Hidden Connections between Regression Models of Strain-Gage Balance Calibration Data

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert

2013-01-01

Hidden connections between regression models of wind tunnel strain-gage balance calibration data are investigated. These connections become visible whenever balance calibration data is supplied in its design format and both the Iterative and Non-Iterative Method are used to process the data. First, it is shown how the regression coefficients of the fitted balance loads of a force balance can be approximated by using the corresponding regression coefficients of the fitted strain-gage outputs. Then, data from the manual calibration of the Ames MK40 six-component force balance is chosen to illustrate how estimates of the regression coefficients of the fitted balance loads can be obtained from the regression coefficients of the fitted strain-gage outputs. The study illustrates that load predictions obtained by applying the Iterative or the Non-Iterative Method originate from two related regression solutions of the balance calibration data as long as balance loads are given in the design format of the balance, gage outputs behave highly linear, strict statistical quality metrics are used to assess regression models of the data, and regression model term combinations of the fitted loads and gage outputs can be obtained by a simple variable exchange.

On the analysis of shock implosion

NASA Astrophysics Data System (ADS)

Mishkin, Eli A.; Alejaldre, Carlos

1984-06-01

An imploding shock wave, coming from infinity, moves through an ideal gas with the adiabatic constant γ. To define a single-valued self-similar coefficient λ(γ), over the whole classical interval 1 < γ < ∞, its boundary values λ(1), λ(∞) are deduced. The conservation equations, cast in form of quadratics, exhibit their singular points P,M,M‧. At P the pressure is maximum, at M the velocity of the gas U1, minus ξ, equals the speed of sound C, at M‧ there is a linear relationship between U1, U˙1 and C. The representative curve of the compressed gas passes analytically through all of them. The relative position of P, M, M‧ leads to three solutions of the quadratic conservation equations. Representative curves of the state of the imploded gas, at various values of γ, are shown. The errors associated with the idealized models of implosion and explosion are evaluated.

Limit Cycle Bifurcations Near a Piecewise Smooth Generalized Homoclinic Loop with a Saddle-Fold Point

NASA Astrophysics Data System (ADS)

Liang, Feng; Wang, Dechang

In this paper, we suppose that a planar piecewise Hamiltonian system, with a straight line of separation, has a piecewise generalized homoclinic loop passing through a Saddle-Fold point, and assume that there exists a family of piecewise smooth periodic orbits near the loop. By studying the asymptotic expansion of the first order Melnikov function corresponding to the period annulus, we obtain the formulas of the first six coefficients in the expansion, based on which, we provide a lower bound for the maximal number of limit cycles bifurcated from the period annulus. As applications, two concrete systems are considered. Especially, the first one reveals that a quadratic piecewise Hamiltonian system can have five limit cycles near a generalized homoclinic loop under a quadratic piecewise smooth perturbation. Compared with the smooth case [Horozov & Iliev, 1994; Han et al., 1999], three more limit cycles are found.

Stochastic Multiresonance for a Fractional Linear Oscillator with Quadratic Trichotomous Noise

NASA Astrophysics Data System (ADS)

Zhu, Jian-Qu; Jin, Wei-Dong; Zheng, Gao; Guo, Feng

2017-11-01

The stochastic multiresonance behavior for a fractional linear oscillator with random system frequency is investigated. The fluctuation of the system frequency is a quadratic trichotomous noise, the memory kernel of the fractional oscillator is modeled as a Mittag-Leffler function. Based on linear system theory, applying Laplace transform and the definition of fractional derivative, the expression of the system output amplitude (SPA) is obtained. Stochastic multiresonance phenomenon is found on the curves of SPA versus the memory time and the memory exponent of the fractional oscillator, as well as versus the trichotomous noise amplitude. The SPA depends non-monotonically on the stationary probability of the trichotomous noise, on the viscous damping coefficient and system characteristic frequency of the oscillator, as well as on the driving frequency of external force. Supported by National Natural Science Foundation of China under Grant No. 61134002

Wrong Signs in Regression Coefficients

NASA Technical Reports Server (NTRS)

McGee, Holly

1999-01-01

When using parametric cost estimation, it is important to note the possibility of the regression coefficients having the wrong sign. A wrong sign is defined as a sign on the regression coefficient opposite to the researcher's intuition and experience. Some possible causes for the wrong sign discussed in this paper are a small range of x's, leverage points, missing variables, multicollinearity, and computational error. Additionally, techniques for determining the cause of the wrong sign are given.

Noninvasive spectral imaging of skin chromophores based on multiple regression analysis aided by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Wiswadarma, Aditya; Hase, Yota; Tanaka, Noriyuki; Maeda, Takaaki; Niizeki, Kyuichi; Aizu, Yoshihisa

2011-08-01

In order to visualize melanin and blood concentrations and oxygen saturation in human skin tissue, a simple imaging technique based on multispectral diffuse reflectance images acquired at six wavelengths (500, 520, 540, 560, 580 and 600nm) was developed. The technique utilizes multiple regression analysis aided by Monte Carlo simulation for diffuse reflectance spectra. Using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are deduced numerically in advance, while oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments with human skin of the human hand during upper limb occlusion and of the inner forearm exposed to UV irradiation demonstrated the ability of the method to evaluate physiological reactions of human skin tissue.

Periodicity analysis of tourist arrivals to Banda Aceh using smoothing SARIMA approach

NASA Astrophysics Data System (ADS)

Miftahuddin, Helida, Desri; Sofyan, Hizir

2017-11-01

Forecasting the number of tourist arrivals who enters a region is needed for tourism businesses, economic and industrial policies, so that the statistical modeling needs to be conducted. Banda Aceh is the capital of Aceh province more economic activity is driven by the services sector, one of which is the tourism sector. Therefore, the prediction of the number of tourist arrivals is needed to develop further policies. The identification results indicate that the data arrival of foreign tourists to Banda Aceh to contain the trend and seasonal nature. Allegedly, the number of arrivals is influenced by external factors, such as economics, politics, and the holiday season caused the structural break in the data. Trend patterns are detected by using polynomial regression with quadratic and cubic approaches, while seasonal is detected by a periodic regression polynomial with quadratic and cubic approach. To model the data that has seasonal effects, one of the statistical methods that can be used is SARIMA (Seasonal Autoregressive Integrated Moving Average). The results showed that the smoothing, a method to detect the trend pattern is cubic polynomial regression approach, with the modified model and the multiplicative periodicity of 12 months. The AIC value obtained was 70.52. While the method for detecting the seasonal pattern is a periodic regression polynomial cubic approach, with the modified model and the multiplicative periodicity of 12 months. The AIC value obtained was 73.37. Furthermore, the best model to predict the number of foreign tourist arrivals to Banda Aceh in 2017 to 2018 is SARIMA (0,1,1)(1,1,0) with MAPE is 26%.

How does the human impact of footpaths affect flora biodiversity in the rainforest?

NASA Astrophysics Data System (ADS)

Chan, J. H. F.

2017-12-01

Tioman Island is the largest Island in the Pahang region in Malaysia, known for its biodiverse reefs and dense rainforests, making it a popular tourist site. Over the course of two weeks, I was able to collect data on how the heavy development of Tioman Island's tourist industry was affecting the biodiversity of the region, specifically the implementation of infrastructure like footpaths. Tioman was an excellent setting for my research as it provided both primary and secondary rainforest with varying amounts of developments, allowing me to draw parallels between the data of the two distinct footpaths. To measure biodiversity against the prevalence of footpaths in forests, I set up 10 adjacent two by one meter quadrats perpendicular to the path, the first being on the path, and counted the quantities of different species within each quadrat. This process was repeated three times with five meter spacings between the various transects to better represent biodiversity in the region. Those three trials were then repeated at a site of contrasting human impact to come up with 60 quadrats' worth of data. Individually, each quadrat's biodiversity was then quantified using the Simpson's Diversity Index, which was then given a Spearman's Rank Correlation Coefficient before being compared with one another. The results of my research showed a general increase in biodiversity levels the further away it was from the path, until a certain point where it dropped and displayed a steady state, which did not fulfill the linear trend I was expecting in my hypothesis.

Radiotherapy Dose Fractionation under Parameter Uncertainty

NASA Astrophysics Data System (ADS)

Davison, Matt; Kim, Daero; Keller, Harald

2011-11-01

In radiotherapy, radiation is directed to damage a tumor while avoiding surrounding healthy tissue. Tradeoffs ensue because dose cannot be exactly shaped to the tumor. It is particularly important to ensure that sensitive biological structures near the tumor are not damaged more than a certain amount. Biological tissue is known to have a nonlinear response to incident radiation. The linear quadratic dose response model, which requires the specification of two clinically and experimentally observed response coefficients, is commonly used to model this effect. This model yields an optimization problem giving two different types of optimal dose sequences (fractionation schedules). Which fractionation schedule is preferred depends on the response coefficients. These coefficients are uncertainly known and may differ from patient to patient. Because of this not only the expected outcomes but also the uncertainty around these outcomes are important, and it might not be prudent to select the strategy with the best expected outcome.

Clinical-Functional Vulnerability Index-20 (IVCF-20): rapid recognition of frail older adults

PubMed Central

de Moraes, Edgar Nunes; do Carmo, Juliana Alves; de Moraes, Flávia Lanna; Azevedo, Raquel Souza; Machado, Carla Jorge; Montilla, Dalia Elena Romero

2016-01-01

ABSTRACT OBJECTIVE To evaluate the adequacy of the Clinical-Functional Vulnerability Index-20, a rapid triage instrument to test vulnerability in Brazilian older adults, for the use in primary health care. METHODS The study included convenience sample of 397 patients aged older than or equal to 60 years attended at Centro de Referência para o Idoso (Reference Center for Older Adults) and of 52 older adults the same age attended at the community. The results of the questionnaire, consisting of 20 questions, were compared with those of the Comprehensive Geriatric Assessment, considered a reference for identifying frail older adults. Spearman’s correlation was evaluated in the Clinical-Functional Vulnerability Index-20 with the Comprehensive Geriatric Assessment; the validity was verified by the area under the ROC curve; reliability was estimated by the percentage of agreement among evaluators and by the kappa coefficient, both with quadratic weighted. The cut-off point was obtained based on the higher accuracy criterion. Cronbach’s alpha, a measure of internal consistency, was estimated. RESULTS The Spearman’s correlation coefficient was high and positive for both groups (0.792 for older adults attended at the Reference Center and 0.305 for older adults from the community [p < 0.001]). The area under the ROC curve for older adults attended at the Reference Center was substantial (0.903). The cut-off point obtained was six, and older adults with scores in Clinical-Functional Vulnerability Index-20 above that value had strong possibility of being frail. For older adults from the community, the quadratic weighted agreement among evaluators was 99.5%, and the global quadratic weighted kappa coefficient was 0.94. Cronbach’s alpha was high for older adults attended at the Reference Center (0.861) and those attended at the community (0.740). CONCLUSIONS The Clinical-Functional Vulnerability Index-20 questionnaire, in the sample examined, turned out to be positively correlated with the Comprehensive Geriatric Assessment, in addition to the results indicating a high degree of validity and reliability. Thus, the Clinical-Functional Vulnerability Index-20 proves to be viable as a triage instrument in the primary health care that identifies frail older adults (older adults at risk of weakening and frail older adults). PMID:28099667

Majorization Minimization by Coordinate Descent for Concave Penalized Generalized Linear Models

PubMed Central

Jiang, Dingfeng; Huang, Jian

2013-01-01

Recent studies have demonstrated theoretical attractiveness of a class of concave penalties in variable selection, including the smoothly clipped absolute deviation and minimax concave penalties. The computation of the concave penalized solutions in high-dimensional models, however, is a difficult task. We propose a majorization minimization by coordinate descent (MMCD) algorithm for computing the concave penalized solutions in generalized linear models. In contrast to the existing algorithms that use local quadratic or local linear approximation to the penalty function, the MMCD seeks to majorize the negative log-likelihood by a quadratic loss, but does not use any approximation to the penalty. This strategy makes it possible to avoid the computation of a scaling factor in each update of the solutions, which improves the efficiency of coordinate descent. Under certain regularity conditions, we establish theoretical convergence property of the MMCD. We implement this algorithm for a penalized logistic regression model using the SCAD and MCP penalties. Simulation studies and a data example demonstrate that the MMCD works sufficiently fast for the penalized logistic regression in high-dimensional settings where the number of covariates is much larger than the sample size. PMID:25309048

[Photometric determination of cobalt by the formation of a multi-ligand complex of Co(II)-C16H16N2S2O2-DEA].

PubMed

Xue, Zhao-ming; Xie, An-jian; Huang, Fang-zhi; Ma, Wen

2002-08-01

The new ligand vanillin S-benzyldithocarbazte(HL) and its complex Co(II)-C16H16N2S2O2-DEA was synthesized and characterized by IR, UV-Vis. The optimum color conditions of the complex in 95% ethanol solution(including reaction temperature T, heating time t, and the concentrations of the three components) have been studied by quadratic regression orthogonal design method. According to the quadratic-regression equation, the maximum absorption intensity and optimum color conditions of the complex were calculated. The results were consistent with those gotten by experiment. The influences of common ions on the determination of cobalt and the methods to eliminate the influence are investigated. The maximum absorption peak of the complex is found at 404 nm and molar absorptivity is 5.29 x 10(4) L.mol-1.cm-1. Beer's law is obeyed in the range of 0-20 micrograms.(25 mL)-1 for Co(II). The composition of Co2+ to HL, and DEA in the complex is 1:2:1. The new method was successfully utilized to the determination of cobalt in VB12 and medicine.

Partial F-tests with multiply imputed data in the linear regression framework via coefficient of determination.

PubMed

Chaurasia, Ashok; Harel, Ofer

2015-02-10

Tests for regression coefficients such as global, local, and partial F-tests are common in applied research. In the framework of multiple imputation, there are several papers addressing tests for regression coefficients. However, for simultaneous hypothesis testing, the existing methods are computationally intensive because they involve calculation with vectors and (inversion of) matrices. In this paper, we propose a simple method based on the scalar entity, coefficient of determination, to perform (global, local, and partial) F-tests with multiply imputed data. The proposed method is evaluated using simulated data and applied to suicide prevention data. Copyright © 2014 John Wiley & Sons, Ltd.

Specifics of soil temperature under winter oilseed rape canopy

NASA Astrophysics Data System (ADS)

Krčmářová, Jana; Středa, Tomáš; Pokorný, Radovan

2014-09-01

The aim of this study was to evaluate the course of soil temperature under the winter oilseed rape canopy and to determine relationships between soil temperature, air temperature and partly soil moisture. In addition, the aim was to describe the dependence by means of regression equations usable for pests and pathogens prediction, crop development, and yields models. The measurement of soil and near the ground air temperatures was performed at the experimental field Žabiče (South Moravia, the Czech Republic). The course of temperature was determined under or in the winter oilseed rape canopy during spring growth season in the course of four years (2010 - 2012 and 2014). In all years, the standard varieties (Petrol, Sherpa) were grown, in 2014 the semi-dwarf variety PX104 was added. Automatic soil sensors were positioned at three depths (0.05, 0.10 and 0.20 m) under soil surface, air temperature sensors in 0.05 m above soil surfaces. The course of soil temperature differs significantly between standard (Sherpa and Petrol) and semi-dwarf (PX104) varieties. Results of the cross correlation analysis showed, that the best interrelationships between air and soil temperature were achieved in 2 hours delay for the soil temperature in 0.05 m, 4 hour delay for 0.10 m and 7 hour delay for 0.20 m for standard varieties. For semi-dwarf variety, this delay reached 6 hour for the soil temperature in 0.05 m, 7 hour delay for 0.10 m and 11 hour for 0.20 m. After the time correction, the determination coefficient (R2) reached values from 0.67 to 0.95 for 0.05 m, 0.50 to 0.84 for 0.10 m in variety Sherpa during all experimental years. For variety PX104 this coefficient reached values from 0.51 to 0.72 in 0.05 m depth and from 0.39 to 0.67 in 0.10 m depth in the year 2014. The determination coefficient in the 0.20 m depth was lower for both varieties; its values were from 0.15 to 0.65 in variety Sherpa. In variety PX104 the values of R2 from 0.23 to 0.57 were determined. When using multiple regressions with quadratic spacing (modelling of hourly soil temperature based on the hourly near surface air temperature and hourly soil moisture in the 0.10-0.40 m profile), the difference between the measured and modelled soil temperatures in the depth of 0.05 m was -3.92 to 3.99°C. The regression equation paired with alternative agrometeorological instruments enables relatively accurate modelling of soil temperatures (R2 = 0.95).

Attenuation of ground-motion spectral amplitudes in southeastern Australia

USGS Publications Warehouse

Allen, T.I.; Cummins, P.R.; Dhu, T.; Schneider, J.F.

2007-01-01

A dataset comprising some 1200 weak- and strong-motion records from 84 earthquakes is compiled to develop a regional ground-motion model for southeastern Australia (SEA). Events were recorded from 1993 to 2004 and range in size from moment magnitude 2.0 ??? M ??? 4.7. The decay of vertical-component Fourier spectral amplitudes is modeled by trilinear geometrical spreading. The decay of low-frequency spectral amplitudes can be approximated by the coefficient of R-1.3 (where R is hypocentral distance) within 90 km of the seismic source. From approximately 90 to 160 km, we observe a transition zone in which the seismic coda are affected by postcritical reflections from midcrustal and Moho discontinuities. In this hypocentral distance range, geometrical spreading is approximately R+0.1. Beyond 160 km, low-frequency seismic energy attenuates rapidly with source-receiver distance, having a geometrical spreading coefficient of R-1.6. The associated regional seismic-quality factor can be expressed by the polynomial: log Q(f) = 3.66 - 1.44 log f + 0.768 (log f)2 + 0.058 (log f)3 for frequencies 0.78 ??? f ??? 19.9 Hz. Fourier spectral amplitudes, corrected for geometrical spreading and anelastic attenuation, are regressed with M to obtain quadratic source scaling coefficients. Modeled vertical-component displacement spectra fit the observed data well. Amplitude residuals are, on average, relatively small and do not vary with hypocentral distance. Predicted source spectra (i.e., at R = 1 km) are consistent with eastern North American (ENA) Models at low frequencies (f less than approximately 2 Hz) indicating that moment magnitudes calculated for SEA earthquakes are consistent with moment magnitude scales used in ENA over the observed magnitude range. The models presented represent the first spectral ground-motion prediction equations develooed for the southeastern Australian region. This work provides a useful framework for the development of regional ground-motion relations for earthquake hazard and risk assessment in SEA.

Adiabatic decay of internal solitons due to Earth's rotation within the framework of the Gardner-Ostrovsky equation

NASA Astrophysics Data System (ADS)

Obregon, Maria; Raj, Nawin; Stepanyants, Yury

2018-03-01

The adiabatic decay of different types of internal wave solitons caused by the Earth's rotation is studied within the framework of the Gardner-Ostrovsky equation. The governing equation describing such processes includes quadratic and cubic nonlinear terms, as well as the Boussinesq and Coriolis dispersions: (ut + c ux + α u ux + α1 u2 ux + β uxxx)x = γ u. It is shown that at the early stage of evolution solitons gradually decay under the influence of weak Earth's rotation described by the parameter γ. The characteristic decay time is derived for different types of solitons for positive and negative coefficients of cubic nonlinearity α1 (both signs of that parameter may occur in the oceans). The coefficient of quadratic nonlinearity α determines only a polarity of solitary wave when α1 < 0 or the asymmetry of solitary waves of opposite polarity when α1 > 0. It is found that the adiabatic theory describes well the decay of solitons having bell-shaped profiles. In contrast to that, large amplitude table-top solitons, which can exist when α1 is negative, are structurally unstable. Under the influence of Earth's rotation, they transfer first to the bell-shaped solitons, which decay then adiabatically. Estimates of the characteristic decay time of internal solitons are presented for the real oceanographic conditions.

A Path Algorithm for Constrained Estimation

PubMed Central

Zhou, Hua; Lange, Kenneth

2013-01-01

Many least-square problems involve affine equality and inequality constraints. Although there are a variety of methods for solving such problems, most statisticians find constrained estimation challenging. The current article proposes a new path-following algorithm for quadratic programming that replaces hard constraints by what are called exact penalties. Similar penalties arise in l1 regularization in model selection. In the regularization setting, penalties encapsulate prior knowledge, and penalized parameter estimates represent a trade-off between the observed data and the prior knowledge. Classical penalty methods of optimization, such as the quadratic penalty method, solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to ∞, one recovers the constrained solution. In the exact penalty method, squared penalties!are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. The exact path-following method starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. Path following in Lasso penalized regression, in contrast, starts with a large value of the penalty constant and works its way downward. In both settings, inspection of the entire solution path is revealing. Just as with the Lasso and generalized Lasso, it is possible to plot the effective degrees of freedom along the solution path. For a strictly convex quadratic program, the exact penalty algorithm can be framed entirely in terms of the sweep operator of regression analysis. A few well-chosen examples illustrate the mechanics and potential of path following. This article has supplementary materials available online. PMID:24039382

Limb-darkening coefficients for the purpose of pulsation mode identification for A-F stars. .

NASA Astrophysics Data System (ADS)

Barban, C.; Goupil, M. J.; van't Veer-Menneret, C.; Garrido, R.; Heiter, U.; Kupka, F.

Limb-darkening coefficients are computed from a set of model atmospheres with: a solar chemical composition, 6000 K< Teff < 8500 K (Delta T_eff=250 K), 2.5 < logg < 4.5 (Delta log g=0.1) and a microturbulent velocity of 2 km/s. Convection is included assuming either the turbulent convection approach of \\citet{cm} or the classical mixing length prescription with alpha =0.5 and 1.25. Four limb-darkening laws have been used: quadratic, cubic, square root and the one of \\citet{cl}. We compare the ATLAS 9 intensities and the ones computed from these laws. We find that Claret's law is the best law for almost all the models, independently of the convection prescription used.

Comparing Regression Coefficients between Nested Linear Models for Clustered Data with Generalized Estimating Equations

ERIC Educational Resources Information Center

Yan, Jun; Aseltine, Robert H., Jr.; Harel, Ofer

2013-01-01

Comparing regression coefficients between models when one model is nested within another is of great practical interest when two explanations of a given phenomenon are specified as linear models. The statistical problem is whether the coefficients associated with a given set of covariates change significantly when other covariates are added into…

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.

Adjusting for Confounding in Early Postlaunch Settings: Going Beyond Logistic Regression Models.

PubMed

Schmidt, Amand F; Klungel, Olaf H; Groenwold, Rolf H H

2016-01-01

Postlaunch data on medical treatments can be analyzed to explore adverse events or relative effectiveness in real-life settings. These analyses are often complicated by the number of potential confounders and the possibility of model misspecification. We conducted a simulation study to compare the performance of logistic regression, propensity score, disease risk score, and stabilized inverse probability weighting methods to adjust for confounding. Model misspecification was induced in the independent derivation dataset. We evaluated performance using relative bias confidence interval coverage of the true effect, among other metrics. At low events per coefficient (1.0 and 0.5), the logistic regression estimates had a large relative bias (greater than -100%). Bias of the disease risk score estimates was at most 13.48% and 18.83%. For the propensity score model, this was 8.74% and >100%, respectively. At events per coefficient of 1.0 and 0.5, inverse probability weighting frequently failed or reduced to a crude regression, resulting in biases of -8.49% and 24.55%. Coverage of logistic regression estimates became less than the nominal level at events per coefficient ≤5. For the disease risk score, inverse probability weighting, and propensity score, coverage became less than nominal at events per coefficient ≤2.5, ≤1.0, and ≤1.0, respectively. Bias of misspecified disease risk score models was 16.55%. In settings with low events/exposed subjects per coefficient, disease risk score methods can be useful alternatives to logistic regression models, especially when propensity score models cannot be used. Despite better performance of disease risk score methods than logistic regression and propensity score models in small events per coefficient settings, bias, and coverage still deviated from nominal.

Meta-analytical synthesis of regression coefficients under different categorization scheme of continuous covariates.

PubMed

Yoneoka, Daisuke; Henmi, Masayuki

2017-11-30

Recently, the number of clinical prediction models sharing the same regression task has increased in the medical literature. However, evidence synthesis methodologies that use the results of these regression models have not been sufficiently studied, particularly in meta-analysis settings where only regression coefficients are available. One of the difficulties lies in the differences between the categorization schemes of continuous covariates across different studies. In general, categorization methods using cutoff values are study specific across available models, even if they focus on the same covariates of interest. Differences in the categorization of covariates could lead to serious bias in the estimated regression coefficients and thus in subsequent syntheses. To tackle this issue, we developed synthesis methods for linear regression models with different categorization schemes of covariates. A 2-step approach to aggregate the regression coefficient estimates is proposed. The first step is to estimate the joint distribution of covariates by introducing a latent sampling distribution, which uses one set of individual participant data to estimate the marginal distribution of covariates with categorization. The second step is to use a nonlinear mixed-effects model with correction terms for the bias due to categorization to estimate the overall regression coefficients. Especially in terms of precision, numerical simulations show that our approach outperforms conventional methods, which only use studies with common covariates or ignore the differences between categorization schemes. The method developed in this study is also applied to a series of WHO epidemiologic studies on white blood cell counts. Copyright © 2017 John Wiley & Sons, Ltd.

Correlation among extinction efficiency and other parameters in an aggregate dust model

NASA Astrophysics Data System (ADS)

Dhar, Tanuj Kumar; Sekhar Das, Himadri

2017-10-01

We study the extinction properties of highly porous Ballistic Cluster-Cluster Aggregate dust aggregates in a wide range of complex refractive indices (1.4≤ n≤ 2.0, 0.001≤ k≤ 1.0) and wavelengths (0.11 {{μ }}{{m}}≤ {{λ }}≤ 3.4 {{μ }} m). An attempt has been made for the first time to investigate the correlation among extinction efficiency ({Q}{ext}), composition of dust aggregates (n,k), wavelength of radiation (λ) and size parameter of the monomers (x). If k is fixed at any value between 0.001 and 1.0, {Q}{ext} increases with increase of n from 1.4 to 2.0. {Q}{ext} and n are correlated via linear regression when the cluster size is small, whereas the correlation is quadratic at moderate and higher sizes of the cluster. This feature is observed at all wavelengths (ultraviolet to optical to infrared). We also find that the variation of {Q}{ext} with n is very small when λ is high. When n is fixed at any value between 1.4 and 2.0, it is observed that {Q}{ext} and k are correlated via a polynomial regression equation (of degree 1, 2, 3 or 4), where the degree of the equation depends on the cluster size, n and λ. The correlation is linear for small size and quadratic/cubic/quartic for moderate and higher sizes. We have also found that {Q}{ext} and x are correlated via a polynomial regression (of degree 3, 4 or 5) for all values of n. The degree of regression is found to be n and k-dependent. The set of relations obtained from our work can be used to model interstellar extinction for dust aggregates in a wide range of wavelengths and complex refractive indices.

Demonstration and Validation of the Geostatistical Temporal-Spatial Algorithm (GTS) for Optimization of Long-Term Monitoring (LTM) of Groundwater at Military and Government Sites

DTIC Science & Technology

2010-08-01

Long - Term Monitoring (LTM) of Groundwater at Military and...Geostatistical Temporal-Spatial Algorithm (GTS) for Optimization of Long - Term Monitoring (LTM) of Groundwater at Military and Government Sites 5a. CONTRACT NUMBER...Council LTM long - term monitoring LTMO long - term monitoring optimization LWQR locally weighted quadratic regression LZ Lower Zone MCL

Regeneration of Douglas-fir cutblocks on the Six Rivers National Forest in northwestern California

Treesearch

R. O. Strothmann

1979-01-01

A survey of 61 cutblocks planted since 1964 evaluated stocking of conifers (trees 1 foot tall or taller) on 2-milacre quadrats. Overall stocking percentage averaged 42.2 and ranged from 15 to 8 1. Overall number of trees per acre averaged 396. In the regression model, based on 36 cutblocks, better stocking was associated with high site class, northerly aspect,...

Feed intake of sheep as affected by body weight, breed, sex, and feed composition.

PubMed

Lewis, R M; Emmans, G C

2010-02-01

The hypotheses tested were that genetic size-scaling for mature BW (A, kg) would reduce variation in intake between kinds of sheep and that quadratic polynomials on u = BW/A with zero intercept would provide good descriptions of the relationship between scaled intake (SI, g/A(0.73) d) and degree of maturity in BW (u) across feeds of differing quality. Both sexes of Suffolk sheep from 2 experimental lines (n = 225) and from 3 breed types (Suffolk, Scottish Blackface, and their cross; n = 149) were recorded weekly for ad libitum feed intake and BW; recording of intake was from weaning through, in some cases, near maturity. Six diets of different quality were fed ad libitum. The relationship between intake and BW on a given feed varied considerably between kinds of sheep. Much, but not all, of that variation was removed by genetic size-scaling. In males, the maximum value of SI was greater than in females (P = 0.07) and was greater in Suffolk than in Scottish Blackface, with the cross intermediate (P = 0.025); there was no difference between the 2 Suffolk lines used (P = 0.106). The quadratic polynomial model, through the origin, was compared with a split-line (spline) regression for describing how SI varied with u. For the spline model, the intercept was not different from zero in any case (P > 0.05). The values of u at which SI achieved its maximum value (u* and SI*) were calculated. Both models fit the data well; the quadratic was preferred because it predicted that SI* would be achieved within the range of the long-run data, as was observed. On a high quality feed, for the spline regression, u* varied little around 0.434 (SD = 0.020) for the 10 different kinds of sheep used. For the quadratic, the mean value of 0.643 (SD = 0.066) was more variable, but there were no consistent effects of kind of sheep. The values of u* and SI* estimated using the quadratic model varied among the 6 feeds: 0.643 and 78.5 on high quality; 0.760 and 79.6 on medium protein content; 0.859 and 73.3 on low protein content; 0.756 and 112 on a low energy content feed; 0.937 and 107 on ryegrass; and 1 (forced, as the fitted value of 1.11 was infeasible) and 135 on Lucerne. The value of u* tended to increase as feed digestibility decreased. We conclude that genetic size-scaling of intake is useful and that a quadratic polynomial with zero intercept provides a good description of the relationship between SI and u for different kinds of sheep on feeds of different quality. Up to u congruent with 0.45, intake was directly proportional to BW.

A New Methodology of Spatial Cross-Correlation Analysis

PubMed Central

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

A new methodology of spatial cross-correlation analysis.

PubMed

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.

Rotordynamic Forces Developed by Labyrinth Seals

DTIC Science & Technology

1984-11-01

the prediction of leakage and the rotordynamic coefficients of Eq. (1) for labyrinth seals . A copy of reference DI) is attached. In comparison to... Leakage of Steam Through Labyrinth Glands," Trans. ASME, Vol. 57, 1935, pp. 115-122. 16. John, E. A. Jamea, Gas Dynamios, Wylie, 1979. -19- • ]{ o -Cr...Quadratic-Upstream Di iferemcing in Uigh Reynolds Number Illiptic a. Xgli. A.. ’"the Leakage of Steam Through Labyrinth flows," of P ohAa. ab o.. l 9

Turing-Hopf bifurcations in a predator-prey model with herd behavior, quadratic mortality and prey-taxis

NASA Astrophysics Data System (ADS)

Liu, Xia; Zhang, Tonghua; Meng, Xinzhu; Zhang, Tongqian

2018-04-01

In this paper, we propose a predator-prey model with herd behavior and prey-taxis. Then, we analyze the stability and bifurcation of the positive equilibrium of the model subject to the homogeneous Neumann boundary condition. By using an abstract bifurcation theory and taking prey-tactic sensitivity coefficient as the bifurcation parameter, we obtain a branch of stable nonconstant solutions bifurcating from the positive equilibrium. Our results show that prey-taxis can yield the occurrence of spatial patterns.

On analytic design of loudspeaker arrays with uniform radiation characteristics

PubMed

Aarts; Janssen

2000-01-01

Some notes on analytical derived loudspeaker arrays with uniform radiation characteristics are presented. The array coefficients are derived via analytical means and compared with so-called maximal flat sequences known from telecommunications and information theory. It appears that the newly derived array, i.e., the quadratic phase array, has a higher efficiency than the Bessel array and a flatter response than the Barker array. The method discussed admits generalization to the design of arrays with desired nonuniform radiating characteristics.

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.)

Highly accurate analytic formulae for projectile motion subjected to quadratic drag

NASA Astrophysics Data System (ADS)

Turkyilmazoglu, Mustafa

2016-05-01

The classical phenomenon of motion of a projectile fired (thrown) into the horizon through resistive air charging a quadratic drag onto the object is revisited in this paper. No exact solution is known that describes the full physical event under such an exerted resistance force. Finding elegant analytical approximations for the most interesting engineering features of dynamical behavior of the projectile is the principal target. Within this purpose, some analytical explicit expressions are derived that accurately predict the maximum height, its arrival time as well as the flight range of the projectile at the highest ascent. The most significant property of the proposed formulas is that they are not restricted to the initial speed and firing angle of the object, nor to the drag coefficient of the medium. In combination with the available approximations in the literature, it is possible to gain information about the flight and complete the picture of a trajectory with high precision, without having to numerically simulate the full governing equations of motion.

A subgradient approach for constrained binary optimization via quantum adiabatic evolution

NASA Astrophysics Data System (ADS)

Karimi, Sahar; Ronagh, Pooya

2017-08-01

Outer approximation method has been proposed for solving the Lagrangian dual of a constrained binary quadratic programming problem via quantum adiabatic evolution in the literature. This should be an efficient prescription for solving the Lagrangian dual problem in the presence of an ideally noise-free quantum adiabatic system. However, current implementations of quantum annealing systems demand methods that are efficient at handling possible sources of noise. In this paper, we consider a subgradient method for finding an optimal primal-dual pair for the Lagrangian dual of a constrained binary polynomial programming problem. We then study the quadratic stable set (QSS) problem as a case study. We see that this method applied to the QSS problem can be viewed as an instance-dependent penalty-term approach that avoids large penalty coefficients. Finally, we report our experimental results of using the D-Wave 2X quantum annealer and conclude that our approach helps this quantum processor to succeed more often in solving these problems compared to the usual penalty-term approaches.

Quadratic dissipation effect on the moonpool resonance

NASA Astrophysics Data System (ADS)

Liu, Heng-xu; Chen, Hai-long; Zhang, Liang; Zhang, Wan-chao; Liu, Ming

2017-12-01

This paper adopted a semi-analytical method based on eigenfunction matching to solve the problem of sharp resonance of cylindrical structures with a moonpool that has a restricted entrance. To eliminate the sharp resonance and to measure the viscous effect, a quadratic dissipation is introduced by assuming an additional dissipative disk at the moonpool entrance. The fluid domain is divided into five cylindrical subdomains, and the velocity potential in each subdomain is obtained by meeting the Laplace equation as well as the boundary conditions. The free-surface elevation at the center of the moonpool, along with the pressure and velocity at the restricted entrance for first-order wave are evaluated. By choosing appropriate dissipation coefficients, the free-surface elevation calculated at the center of the moonpool is in coincidence with the measurements in model tests both at the peak period and amplitude at resonance. It is shown that the sharp resonance in the potential flow theory can be eliminated and the viscous effect can be estimated with a simple method in some provided hydrodynamic models.

Coherence solution for bidirectional reflectance distributions of surfaces with wavelength-scale statistics.

PubMed

Hoover, Brian G; Gamiz, Victor L

2006-02-01

The scalar bidirectional reflectance distribution function (BRDF) due to a perfectly conducting surface with roughness and autocorrelation width comparable with the illumination wavelength is derived from coherence theory on the assumption of a random reflective phase screen and an expansion valid for large effective roughness. A general quadratic expansion of the two-dimensional isotropic surface autocorrelation function near the origin yields representative Cauchy and Gaussian BRDF solutions and an intermediate general solution as the sum of an incoherent component and a nonspecular coherent component proportional to an integral of the plasma dispersion function in the complex plane. Plots illustrate agreement of the derived general solution with original bistatic BRDF data due to a machined aluminum surface, and comparisons are drawn with previously published data in the examination of variations with incident angle, roughness, illumination wavelength, and autocorrelation coefficients in the bistatic and monostatic geometries. The general quadratic autocorrelation expansion provides a BRDF solution that smoothly interpolates between the well-known results of the linear and parabolic approximations.

SPSS macros to compare any two fitted values from a regression model.

PubMed

Weaver, Bruce; Dubois, Sacha

2012-12-01

In regression models with first-order terms only, the coefficient for a given variable is typically interpreted as the change in the fitted value of Y for a one-unit increase in that variable, with all other variables held constant. Therefore, each regression coefficient represents the difference between two fitted values of Y. But the coefficients represent only a fraction of the possible fitted value comparisons that might be of interest to researchers. For many fitted value comparisons that are not captured by any of the regression coefficients, common statistical software packages do not provide the standard errors needed to compute confidence intervals or carry out statistical tests-particularly in more complex models that include interactions, polynomial terms, or regression splines. We describe two SPSS macros that implement a matrix algebra method for comparing any two fitted values from a regression model. The !OLScomp and !MLEcomp macros are for use with models fitted via ordinary least squares and maximum likelihood estimation, respectively. The output from the macros includes the standard error of the difference between the two fitted values, a 95% confidence interval for the difference, and a corresponding statistical test with its p-value.

Implementations of geographically weighted lasso in spatial data with multicollinearity (Case study: Poverty modeling of Java Island)

NASA Astrophysics Data System (ADS)

Setiyorini, Anis; Suprijadi, Jadi; Handoko, Budhi

2017-03-01

Geographically Weighted Regression (GWR) is a regression model that takes into account the spatial heterogeneity effect. In the application of the GWR, inference on regression coefficients is often of interest, as is estimation and prediction of the response variable. Empirical research and studies have demonstrated that local correlation between explanatory variables can lead to estimated regression coefficients in GWR that are strongly correlated, a condition named multicollinearity. It later results on a large standard error on estimated regression coefficients, and, hence, problematic for inference on relationships between variables. Geographically Weighted Lasso (GWL) is a method which capable to deal with spatial heterogeneity and local multicollinearity in spatial data sets. GWL is a further development of GWR method, which adds a LASSO (Least Absolute Shrinkage and Selection Operator) constraint in parameter estimation. In this study, GWL will be applied by using fixed exponential kernel weights matrix to establish a poverty modeling of Java Island, Indonesia. The results of applying the GWL to poverty datasets show that this method stabilizes regression coefficients in the presence of multicollinearity and produces lower prediction and estimation error of the response variable than GWR does.

Application of Box-Behnken design for modeling of lead adsorption onto unmodified and NaCl-modified zeolite NaA obtained from biosilica.

PubMed

Terzioğlu, Pinar; Yücel, Sevil; Öztürk, Mehmet

2017-01-01

The main objective of the present study was to optimize lead adsorption onto zeolite NaA. For this purpose, to synthesize zeolite NaA under hydrothermal conditions, local wheat husk was precleaned with chemical treatment using hydrochloric acid solution. The unmodified (ZU) and NaCl-modified (ZN) zeolites were characterized by Brunauer-Emmett-Teller, scanning electron microscopy coupled with energy dispersive spectroscopy and X-ray diffraction. The optimization of adsorption process was examined using Box-Behnken Experimental Design in response surface methodology by Design Expert Version 7.0.0 (Stat-Ease, USA). The effects of initial lead (II) concentration, temperature, and time were selected as independent variables. Lack of fit test indicates that the quadratic regression model was significant with the high coefficients of determination values for both adsorbents. Optimum process conditions for lead (II) adsorption onto ZU and ZN were found to be 64.40°C and 64.80°C, respectively, and 90.80 min, and 350 mg L -1 initial lead(II) concentration for both adsorbents. Under these conditions, maximum adsorption capacities of ZU and ZN for lead (II) were 293.38 mg g -1 and 321.85 mg g -1 , respectively.

Optimization of Crude Oil and PAHs Degradation by Stenotrophomonas rhizophila KX082814 Strain through Response Surface Methodology Using Box-Behnken Design

PubMed Central

Virupakshappa, Praveen Kumar Siddalingappa; Mishra, Gaurav; Mehkri, Mohammed Ameenuddin

2016-01-01

The present paper describes the process optimization study for crude oil degradation which is a continuation of our earlier work on hydrocarbon degradation study of the isolate Stenotrophomonas rhizophila (PM-1) with GenBank accession number KX082814. Response Surface Methodology with Box-Behnken Design was used to optimize the process wherein temperature, pH, salinity, and inoculum size (at three levels) were used as independent variables and Total Petroleum Hydrocarbon, Biological Oxygen Demand, and Chemical Oxygen Demand of crude oil and PAHs as dependent variables (response). The statistical analysis, via ANOVA, showed coefficient of determination R 2 as 0.7678 with statistically significant P value 0.0163 fitting in second-order quadratic regression model for crude oil removal. The predicted optimum parameters, namely, temperature, pH, salinity, and inoculum size, were found to be 32.5°C, 9, 12.5, and 12.5 mL, respectively. At this optimum condition, the observed and predicted PAHs and crude oil removal were found to be 71.82% and 79.53% in validation experiments, respectively. The % TPH results correlate with GC/MS studies, BOD, COD, and TPC. The validation of numerical optimization was done through GC/MS studies and % removal of crude oil. PMID:28116165

Height reduction among prenatally exposed atomic-bomb survivors: A longitudinal study of growth

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

Nakashima, Eiji; Funamoto, Sachiyo; Carter, R.L.

Using a random coefficient regression model, sex-specific longitudinal analyses of height were made on 801 (392 male and 409 female) atomic-bomb survivors exposed in utero to detect dose effects on standing height. The data set resulted from repeated measurements of standing height of adolescents (age 10-18 y). The dose effect, if any, was assumed to be linear. Gestational ages at the time of radiation exposure were divided into trimesters. Since an earlier longitudinal data analysis has demonstrated radiation effects on height, the emphasis in this paper is on the interaction between dose and gestational age at exposure and radiation effectsmore » on the age of occurrence of the adolescent growth spurt. For males, a cubic polynomial growth-curve model applied to the data was affected significantly by radiation. The dose by trimester interaction effect was not significant. The onset of adolescent growth spurt was estimated at about 13 y at 0 Gy. There was no effect of radiation on the adolescent growth spurt For females, a quadratic polynomial growth-curve model was fitted to the data. The dose effect was significant, while the dose by trimester interaction was again not significant. 27 refs., 3 figs., 4 tabs.« less

Calibration of Safecast dose rate measurements.

PubMed

Cervone, Guido; Hultquist, Carolynne

2018-10-01

A methodology is presented to calibrate contributed Safecast dose rate measurements acquired between 2011 and 2016 in the Fukushima prefecture of Japan. The Safecast data are calibrated using observations acquired by the U.S. Department of Energy at the time of the 2011 Fukushima Daiichi power plant nuclear accident. The methodology performs a series of interpolations between the U.S. government and contributed datasets at specific temporal windows and at corresponding spatial locations. The coefficients found for all the different temporal windows are aggregated and interpolated using quadratic regressions to generate a time dependent calibration function. Normal background radiation, decay rates, and missing values are taken into account during the analysis. Results show that the standard Safecast static transformation function overestimates the official measurements because it fails to capture the presence of two different Cesium isotopes and their changing magnitudes with time. A model is created to predict the ratio of the isotopes from the time of the accident through 2020. The proposed time dependent calibration takes into account this Cesium isotopes ratio, and it is shown to reduce the error between U.S. government and contributed data. The proposed calibration is needed through 2020, after which date the errors introduced by ignoring the presence of different isotopes will become negligible. Copyright © 2018 Elsevier Ltd. All rights reserved.

Validation of UHPLC-MS/MS methods for the determination of kaempferol and its metabolite 4-hydroxyphenyl acetic acid, and application to in vitro blood-brain barrier and intestinal drug permeability studies.

PubMed

Moradi-Afrapoli, Fahimeh; Oufir, Mouhssin; Walter, Fruzsina R; Deli, Maria A; Smiesko, Martin; Zabela, Volha; Butterweck, Veronika; Hamburger, Matthias

2016-09-05

Sedative and anxiolytic-like properties of flavonoids such as kaempferol and quercetin, and of some of their intestinal metabolites, have been demonstrated in pharmacological studies. However, routes of administration were shown to be critical for observing in vivo activity. Therefore, the ability to cross intestinal and blood-brain barriers was assessed in cell-based models for kaempferol (KMF), and for the major intestinal metabolite of KMF, 4-hydroxyphenylacetic acid (4-HPAA). Intestinal transport studies were performed with Caco-2 cells, and blood-brain barrier transport studies with an immortalized monoculture human model and a primary triple-co-culture rat model. UHPLC-MS/MS methods for KMF and 4-HPAA in Ringer-HEPES buffer and in Hank's balanced salt solution were validated according to industry guidelines. For all methods, calibration curves were fitted by least-squares quadratic regression with 1/X(2) as weighing factor, and mean coefficients of determination (R(2)) were >0.99. Data obtained with all barrier models showed high intestinal and blood-brain barrier permeation of KMF, and no permeability of 4-HPAA, when compared to barrier integrity markers. Copyright © 2016 Elsevier B.V. All rights reserved.

A hybrid PSO-SVM-based method for predicting the friction coefficient between aircraft tire and coating

NASA Astrophysics Data System (ADS)

Zhan, Liwei; Li, Chengwei

2017-02-01

A hybrid PSO-SVM-based model is proposed to predict the friction coefficient between aircraft tire and coating. The presented hybrid model combines a support vector machine (SVM) with particle swarm optimization (PSO) technique. SVM has been adopted to solve regression problems successfully. Its regression accuracy is greatly related to optimizing parameters such as the regularization constant C , the parameter gamma γ corresponding to RBF kernel and the epsilon parameter \\varepsilon in the SVM training procedure. However, the friction coefficient which is predicted based on SVM has yet to be explored between aircraft tire and coating. The experiment reveals that drop height and tire rotational speed are the factors affecting friction coefficient. Bearing in mind, the friction coefficient can been predicted using the hybrid PSO-SVM-based model by the measured friction coefficient between aircraft tire and coating. To compare regression accuracy, a grid search (GS) method and a genetic algorithm (GA) are used to optimize the relevant parameters (C , γ and \\varepsilon ), respectively. The regression accuracy could be reflected by the coefficient of determination ({{R}2} ). The result shows that the hybrid PSO-RBF-SVM-based model has better accuracy compared with the GS-RBF-SVM- and GA-RBF-SVM-based models. The agreement of this model (PSO-RBF-SVM) with experiment data confirms its good performance.

Nonlinear Associations between Plasma Cholesterol Levels and Neuropsychological Function

PubMed Central

Wendell, Carrington R.; Zonderman, Alan B.; Katzel, Leslie I.; Rosenberger, William F.; Plamadeala, Victoria V.; Hosey, Megan M.; Waldstein, Shari R.

2016-01-01

Objective Although both high and low levels of total and low-density lipoprotein (LDL) cholesterol have been associated with poor neuropsychological function, little research has examined nonlinear effects. We examined quadratic relations of cholesterol to performance on a comprehensive neuropsychological battery. Method Participants were 190 older adults (53% men, ages 54–83) free of major medical, neurologic, and psychiatric disease. Measures of fasting plasma total and high-density lipoprotein (HDL) cholesterol were assayed, and LDL cholesterol was calculated. Participants completed neuropsychological measures of attention, executive function, memory, visuospatial judgment, and manual speed/dexterity. Multiple regression analyses examined cholesterol levels as quadratic predictors of each measure of cognitive performance, with age (dichotomized as <70 vs. 70+) as an effect modifier. Results A significant quadratic effect of total cholesterol2 × age was identified for Logical Memory II (b=−.0013, p=.039), such that the 70+ group performed best at high and low levels of total cholesterol than at mid-range total cholesterol (U-shaped), and the <70 group performed worse at high and low levels of total cholesterol than at mid-range total cholesterol (inverted U-shape). Similarly, significant U- and J-shaped effects of LDL cholesterol2 × age were identified for Visual Reproduction II (b=−.0020, p=.026) and log of Trails B (b=.0001, p=.044). Quadratic associations between HDL cholesterol and cognitive performance were nonsignificant. Conclusions Results indicate differential associations between cholesterol and neuropsychological function across different ages and domains of function. High and low total and LDL cholesterol may confer both risk and benefit for suboptimal cognitive function at different ages. PMID:27280580

The dynamic model of enterprise revenue management

NASA Astrophysics Data System (ADS)

Mitsel, A. A.; Kataev, M. Yu; Kozlov, S. V.; Korepanov, K. V.

2017-01-01

The article presents the dynamic model of enterprise revenue management. This model is based on the quadratic criterion and linear control law. The model is founded on multiple regression that links revenues with the financial performance of the enterprise. As a result, optimal management is obtained so as to provide the given enterprise revenue, namely, the values of financial indicators that ensure the planned profit of the organization are acquired.

[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

PubMed

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

On the modular structure of the genus-one Type II superstring low energy expansion

NASA Astrophysics Data System (ADS)

D'Hoker, Eric; Green, Michael B.; Vanhove, Pierre

2015-08-01

The analytic contribution to the low energy expansion of Type II string amplitudes at genus-one is a power series in space-time derivatives with coefficients that are determined by integrals of modular functions over the complex structure modulus of the world-sheet torus. These modular functions are associated with world-sheet vacuum Feynman diagrams and given by multiple sums over the discrete momenta on the torus. In this paper we exhibit exact differential and algebraic relations for a certain infinite class of such modular functions by showing that they satisfy Laplace eigenvalue equations with inhomogeneous terms that are polynomial in non-holomorphic Eisenstein series. Furthermore, we argue that the set of modular functions that contribute to the coefficients of interactions up to order are linear sums of functions in this class and quadratic polynomials in Eisenstein series and odd Riemann zeta values. Integration over the complex structure results in coefficients of the low energy expansion that are rational numbers multiplying monomials in odd Riemann zeta values.

Velocity and Drag Evolution From the Leading Edge of a Model Mangrove Forest

NASA Astrophysics Data System (ADS)

Maza, Maria; Adler, Katherine; Ramos, Diogo; Garcia, Adrian Mikhail; Nepf, Heidi

2017-11-01

An experimental study of unidirectional flow through a model mangrove forest measured both velocity and forces on individual trees. The individual trees were 1/12th scale models of mature Rhizophora, including 24 prop roots distributed in a three-dimensional layout. Thirty-two model trees were distributed in a staggered array producing a 2.5 m long forest. The velocity evolved from a boundary layer profile at the forest leading edge to a vertical profile determined by the vertical distribution of frontal area, with significantly higher velocity above the prop roots. Fully developed conditions were reached at the fifth tree row from the leading edge. Within the root zone the velocity was reduced by up to 50% and the TKE was increased by as much as fivefold, relative to the upstream conditions. TKE in the root zone was mainly produced by root and trunk wakes, and it agreed in magnitude with the estimation obtained using the Tanino and Nepf (2008) formulation. Maximum TKE occurred at the top of the roots, where a strong shear region was associated with the change in frontal area. The drag measured on individual trees decreased from the leading edge and reached a constant value at the fifth row and beyond, i.e., in the fully developed region. The drag exhibited a quadratic dependence on velocity, which justified the definition of a quadratic drag coefficient. Once the correct drag length-scale was defined, the measured drag coefficients collapsed to a single function of Reynolds number.

Anisotropic perception of visual angle: implications for the horizontal-vertical illusion, overconstancy of size, and the moon illusion.

PubMed

Higashiyama, A

1992-03-01

Three experiments investigated anisotropic perception of visual angle outdoors. In Experiment 1, scales for vertical and horizontal visual angles ranging from 20 degrees to 80 degrees were constructed with the method of angle production (in which the subject reproduced a visual angle with a protractor) and the method of distance production (in which the subject produced a visual angle by adjusting viewing distance). In Experiment 2, scales for vertical and horizontal visual angles of 5 degrees-30 degrees were constructed with the method of angle production and were compared with scales for orientation in the frontal plane. In Experiment 3, vertical and horizontal visual angles of 3 degrees-80 degrees were judged with the method of verbal estimation. The main results of the experiments were as follows: (1) The obtained angles for visual angle are described by a quadratic equation, theta' = a + b theta + c theta 2 (where theta is the visual angle; theta', the obtained angle; a, b, and c, constants). (2) The linear coefficient b is larger than unity and is steeper for vertical direction than for horizontal direction. (3) The quadratic coefficient c is generally smaller than zero and is negatively larger for vertical direction than for horizontal direction. And (4) the obtained angle for visual angle is larger than that for orientation. From these results, it was possible to predict the horizontal-vertical illusion, over-constancy of size, and the moon illusion.

Limb darkening and exoplanets - II. Choosing the best law for optimal retrieval of transit parameters

NASA Astrophysics Data System (ADS)

Espinoza, Néstor; Jordán, Andrés

2016-04-01

Very precise measurements of exoplanet transit light curves both from ground- and space-based observatories make it now possible to fit the limb-darkening coefficients in the transit-fitting procedure rather than fix them to theoretical values. This strategy has been shown to give better results, as fixing the coefficients to theoretical values can give rise to important systematic errors which directly impact the physical properties of the system derived from such light curves such as the planetary radius. However, studies of the effect of limb-darkening assumptions on the retrieved parameters have mostly focused on the widely used quadratic limb-darkening law, leaving out other proposed laws that are either simpler or better descriptions of model intensity profiles. In this work, we show that laws such as the logarithmic, square-root and three-parameter law do a better job that the quadratic and linear laws when deriving parameters from transit light curves, both in terms of bias and precision, for a wide range of situations. We therefore recommend to study which law to use on a case-by-case basis. We provide code to guide the decision of when to use each of these laws and select the optimal one in a mean-square error sense, which we note has a dependence on both stellar and transit parameters. Finally, we demonstrate that the so-called exponential law is non-physical as it typically produces negative intensities close to the limb and should therefore not be used.

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.

An efficient inverse radiotherapy planning method for VMAT using quadratic programming optimization.

PubMed

Hoegele, W; Loeschel, R; Merkle, N; Zygmanski, P

2012-01-01

The purpose of this study is to investigate the feasibility of an inverse planning optimization approach for the Volumetric Modulated Arc Therapy (VMAT) based on quadratic programming and the projection method. The performance of this method is evaluated against a reference commercial planning system (eclipse(TM) for rapidarc(TM)) for clinically relevant cases. The inverse problem is posed in terms of a linear combination of basis functions representing arclet dose contributions and their respective linear coefficients as degrees of freedom. MLC motion is decomposed into basic motion patterns in an intuitive manner leading to a system of equations with a relatively small number of equations and unknowns. These equations are solved using quadratic programming under certain limiting physical conditions for the solution, such as the avoidance of negative dose during optimization and Monitor Unit reduction. The modeling by the projection method assures a unique treatment plan with beneficial properties, such as the explicit relation between organ weightings and the final dose distribution. Clinical cases studied include prostate and spine treatments. The optimized plans are evaluated by comparing isodose lines, DVH profiles for target and normal organs, and Monitor Units to those obtained by the clinical treatment planning system eclipse(TM). The resulting dose distributions for a prostate (with rectum and bladder as organs at risk), and for a spine case (with kidneys, liver, lung and heart as organs at risk) are presented. Overall, the results indicate that similar plan qualities for quadratic programming (QP) and rapidarc(TM) could be achieved at significantly more efficient computational and planning effort using QP. Additionally, results for the quasimodo phantom [Bohsung et al., "IMRT treatment planning: A comparative inter-system and inter-centre planning exercise of the estro quasimodo group," Radiother. Oncol. 76(3), 354-361 (2005)] are presented as an example for an extreme concave case. Quadratic programming is an alternative approach for inverse planning which generates clinically satisfying plans in comparison to the clinical system and constitutes an efficient optimization process characterized by uniqueness and reproducibility of the solution.

Detection of Cutting Tool Wear using Statistical Analysis and Regression Model

NASA Astrophysics Data System (ADS)

Ghani, Jaharah A.; Rizal, Muhammad; Nuawi, Mohd Zaki; Haron, Che Hassan Che; Ramli, Rizauddin

2010-10-01

This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals. A statistical-based method called Integrated Kurtosis-based Algorithm for Z-Filter technique, called I-kaz was used for developing a regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out using a CNC turning machine Colchester Master Tornado T4 in dry cutting condition. A Kistler 9255B dynamometer was used to measure the cutting force signals, which were transmitted, analyzed, and displayed in the DasyLab software. Various force signals from machining operation were analyzed, and each has its own I-kaz 3D coefficient. This coefficient was examined and its relationship with flank wear lands (VB) was determined. A regression model was developed due to this relationship, and results of the regression model shows that the I-kaz 3D coefficient value decreases as tool wear increases. The result then is used for real time tool wear monitoring.

Alcohol-related problems and life satisfaction predict motivation to change among mandated college students.

PubMed

Diulio, Andrea R; Cero, Ian; Witte, Tracy K; Correia, Christopher J

2014-04-01

The present study investigated the role specific types of alcohol-related problems and life satisfaction play in predicting motivation to change alcohol use. Participants were 548 college students mandated to complete a brief intervention following an alcohol-related policy violation. Using hierarchical multiple regression, we tested for the presence of interaction and quadratic effects on baseline data collected prior to the intervention. A significant interaction indicated that the relationship between a respondent's personal consequences and his/her motivation to change differs depending upon the level of concurrent social consequences. Additionally quadratic effects for abuse/dependence symptoms and life satisfaction were found. The quadratic probes suggest that abuse/dependence symptoms and poor life satisfaction are both positively associated with motivation to change for a majority of the sample; however, the nature of these relationships changes for participants with more extreme scores. Results support the utility of using a multidimensional measure of alcohol related problems and assessing non-linear relationships when assessing predictors of motivation to change. The results also suggest that the best strategies for increasing motivation may vary depending on the types of alcohol-related problems and level of life satisfaction the student is experiencing and highlight potential directions for future research. Copyright © 2014. Published by Elsevier Ltd.

SCI model structure determination program (OSR) user's guide. [optimal subset regression

NASA Technical Reports Server (NTRS)

1979-01-01

The computer program, OSR (Optimal Subset Regression) which estimates models for rotorcraft body and rotor force and moment coefficients is described. The technique used is based on the subset regression algorithm. Given time histories of aerodynamic coefficients, aerodynamic variables, and control inputs, the program computes correlation between various time histories. The model structure determination is based on these correlations. Inputs and outputs of the program are given.

Ecotoxicology of phenylphosphonothioates.

PubMed Central

Francis, B M; Hansen, L G; Fukuto, T R; Lu, P Y; Metcalf, R L

1980-01-01

The phenylphosphonothioate insecticides EPN and leptophos, and several analogs, were evaluated with respect to their delayed neurotoxic effects in hens and their environmental behavior in a terrestrial-aquatic model ecosystem. Acute toxicity to insects was highly correlated with sigma sigma of the substituted phenyl group (regression coefficient r = -0.91) while acute toxicity to mammals was slightly less well correlated (regression coefficient r = -0.71), and neurotoxicity was poorly correlated with sigma sigma (regression coefficient r = -0.35). Both EPN and leptophos were markedly more persistent and bioaccumulative in the model ecosystem than parathion. Desbromoleptophos, a contaminant and metabolite of leptophos, was seen to be a highly stable and persistent terminal residue of leptophos. PMID:6159210

Optimization study for Pb(II) and COD sequestration by consortium of sulphate-reducing bacteria

NASA Astrophysics Data System (ADS)

Verma, Anamika; Bishnoi, Narsi R.; Gupta, Asha

2017-09-01

In this study, initial minimum inhibitory concentration (MIC) of Pb(II) ions was analysed to check optimum concentration of Pb(II) ions at which the growth of sulphate-reducing consortium (SRC) was found to be maximum. 80 ppm of Pb(II) ions was investigated as minimum inhibitory concentration for SRC. Influence of electron donors such as lactose, sucrose, glucose and sodium lactate was examined to investigate best carbon source for growth and activity of sulphate-reducing bacteria. Sodium lactate was found to be the prime carbon source for SRC. Later optimization of various parameters was executed using Box-Behnken design model of response surface methodology to explore the effectiveness of three independent operating variables, namely, pH (5.0-9.0), temperature (32-42 °C) and time (5.0-9.0 days), on dependent variables, i.e. protein content, precipitation of Pb(II) ions, and removal of COD by SRC biomass. Maximum removal of COD and Pb(II) was observed to be 91 and 98 %, respectively, at pH 7.0 and temperature 37 °C and incubation time 7 days. According to response surface analysis and analysis of variance, the experimental data were perfectly fitted to the quadratic model, and the interactive influence of pH, temperature and time on Pb(II) and COD removal was highly significant. A high regression coefficient between the variables and response ( r 2 = 0.9974) corroborate eminent evaluation of experimental data by second-order polynomial regression model. SEM and Fourier transform infrared analysis was performed to investigate morphology of PbS precipitates, sorption mechanism and involved functional groups in metal-free and metal-loaded biomass of SRC for Pb(II) binding.

[Population of Lytechinus variegatus (Echinoidea: Toxopneustidae) and structural characteristics of seagrass of Thalassia testudinum in Mochima Bay, Venezuela)].

PubMed

Noriega, Nicida; Cróquer, Aldo; Pauls, Sheila M

2002-03-01

To compare the general features of Thalassia testudinum seagrass at Mochima Bay with sea urchin (Lxtechinus variegatus) abundance and distribution, three T. testudinum seagrass beds were selected, from the mouth (strong wave exposure) to the inner bay (calm waters). Each site was surveyed by using 5 line transects (20 m long) parallel to the coast and 1 m2 quadrats. In situ measurements of T. testudinum cover, shoot and leaf density were taken. Estimation of dry biomass for each seagrass fraction (leaves, rhizomes and roots) and leaf length were obtained from 25 vegetation samples extracted per site using cores (15 cm diameter). A multivariate analysis of variance (Manova) and a less significative difference test (LSD) were performed to examine differences between sites and within sites at different depths. A stepwise multiple regression analysis was done, dependent variable was sea urchin density; independent variables: vegetation values at each site. The only seagrass species found in the three sites was T. testudinum, and cover was 56-100%, leaf density 100-1000 leaf/m2, lengths 6-18.8 cm and shoot density 20-475 shoots/m2. The highest sea urchin densities were found at Isla Redonda and Ensenada Toporo (1-3.6 ind/m2), the lowest at Playa Colorada (0.6-0.8 ind/m2). Significant differences in seagrass features between sites were obtained (Manova p < 0.001), but not between depths (Manova p < 0.320). The regression coefficient between sea urchin density and seagrass parameters was statistically significant (r2 = 0.154, p < 0.007), however, total biomass was the only variable with a significant effect on sea urchin distribution (beta = 0.308, p < 0.032). The other variables did not explain satisfactorily L. variegatus abundance and distribution.

Adherence to preferable behavior for lipid control by high-risk dyslipidemic Japanese patients under pravastatin treatment: the APPROACH-J study.

PubMed

Kitagawa, Yasuhisa; Teramoto, Tamio; Daida, Hiroyuki

2012-01-01

We evaluated the impact of adherence to preferable behavior on serum lipid control assessed by a self-reported questionnaire in high-risk patients taking pravastatin for primary prevention of coronary artery disease. High-risk patients taking pravastatin were followed for 2 years. Questionnaire surveys comprising 21 questions, including 18 questions concerning awareness of health, and current status of diet, exercise, and drug therapy, were conducted at baseline and after 1 year. Potential domains were established by factor analysis from the results of questionnaires, and adherence scores were calculated in each domain. The relationship between adherence scores and lipid values during the 1-year treatment period was analyzed by each domain using multiple regression analysis. A total of 5,792 patients taking pravastatin were included in the analysis. Multiple regression analysis showed a significant correlation in terms of "Intake of high fat/cholesterol/sugar foods" (regression coefficient -0.58, p=0.0105) and "Adherence to instructions for drug therapy" (regression coefficient -6.61, p<0.0001). Low-density lipoprotein cholesterol (LDL-C) values were significantly lower in patients who had an increase in the adherence score in the "Awareness of health" domain compared with those with a decreased score. There was a significant correlation between high-density lipoprotein (HDL-C) values and "Awareness of health" (regression coefficient 0.26; p= 0.0037), "Preferable dietary behaviors" (regression coefficient 0.75; p<0.0001), and "Exercise" (regression coefficient 0.73; p= 0.0002). Similar relations were seen with triglycerides. In patients who have a high awareness of their health, a positive attitude toward lipid-lowering treatment including diet, exercise, and high adherence to drug therapy, is related with favorable overall lipid control even in patients under treatment with pravastatin.

Polyspectral signal analysis techniques for condition based maintenance of helicopter drive-train system

NASA Astrophysics Data System (ADS)

Hassan Mohammed, Mohammed Ahmed

For an efficient maintenance of a diverse fleet of air- and rotorcraft, effective condition based maintenance (CBM) must be established based on rotating components monitored vibration signals. In this dissertation, we present theory and applications of polyspectral signal processing techniques for condition monitoring of critical components in the AH-64D helicopter tail rotor drive train system. Currently available vibration-monitoring tools are mostly built around auto- and cross-power spectral analysis which have limited performance in detecting frequency correlations higher than second order. Studying higher order correlations and their Fourier transforms, higher order spectra, provides more information about the vibration signals which helps in building more accurate diagnostic models of the mechanical system. Based on higher order spectral analysis, different signal processing techniques are developed to assess health conditions of different critical rotating-components in the AH-64D helicopter drive-train. Based on cross-bispectrum, quadratic nonlinear transfer function is presented to model second order nonlinearity in a drive-shaft running between the two hanger bearings. Then, quadratic-nonlinearity coupling coefficient between frequency harmonics of the rotating shaft is used as condition metric to study different seeded shaft faults compared to baseline case, namely: shaft misalignment, shaft imbalance, and combination of shaft misalignment and imbalance. The proposed quadratic-nonlinearity metric shows better capabilities in distinguishing the four studied shaft settings than the conventional linear coupling based on cross-power spectrum. We also develop a new concept of Quadratic-Nonlinearity Power-Index spectrum, QNLPI(f), that can be used in signal detection and classification, based on bicoherence spectrum. The proposed QNLPI(f) is derived as a projection of the three-dimensional bicoherence spectrum into two-dimensional spectrum that quantitatively describes how much of the mean square power at certain frequency f is generated due to nonlinear quadratic interaction between different frequency components. The proposed index, QNLPI(f), can be used to simplify the study of bispectrum and bicoherence signal spectra. It also inherits useful characteristics from the bicoherence such as high immunity to additive Gaussian noise, high capability of nonlinear-systems identifications, and amplification invariance. The quadratic-nonlinear power spectral density PQNL(f) and percentage of quadratic nonlinear power PQNLP are also introduced based on the QNLPI(f). Concept of the proposed indices and their computational considerations are discussed first using computer generated data, and then applied to real-world vibration data to assess health conditions of different rotating components in the drive train including drive-shaft, gearbox, and hanger bearing faults. The QNLPI(f) spectrum enables us to gain more details about nonlinear harmonic generation patterns that can be used to distinguish between different cases of mechanical faults, which in turn helps to gaining more diagnostic/prognostic capabilities.

[Habitat suitability index of larval Japanese Halfbeak (Hyporhamphus sajori) in Bohai Sea based on geographically weighted regression.

PubMed

Zhao, Yang; Zhang, Xue Qing; Bian, Xiao Dong

2018-01-01

To investigate the early supplementary processes of fishre sources in the Bohai Sea, the geographically weighted regression (GWR) was introduced to the habitat suitability index (HSI) model. The Bohai Sea larval Japanese Halfbeak HSI GWR model was established with four environmental variables, including sea surface temperature (SST), sea surface salinity (SSS), water depth (DEP), and chlorophyll a concentration (Chl a). Results of the simulation showed that the four variables had different performances in August 2015. SST and Chl a were global variables, and had little impacts on HSI, with the regression coefficients of -0.027 and 0.006, respectively. SSS and DEP were local variables, and had larger impacts on HSI, while the average values of absolute values of their regression coefficients were 0.075 and 0.129, respectively. In the central Bohai Sea, SSS showed a negative correlation with HSI, and the most negative correlation coefficient was -0.3. In contrast, SSS was correlated positively but weakly with HSI in the three bays of Bohai Sea, and the largest correlation coefficient was 0.1. In particular, DEP and HSI were negatively correlated in the entire Bohai Sea, while they were more negatively correlated in the three bays of Bohai than in the central Bohai Sea, and the most negative correlation coefficient was -0.16 in the three bays. The Poisson regression coefficient of the HSI GWR model was 0.705, consistent with field measurements. Therefore, it could provide a new method for the research on fish habitats in the future.

Technical note: how to determine the FDG activity for tumour PET imaging that satisfies European guidelines.

PubMed

Koopman, Daniëlle; van Osch, Jochen A C; Jager, Pieter L; Tenbergen, Carlijn J A; Knollema, Siert; Slump, Cornelis H; van Dalen, Jorn A

2016-12-01

For tumour imaging with PET, the literature proposes to administer a patient-specific FDG activity that depends quadratically on a patient's body weight. However, a practical approach on how to implement such a protocol in clinical practice is currently lacking. We aimed to provide a practical method to determine a FDG activity formula for whole-body PET examinations that satisfies both the EANM guidelines and this quadratic relation. We have developed a methodology that results in a formula describing the patient-specific FDG activity to administer. A PET study using the NEMA NU-2001 image quality phantom forms the basis of our method. This phantom needs to be filled with 2.0 and 20.0 kBq FDG/mL in the background and spheres, respectively. After a PET acquisition of 10 min, a reconstruction has to be performed that results in sphere recovery coefficients (RCs) that are within the specifications as defined by the EANM Research Ltd (EARL). By performing reconstructions based on shorter scan durations, the minimal scan time per bed position (T min) needs to be extracted using an image coefficient of variation (COV) of 15 %. At T min, the RCs should be within EARL specifications as well. Finally, the FDG activity (in MBq) to administer can be described by [Formula: see text] with c a constant that is typically 0.0533 (MBq/kg(2)), w the patient's body weight (in kg), and t the scan time per bed position that is chosen in a clinical setting (in seconds). We successfully demonstrated this methodology using a state-of-the-art PET/CT scanner. We provide a practical method that results in a formula describing the FDG activity to administer to individual patients for whole-body PET examinations, taking into account both the EANM guidelines and a quadratic relation between FDG activity and patient's body weight. This formula is generally applicable to any PET system, using a specified image reconstruction and scan time per bed position.

Retrospective Cost Adaptive Control with Concurrent Closed-Loop Identification

NASA Astrophysics Data System (ADS)

Sobolic, Frantisek M.

Retrospective cost adaptive control (RCAC) is a discrete-time direct adaptive control algorithm for stabilization, command following, and disturbance rejection. RCAC is known to work on systems given minimal modeling information which is the leading numerator coefficient and any nonminimum-phase (NMP) zeros of the plant transfer function. This information is normally needed a priori and is key in the development of the filter, also known as the target model, within the retrospective performance variable. A novel approach to alleviate the need for prior modeling of both the leading coefficient of the plant transfer function as well as any NMP zeros is developed. The extension to the RCAC algorithm is the use of concurrent optimization of both the target model and the controller coefficients. Concurrent optimization of the target model and controller coefficients is a quadratic optimization problem in the target model and controller coefficients separately. However, this optimization problem is not convex as a joint function of both variables, and therefore nonconvex optimization methods are needed. Finally, insights within RCAC that include intercalated injection between the controller numerator and the denominator, unveil the workings of RCAC fitting a specific closed-loop transfer function to the target model. We exploit this interpretation by investigating several closed-loop identification architectures in order to extract this information for use in the target model.

Quantum corrections to the gravitational potentials of a point source due to conformal fields in de Sitter

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

Fröb, Markus B.; Verdaguer, Enric, E-mail: mfroeb@itp.uni-leipzig.de, E-mail: enric.verdaguer@ub.edu

We derive the leading quantum corrections to the gravitational potentials in a de Sitter background, due to the vacuum polarization from loops of conformal fields. Our results are valid for arbitrary conformal theories, even strongly interacting ones, and are expressed using the coefficients b and b' appearing in the trace anomaly. Apart from the de Sitter generalization of the known flat-space results, we find two additional contributions: one which depends on the finite coefficients of terms quadratic in the curvature appearing in the renormalized effective action, and one which grows logarithmically with physical distance. While the first contribution corresponds tomore » a rescaling of the effective mass, the second contribution leads to a faster fall-off of the Newton potential at large distances, and is potentially measurable.« less

Methods of Optimizing X-Ray Optical Prescriptions for Wide-Field Applications

NASA Technical Reports Server (NTRS)

Elsner, R. F.; O'Dell, S. L.; Ramsey, B. D.; Weisskopf, M. C.

2010-01-01

We are working on the development of a method for optimizing wide-field x-ray telescope mirror prescriptions, including polynomial coefficients, mirror shell relative displacements, and (assuming 4 focal plane detectors) detector placement and tilt that does not require a search through the multi-dimensional parameter space. Under the assumption that the parameters are small enough that second order expansions are valid, we show that the performance at the detector surface can be expressed as a quadratic function of the parameters with numerical coefficients derived from a ray trace through the underlying Wolter I optic. The best values for the parameters are found by solving the linear system of equations creating by setting derivatives of this function with respect to each parameter to zero. We describe the present status of this development effort.

Optimized face recognition algorithm using radial basis function neural networks and its practical applications.

PubMed

Yoo, Sung-Hoon; Oh, Sung-Kwun; Pedrycz, Witold

2015-09-01

In this study, we propose a hybrid method of face recognition by using face region information extracted from the detected face region. In the preprocessing part, we develop a hybrid approach based on the Active Shape Model (ASM) and the Principal Component Analysis (PCA) algorithm. At this step, we use a CCD (Charge Coupled Device) camera to acquire a facial image by using AdaBoost and then Histogram Equalization (HE) is employed to improve the quality of the image. ASM extracts the face contour and image shape to produce a personal profile. Then we use a PCA method to reduce dimensionality of face images. In the recognition part, we consider the improved Radial Basis Function Neural Networks (RBF NNs) to identify a unique pattern associated with each person. The proposed RBF NN architecture consists of three functional modules realizing the condition phase, the conclusion phase, and the inference phase completed with the help of fuzzy rules coming in the standard 'if-then' format. In the formation of the condition part of the fuzzy rules, the input space is partitioned with the use of Fuzzy C-Means (FCM) clustering. In the conclusion part of the fuzzy rules, the connections (weights) of the RBF NNs are represented by four kinds of polynomials such as constant, linear, quadratic, and reduced quadratic. The values of the coefficients are determined by running a gradient descent method. The output of the RBF NNs model is obtained by running a fuzzy inference method. The essential design parameters of the network (including learning rate, momentum coefficient and fuzzification coefficient used by the FCM) are optimized by means of Differential Evolution (DE). The proposed P-RBF NNs (Polynomial based RBF NNs) are applied to facial recognition and its performance is quantified from the viewpoint of the output performance and recognition rate. Copyright © 2015 Elsevier Ltd. All rights reserved.

VIIRS thermal emissive bands on-orbit calibration coefficient performance using vicarious calibration results

NASA Astrophysics Data System (ADS)

Moyer, D.; Moeller, C.; De Luccia, F.

2013-09-01

The Visible Infrared Imager Radiometer Suite (VIIRS), a primary sensor on-board the Suomi-National Polar-orbiting Partnership (SNPP) spacecraft, was launched October 28, 2011. It has 22 bands: 7 thermal emissive bands (TEBs), 14 reflective solar bands (RSBs) and a Day Night Band (DNB). The TEBs cover the spectral wavelengths between 3.7 to 12 μm and have two 371 m and five 742 m spatial resolution bands. A VIIRS Key Performance Parameter (KPP) is the sea surface temperature (SST) which uses bands M12 (3.7 μm), M15 (10.8 μm) and M16's (12.0 μm) calibrated Science Data Records (SDRs). The TEB SDRs rely on pre-launch calibration coefficients used in a quadratic algorithm to convert the detector's response to calibrated radiance. This paper will evaluate the performance of these prelaunch calibration coefficients using vicarious calibration information from the Cross-track Infrared Sounder (CrIS) also onboard the SNPP spacecraft and the Infrared Atmospheric Sounding Interferometer (IASI) on-board the Meteorological Operational (MetOp) satellite. Changes to the pre-launch calibration coefficients' offset term c0 to improve the SDR's performance at cold scene temperatures will also be discussed.

Resolving puzzles of massive gravity with and without violation of Lorentz symmetry

NASA Astrophysics Data System (ADS)

Mironov, Andrei; Mironov, Sergey; Morozov, Alexei; Morozov, Andrey

2010-06-01

We perform a systematic study of various versions of massive gravity with and without violations of the Lorentz symmetry in arbitrary dimension. These theories are well known to possess very unusual properties, unfamiliar from studies of gauge and Lorentz invariant models. These peculiarities are caused by the mixing of familiar transverse fields with the revived longitudinal and pure gauge (Stueckelberg) fields and are all seen already in the quadratic approximation. They are all associated with non-trivial dispersion laws, which easily allow superluminal propagation, ghosts, tachyons and essential irrationalities. Moreover, the coefficients in front of emerging modes are small, which makes the theories essentially non-perturbative within a large Vainshtein radius. Attempts to get rid of unwanted degrees of freedom by giving them infinite masses lead to the DVZ discontinuities in the parameter (moduli) space, caused by non-permutability of different limits. Also, the condition mgh = ∞ can not be preserved already in non-trivial gravitational backgrounds and is unstable under any other perturbations of the linearized gravity. At the same time, an a priori healthy model of massive gravity in the quadratic approximation definitely exists: it is provided by any mass level of the Kaluza-Klein tower. It bypasses the problems because the gravity field is mixed with other fields, and this explains why such mixing helps in other models. At the same time, this can imply that the really healthy massive gravity can still require an infinite number of extra fields beyond the quadratic approximation.

Nonlinear associations between plasma cholesterol levels and neuropsychological function.

PubMed

Wendell, Carrington R; Zonderman, Alan B; Katzel, Leslie I; Rosenberger, William F; Plamadeala, Victoria V; Hosey, Megan M; Waldstein, Shari R

2016-11-01

Although both high and low levels of total and low-density lipoprotein (LDL) cholesterol have been associated with poor neuropsychological function, little research has examined nonlinear effects. We examined quadratic relations of cholesterol to performance on a comprehensive neuropsychological battery. Participants were 190 older adults (53% men, ages 54-83) free of major medical, neurologic, and psychiatric disease. Measures of fasting plasma total and high-density lipoprotein (HDL) cholesterol were assayed, and LDL cholesterol was calculated. Participants completed neuropsychological measures of attention, executive function, memory, visuospatial judgment, and manual speed and dexterity. Multiple regression analyses examined cholesterol levels as quadratic predictors of each measure of cognitive performance, with age (dichotomized as <70 vs. 70+) as an effect modifier. A significant quadratic effect of Total Cholesterol² × Age was identified for Logical Memory II ( b = -.0013, p = .039), such that the 70+ group performed best at high and low levels of total cholesterol than at midrange total cholesterol (U-shaped) and the <70 group performed worse at high and low levels of total cholesterol than at midrange total cholesterol (inverted U shape). Similarly, significant U- and J-shaped effects of LDL Cholesterol² × Age were identified for Visual Reproduction II ( b = -.0020, p = .026) and log of the Trail Making Test, Part B (b = .0001, p = .044). Quadratic associations between HDL cholesterol and cognitive performance were nonsignificant. Results indicate differential associations between cholesterol and neuropsychological function across different ages and domains of function. High and low total and LDL cholesterol may confer both risk and benefit for suboptimal cognitive function at different ages. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Confidence Intervals for Squared Semipartial Correlation Coefficients: The Effect of Nonnormality

ERIC Educational Resources Information Center

Algina, James; Keselman, H. J.; Penfield, Randall D.

2010-01-01

The increase in the squared multiple correlation coefficient ([delta]R[superscript 2]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. Algina, Keselman, and Penfield found that intervals based on asymptotic principles were typically very inaccurate, even though the sample size…

Estimation of octanol/water partition coefficients using LSER parameters

USGS Publications Warehouse

Luehrs, Dean C.; Hickey, James P.; Godbole, Kalpana A.; Rogers, Tony N.

1998-01-01

The logarithms of octanol/water partition coefficients, logKow, were regressed against the linear solvation energy relationship (LSER) parameters for a training set of 981 diverse organic chemicals. The standard deviation for logKow was 0.49. The regression equation was then used to estimate logKow for a test of 146 chemicals which included pesticides and other diverse polyfunctional compounds. Thus the octanol/water partition coefficient may be estimated by LSER parameters without elaborate software but only moderate accuracy should be expected.

Thermal requirements of Dermanyssus gallinae (De Geer, 1778) (Acari: Dermanyssidae).

PubMed

Tucci, Edna Clara; do Prado, Angelo P; de Araújo, Raquel Pires

2008-01-01

The thermal requirements for development of Dermanyssus gallinae were studied under laboratory conditions at 15, 20, 25, 30 and 35 degrees C, a 12h photoperiod and 60-85% RH. The thermal requirements for D. gallinae were as follows. Preoviposition: base temperature 3.4 degrees C, thermal constant (k) 562.85 degree-hours, determination coefficient (R(2)) 0.59, regression equation: Y= -0.006035 + 0.001777x. Egg: base temperature 10.60 degrees C, thermal constant (k) 689.65 degree-hours, determination coefficient (R(2)) 0.94, regression equation: Y= -0.015367 + 0.001450x. Larva: base temperature 9.82 degrees C, thermal constant (k) 464.91 degree-hours, determination coefficient (R(2)) 0.87, regression equation: Y= -0.021123 + 0.002151x. Protonymph: base temperature 10.17 degrees C, thermal constant (k) 504.49 degree-hours, determination coefficient (R(2)) 0.90, regression equation: Y= -0.020152 + 0.001982x. Deutonymph: base temperature 11.80 degrees C, thermal constant (k) 501.11 degree-hours, determination coefficient (R(2)) 0.99, regression equation: Y= -0.023555 + 0.001996x. The results obtained showed that 15 to 42 generations of Dermanyssus gallinae may occur during the year in the State of São Paulo, as estimated based on isotherm charts. Dermanyssus gallinae may develop continually in the State of São Paulo, with a population decrease in the winter. There were differences between the developmental stages of D. gallinae in relation to thermal requirements.

Optimization of thermo-alkaline disintegration of sewage sludge for enhanced biogas yield.

PubMed

Shehu, Muhammad Sani; Abdul Manan, Zainuddin; Alwi, Sharifah Rafidah Wan

2012-06-01

Optimization of thermo-alkaline disintegration of sewage sludge for enhanced biogas yield was carried out using response surface methodology (RSM) and Box-Behnken design of experiment. The individual linear and quadratic effects as well as the interactive effects of temperature, NaOH concentration and time on the degree of disintegration were investigated. The optimum degree of disintegration achieved was 61.45% at 88.50 °C, 2.29 M NaOH (24.23%w/w total solids) and 21 min retention time. Linear and quadratic effects of temperature are most significant in affecting the degree of disintegration. The coefficient of determination (R(2)) of 99.5% confirms that the model used in predicting the degree of disintegration process has a very good fitness with the experimental variables. The disintegrated sludge increased the biogas yield by 36%v/v compared to non-disintegrated sludge. The RSM with Box-Behnken design is an effective tool in predicting the optimum degree of disintegration of sewage sludge for increased biogas yield. Copyright © 2012 Elsevier Ltd. All rights reserved.

Advanced Energy Storage Management in Distribution Network

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

Liu, Guodong; Ceylan, Oguzhan; Xiao, Bailu

2016-01-01

With increasing penetration of distributed generation (DG) in the distribution networks (DN), the secure and optimal operation of DN has become an important concern. In this paper, an iterative mixed integer quadratic constrained quadratic programming model to optimize the operation of a three phase unbalanced distribution system with high penetration of Photovoltaic (PV) panels, DG and energy storage (ES) is developed. The proposed model minimizes not only the operating cost, including fuel cost and purchasing cost, but also voltage deviations and power loss. The optimization model is based on the linearized sensitivity coefficients between state variables (e.g., node voltages) andmore » control variables (e.g., real and reactive power injections of DG and ES). To avoid slow convergence when close to the optimum, a golden search method is introduced to control the step size and accelerate the convergence. The proposed algorithm is demonstrated on modified IEEE 13 nodes test feeders with multiple PV panels, DG and ES. Numerical simulation results validate the proposed algorithm. Various scenarios of system configuration are studied and some critical findings are concluded.« less

Integrate-and-fire neurons driven by asymmetric dichotomous noise.

PubMed

Droste, Felix; Lindner, Benjamin

2014-12-01

We consider a general integrate-and-fire (IF) neuron driven by asymmetric dichotomous noise. In contrast to the Gaussian white noise usually used in the so-called diffusion approximation, this noise is colored, i.e., it exhibits temporal correlations. We give an analytical expression for the stationary voltage distribution of a neuron receiving such noise and derive recursive relations for the moments of the first passage time density, which allow us to calculate the firing rate and the coefficient of variation of interspike intervals. We study how correlations in the input affect the rate and regularity of firing under variation of the model's parameters for leaky and quadratic IF neurons. Further, we consider the limit of small correlation times and find lowest order corrections to the first passage time moments to be proportional to the square root of the correlation time. We show analytically that to this lowest order, correlations always lead to a decrease in firing rate for a leaky IF neuron. All theoretical expressions are compared to simulations of leaky and quadratic IF neurons.

Effect of Evolutionary Anisotropy on Earing Prediction in Cylindrical Cup Drawing

NASA Astrophysics Data System (ADS)

Choi, H. J.; Lee, K. J.; Choi, Y.; Bae, G.; Ahn, D.-C.; Lee, M.-G.

2017-05-01

The formability of sheet metals is associated with their planar anisotropy, and finite element simulations have been applied to the sheet metal-forming process by describing the anisotropic behaviors using yield functions and hardening models. In this study, the evaluation of anisotropic constitutive models was performed based on the non-uniform height profile or earing in circular cylindrical cup drawing. Two yield functions, a quadratic Hill1948 and a non-quadratic Yld2000-2d model, were used under non-associated and associated flow rules, respectively, to simultaneously capture directional differences in yield stress and r value. The effect of the evolution of anisotropy on the earing prediction was also investigated by employing simplified equivalent plastic strain rate-dependent anisotropic coefficients. The computational results were in good agreement with experiments when the proper choice of the yield function and flow rule, which predicts the planar anisotropy, was made. Moreover, the accuracy of the earing profile could be significantly enhanced if the evolution of anisotropy between uniaxial and biaxial stress states was additionally considered.

Coordination of multiple appendages in drag-based swimming.

PubMed

Alben, Silas; Spears, Kevin; Garth, Stephen; Murphy, David; Yen, Jeannette

2010-11-06

Krill are aquatic crustaceans that engage in long distance migrations, either vertically in the water column or horizontally for 10 km (over 200,000 body lengths) per day. Hence efficient locomotory performance is crucial for their survival. We study the swimming kinematics of krill using a combination of experiment and analysis. We quantify the propulsor kinematics for tethered and freely swimming krill in experiments, and find kinematics that are very nearly metachronal. We then formulate a drag coefficient model which compares metachronal, synchronous and intermediate motions for a freely swimming body with two legs. With fixed leg velocity amplitude, metachronal kinematics give the highest average body speed for both linear and quadratic drag laws. The same result holds for five legs with the quadratic drag law. When metachronal kinematics is perturbed towards synchronous kinematics, an analysis shows that the velocity increase on the power stroke is outweighed by the velocity decrease on the recovery stroke. With fixed time-averaged work done by the legs, metachronal kinematics again gives the highest average body speed, although the advantage over synchronous kinematics is reduced.

Dynamics of a new family of iterative processes for quadratic polynomials

NASA Astrophysics Data System (ADS)

Gutiérrez, J. M.; Hernández, M. A.; Romero, N.

2010-03-01

In this work we show the presence of the well-known Catalan numbers in the study of the convergence and the dynamical behavior of a family of iterative methods for solving nonlinear equations. In fact, we introduce a family of methods, depending on a parameter . These methods reach the order of convergence m+2 when they are applied to quadratic polynomials with different roots. Newton's and Chebyshev's methods appear as particular choices of the family appear for m=0 and m=1, respectively. We make both analytical and graphical studies of these methods, which give rise to rational functions defined in the extended complex plane. Firstly, we prove that the coefficients of the aforementioned family of iterative processes can be written in terms of the Catalan numbers. Secondly, we make an incursion into its dynamical behavior. In fact, we show that the rational maps related to these methods can be written in terms of the entries of the Catalan triangle. Next we analyze its general convergence, by including some computer plots showing the intricate structure of the Universal Julia sets associated with the methods.

Estimation of positive semidefinite correlation matrices by using convex quadratic semidefinite programming.

PubMed

Fushiki, Tadayoshi

2009-07-01

The correlation matrix is a fundamental statistic that is used in many fields. For example, GroupLens, a collaborative filtering system, uses the correlation between users for predictive purposes. Since the correlation is a natural similarity measure between users, the correlation matrix may be used in the Gram matrix in kernel methods. However, the estimated correlation matrix sometimes has a serious defect: although the correlation matrix is originally positive semidefinite, the estimated one may not be positive semidefinite when not all ratings are observed. To obtain a positive semidefinite correlation matrix, the nearest correlation matrix problem has recently been studied in the fields of numerical analysis and optimization. However, statistical properties are not explicitly used in such studies. To obtain a positive semidefinite correlation matrix, we assume the approximate model. By using the model, an estimate is obtained as the optimal point of an optimization problem formulated with information on the variances of the estimated correlation coefficients. The problem is solved by a convex quadratic semidefinite program. A penalized likelihood approach is also examined. The MovieLens data set is used to test our approach.

Biostatistics Series Module 6: Correlation and Linear Regression.

PubMed

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Biostatistics Series Module 6: Correlation and Linear Regression

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient (r). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation (y = a + bx), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous. PMID:27904175

Sparse Regression as a Sparse Eigenvalue Problem

NASA Technical Reports Server (NTRS)

Moghaddam, Baback; Gruber, Amit; Weiss, Yair; Avidan, Shai

2008-01-01

We extend the l0-norm "subspectral" algorithms for sparse-LDA [5] and sparse-PCA [6] to general quadratic costs such as MSE in linear (kernel) regression. The resulting "Sparse Least Squares" (SLS) problem is also NP-hard, by way of its equivalence to a rank-1 sparse eigenvalue problem (e.g., binary sparse-LDA [7]). Specifically, for a general quadratic cost we use a highly-efficient technique for direct eigenvalue computation using partitioned matrix inverses which leads to dramatic x103 speed-ups over standard eigenvalue decomposition. This increased efficiency mitigates the O(n4) scaling behaviour that up to now has limited the previous algorithms' utility for high-dimensional learning problems. Moreover, the new computation prioritizes the role of the less-myopic backward elimination stage which becomes more efficient than forward selection. Similarly, branch-and-bound search for Exact Sparse Least Squares (ESLS) also benefits from partitioned matrix inverse techniques. Our Greedy Sparse Least Squares (GSLS) generalizes Natarajan's algorithm [9] also known as Order-Recursive Matching Pursuit (ORMP). Specifically, the forward half of GSLS is exactly equivalent to ORMP but more efficient. By including the backward pass, which only doubles the computation, we can achieve lower MSE than ORMP. Experimental comparisons to the state-of-the-art LARS algorithm [3] show forward-GSLS is faster, more accurate and more flexible in terms of choice of regularization

Testing failure surface prediction methods and deposit reconstruction for the landslides cluster occurring during Talas Typhoon (Japan)

NASA Astrophysics Data System (ADS)

Jaboyedoff, Michel; Chigira, Masahiro; Arai, Noriyuki; Derron, Marc-Henri; Rudaz, Benjamin; Tsou, Ching-Ying

2016-04-01

Talas Typhoon hit Japan from 2 to 5 September 2011. It induced more than 70 deep-seated landslides in Kii peninsula. The hi-resolution topography of these landslides have been acquired by aerial 1 m LiDAR digital elevation models (DEM) before (pre-DEM) and after (post-DEM) the events (data from Nara prefectural Government and the Kinki Regional development Bureau of Ministry of Land, Infrastructure, Transportation, and Tourism). This extraordinary opportunity allows us to test methods to construct failure surface geometries, buried valley topographies and/or to rebuild deposits surfaces. We tested the sloping base local level method (SLBL) on 5 deep seated landslides which occurred during Typhoon Talas (Akatani, Kitamata, Nagatono, Shimizu and Akatani-East; see Chigira et al., 2013). The SLBL corresponds to a quadratic surface with a constant second derivative in all x-y directions. This curvature can be based on the knowledge of the length of the landslide and its maximum thickness. We used mainly hillshade DEM, slope maps and Coltop schemes to define the limits of landslides and to interpret their structures. Different attempts were performed to reconstruct the failure surface and deposits depending on a priori knowledge. Basically the morphological features extracted from the pre-DEM were used to delineate the limits of the landslides. The curvature of the failure surface was obtained by "expert" interpretations. The failure surfaces obtained using SLBL are in good agreement with the failure surface observed on the post-DEM. The results are improved when (1) they are adjusted to obtain similar estimate of the volume deduced by Chigira et al. (2013), and when (2) the contours of the landslides used comes from an interpretation of both post and pre-DEM. In order to obtain the expansion coefficient some of these landslide, the missing volume of the deposits (by river erosion) were calculated using inverse SLBL. The coefficient of expansion ranges from 13% to 30%. The reconstruction of topography before the landslides in the scar or below the deposits gives also reliable results. Even if in many of the above cases the failure surface is controlled by structures (faults, joints, bedding, etc.), the quadratic surface used in SLBL seems to be a suitable solution to fit failure surfaces. If the structures are controlling large parts of the surface of failure, usually several of them are participating to the failure surfaces. It seems that this network of surfaces tends to adopt quadratic shapes when combined. Looking at other landslides or rockslide scar profiles around the world, the quadratic shape appears as very relevant. These study shows the efficiency of the SLBL method as a tool to estimate quickly the failure surface without a lot of knowledge. Preliminary investigations indicates that failure surface are roughly close to quadratic surface. References: Chigira M., Tsou C.-Y., Matsushi Y., Hiraishi N., Matsuzawa M. 2013.Topographic precursors and geological structures of deep-seated catastrophic landslides caused by Typhoon Talas. Geomorphology 201, 479-493

Lie algebraic approach to the time-dependent quantum general harmonic oscillator and the bi-dimensional charged particle in time-dependent electromagnetic fields

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

Ibarra-Sierra, V.G.; Sandoval-Santana, J.C.; Cardoso, J.L.

We discuss the one-dimensional, time-dependent general quadratic Hamiltonian and the bi-dimensional charged particle in time-dependent electromagnetic fields through the Lie algebraic approach. Such method consists in finding a set of generators that form a closed Lie algebra in terms of which it is possible to express a quantum Hamiltonian and therefore the evolution operator. The evolution operator is then the starting point to obtain the propagator as well as the explicit form of the Heisenberg picture position and momentum operators. First, the set of generators forming a closed Lie algebra is identified for the general quadratic Hamiltonian. This algebra ismore » later extended to study the Hamiltonian of a charged particle in electromagnetic fields exploiting the similarities between the terms of these two Hamiltonians. These results are applied to the solution of five different examples: the linear potential which is used to introduce the Lie algebraic method, a radio frequency ion trap, a Kanai–Caldirola-like forced harmonic oscillator, a charged particle in a time dependent magnetic field, and a charged particle in constant magnetic field and oscillating electric field. In particular we present exact analytical expressions that are fitting for the study of a rotating quadrupole field ion trap and magneto-transport in two-dimensional semiconductor heterostructures illuminated by microwave radiation. In these examples we show that this powerful method is suitable to treat quadratic Hamiltonians with time dependent coefficients quite efficiently yielding closed analytical expressions for the propagator and the Heisenberg picture position and momentum operators. -- Highlights: •We deal with the general quadratic Hamiltonian and a particle in electromagnetic fields. •The evolution operator is worked out through the Lie algebraic approach. •We also obtain the propagator and Heisenberg picture position and momentum operators. •Analytical expressions for a rotating quadrupole field ion trap are presented. •Exact solutions for magneto-transport in variable electromagnetic fields are shown.« less

Quadrat Data for Fermilab Prairie Plant Survey

Science.gov Websites

Quadrat Data 2012 Quadrat Data 2013 Quadrat Data None taken by volunteers in 2014 due to weather problems . 2015 Quadrat Data 2016 Quadrat Data None taken by volunteers in 2017 due to weather and other problems

Factor Scores, Structure Coefficients, and Communality Coefficients

ERIC Educational Resources Information Center

Goodwyn, Fara

2012-01-01

This paper presents heuristic explanations of factor scores, structure coefficients, and communality coefficients. Common misconceptions regarding these topics are clarified. In addition, (a) the regression (b) Bartlett, (c) Anderson-Rubin, and (d) Thompson methods for calculating factor scores are reviewed. Syntax necessary to execute all four…

Uni- and multi-variable modelling of flood losses: experiences gained from the Secchia river inundation event.

NASA Astrophysics Data System (ADS)

Carisi, Francesca; Domeneghetti, Alessio; Kreibich, Heidi; Schröter, Kai; Castellarin, Attilio

2017-04-01

Flood risk is function of flood hazard and vulnerability, therefore its accurate assessment depends on a reliable quantification of both factors. The scientific literature proposes a number of objective and reliable methods for assessing flood hazard, yet it highlights a limited understanding of the fundamental damage processes. Loss modelling is associated with large uncertainty which is, among other factors, due to a lack of standard procedures; for instance, flood losses are often estimated based on damage models derived in completely different contexts (i.e. different countries or geographical regions) without checking its applicability, or by considering only one explanatory variable (i.e. typically water depth). We consider the Secchia river flood event of January 2014, when a sudden levee-breach caused the inundation of nearly 200 km2 in Northern Italy. In the aftermath of this event, local authorities collected flood loss data, together with additional information on affected private households and industrial activities (e.g. buildings surface and economic value, number of company's employees and others). Based on these data we implemented and compared a quadratic-regression damage function, with water depth as the only explanatory variable, and a multi-variable model that combines multiple regression trees and considers several explanatory variables (i.e. bagging decision trees). Our results show the importance of data collection revealing that (1) a simple quadratic regression damage function based on empirical data from the study area can be significantly more accurate than literature damage-models derived for a different context and (2) multi-variable modelling may outperform the uni-variable approach, yet it is more difficult to develop and apply due to a much higher demand of detailed data.

Selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays and impacts of using incorrect weighting factors on curve stability, data quality, and assay performance.

PubMed

Gu, Huidong; Liu, Guowen; Wang, Jian; Aubry, Anne-Françoise; Arnold, Mark E

2014-09-16

A simple procedure for selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays is reported. The correct weighting factor is determined by the relationship between the standard deviation of instrument responses (σ) and the concentrations (x). The weighting factor of 1, 1/x, or 1/x(2) should be selected if, over the entire concentration range, σ is a constant, σ(2) is proportional to x, or σ is proportional to x, respectively. For the first time, we demonstrated with detailed scientific reasoning, solid historical data, and convincing justification that 1/x(2) should always be used as the weighting factor for all bioanalytical LC-MS/MS assays. The impacts of using incorrect weighting factors on curve stability, data quality, and assay performance were thoroughly investigated. It was found that the most stable curve could be obtained when the correct weighting factor was used, whereas other curves using incorrect weighting factors were unstable. It was also found that there was a very insignificant impact on the concentrations reported with calibration curves using incorrect weighting factors as the concentrations were always reported with the passing curves which actually overlapped with or were very close to the curves using the correct weighting factor. However, the use of incorrect weighting factors did impact the assay performance significantly. Finally, the difference between the weighting factors of 1/x(2) and 1/y(2) was discussed. All of the findings can be generalized and applied into other quantitative analysis techniques using calibration curves with weighted least-squares regression algorithm.

Meta-regression approximations to reduce publication selection bias.

PubMed

Stanley, T D; Doucouliagos, Hristos

2014-03-01

Publication selection bias is a serious challenge to the integrity of all empirical sciences. We derive meta-regression approximations to reduce this bias. Our approach employs Taylor polynomial approximations to the conditional mean of a truncated distribution. A quadratic approximation without a linear term, precision-effect estimate with standard error (PEESE), is shown to have the smallest bias and mean squared error in most cases and to outperform conventional meta-analysis estimators, often by a great deal. Monte Carlo simulations also demonstrate how a new hybrid estimator that conditionally combines PEESE and the Egger regression intercept can provide a practical solution to publication selection bias. PEESE is easily expanded to accommodate systematic heterogeneity along with complex and differential publication selection bias that is related to moderator variables. By providing an intuitive reason for these approximations, we can also explain why the Egger regression works so well and when it does not. These meta-regression methods are applied to several policy-relevant areas of research including antidepressant effectiveness, the value of a statistical life, the minimum wage, and nicotine replacement therapy. Copyright © 2013 John Wiley & Sons, Ltd.

Multiple linear regression analysis

NASA Technical Reports Server (NTRS)

Edwards, T. R.

1980-01-01

Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

Application of Box-Behnken design for ultrasonic-assisted extraction of polysaccharides from Paeonia emodi.

PubMed

Ahmad, Ajaz; Alkharfy, Khalid M; Wani, Tanveer A; Raish, Mohammad

2015-01-01

The objective of the present work was to study the ultrasonic assisted extraction and optimization of polysaccharides from Paeonia emodi and evaluation of its anti-inflammatory response. Specifically, the optimization of polysaccharides was carried out using Box-Behnken statistical experimental design. Response surface methodology (RSM) of three factors (extraction temperature, extraction time and liquid solid ratio) was employed to optimize the percentage yield of the polysaccharides. The experimental data were fitted to quadratic response surface models using multiple regression analysis with high coefficient of determination value (R) of 0.9906. The highest polysaccharide yield (8.69%) as per the Derringer's desirability prediction tool was obtained under the optimal extraction condition (extraction temperature 47.03 °C, extraction time 15.68 min, and liquid solid ratio 1.29 ml/g) with a desirability value of 0.98. These optimized values of tested parameters were validated under similar conditions (n = 6), an average of 8.13 ± 2.08% of polysaccharide yield was obtained in an optimized extraction conditions with 93.55% validity. The anti-inflammatory effect of polysaccharides of P. emodi were studied on carrageenan induced paw edema. In vivo results showed that the P. emodi 200mg/kg of polysaccharide extract exhibited strong potential against inflammatory response induced by 1% suspension of carrageenean in normal saline. Copyright © 2014 Elsevier B.V. All rights reserved.

A review of spatio-temporal modelling of quadrat count data with application to striga occurrence in a pearl millet field

NASA Astrophysics Data System (ADS)

Hess, Dale; van Lieshout, Marie-Colette; Payne, Bill; Stein, Alfred

This paper describes how spatial statistical techniques may be used to analyse weed occurrence in tropical fields. Quadrat counts of weed numbers are available over a series of years, as well as data on explanatory variables, and the aim is to smooth the data and assess spatial and temporal trends. We review a range of models for correlated count data. As an illustration, we consider data on striga infestation of a 60 × 24 m 2 millet field in Niger collected from 1985 until 1991, modelled by independent Poisson counts and a prior auto regression term enforcing spatial coherence. The smoothed fields show the presence of a seed bank, the estimated model parameters indicate a decay in the striga numbers over time, as well as a clear correlation with the amount of rainfall in 15 consecutive days following the sowing date. Such results could contribute to precision agriculture as a guide to more cost-effective striga control strategies.

Response surface modeling of acid activation of raw diatomite using in sunflower oil bleaching by: Box-Behnken experimental design.

PubMed

Larouci, M; Safa, M; Meddah, B; Aoues, A; Sonnet, P

2015-03-01

The optimum conditions for acid activation of diatomite for maximizing bleaching efficiency of the diatomite in sun flower oil treatment were studied. Box-Behnken experimental design combining with response surface modeling (RSM) and quadratic programming (QP) was employed to obtain the optimum conditions of three independent variables (acid concentration, activation time and solid to liquid) for acid activation of diatomite. The significance of independent variables and their interactions were tested by means of the analysis of variance (ANOVA) with 95 % confidence limits (α = 0.05). The optimum values of the selected variables were obtained by solving the quadratic regression model, as well as by analyzing the response surface contour plots. The experimental conditions at this global point were determined to be acid concentration = 8.963 N, activation time = 11.9878 h, and solid to liquid ratio = 221.2113 g/l, the corresponding bleaching efficiency was found to be about 99 %.

Regional income inequality model based on theil index decomposition and weighted variance coeficient

NASA Astrophysics Data System (ADS)

Sitepu, H. R.; Darnius, O.; Tambunan, W. N.

2018-03-01

Regional income inequality is an important issue in the study on economic development of a certain region. Rapid economic development may not in accordance with people’s per capita income. The method of measuring the regional income inequality has been suggested by many experts. This research used Theil index and weighted variance coefficient in order to measure the regional income inequality. Regional income decomposition which becomes the productivity of work force and their participation in regional income inequality, based on Theil index, can be presented in linear relation. When the economic assumption in j sector, sectoral income value, and the rate of work force are used, the work force productivity imbalance can be decomposed to become the component in sectors and in intra-sectors. Next, weighted variation coefficient is defined in the revenue and productivity of the work force. From the quadrate of the weighted variation coefficient result, it was found that decomposition of regional revenue imbalance could be analyzed by finding out how far each component contribute to regional imbalance which, in this research, was analyzed in nine sectors of economic business.

Estimation of dietary arginine requirements for Longyan laying ducks.

PubMed

Xia, Weiguang; Fouad, Ahmed Mohamed; Chen, Wei; Ruan, Dong; Wang, Shuang; Fan, Qiuli; Wang, Ying; Cui, Yiyan; Zheng, Chuntian

2017-01-01

This study aimed to establish the arginine requirements of Longyan ducks from 17 to 31 wk of age based on egg production, egg quality, plasma, and ovarian indices, as well as the expression of vitellogenesis-related genes. In total, 660 Longyan ducks with similar body weight at 15 wk of age were assigned randomly to 5 treatments, each with 6 replicates of 22 birds, and fed a corn-corn gluten meal basal diet (0.66% arginine) supplemented with either 0, 0.20%, 0.40%, 0.60%, or 0.80% arginine. Dietary arginine did not affect egg production by laying ducks, but it increased (linear, P < 0.01) the egg weight at 22 to 31 and 17 to 31 wk of age. Dietary arginine increased the yolk color score (linearly, P < 0.05) and the yolk percentage (quadratic, P < 0.05), where the maximum values were obtained with 1.26% arginine. Dietary arginine affected the total shell percentage and shell thickness, with the highest values using 1.46% arginine (P < 0.01). The weight and number of small yellow follicles (SYFs) increased (quadratic, P < 0.05) with the dietary arginine level and there was a quadratic response (P < 0.05) in terms of the SYFs weight/ovarian weight; the highest values were obtained in ducks fed 1.26% arginine. The plasma arginine concentration exhibited a quadratic (P < 0.05) response to dietary arginine. The plasma progesterone concentration decreased (linear, P < 0.05) as dietary arginine increased. The mRNA abundance of the very low density lipoprotein receptor-b increased in the second large yellow follicle membranes (quadratic, P < 0.05) with the dietary arginine level, where the highest value occurred with 1.26% arginine. According to the regression model, the dietary arginine requirements for Longyan laying ducks aged 17 to 31 wk are 1.06%, 1.13%, 1.22%, and 1.11% to obtain the maximum yolk percentage, SYFs number, SYFs weight, and SYFs weight/ovarian weight, respectively. © 2016 Poultry Science Association Inc.

Chaos in high-dimensional dissipative dynamical systems

PubMed Central

Ispolatov, Iaroslav; Madhok, Vaibhav; Allende, Sebastian; Doebeli, Michael

2015-01-01

For dissipative dynamical systems described by a system of ordinary differential equations, we address the question of how the probability of chaotic dynamics increases with the dimensionality of the phase space. We find that for a system of d globally coupled ODE’s with quadratic and cubic non-linearities with randomly chosen coefficients and initial conditions, the probability of a trajectory to be chaotic increases universally from ~10−5 − 10−4 for d = 3 to essentially one for d ~ 50. In the limit of large d, the invariant measure of the dynamical systems exhibits universal scaling that depends on the degree of non-linearity, but not on the choice of coefficients, and the largest Lyapunov exponent converges to a universal scaling limit. Using statistical arguments, we provide analytical explanations for the observed scaling, universality, and for the probability of chaos. PMID:26224119

Initial On-Orbit Radiometric Calibration of the Suomi NPP VIIRS Reflective Solar Bands

NASA Technical Reports Server (NTRS)

Lei, Ning; Wang, Zhipeng; Fulbright, Jon; Lee, Shihyan; McIntire, Jeff; Chiang, Vincent; Xiong, Jack

2012-01-01

The on-orbit radiometric response calibration of the VISible/Near InfraRed (VISNIR) and the Short-Wave InfraRed (SWIR) bands of the Visible/Infrared Imager/Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) satellite is carried out through a Solar Diffuser (SD). The transmittance of the SD screen and the SD's Bidirectional Reflectance Distribution Function (BRDF) are measured before launch and tabulated, allowing the VIIRS sensor aperture spectral radiance to be accurately determined. The radiometric response of a detector is described by a quadratic polynomial of the detector?s digital number (dn). The coefficients were determined before launch. Once on orbit, the coefficients are assumed to change by a common factor: the F-factor. The radiance scattered from the SD allows the determination of the F-factor. In this Proceeding, we describe the methodology and the associated algorithms in the determination of the F-factors and discuss the results.

Concerning the Development of the Wide-Field Optics for WFXT Including Methods of Optimizing X-Ray Optical Prescriptions for Wide-Field Applications

NASA Technical Reports Server (NTRS)

Weisskopf, M. C.; Elsner, R. F.; O'Dell, S. L.; Ramsey, B. D.

2010-01-01

We present a progress report on the various endeavors we are undertaking at MSFC in support of the Wide Field X-Ray Telescope development. In particular we discuss assembly and alignment techniques, in-situ polishing corrections, and the results of our efforts to optimize mirror prescriptions including polynomial coefficients, relative shell displacements, detector placements and tilts. This optimization does not require a blind search through the multi-dimensional parameter space. Under the assumption that the parameters are small enough so that second order expansions are valid, we show that the performance at the detector can be expressed as a quadratic function with numerical coefficients derived from a ray trace through the underlying Wolter I optic. The optimal values for the parameters are found by solving the linear system of equations creating by setting derivatives of this function with respect to each parameter to zero.

Construction of Orthonormal Wavelets Using Symbolic Algebraic Methods

NASA Astrophysics Data System (ADS)

Černá, Dana; Finěk, Václav

2009-09-01

Our contribution is concerned with the solution of nonlinear algebraic equations systems arising from the computation of scaling coefficients of orthonormal wavelets with compact support. Specifically Daubechies wavelets, symmlets, coiflets, and generalized coiflets. These wavelets are defined as a solution of equation systems which are partly linear and partly nonlinear. The idea of presented methods consists in replacing those equations for scaling coefficients by equations for scaling moments. It enables us to eliminate some quadratic conditions in the original system and then simplify it. The simplified system is solved with the aid of the Gröbner basis method. The advantage of our approach is that in some cases, it provides all possible solutions and these solutions can be computed to arbitrary precision. For small systems, we are even able to find explicit solutions. The computation was carried out by symbolic algebra software Maple.

Two-dimensional simulation research of secondary electron emission avalanche discharge on vacuum insulator surface

NASA Astrophysics Data System (ADS)

Cai, Libing; Wang, Jianguo; Zhu, Xiangqin; Wang, Yue; Zhang, Dianhui

2015-01-01

Based on the secondary electron emission avalanche (SEEA) model, the SEEA discharge on the vacuum insulator surface is simulated by using a 2D PIC-MCC code developed by ourselves. The evolutions of the number of discharge electrons, insulator surface charge, current, and 2D particle distribution are obtained. The effects of the strength of the applied electric field, secondary electron yield coefficient, rise time of the pulse, length of the insulator on the discharge are investigated. The results show that the number of the SEEA electrons presents a quadratic dependence upon the applied field strength. The SEEA current, which is on the order of Ampere, is directly proportional to the field strength and secondary electron yield coefficient. Finally, the electron-stimulated outgassing is included in the simulation code, and a three-phase discharge curve is presented by the simulation, which agrees with the experimental data.

Testing for gene-environment interaction under exposure misspecification.

PubMed

Sun, Ryan; Carroll, Raymond J; Christiani, David C; Lin, Xihong

2017-11-09

Complex interplay between genetic and environmental factors characterizes the etiology of many diseases. Modeling gene-environment (GxE) interactions is often challenged by the unknown functional form of the environment term in the true data-generating mechanism. We study the impact of misspecification of the environmental exposure effect on inference for the GxE interaction term in linear and logistic regression models. We first examine the asymptotic bias of the GxE interaction regression coefficient, allowing for confounders as well as arbitrary misspecification of the exposure and confounder effects. For linear regression, we show that under gene-environment independence and some confounder-dependent conditions, when the environment effect is misspecified, the regression coefficient of the GxE interaction can be unbiased. However, inference on the GxE interaction is still often incorrect. In logistic regression, we show that the regression coefficient is generally biased if the genetic factor is associated with the outcome directly or indirectly. Further, we show that the standard robust sandwich variance estimator for the GxE interaction does not perform well in practical GxE studies, and we provide an alternative testing procedure that has better finite sample properties. © 2017, The International Biometric Society.

Effects of in ovo feeding of cationic amino acids on hatchability, hatch weights, and organ developments in domestic pigeon squabs (Columba livia).

PubMed

Zhang, X Y; Li, L L; Miao, L P; Zhang, N N; Zou, X T

2018-01-01

This study was conducted to evaluate the effect of in ovo feeding of cationic amino acids on hatchability, hatch weights, and organ developments in pigeon squabs. Two experiments were conducted in this study. Eggs in Exp. 1 were subjected to modification of in ovo feeding in pigeons. Optimal time was determined by checking amniotic fluid volume, and suitable length was confirmed through ink injection. Results showed that the optimum time of in ovo feeding was on d 13 of embryonic development, and the suitable injected length was 20 mm to reach the amniotic cavity of the embryo. Eggs in Exp. 2 were transferred to access in ovo feeding of cationic amino acids. A total of 75 fertile pigeon eggs was randomly distributed into 5 treatments of 15 replicate eggs. Treatments in Exp. 2 consisted of non-injected controls (Control), a sterile buffered solution (0.75% saline), or a cationic amino acid mixture (> 98.5% purity crystalline L-arginine, > 98% purity crystalline L-lysine, and > 98.5% purity L-histidine) containing 0.1, 1, or 10% concentration (Conc.), which were relative to their total content in the eggs, respectively. The crystalline amino acids were dissolved in 200 μL buffered solution prior to in ovo feeding. After hatching, hatch weight (HW) and organ weight (OW) of the squabs were measured immediately. In ovo feeding of cationic amino acids increased the proportions of yolk-free hatch weight to hatch weight (YFHW/HW) (quadratic P = 0.01), and those of OW to YFHW including the heart (quadratic P = 0.01), kidney (quadratic P < 0.01), and liver (quadratic P = 0.02) compared to the control group, and the levels of those ratios were maximized in the 1% Conc group. Also, a proportion of small intestine weight to YFHW improved (linear P = 0.02, quadratic P = 0.05) after in ovo feeding. The organ weight of the head, leg, heart, lung, kidney, proventriculus, pancreas, liver, and small intestine correlated with YFHW positively (0.4 < correlation coefficient < 0.8, P < 0.05). In conclusion, cationic amino acids injection into amnion can improve the embryonic development, which may be mediated by the increment of relative organ weight. © 2017 Poultry Science Association Inc.

On Using the Average Intercorrelation Among Predictor Variables and Eigenvector Orientation to Choose a Regression Solution.

ERIC Educational Resources Information Center

Mugrage, Beverly; And Others

Three ridge regression solutions are compared with ordinary least squares regression and with principal components regression using all components. Ridge regression, particularly the Lawless-Wang solution, out-performed ordinary least squares regression and the principal components solution on the criteria of stability of coefficient and closeness…

Time series forecasting using ERNN and QR based on Bayesian model averaging

NASA Astrophysics Data System (ADS)

Pwasong, Augustine; Sathasivam, Saratha

2017-08-01

The Bayesian model averaging technique is a multi-model combination technique. The technique was employed to amalgamate the Elman recurrent neural network (ERNN) technique with the quadratic regression (QR) technique. The amalgamation produced a hybrid technique known as the hybrid ERNN-QR technique. The potentials of forecasting with the hybrid technique are compared with the forecasting capabilities of individual techniques of ERNN and QR. The outcome revealed that the hybrid technique is superior to the individual techniques in the mean square error sense.

Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

PubMed

Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa

2008-01-01

This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.

Representation of turbulent shear stress by a product of mean velocity differences

NASA Technical Reports Server (NTRS)

Braun, W. H.

1977-01-01

A quadratic form in the mean velocity for the turbulent shear stress is presented. It is expressed as the product of two velocity differences whose roots are the maximum velocity in the flow and a cutoff velocity below which the turbulent shear stress vanishes. Application to pipe and channel flows yields the centerline velocity as a function of pressure gradient, as well as the velocity profile. The flat plate, boundary-layer problem is solved by a system of integral equations to obtain friction coefficient, displacement thickness, and momentum-loss thickness. Comparisons are made with experiment.

Interdependence of different symmetry energy elements

NASA Astrophysics Data System (ADS)

Mondal, C.; Agrawal, B. K.; De, J. N.; Samaddar, S. K.; Centelles, M.; Viñas, X.

2017-08-01

Relations between the nuclear symmetry energy coefficient and its density derivatives are derived. The relations hold for a class of interactions with quadratic momentum dependence and a power-law density dependence. The structural connection between the different symmetry energy elements as obtained seems to be followed by almost all reasonable nuclear energy density functionals, both relativistic and nonrelativistic, suggesting a universality in the correlation structure. This, coupled with known values of some well-accepted constants related to nuclear matter, helps in constraining values of different density derivatives of the nuclear symmetry energy, shedding light on the isovector part of the nuclear interaction.

Shrinkage regression-based methods for microarray missing value imputation.

PubMed

Wang, Hsiuying; Chiu, Chia-Chun; Wu, Yi-Ching; Wu, Wei-Sheng

2013-01-01

Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected. Inaccurate missing value estimation results in reducing the power of downstream microarray data analyses. Many types of methods have been developed to estimate missing values. Among them, the regression-based methods are very popular and have been shown to perform better than the other types of methods in many testing microarray datasets. To further improve the performances of the regression-based methods, we propose shrinkage regression-based methods. Our methods take the advantage of the correlation structure in the microarray data and select similar genes for the target gene by Pearson correlation coefficients. Besides, our methods incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the coefficients of the regression model, and then use the new coefficients to estimate missing values. Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do. Imputation of missing values is a very important aspect of microarray data analyses because most of the downstream analyses require a complete dataset. Therefore, exploring accurate and efficient methods for estimating missing values has become an essential issue. Since our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression-based methods.

Use of random regression to estimate genetic parameters of temperament across an age continuum in a crossbred cattle population.

PubMed

Littlejohn, B P; Riley, D G; Welsh, T H; Randel, R D; Willard, S T; Vann, R C

2018-05-12

The objective was to estimate genetic parameters of temperament in beef cattle across an age continuum. The population consisted predominantly of Brahman-British crossbred cattle. Temperament was quantified by: 1) pen score (PS), the reaction of a calf to a single experienced evaluator on a scale of 1 to 5 (1 = calm, 5 = excitable); 2) exit velocity (EV), the rate (m/sec) at which a calf traveled 1.83 m upon exiting a squeeze chute; and 3) temperament score (TS), the numerical average of PS and EV. Covariates included days of age and proportion of Bos indicus in the calf and dam. Random regression models included the fixed effects determined from the repeated measures models, except for calf age. Likelihood ratio tests were used to determine the most appropriate random structures. In repeated measures models, the proportion of Bos indicus in the calf was positively related with each calf temperament trait (0.41 ± 0.20, 0.85 ± 0.21, and 0.57 ± 0.18 for PS, EV, and TS, respectively; P < 0.01). There was an effect of contemporary group (combinations of season, year of birth, and management group) and dam age (P < 0.001) in all models. From repeated records analyses, estimates of heritability (h2) were 0.34 ± 0.04, 0.31 ± 0.04, and 0.39 ± 0.04, while estimates of permanent environmental variance as a proportion of the phenotypic variance (c2) were 0.30 ± 0.04, 0.31 ± 0.03, and 0.34 ± 0.04 for PS, EV, and TS, respectively. Quadratic additive genetic random regressions on Legendre polynomials of age were significant for all traits. Quadratic permanent environmental random regressions were significant for PS and TS, but linear permanent environmental random regressions were significant for EV. Random regression results suggested that these components change across the age dimension of these data. There appeared to be an increasing influence of permanent environmental effects and decreasing influence of additive genetic effects corresponding to increasing calf age for EV, and to a lesser extent for TS. Inherited temperament may be overcome by accumulating environmental stimuli with increases in age, especially after weaning.

The microcomputer scientific software series 2: general linear model--regression.

Treesearch

Harold M. Rauscher

1983-01-01

The general linear model regression (GLMR) program provides the microcomputer user with a sophisticated regression analysis capability. The output provides a regression ANOVA table, estimators of the regression model coefficients, their confidence intervals, confidence intervals around the predicted Y-values, residuals for plotting, a check for multicollinearity, a...

A different approach to X-ray stress analysis

NASA Astrophysics Data System (ADS)

Ogilvie, Robert E.

2007-07-01

A different approach to X-ray stress analysis has been developed. At the outset, it must be noted that the material to be analyzed is assumed homogeneous and isotropic. If a sphere with radius r within a specimen is subjected to a state of stress, the sphere is deformed into an ellipsoid. The semi-axes of the ellipsoid have the values of ( r + ɛx), ( r + ɛy), and ( r + ɛz), which are replaced by dx, dy, and dz, or for the cubic case, ax, ay, and az. In this technique, at a particular ϕ angle (see Fig. 1), the two-theta position of a high angle (hkl) peak is determined at ψ angles of 0, 15, 30, and 45°. These measurements are repeated for 3 to 6 ϕ angles in steps of 30°. The dϕψ or aϕψ values are then determined from the peak positions. The data is then fitted to the general quadratic equation for an ellipsoid by the method of least squares. From the coefficients of the quadratic equation, the angle between the laboratory and the specimen coordinates (direction of the principle stress) can be determined. Applying the general rotation of axes equations to the quadratic, the equation of the ellipse in the x- y plane is determined. The ax, ay, and az values for the principal axes of the lattice parameter ellipsoid are then evaluated. It is then possible to determine the unstressed a0 value from Hooke's Law using ax, ay, and az. The magnitude of the principal strains/stresses is then determined.

Linkages between Snow Cover Seasonality, Terrain, and Land Surface Phenology in the Highland Pastures of Kyrgyzstan

NASA Astrophysics Data System (ADS)

Henebry, Geoffrey; Tomaszewska, Monika; Kelgenbaeva, Kamilya

2017-04-01

In the highlands of Kyrgyzstan, vertical transhumance is the foundation of montane agropastoralism. Terrain attributes, such as elevation, slope, and aspect, affect snow cover seasonality, which is a key influence on the timing of plant growth and forage availability. Our study areas include the highland pastures in Central Tien Shan mountains, specifically in the rayons of Naryn and At-Bashy in Naryn oblast, and Alay and Chong-Alay rayons in Osh oblast. To explore the linkages between snow cover seasonality and land surface phenology as modulated by terrain and variations in thermal time, we use 16 years (2001-2016) of Landsat surface reflectance data at 30 m resolution with MODIS land surface temperature and snow cover products at 1 km and 500 m resolution, respectively, and two digital elevation models, SRTM and ASTER GDEM. We model snow cover seasonality using frost degree-days and land surface phenology using growing degree-days as quadratic functions of thermal time: a convex quadratic (CxQ) model for land surface phenology and a concave quadratic (CvQ) model for snow cover seasonality. From the fitted parameter coefficients, we calculated phenometrics, including "peak height" and "thermal time to peak" for the CxQ models and "trough depth" and "thermal time to trough" for the CvQ models. We explore how these phenometrics change as a function of elevation and slope-aspect interactions and due to interannual variability. Further, we examine how snow cover duration and timing affects the subsequent peak height and thermal time to peak in wetter, drier, and normal years.

Automatic bone outer contour extraction from B-modes ultrasound images based on local phase symmetry and quadratic polynomial fitting

NASA Astrophysics Data System (ADS)

Karlita, Tita; Yuniarno, Eko Mulyanto; Purnama, I. Ketut Eddy; Purnomo, Mauridhi Hery

2017-06-01

Analyzing ultrasound (US) images to get the shapes and structures of particular anatomical regions is an interesting field of study since US imaging is a non-invasive method to capture internal structures of a human body. However, bone segmentation of US images is still challenging because it is strongly influenced by speckle noises and it has poor image quality. This paper proposes a combination of local phase symmetry and quadratic polynomial fitting methods to extract bone outer contour (BOC) from two dimensional (2D) B-modes US image as initial steps of three-dimensional (3D) bone surface reconstruction. By using local phase symmetry, the bone is initially extracted from US images. BOC is then extracted by scanning one pixel on the bone boundary in each column of the US images using first phase features searching method. Quadratic polynomial fitting is utilized to refine and estimate the pixel location that fails to be detected during the extraction process. Hole filling method is then applied by utilize the polynomial coefficients to fill the gaps with new pixel. The proposed method is able to estimate the new pixel position and ensures smoothness and continuity of the contour path. Evaluations are done using cow and goat bones by comparing the resulted BOCs with the contours produced by manual segmentation and contours produced by canny edge detection. The evaluation shows that our proposed methods produces an excellent result with average MSE before and after hole filling at the value of 0.65.

Stemflow variation in Mexico's northeastern forest communities: Its contribution to soil moisture content and aquifer recharge

NASA Astrophysics Data System (ADS)

Návar, José

2011-09-01

SummaryStemflow hydro-ecological importance was measured in trees and assessed in Mexico's northeast forest stands by answering three basic questions: (a) what are the intra and inter-specific stemflow variations; (b) is the stemflow coefficient constant from tree level to stand scales? and (c) what is the stemflow area and wetted soil volume in individual trees and the stemflow volume discharged at the stand scale in two plant communities of northeastern Mexico? Gross rainfall and stemflow flux measurements were conducted on 78 trees of semi-arid, sub-tropical (31 Diospyros texana; 14 Acacia rigidula; four Bumelia celastrina; five Condalia hookeri; three Cordia bioissieri; three Pithecellobium pallens) and temperate forest communities (six Pinus pseudostrobus Lindl. and 12 Quercus spp.). Stemflow was extrapolated from individual trees to the stand scale using 98 inventory plots (1600 m 2 ha -1 each) placed in oak-pine forests and 37 quadrats (5 m × 5 m each) distributed across the Tamaulipan thornscrub forest range. Stemflow infiltration flux and infiltration area measurements assessed the wetted soil volume. Daily measurements were conducted from May of 1997 to November of 1998. Results showed that stemflow coefficients varied between plant communities since they averaged (confidence intervals, α = 0.05) 2.49% (0.57), 0.30% (0.09), and 0.77% (0.27) of the bulk precipitation for Tamaulipan thornscrub, pine, and oak forests, respectively. Intra-specific stemflow variations could not be identified in Tamaulipan although in temperate tree species. Basal diameter explained intra-specific stemflow variation in both plant communities. Stemflow increased threefold since it accounted for by 6.38% and 2.19% of the total bulk rainfall for Tamaulipan thornscrub quadrats and temperate oak-pine inventory plots, respectively. Small shrubs growing underneath large trees, in combination with the presence of small-diameter trees that recorded the largest stemflow coefficients appear to explain the increase of the stemflow coefficient from trees to stands. Stemflow replenishes soil moisture on the average 4.5 (1.4) times larger than does incident rainfall in open soils and appear to contribute to aquifer recharge in temperate forests due to a combination of shallow soils, high infiltration fluxes and the stemflow volume generated during rainfalls with depths >15 mm. Tracing studies should be conducted to test the hypothesis of the stemflow contribution to aquifer recharge in temperate forests of northeastern Mexico.

Innovating patient care delivery: DSRIP's interrupted time series analysis paradigm.

PubMed

Shenoy, Amrita G; Begley, Charles E; Revere, Lee; Linder, Stephen H; Daiger, Stephen P

2017-12-08

Adoption of Medicaid Section 1115 waiver is one of the many ways of innovating healthcare delivery system. The Delivery System Reform Incentive Payment (DSRIP) pool, one of the two funding pools of the waiver has four categories viz. infrastructure development, program innovation and redesign, quality improvement reporting and lastly, bringing about population health improvement. A metric of the fourth category, preventable hospitalization (PH) rate was analyzed in the context of eight conditions for two time periods, pre-reporting years (2010-2012) and post-reporting years (2013-2015) for two hospital cohorts, DSRIP participating and non-participating hospitals. The study explains how DSRIP impacted Preventable Hospitalization (PH) rates of eight conditions for both hospital cohorts within two time periods. Eight PH rates were regressed as the dependent variable with time, intervention and post-DSRIP Intervention as independent variables. PH rates of eight conditions were then consolidated into one rate for regressing with the above independent variables to evaluate overall impact of DSRIP. An interrupted time series regression was performed after accounting for auto-correlation, stationarity and seasonality in the dataset. In the individual regression model, PH rates showed statistically significant coefficients for seven out of eight conditions in DSRIP participating hospitals. In the combined regression model, the coefficient of the PH rate showed a statistically significant decrease with negative p-values for regression coefficients in DSRIP participating hospitals compared to positive/increased p-values for regression coefficients in DSRIP non-participating hospitals. Several macro- and micro-level factors may have likely contributed DSRIP hospitals outperforming DSRIP non-participating hospitals. Healthcare organization/provider collaboration, support from healthcare professionals, DSRIP's design, state reimbursement and coordination in care delivery methods may have led to likely success of DSRIP. IV, a retrospective cohort study based on longitudinal data. Copyright © 2017 Elsevier Inc. All rights reserved.

Limb and gravity-darkening coefficients for the TESS satellite at several metallicities, surface gravities, and microturbulent velocities

NASA Astrophysics Data System (ADS)

Claret, A.

2017-04-01

Aims: We present new gravity and limb-darkening coefficients for a wide range of effective temperatures, gravities, metallicities, and microturbulent velocities. These coefficients can be used in many different fields of stellar physics as synthetic light curves of eclipsing binaries and planetary transits, stellar diameters, line profiles in rotating stars, and others. Methods: The limb-darkening coefficients were computed specifically for the photometric system of the space mission tess and were performed by adopting the least-square method. In addition, the linear and bi-parametric coefficients, by adopting the flux conservation method, are also available. On the other hand, to take into account the effects of tidal and rotational distortions, we computed the passband gravity-darkening coefficients y(λ) using a general differential equation in which we consider the effects of convection and of the partial derivative (∂lnI(λ) /∂lng)Teff. Results: To generate the limb-darkening coefficients we adopt two stellar atmosphere models: atlas (plane-parallel) and phoenix (spherical, quasi-spherical, and r-method). The specific intensity distribution was fitted using five approaches: linear, quadratic, square root, logarithmic, and a more general one with four terms. These grids cover together 19 metallicities ranging from 10-5 up to 10+1 solar abundances, 0 ≤ log g ≤ 6.0 and 1500 K ≤Teff ≤ 50 000 K. The calculations of the gravity-darkening coefficients were performed for all plane-parallel ATLAS models. Tables 2-29 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/600/A30

Comparison between light scattering and gravimetric samplers for PM10 mass concentration in poultry and pig houses

NASA Astrophysics Data System (ADS)

Cambra-López, María; Winkel, Albert; Mosquera, Julio; Ogink, Nico W. M.; Aarnink, André J. A.

2015-06-01

The objective of this study was to compare co-located real-time light scattering devices and equivalent gravimetric samplers in poultry and pig houses for PM10 mass concentration, and to develop animal-specific calibration factors for light scattering samplers. These results will contribute to evaluate the comparability of different sampling instruments for PM10 concentrations. Paired DustTrak light scattering device (DustTrak aerosol monitor, TSI, U.S.) and PM10 gravimetric cyclone sampler were used for measuring PM10 mass concentrations during 24 h periods (from noon to noon) inside animal houses. Sampling was conducted in 32 animal houses in the Netherlands, including broilers, broiler breeders, layers in floor and in aviary system, turkeys, piglets, growing-finishing pigs in traditional and low emission housing with dry and liquid feed, and sows in individual and group housing. A total of 119 pairs of 24 h measurements (55 for poultry and 64 for pigs) were recorded and analyzed using linear regression analysis. Deviations between samplers were calculated and discussed. In poultry, cyclone sampler and DustTrak data fitted well to a linear regression, with a regression coefficient equal to 0.41, an intercept of 0.16 mg m-3 and a correlation coefficient of 0.91 (excluding turkeys). Results in turkeys showed a regression coefficient equal to 1.1 (P = 0.49), an intercept of 0.06 mg m-3 (P < 0.0001) and a correlation coefficient of 0.98. In pigs, we found a regression coefficient equal to 0.61, an intercept of 0.05 mg m-3 and a correlation coefficient of 0.84. Measured PM10 concentrations using DustTraks were clearly underestimated (approx. by a factor 2) in both poultry and pig housing systems compared with cyclone pre-separators. Absolute, relative, and random deviations increased with concentration. DustTrak light scattering devices should be self-calibrated to investigate PM10 mass concentrations accurately in animal houses. We recommend linear regression equations as animal-specific calibration factors for DustTraks instead of manufacturer calibration factors, especially in heavily dusty environments such as animal houses.

Poor methodological quality and reporting standards of systematic reviews in burn care management.

PubMed

Wasiak, Jason; Tyack, Zephanie; Ware, Robert; Goodwin, Nicholas; Faggion, Clovis M

2017-10-01

The methodological and reporting quality of burn-specific systematic reviews has not been established. The aim of this study was to evaluate the methodological quality of systematic reviews in burn care management. Computerised searches were performed in Ovid MEDLINE, Ovid EMBASE and The Cochrane Library through to February 2016 for systematic reviews relevant to burn care using medical subject and free-text terms such as 'burn', 'systematic review' or 'meta-analysis'. Additional studies were identified by hand-searching five discipline-specific journals. Two authors independently screened papers, extracted and evaluated methodological quality using the 11-item A Measurement Tool to Assess Systematic Reviews (AMSTAR) tool and reporting quality using the 27-item Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Characteristics of systematic reviews associated with methodological and reporting quality were identified. Descriptive statistics and linear regression identified features associated with improved methodological quality. A total of 60 systematic reviews met the inclusion criteria. Six of the 11 AMSTAR items reporting on 'a priori' design, duplicate study selection, grey literature, included/excluded studies, publication bias and conflict of interest were reported in less than 50% of the systematic reviews. Of the 27 items listed for PRISMA, 13 items reporting on introduction, methods, results and the discussion were addressed in less than 50% of systematic reviews. Multivariable analyses showed that systematic reviews associated with higher methodological or reporting quality incorporated a meta-analysis (AMSTAR regression coefficient 2.1; 95% CI: 1.1, 3.1; PRISMA regression coefficient 6·3; 95% CI: 3·8, 8·7) were published in the Cochrane library (AMSTAR regression coefficient 2·9; 95% CI: 1·6, 4·2; PRISMA regression coefficient 6·1; 95% CI: 3·1, 9·2) and included a randomised control trial (AMSTAR regression coefficient 1·4; 95%CI: 0·4, 2·4; PRISMA regression coefficient 3·4; 95% CI: 0·9, 5·8). The methodological and reporting quality of systematic reviews in burn care requires further improvement with stricter adherence by authors to the PRISMA checklist and AMSTAR tool. © 2016 Medicalhelplines.com Inc and John Wiley & Sons Ltd.

Solid harmonic wavelet scattering for predictions of molecule properties

NASA Astrophysics Data System (ADS)

Eickenberg, Michael; Exarchakis, Georgios; Hirn, Matthew; Mallat, Stéphane; Thiry, Louis

2018-06-01

We present a machine learning algorithm for the prediction of molecule properties inspired by ideas from density functional theory (DFT). Using Gaussian-type orbital functions, we create surrogate electronic densities of the molecule from which we compute invariant "solid harmonic scattering coefficients" that account for different types of interactions at different scales. Multilinear regressions of various physical properties of molecules are computed from these invariant coefficients. Numerical experiments show that these regressions have near state-of-the-art performance, even with relatively few training examples. Predictions over small sets of scattering coefficients can reach a DFT precision while being interpretable.

Genetic analyses of stillbirth in relation to litter size using random regression models.

PubMed

Chen, C Y; Misztal, I; Tsuruta, S; Herring, W O; Holl, J; Culbertson, M

2010-12-01

Estimates of genetic parameters for number of stillborns (NSB) in relation to litter size (LS) were obtained with random regression models (RRM). Data were collected from 4 purebred Duroc nucleus farms between 2004 and 2008. Two data sets with 6,575 litters for the first parity (P1) and 6,259 litters for the second to fifth parity (P2-5) with a total of 8,217 and 5,066 animals in the pedigree were analyzed separately. Number of stillborns was studied as a trait on sow level. Fixed effects were contemporary groups (farm-year-season) and fixed cubic regression coefficients on LS with Legendre polynomials. Models for P2-5 included the fixed effect of parity. Random effects were additive genetic effects for both data sets with permanent environmental effects included for P2-5. Random effects modeled with Legendre polynomials (RRM-L), linear splines (RRM-S), and degree 0 B-splines (RRM-BS) with regressions on LS were used. For P1, the order of polynomial, the number of knots, and the number of intervals used for respective models were quadratic, 3, and 3, respectively. For P2-5, the same parameters were linear, 2, and 2, respectively. Heterogeneous residual variances were considered in the models. For P1, estimates of heritability were 12 to 15%, 5 to 6%, and 6 to 7% in LS 5, 9, and 13, respectively. For P2-5, estimates were 15 to 17%, 4 to 5%, and 4 to 6% in LS 6, 9, and 12, respectively. For P1, average estimates of genetic correlations between LS 5 to 9, 5 to 13, and 9 to 13 were 0.53, -0.29, and 0.65, respectively. For P2-5, same estimates averaged for RRM-L and RRM-S were 0.75, -0.21, and 0.50, respectively. For RRM-BS with 2 intervals, the correlation was 0.66 between LS 5 to 7 and 8 to 13. Parameters obtained by 3 RRM revealed the nonlinear relationship between additive genetic effect of NSB and the environmental deviation of LS. The negative correlations between the 2 extreme LS might possibly indicate different genetic bases on incidence of stillbirth.

Space Shuttle Main Engine performance analysis

NASA Technical Reports Server (NTRS)

Santi, L. Michael

1993-01-01

For a number of years, NASA has relied primarily upon periodically updated versions of Rocketdyne's power balance model (PBM) to provide space shuttle main engine (SSME) steady-state performance prediction. A recent computational study indicated that PBM predictions do not satisfy fundamental energy conservation principles. More recently, SSME test results provided by the Technology Test Bed (TTB) program have indicated significant discrepancies between PBM flow and temperature predictions and TTB observations. Results of these investigations have diminished confidence in the predictions provided by PBM, and motivated the development of new computational tools for supporting SSME performance analysis. A multivariate least squares regression algorithm was developed and implemented during this effort in order to efficiently characterize TTB data. This procedure, called the 'gains model,' was used to approximate the variation of SSME performance parameters such as flow rate, pressure, temperature, speed, and assorted hardware characteristics in terms of six assumed independent influences. These six influences were engine power level, mixture ratio, fuel inlet pressure and temperature, and oxidizer inlet pressure and temperature. A BFGS optimization algorithm provided the base procedure for determining regression coefficients for both linear and full quadratic approximations of parameter variation. Statistical information relative to data deviation from regression derived relations was also computed. A new strategy for integrating test data with theoretical performance prediction was also investigated. The current integration procedure employed by PBM treats test data as pristine and adjusts hardware characteristics in a heuristic manner to achieve engine balance. Within PBM, this integration procedure is called 'data reduction.' By contrast, the new data integration procedure, termed 'reconciliation,' uses mathematical optimization techniques, and requires both measurement and balance uncertainty estimates. The reconciler attempts to select operational parameters that minimize the difference between theoretical prediction and observation. Selected values are further constrained to fall within measurement uncertainty limits and to satisfy fundamental physical relations (mass conservation, energy conservation, pressure drop relations, etc.) within uncertainty estimates for all SSME subsystems. The parameter selection problem described above is a traditional nonlinear programming problem. The reconciler employs a mixed penalty method to determine optimum values of SSME operating parameters associated with this problem formulation.

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

Hall, Matthew D.; Schultheiss, Timothy E., E-mail: schultheiss@coh.org; Smith, David D.

Purpose/Objective(s): To perform a meta-regression on published data and to model the 5-year probability of cataract development after hematopoietic stem cell transplantation (HSCT) with and without total body irradiation (TBI). Methods and Materials: Eligible studies reporting cataract incidence after HSCT with TBI were identified by a PubMed search. Seventeen publications provided complete information on radiation dose schedule, fractionation, dose rate, and actuarial cataract incidence. Chemotherapy-only regimens were included as zero radiation dose regimens. Multivariate meta-regression with a weighted generalized linear model was used to model the 5-year cataract incidence and contributory factors. Results: Data from 1386 patients in 21 seriesmore » were included for analysis. TBI was administered to a total dose of 0 to 15.75 Gy with single or fractionated schedules with a dose rate of 0.04 to 0.16 Gy/min. Factors significantly associated with 5-year cataract incidence were dose, dose times dose per fraction (D•dpf), pediatric versus adult status, and the absence of an ophthalmologist as an author. Dose rate, graft versus host disease, steroid use, hyperfractionation, and number of fractions were not significant. Five-fold internal cross-validation showed a model validity of 83% ± 8%. Regression diagnostics showed no evidence of lack-of-fit and no patterns in the studentized residuals. The α/β ratio from the linear quadratic model, estimated as the ratio of the coefficients for dose and D•dpf, was 0.76 Gy (95% confidence interval [CI], 0.05-1.55). The odds ratio for pediatric patients was 2.8 (95% CI, 1.7-4.6) relative to adults. Conclusions: Dose, D•dpf, pediatric status, and regimented follow-up care by an ophthalmologist were predictive of 5-year cataract incidence after HSCT. The low α/β ratio indicates the importance of fractionation in reducing cataracts. Dose rate effects have been observed in single institution studies but not in the combined data analyzed here. Although data were limited to articles with 5-year actuarial estimates, the development of radiation-induced cataracts extends beyond this time.« less

Description of Aspergillus flavus growth under the influence of different factors (water activity, incubation temperature, protein and fat concentration, pH, and cinnamon essential oil concentration) by kinetic, probability of growth, and time-to-detection models.

PubMed

Kosegarten, Carlos E; Ramírez-Corona, Nelly; Mani-López, Emma; Palou, Enrique; López-Malo, Aurelio

2017-01-02

A Box-Behnken design was used to determine the effect of protein concentration (0, 5, or 10g of casein/100g), fat (0, 3, or 6g of corn oil/100g), a w (0.900, 0.945, or 0.990), pH (3.5, 5.0, or 6.5), concentration of cinnamon essential oil (CEO, 0, 200, or 400μL/kg) and incubation temperature (15, 25, or 35°C) on the growth of Aspergillus flavus during 50days of incubation. Mold response under the evaluated conditions was modeled by the modified Gompertz equation, logistic regression, and time-to-detection model. The obtained polynomial regression models allow the significant coefficients (p<0.05) for linear, quadratic and interaction effects for the Gompertz equation's parameters to be identified, which adequately described (R 2 >0.967) the studied mold responses. After 50days of incubation, every tested model system was classified according to the observed response as 1 (growth) or 0 (no growth), then a binary logistic regression was utilized to model A. flavus growth interface, allowing to predict the probability of mold growth under selected combinations of tested factors. The time-to-detection model was utilized to estimate the time at which A. flavus visible growth begins. Water activity, temperature, and CEO concentration were the most important factors affecting fungal growth. It was observed that there is a range of possible combinations that may induce growth, such that incubation conditions and the amount of essential oil necessary for fungal growth inhibition strongly depend on protein and fat concentrations as well as on the pH of studied model systems. The probabilistic model and the time-to-detection models constitute another option to determine appropriate storage/processing conditions and accurately predict the probability and/or the time at which A. flavus growth occurs. Copyright © 2016 Elsevier B.V. All rights reserved.

The use of experimental design in the development of an HPLC-ECD method for the analysis of captopril.

PubMed

Khamanga, Sandile M; Walker, Roderick B

2011-01-15

An accurate, sensitive and specific high performance liquid chromatography-electrochemical detection (HPLC-ECD) method that was developed and validated for captopril (CPT) is presented. Separation was achieved using a Phenomenex(®) Luna 5 μm (C(18)) column and a mobile phase comprised of phosphate buffer (adjusted to pH 3.0): acetonitrile in a ratio of 70:30 (v/v). Detection was accomplished using a full scan multi channel ESA Coulometric detector in the "oxidative-screen" mode with the upstream electrode (E(1)) set at +600 mV and the downstream (analytical) electrode (E(2)) set at +950 mV, while the potential of the guard cell was maintained at +1050 mV. The detector gain was set at 300. Experimental design using central composite design (CCD) was used to facilitate method development. Mobile phase pH, molarity and concentration of acetonitrile (ACN) were considered the critical factors to be studied to establish the retention time of CPT and cyclizine (CYC) that was used as the internal standard. Twenty experiments including centre points were undertaken and a quadratic model was derived for the retention time for CPT using the experimental data. The method was validated for linearity, accuracy, precision, limits of quantitation and detection, as per the ICH guidelines. The system was found to produce sharp and well-resolved peaks for CPT and CYC with retention times of 3.08 and 7.56 min, respectively. Linear regression analysis for the calibration curve showed a good linear relationship with a regression coefficient of 0.978 in the concentration range of 2-70 μg/mL. The linear regression equation was y=0.0131x+0.0275. The limits of detection (LOQ) and quantitation (LOD) were found to be 2.27 and 0.6 μg/mL, respectively. The method was used to analyze CPT in tablets. The wide range for linearity, accuracy, sensitivity, short retention time and composition of the mobile phase indicated that this method is better for the quantification of CPT than the pharmacopoeial methods. Copyright © 2010 Elsevier B.V. All rights reserved.

A meta-model analysis of a finite element simulation for defining poroelastic properties of intervertebral discs.

PubMed

Nikkhoo, Mohammad; Hsu, Yu-Chun; Haghpanahi, Mohammad; Parnianpour, Mohamad; Wang, Jaw-Lin

2013-06-01

Finite element analysis is an effective tool to evaluate the material properties of living tissue. For an interactive optimization procedure, the finite element analysis usually needs many simulations to reach a reasonable solution. The meta-model analysis of finite element simulation can be used to reduce the computation of a structure with complex geometry or a material with composite constitutive equations. The intervertebral disc is a complex, heterogeneous, and hydrated porous structure. A poroelastic finite element model can be used to observe the fluid transferring, pressure deviation, and other properties within the disc. Defining reasonable poroelastic material properties of the anulus fibrosus and nucleus pulposus is critical for the quality of the simulation. We developed a material property updating protocol, which is basically a fitting algorithm consisted of finite element simulations and a quadratic response surface regression. This protocol was used to find the material properties, such as the hydraulic permeability, elastic modulus, and Poisson's ratio, of intact and degenerated porcine discs. The results showed that the in vitro disc experimental deformations were well fitted with limited finite element simulations and a quadratic response surface regression. The comparison of material properties of intact and degenerated discs showed that the hydraulic permeability significantly decreased but Poisson's ratio significantly increased for the degenerated discs. This study shows that the developed protocol is efficient and effective in defining material properties of a complex structure such as the intervertebral disc.

Effect of simultaneous variation in temperature and ammonia concentration on percent fertilization and hatching in Crassostrea ariakensis.

PubMed

Hui, Wang; Jiahui, Liu; Hongshuai, Yang; Jin, Liu; Zhigang, Liu

2014-04-01

The combined effects of temperature and ammonia concentration on the percent fertilization and percent hatching in Crassostrea ariakensis were examined under laboratory conditions using the central composite design and response surface methodology. The results indicated: (1) The linear effects of temperature and ammonia concentration on the percent fertilization were significant (P<0.05), and the quadratic effects were highly significant (P<0.01). The interactive effect between temperature and ammonia concentration on the percent fertilization was not significant (P>0.05). (2) The linear effect of temperature on the percent hatching was highly significant (P<0.01), and that of ammonia concentration was nonsignificant (P>0.05). The quadratic effects of temperature and ammonia concentration on the percent hatching were highly significant (P<0.01). The interaction on the percent hatching was not significant (P>0.05). Temperature was more important than ammonia in influencing the fertilization and hatching in C. ariakensis. (3) The model equations of the percent fertilization and hatching towards temperature and ammonia concentration were established, with the coefficients of determination R(2)=99.4% and 99.76%, respectively. Through the lack-of-fit test, these models were of great adequacy. The predictive coefficients of determination for the two model equations were as high as 94.6% and 98.03%, respectively, showing that they could be used for practical projection. (4) Via the statistical simultaneous optimization technique, the optimal factor level combination, i.e., 25°C/0.038mgmL(-1), was derived, at which the greatest percent fertilization 95.25% and hatching 83.26% was achieved, with the desirability being 97.81%. Our results may provide advantageous guidelines for the successful reproduction of C. ariakensis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Wilson polynomials/functions and intertwining operators for the generic quantum superintegrable system on the 2-sphere

NASA Astrophysics Data System (ADS)

Miller, W., Jr.; Li, Q.

2015-04-01

The Wilson and Racah polynomials can be characterized as basis functions for irreducible representations of the quadratic symmetry algebra of the quantum superintegrable system on the 2-sphere, HΨ = EΨ, with generic 3-parameter potential. Clearly, the polynomials are expansion coefficients for one eigenbasis of a symmetry operator L2 of H in terms of an eigenbasis of another symmetry operator L1, but the exact relationship appears not to have been made explicit. We work out the details of the expansion to show, explicitly, how the polynomials arise and how the principal properties of these functions: the measure, 3-term recurrence relation, 2nd order difference equation, duality of these relations, permutation symmetry, intertwining operators and an alternate derivation of Wilson functions - follow from the symmetry of this quantum system. This paper is an exercise to show that quantum mechancal concepts and recurrence relations for Gausian hypergeometrc functions alone suffice to explain these properties; we make no assumptions about the structure of Wilson polynomial/functions, but derive them from quantum principles. There is active interest in the relation between multivariable Wilson polynomials and the quantum superintegrable system on the n-sphere with generic potential, and these results should aid in the generalization. Contracting function space realizations of irreducible representations of this quadratic algebra to the other superintegrable systems one can obtain the full Askey scheme of orthogonal hypergeometric polynomials. All of these contractions of superintegrable systems with potential are uniquely induced by Wigner Lie algebra contractions of so(3, C) and e(2,C). All of the polynomials produced are interpretable as quantum expansion coefficients. It is important to extend this process to higher dimensions.

Regression model, artificial neural network, and cost estimation for biosorption of Ni(II)-ions from aqueous solutions by Potamogeton pectinatus.

PubMed

Fawzy, Manal; Nasr, Mahmoud; Adel, Samar; Helmi, Shacker

2018-03-21

This study investigated the application of Potamogeton pectinatus for Ni(II)-ions biosorption from aqueous solutions. FTIR spectra showed that the functional groups of -OH, C-H, -C = O, and -COO- could form an organometallic complex with Ni(II)-ions on the biomaterial surface. SEM/EDX analysis indicated that the voids on the biosorbent surface were blocked due to Ni(II)-ions uptake via an ion exchange mechanism. For Ni(II)-ions of 50 mg/L, the adsorption efficiency recorded 63.4% at pH: 5, biosorbent dosage: 10 g/L, and particle-diameter: 0.125-0.25 mm within 180 minutes. A quadratic model depicted that the plot of removal efficiency against pH or contact time caused quadratic-linear concave up curves, whereas the curve of initial Ni(II)-ions was quadratic-linear convex down. Artificial neural network with a structure of 5 - 6 - 1 was able to predict the adsorption efficiency (R 2 : 0.967). The relative importance of inputs was: initial Ni(II)-ions > pH > contact time > biosorbent dosage > particle-size. Freundlich isotherm described well the adsorption mechanism (R 2 : 0.974), which indicated a multilayer adsorption onto energetically heterogeneous surfaces. The net cost of using P. pectinatus for the removal of Ni(II)-ions (4.25 ± 1.26 mg/L) from real industrial effluents within 30 minutes was 3.4 $USD/m 3 .

Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Red River of the North at Fargo and Grand Forks, North Dakota, 2003-12

USGS Publications Warehouse

Galloway, Joel M.

2014-01-01

The Red River of the North (hereafter referred to as “Red River”) Basin is an important hydrologic region where water is a valuable resource for the region’s economy. Continuous water-quality monitors have been operated by the U.S. Geological Survey, in cooperation with the North Dakota Department of Health, Minnesota Pollution Control Agency, City of Fargo, City of Moorhead, City of Grand Forks, and City of East Grand Forks at the Red River at Fargo, North Dakota, from 2003 through 2012 and at Grand Forks, N.Dak., from 2007 through 2012. The purpose of the monitoring was to provide a better understanding of the water-quality dynamics of the Red River and provide a way to track changes in water quality. Regression equations were developed that can be used to estimate concentrations and loads for dissolved solids, sulfate, chloride, nitrate plus nitrite, total phosphorus, and suspended sediment using explanatory variables such as streamflow, specific conductance, and turbidity. Specific conductance was determined to be a significant explanatory variable for estimating dissolved solids concentrations at the Red River at Fargo and Grand Forks. The regression equations provided good relations between dissolved solid concentrations and specific conductance for the Red River at Fargo and at Grand Forks, with adjusted coefficients of determination of 0.99 and 0.98, respectively. Specific conductance, log-transformed streamflow, and a seasonal component were statistically significant explanatory variables for estimating sulfate in the Red River at Fargo and Grand Forks. Regression equations provided good relations between sulfate concentrations and the explanatory variables, with adjusted coefficients of determination of 0.94 and 0.89, respectively. For the Red River at Fargo and Grand Forks, specific conductance, streamflow, and a seasonal component were statistically significant explanatory variables for estimating chloride. For the Red River at Grand Forks, a time component also was a statistically significant explanatory variable for estimating chloride. The regression equations for chloride at the Red River at Fargo provided a fair relation between chloride concentrations and the explanatory variables, with an adjusted coefficient of determination of 0.66 and the equation for the Red River at Grand Forks provided a relatively good relation between chloride concentrations and the explanatory variables, with an adjusted coefficient of determination of 0.77. Turbidity and streamflow were statistically significant explanatory variables for estimating nitrate plus nitrite concentrations at the Red River at Fargo and turbidity was the only statistically significant explanatory variable for estimating nitrate plus nitrite concentrations at Grand Forks. The regression equation for the Red River at Fargo provided a relatively poor relation between nitrate plus nitrite concentrations, turbidity, and streamflow, with an adjusted coefficient of determination of 0.46. The regression equation for the Red River at Grand Forks provided a fair relation between nitrate plus nitrite concentrations and turbidity, with an adjusted coefficient of determination of 0.73. Some of the variability that was not explained by the equations might be attributed to different sources contributing nitrates to the stream at different times. Turbidity, streamflow, and a seasonal component were statistically significant explanatory variables for estimating total phosphorus at the Red River at Fargo and Grand Forks. The regression equation for the Red River at Fargo provided a relatively fair relation between total phosphorus concentrations, turbidity, streamflow, and season, with an adjusted coefficient of determination of 0.74. The regression equation for the Red River at Grand Forks provided a good relation between total phosphorus concentrations, turbidity, streamflow, and season, with an adjusted coefficient of determination of 0.87. For the Red River at Fargo, turbidity and streamflow were statistically significant explanatory variables for estimating suspended-sediment concentrations. For the Red River at Grand Forks, turbidity was the only statistically significant explanatory variable for estimating suspended-sediment concentration. The regression equation at the Red River at Fargo provided a good relation between suspended-sediment concentration, turbidity, and streamflow, with an adjusted coefficient of determination of 0.95. The regression equation for the Red River at Grand Forks provided a good relation between suspended-sediment concentration and turbidity, with an adjusted coefficient of determination of 0.96.

Statistical model to perform error analysis of curve fits of wind tunnel test data using the techniques of analysis of variance and regression analysis

NASA Technical Reports Server (NTRS)

Alston, D. W.

1981-01-01

The considered research had the objective to design a statistical model that could perform an error analysis of curve fits of wind tunnel test data using analysis of variance and regression analysis techniques. Four related subproblems were defined, and by solving each of these a solution to the general research problem was obtained. The capabilities of the evolved true statistical model are considered. The least squares fit is used to determine the nature of the force, moment, and pressure data. The order of the curve fit is increased in order to delete the quadratic effect in the residuals. The analysis of variance is used to determine the magnitude and effect of the error factor associated with the experimental data.

Reduction of shading-derived artifacts in skin chromophore imaging without measurements or assumptions about the shape of the subject

NASA Astrophysics Data System (ADS)

Yoshida, Kenichiro; Nishidate, Izumi; Ojima, Nobutoshi; Iwata, Kayoko

2014-01-01

To quantitatively evaluate skin chromophores over a wide region of curved skin surface, we propose an approach that suppresses the effect of the shading-derived error in the reflectance on the estimation of chromophore concentrations, without sacrificing the accuracy of that estimation. In our method, we use multiple regression analysis, assuming the absorbance spectrum as the response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as the predictor variables. The concentrations of melanin and total hemoglobin are determined from the multiple regression coefficients using compensation formulae (CF) based on the diffuse reflectance spectra derived from a Monte Carlo simulation. To suppress the shading-derived error, we investigated three different combinations of multiple regression coefficients for the CF. In vivo measurements with the forearm skin demonstrated that the proposed approach can reduce the estimation errors that are due to shading-derived errors in the reflectance. With the best combination of multiple regression coefficients, we estimated that the ratio of the error to the chromophore concentrations is about 10%. The proposed method does not require any measurements or assumptions about the shape of the subjects; this is an advantage over other studies related to the reduction of shading-derived errors.

Design a software real-time operation platform for wave piercing catamarans motion control using linear quadratic regulator based genetic algorithm.

PubMed

Liang, Lihua; Yuan, Jia; Zhang, Songtao; Zhao, Peng

2018-01-01

This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller.

Design a software real-time operation platform for wave piercing catamarans motion control using linear quadratic regulator based genetic algorithm

PubMed Central

Liang, Lihua; Zhang, Songtao; Zhao, Peng

2018-01-01

This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller. PMID:29709008

A tight upper bound for quadratic knapsack problems in grid-based wind farm layout optimization

NASA Astrophysics Data System (ADS)

Quan, Ning; Kim, Harrison M.

2018-03-01

The 0-1 quadratic knapsack problem (QKP) in wind farm layout optimization models possible turbine locations as nodes, and power loss due to wake effects between pairs of turbines as edges in a complete graph. The goal is to select up to a certain number of turbine locations such that the sum of selected node and edge coefficients is maximized. Finding the optimal solution to the QKP is difficult in general, but it is possible to obtain a tight upper bound on the QKP's optimal value which facilitates the use of heuristics to solve QKPs by giving a good estimate of the optimality gap of any feasible solution. This article applies an upper bound method that is especially well-suited to QKPs in wind farm layout optimization due to certain features of the formulation that reduce the computational complexity of calculating the upper bound. The usefulness of the upper bound was demonstrated by assessing the performance of the greedy algorithm for solving QKPs in wind farm layout optimization. The results show that the greedy algorithm produces good solutions within 4% of the optimal value for small to medium sized problems considered in this article.

Absorption by H2O and H2O-N2 mixtures at 153 GHz

NASA Technical Reports Server (NTRS)

Bauer, A.; Godon, M.; Carlier, J.; Ma, Q.; Tippings, R. H.

1993-01-01

New experimental data on and a theoretical analysis of the absorption coefficient at 153 GHz are presented for pure water vapor and water vapor-nitrogen mixtures. This frequency is 30 GHz lower than the resonant frequency of the nearest strong water line (183 GHz) and complements our previous measurements at 213 GHz. The pressure dependence is observed to be quadratic in the case of pure water vapor, while in the case of mixtures there are both linear and quadratic density components. By fitting our experimental data taken at several temperatures we have obtained the temperature dependence of the absorption. Our experimental data are compared to several theoretical models with and without a continuum contribution, and we find that none of the models is in very good agreement with the data; in the case of pure water vapor, the continuum contribution calculated using the recent theoretical absorption gives the best results. In general, the agreement between the data and the various models is less satisfactory than found previously in the high-frequency wing. The anisotropy in the observed absorption differs from that currently used in atmospheric models.

Modeling and dynamic properties of dual-chamber solid and liquid mixture vibration isolator

NASA Astrophysics Data System (ADS)

Li, F. S.; Chen, Q.; Zhou, J. H.

2016-07-01

The dual-chamber solid and liquid mixture (SALiM) vibration isolator, mainly proposed for vibration isolation of heavy machines with low frequency, consists of four principle parts: SALiM working media including elastic elements and incompressible oil, multi-layers bellows container, rigid reservoir and the oil tube connecting the two vessels. The isolation system under study is governed by a two-degrees-of-freedom (2-DOF) nonlinear equation including quadratic damping. Simplifying the nonlinear damping into viscous damping, the equivalent stiffness and damping model is derived from the equation for the response amplitude. Theoretical analysis and numerical simulation reveal that the isolator's stiffness and damping have multiple properties with different parameters, among which the effects of exciting frequency, vibrating amplitude, quadratic damping coefficient and equivalent stiffness of the two chambers on the isolator's dynamics are discussed in depth. Based on the boundary characteristics of stiffness and damping and the main causes for stiffness hardening effect, improvement strategies are proposed to obtain better dynamic properties. At last, experiments were implemented and the test results were generally consistent with the theoretical ones, which verified the reliability of the nonlinear dynamic model.

Theory of Band Warping and its Effects on Thermoelectronic Transport Properties

NASA Astrophysics Data System (ADS)

Mecholsky, Nicholas; Resca, Lorenzo; Pegg, Ian; Fornari, Marco

2015-03-01

Transport properties of materials depend upon features of band structures near extrema in the BZ. Such features are generally described in terms of quadratic expansions and effective masses. Such expansions, however, are permissible only under strict conditions that are sometimes violated by materials. Suggestive terms such as ``band warping'' have been used to refer to such situations and ad hoc methods have been developed to treat them. We develop a generally applicable theory, based on radial expansions, and a corresponding definition of angular effective mass which also accounts for effects of band non-parabolicity and anisotropy. Further, we develop precise procedures to evaluate band warping quantitatively and as an example we analyze the warping features of valence bands in silicon using first-principles calculations and we compare those with semi-empirical models. We use our theory to generalize derivations of transport coefficients for cases of either single or multiple electronic bands, with either quadratically expansible or warped energy surfaces. We introduce the transport-equivalent ellipsoid and illustrate the drastic effects that band warping can induce on thermoelectric properties using multi-band models. Vitreous State Laboratory and Samsung's GRO program.

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 Factorability of Quadratics: Motivation for More Techniques

ERIC Educational Resources Information Center

Bosse, Michael J.; Nandakumar, N. R.

2005-01-01

Typically, secondary and college algebra students attempt to utilize either completing the square or the quadratic formula as techniques to solve a quadratic equation only after frustration with factoring has arisen. While both completing the square and the quadratic formula are techniques which can determine solutions for all quadratic equations,…

Exact Analysis of Squared Cross-Validity Coefficient in Predictive Regression Models

ERIC Educational Resources Information Center

Shieh, Gwowen

2009-01-01

In regression analysis, the notion of population validity is of theoretical interest for describing the usefulness of the underlying regression model, whereas the presumably more important concept of population cross-validity represents the predictive effectiveness for the regression equation in future research. It appears that the inference…

The birth canal: correlation between the pubic arch angle, the interspinous diameter, and the obstetrical conjugate: a computed tomography biometric study in reproductive age women.

PubMed

Perlman, Sharon; Raviv-Zilka, Lisa; Levinsky, Denis; Gidron, Ayelet; Achiron, Reuven; Gilboa, Yinon; Kivilevitch, Zvi

2018-04-22

Assessment of pelvic configuration is an important factor in the prediction of a successful vaginal birth. However, manual evaluation of the pelvis is practically a vanishing art, and imaging techniques are not available as a real-time bed-side tool. Unlike the obstetrical conjugate diameter (OC) and inter spinous diameter (ISD), the pubic arch angle (PAA) can be easily measured by transperineal ultrasound. Three-dimensional computed tomography bone reconstructions were used to measure the three main birth canal diameters, evaluate the correlation between them, and establish the normal reference range for the inlet, mid-, and pelvic outlet. Measurements of the PAA, obstetric conjugate (OC), and ISD were performed offline using three-dimensional post processing reconstruction in bone algorithm application of the pelvis on examinations performed for suspected renal colic in nonpregnant reproductive age woman. The mean of two measurements was used for statistical analysis which included reproducibility of measurements, regression curve estimation between PAA, OC, and ISD, and calculation of the respective reference range centiles for each PAA degree. Two hundred ninety-eight women comprised the study group. The mean ± SD of the PAA, ISD, and OC were 104.9° (±7.4), 103.8 mm (±7.3), and 129.9 mm (±8.3), respectively. The intra- and interobserver agreement defined by the intraclass correlation coefficient (ICC) was excellent for all parameters (range 0.905-0.993). A significant positive correlation was found between PAA and ISD and between PAA and OCD (Pearson's correlation = 0.373 (p < .001), and 0.163 (p = .022), respectively). The best regression formula was found with quadratic regression for inter spinous diameter (ISD): 34.122778 + (0.962182*PAA - 0.002830*PAA 2 ), and linear regression for obstetric conjugate (OC): 110.638397 + 0.183156*PAA. Modeled mean, SD, and reference centiles of the ISD and OCD were calculated using the above regression models as function of the PAA. We report significant correlation between the three pelvic landmarks with greatest impact on the prediction of a successful vaginal delivery: the PAA which is easily measured sonographically and the ISD and OC which are not measurable by ultrasound. This correlation may serve as a basis for future studies to assess its utility and prognostic value for a safe vaginal delivery.

Comparing spatially varying coefficient models: a case study examining violent crime rates and their relationships to alcohol outlets and illegal drug arrests

NASA Astrophysics Data System (ADS)

Wheeler, David C.; Waller, Lance A.

2009-03-01

In this paper, we compare and contrast a Bayesian spatially varying coefficient process (SVCP) model with a geographically weighted regression (GWR) model for the estimation of the potentially spatially varying regression effects of alcohol outlets and illegal drug activity on violent crime in Houston, Texas. In addition, we focus on the inherent coefficient shrinkage properties of the Bayesian SVCP model as a way to address increased coefficient variance that follows from collinearity in GWR models. We outline the advantages of the Bayesian model in terms of reducing inflated coefficient variance, enhanced model flexibility, and more formal measuring of model uncertainty for prediction. We find spatially varying effects for alcohol outlets and drug violations, but the amount of variation depends on the type of model used. For the Bayesian model, this variation is controllable through the amount of prior influence placed on the variance of the coefficients. For example, the spatial pattern of coefficients is similar for the GWR and Bayesian models when a relatively large prior variance is used in the Bayesian model.

Application of low-dimensional techniques for closed-loop control of turbulent flows

NASA Astrophysics Data System (ADS)

Ausseur, Julie

The groundwork for an advanced closed-loop control of separated shear layer flows is laid out in this document. The experimental testbed for the present investigation is the turbulent flow over a NACA-4412 model airfoil tested in the Syracuse University subsonic wind tunnel at Re=135,000. The specified control objective is to delay separation - or stall - by constantly keeping the flow attached to the surface of the wing. The proper orthogonal decomposition (POD) is shown to he a valuable tool to provide a low-dimensional estimate of the flow state and the first POD expansion coefficient is proposed to he used as the control variable. Other reduced-order techniques such as the modified linear and quadratic stochastic measurement methods (mLSM, mQSM) are applied to reduce the complexity of the flow field and their ability to accurately estimate the flow state from surface pressure measurements alone is examined. A simple proportional feedback control is successfully implemented in real-time using these tools and flow separation is efficiently delayed by over 3 degrees angle of attack. To further improve the quality of the flow state estimate, the implementation of a Kalman filter is foreseen, in which the knowledge of the flow dynamics is added to the computation of the control variable to correct for the potential measurement errors. To this aim, a reduced-order model (ROM) of the flow is developed using the least-squares method to obtain the coefficients of the POD/Galerkin projection of the Navier-Stokes equations from experimental data. To build the training ensemble needed in this experimental procedure, the spectral mLSM is performed to generate time-resolved series of POD expansion coefficients from which temporal derivatives are computed. This technique, which is applied to independent PIV velocity snapshots and time-resolved surface measurements, is able to retrieve the rational temporal evolution of the flow physics in the entire 2-D measurement area. The quality of the spectral measurements is confirmed by the results from both the linear and quadratic dynamical systems. The preliminary results from the linear ROM strengthens the motivation for future control implementation of a linear Kalman filter in this flow.

Harmonic regression of Landsat time series for modeling attributes from national forest inventory data

NASA Astrophysics Data System (ADS)

Wilson, Barry T.; Knight, Joseph F.; McRoberts, Ronald E.

2018-03-01

Imagery from the Landsat Program has been used frequently as a source of auxiliary data for modeling land cover, as well as a variety of attributes associated with tree cover. With ready access to all scenes in the archive since 2008 due to the USGS Landsat Data Policy, new approaches to deriving such auxiliary data from dense Landsat time series are required. Several methods have previously been developed for use with finer temporal resolution imagery (e.g. AVHRR and MODIS), including image compositing and harmonic regression using Fourier series. The manuscript presents a study, using Minnesota, USA during the years 2009-2013 as the study area and timeframe. The study examined the relative predictive power of land cover models, in particular those related to tree cover, using predictor variables based solely on composite imagery versus those using estimated harmonic regression coefficients. The study used two common non-parametric modeling approaches (i.e. k-nearest neighbors and random forests) for fitting classification and regression models of multiple attributes measured on USFS Forest Inventory and Analysis plots using all available Landsat imagery for the study area and timeframe. The estimated Fourier coefficients developed by harmonic regression of tasseled cap transformation time series data were shown to be correlated with land cover, including tree cover. Regression models using estimated Fourier coefficients as predictor variables showed a two- to threefold increase in explained variance for a small set of continuous response variables, relative to comparable models using monthly image composites. Similarly, the overall accuracies of classification models using the estimated Fourier coefficients were approximately 10-20 percentage points higher than the models using the image composites, with corresponding individual class accuracies between six and 45 percentage points higher.

Controllable parabolic-cylinder optical rogue wave.

PubMed

Zhong, Wei-Ping; Chen, Lang; Belić, Milivoj; Petrović, Nikola

2014-10-01

We demonstrate controllable parabolic-cylinder optical rogue waves in certain inhomogeneous media. An analytical rogue wave solution of the generalized nonlinear Schrödinger equation with spatially modulated coefficients and an external potential in the form of modulated quadratic potential is obtained by the similarity transformation. Numerical simulations are performed for comparison with the analytical solutions and to confirm the stability of the rogue wave solution obtained. These optical rogue waves are built by the products of parabolic-cylinder functions and the basic rogue wave solution of the standard nonlinear Schrödinger equation. Such rogue waves may appear in different forms, as the hump and paw profiles.

Propagation regimes and populations of internal waves in the Mediterranean Sea basin

NASA Astrophysics Data System (ADS)

Kurkina, Oxana; Rouvinskaya, Ekaterina; Talipova, Tatiana; Soomere, Tarmo

2017-02-01

The geographical and seasonal distributions of kinematic and nonlinear parameters of long internal waves are derived from the Generalized Digital Environmental Model (GDEM) climatology for the Mediterranean Sea region, including the Black Sea. The considered parameters are phase speed of long internal waves and the coefficients at the dispersion, quadratic and cubic terms of the weakly-nonlinear Korteweg-de Vries-type models (in particular, the Gardner model). These parameters govern the possible polarities and shapes of solitary internal waves, their limiting amplitudes and propagation speeds. The key outcome is an express estimate of the expected parameters of internal waves for different regions of the Mediterranean basin.

RBE of quasi-monoenergetic 60 MeV neutron radiation for induction of dicentric chromosomes in human lymphocytes.

PubMed

Nolte, R; Mühlbradt, K-H; Meulders, J P; Stephan, G; Haney, M; Schmid, E

2005-12-01

The production of dicentric chromosomes in human lymphocytes by high-energy neutron radiation was studied using a quasi-monoenergetic 60 MeV neutron beam. The average yield coefficient [see text] of the linear dose-response relationship for dicentric chromosomes was measured to be (0.146+/-0.016) Gy-1. This confirms our earlier observations that above 400 keV, the yield of dicentric chromosomes decreases with increasing neutron energy. Using the linear-quadratic dose-response relationship for dicentric chromosomes established in blood of the same donor for 60Co gamma-rays as a reference radiation, an average maximum low-dose RBE (RBEM) of 14+/-4 for 60 MeV quasi-monoenergetic neutrons with a dose-weighted average energy [see text] of 41.0 MeV is obtained. A correction procedure was applied, to account for the low-energy continuum of the quasi-monoenergetic spectral neutron distribution, and the yield coefficient alpha for 60 MeV neutrons was determined from the measured average yield coefficient [see text]. For alpha, a value of (0.115+/-0.026) Gy-1 was obtained corresponding to an RBEM of 11+/-4. The present experiments extend earlier investigations with monoenergetic neutrons to higher energies.

Influence of temperature and charge effects on thermophoresis of polystyrene beads⋆.

PubMed

Syshchyk, Olga; Afanasenkau, Dzmitry; Wang, Zilin; Kriegs, Hartmut; Buitenhuis, Johan; Wiegand, Simone

2016-12-01

We study the thermodiffusion behavior of spherical polystyrene beads with a diameter of 25 nm by infrared thermal diffusion Forced Rayleigh Scattering (IR-TDFRS). Similar beads were used to investigate the radial dependence of the Soret coefficient by different authors. While Duhr and Braun (Proc. Natl. Acad. Sci. U.S.A. 104, 9346 (2007)) observed a quadratic radial dependence Braibanti et al. (Phys. Rev. Lett. 100, 108303 (2008)) found a linear radial dependence of the Soret coefficient. We demonstrated that special care needs to be taken to obtain reliable thermophoretic data, because the measurements are very sensitive to surface properties. The colloidal particles were characterized by transmission electron microscopy and dynamic light scattering (DLS) experiments were performed. We carried out systematic thermophoretic measurements as a function of temperature, buffer and surfactant concentration. The temperature dependence was analyzed using an empirical formula. To describe the Debye length dependence we used a theoretical model by Dhont. The resulting surface charge density is in agreement with previous literature results. Finally, we analyze the dependence of the Soret coefficient on the concentration of the anionic surfactant sodium dodecyl sulfate (SDS), applying an empirical thermodynamic approach accounting for chemical contributions.

SPSS and SAS programs for comparing Pearson correlations and OLS regression coefficients.

PubMed

Weaver, Bruce; Wuensch, Karl L

2013-09-01

Several procedures that use summary data to test hypotheses about Pearson correlations and ordinary least squares regression coefficients have been described in various books and articles. To our knowledge, however, no single resource describes all of the most common tests. Furthermore, many of these tests have not yet been implemented in popular statistical software packages such as SPSS and SAS. In this article, we describe all of the most common tests and provide SPSS and SAS programs to perform them. When they are applicable, our code also computes 100 × (1 - α)% confidence intervals corresponding to the tests. For testing hypotheses about independent regression coefficients, we demonstrate one method that uses summary data and another that uses raw data (i.e., Potthoff analysis). When the raw data are available, the latter method is preferred, because use of summary data entails some loss of precision due to rounding.

Quantitative Structure-Activity Relationship of Insecticidal Activity of Benzyl Ether Diamidine Derivatives

NASA Astrophysics Data System (ADS)

Zhai, Mengting; Chen, Yan; Li, Jing; Zhou, Jun

2017-12-01

The molecular electrongativity distance vector (MEDV-13) was used to describe the molecular structure of benzyl ether diamidine derivatives in this paper, Based on MEDV-13, The three-parameter (M 3, M 15, M 47) QSAR model of insecticidal activity (pIC 50) for 60 benzyl ether diamidine derivatives was constructed by leaps-and-bounds regression (LBR) . The traditional correlation coefficient (R) and the cross-validation correlation coefficient (R CV ) were 0.975 and 0.971, respectively. The robustness of the regression model was validated by Jackknife method, the correlation coefficient R were between 0.971 and 0.983. Meanwhile, the independent variables in the model were tested to be no autocorrelation. The regression results indicate that the model has good robust and predictive capabilities. The research would provide theoretical guidance for the development of new generation of anti African trypanosomiasis drugs with efficiency and low toxicity.

Consistent model identification of varying coefficient quantile regression with BIC tuning parameter selection

PubMed Central

Zheng, Qi; Peng, Limin

2016-01-01

Quantile regression provides a flexible platform for evaluating covariate effects on different segments of the conditional distribution of response. As the effects of covariates may change with quantile level, contemporaneously examining a spectrum of quantiles is expected to have a better capacity to identify variables with either partial or full effects on the response distribution, as compared to focusing on a single quantile. Under this motivation, we study a general adaptively weighted LASSO penalization strategy in the quantile regression setting, where a continuum of quantile index is considered and coefficients are allowed to vary with quantile index. We establish the oracle properties of the resulting estimator of coefficient function. Furthermore, we formally investigate a BIC-type uniform tuning parameter selector and show that it can ensure consistent model selection. Our numerical studies confirm the theoretical findings and illustrate an application of the new variable selection procedure. PMID:28008212

Some New Estimation Methods for Weighted Regression When There are Possible Outliers.

DTIC Science & Technology

1985-01-01

about influential points, and to add to our understanding of the structure of the data In Section 2 we show, by considering the influence function , why... influence function lampel; 1968, 1974) for the maximum likelihood esti- mator is proportional to (EP-l)h(x), where £= (y-x’B)exp[-h’(x)e], and is thus...unbounded. Since the influence function for the MLE is quadratic in the residual c, in theory a point with a sufficiently large residual can have an

Temperature preference of the white perch, Morone americana, collected in the Wicomico River, Maryland

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

Hall, L.W. Jr.; Hocutt, C.H.; Stauffer, J.R. Jr.

1979-06-01

Temperature preference tests were conducted on fresh water white perch (Morone americana), collected from the Wicomico River, Maryland. Collection temperature was 27/sup 0/C and acclimation temperatures used in temperature preference tests were 6, 12, 18, 24, 30, and 33/sup 0/C. The following methods were used to determine the final temperature preference:linear regression, quadratic equation, and eyeball plots. Recorded final temperature preference values were 28.9, 29.3, and 30.6/sup 0/C using each method respectively.

Quadratic spatial soliton interactions

NASA Astrophysics Data System (ADS)

Jankovic, Ladislav

Quadratic spatial soliton interactions were investigated in this Dissertation. The first part deals with characterizing the principal features of multi-soliton generation and soliton self-reflection. The second deals with two beam processes leading to soliton interactions and collisions. These subjects were investigated both theoretically and experimentally. The experiments were performed by using potassium niobate (KNBO 3) and periodically poled potassium titanyl phosphate (KTP) crystals. These particular crystals were desirable for these experiments because of their large nonlinear coefficients and, more importantly, because the experiments could be performed under non-critical-phase-matching (NCPM) conditions. The single soliton generation measurements, performed on KNBO3 by launching the fundamental component only, showed a broad angular acceptance bandwidth which was important for the soliton collisions performed later. Furthermore, at high input intensities multi-soliton generation was observed for the first time. The influence on the multi-soliton patterns generated of the input intensity and beam symmetry was investigated. The combined experimental and theoretical efforts indicated that spatial and temporal noise on the input laser beam induced multi-soliton patterns. Another research direction pursued was intensity dependent soliton routing by using of a specially engineered quadratically nonlinear interface within a periodically poled KTP sample. This was the first time demonstration of the self-reflection phenomenon in a system with a quadratic nonlinearity. The feature investigated is believed to have a great potential for soliton routing and manipulation by engineered structures. A detailed investigation was conducted on two soliton interaction and collision processes. Birth of an additional soliton resulting from a two soliton collision was observed and characterized for the special case of a non-planar geometry. A small amount of spiraling, up to 30 degrees rotation, was measured in the experiments performed. The parameters relevant for characterizing soliton collision processes were also studied in detail. Measurements were performed for various collision angles (from 0.2 to 4 degrees), phase mismatch, relative phase between the solitons and the distance to the collision point within the sample (which affects soliton formation). Both the individual and combined effects of these collision variables were investigated. Based on the research conducted, several all-optical switching scenarios were proposed.

Visual associations cued recall A Paradigm for Measuring Episodic Memory Decline in Alzheimer's Disease.

PubMed

Meyer, Sascha R A; Spaan, Pauline E J; Boelaarts, Leo; Ponds, Rudolf W H M; Schmand, Ben; de Jonghe, Jos F M

2016-09-01

Repeated measurements of episodic memory are needed for monitoring amnestic mild cognitive impairment (aMCI) and mild Alzheimer's disease (AD). Most episodic memory tests may pose a challenge to patients, even when they are in the milder stages of the disease. This cross-sectional study compared floor effects of the Visual Association Test (VAT) and the Rey Auditory Verbal Learning Test (RAVLT) in healthy elderly controls and in patients with aMCI or AD (N = 125). A hierarchical multiple regression analysis was used to examine whether linear or quadratic trends best fitted the data of cognitive test performance across global cognitive impairment. Results showed that VAT total scores decreased linearly across the range of global cognitive impairment, whereas RAVLT total scores showed a quadratic trend, with total scores levelling off for 90% of aMCI patients and 94% of AD patients. We conclude that the VAT shows few if any floor effects in patients with aMCI and mild AD and is therefore a potentially promising cognitive test for monitoring episodic memory impairment.

Redefining ADHD Using an Adult Population: Should Inattention be Viewed as a Separate Dimension From Cognitive and Physiological Activity Level?

PubMed

Miller, Nathan; Prevatt, Frances

2017-10-01

The purpose of this study was to reexamine the latent structure of ADHD and sluggish cognitive tempo (SCT) due to issues with construct validity. Two proposed changes to the construct include viewing hyperactivity and sluggishness (hypoactivity) as a single continuum of activity level, and viewing inattention as a separate dimension from activity level. Data were collected from 1,398 adults using Amazon's MTurk. A new scale measuring activity level was developed, and scores of Inattention were regressed onto scores of Activity Level using curvilinear regression. The Activity Level scale showed acceptable levels of internal consistency, normality, and unimodality. Curvilinear regression indicates that a quadratic (curvilinear) model accurately explains a small but significant portion of the variance in levels of inattention. Hyperactivity and hypoactivity may be viewed as a continuum, rather than separate disorders. Inattention may have a U-shaped relationship with activity level. Linear analyses may be insufficient and inaccurate for studying ADHD.

An investigation of the detection of tornadic thunderstorms by observing storm top features using geosynchronous satellite imagery

NASA Technical Reports Server (NTRS)

Anderson, Charles E.

1991-01-01

The number of tornado outbreak cases studied in detail was increased from the original 8. Detailed ground and aerial studies were carried out of two outbreak cases of considerable importance. It was demonstrated that multiple regression was able to predict the tornadic potential of a given thunderstorm cell by its cirrus anvil plume characteristics. It was also shown that the plume outflow intensity and the deviation of the plume alignment from storm relative winds at anvil altitude could account for the variance in tornadic potential for a given cell ranging from 0.37 to 0.82 for linear to values near 0.9 for quadratic regression. Several predictors were used in various discriminant analysis models and in censored regression models to obtain forecasts of whether a cell is tornadic and how strong tornadic it could be potentially. The experiments were performed with the synoptic scale vertical shear in the horizontal wind and with synoptic scale surface vorticity in the proximity of the cell.

Testing a single regression coefficient in high dimensional linear models

PubMed Central

Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2017-01-01

In linear regression models with high dimensional data, the classical z-test (or t-test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z-test to assess the significance of each covariate. Based on the p-value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively. PMID:28663668

Testing a single regression coefficient in high dimensional linear models.

PubMed

Lan, Wei; Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2016-11-01

In linear regression models with high dimensional data, the classical z -test (or t -test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z -test to assess the significance of each covariate. Based on the p -value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively.

Synthesis of linear regression coefficients by recovering the within-study covariance matrix from summary statistics.

PubMed

Yoneoka, Daisuke; Henmi, Masayuki

2017-06-01

Recently, the number of regression models has dramatically increased in several academic fields. However, within the context of meta-analysis, synthesis methods for such models have not been developed in a commensurate trend. One of the difficulties hindering the development is the disparity in sets of covariates among literature models. If the sets of covariates differ across models, interpretation of coefficients will differ, thereby making it difficult to synthesize them. Moreover, previous synthesis methods for regression models, such as multivariate meta-analysis, often have problems because covariance matrix of coefficients (i.e. within-study correlations) or individual patient data are not necessarily available. This study, therefore, proposes a brief explanation regarding a method to synthesize linear regression models under different covariate sets by using a generalized least squares method involving bias correction terms. Especially, we also propose an approach to recover (at most) threecorrelations of covariates, which is required for the calculation of the bias term without individual patient data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Basis for a neuronal version of Grover's quantum algorithm

PubMed Central

Clark, Kevin B.

2014-01-01

Grover's quantum (search) algorithm exploits principles of quantum information theory and computation to surpass the strong Church–Turing limit governing classical computers. The algorithm initializes a search field into superposed N (eigen)states to later execute nonclassical “subroutines” involving unitary phase shifts of measured states and to produce root-rate or quadratic gain in the algorithmic time (O(N1/2)) needed to find some “target” solution m. Akin to this fast technological search algorithm, single eukaryotic cells, such as differentiated neurons, perform natural quadratic speed-up in the search for appropriate store-operated Ca2+ response regulation of, among other processes, protein and lipid biosynthesis, cell energetics, stress responses, cell fate and death, synaptic plasticity, and immunoprotection. Such speed-up in cellular decision making results from spatiotemporal dynamics of networked intracellular Ca2+-induced Ca2+ release and the search (or signaling) velocity of Ca2+ wave propagation. As chemical processes, such as the duration of Ca2+ mobilization, become rate-limiting over interstore distances, Ca2+ waves quadratically decrease interstore-travel time from slow saltatory to fast continuous gradients proportional to the square-root of the classical Ca2+ diffusion coefficient, D1/2, matching the computing efficiency of Grover's quantum algorithm. In this Hypothesis and Theory article, I elaborate on these traits using a fire-diffuse-fire model of store-operated cytosolic Ca2+ signaling valid for glutamatergic neurons. Salient model features corresponding to Grover's quantum algorithm are parameterized to meet requirements for the Oracle Hadamard transform and Grover's iteration. A neuronal version of Grover's quantum algorithm figures to benefit signal coincidence detection and integration, bidirectional synaptic plasticity, and other vital cell functions by rapidly selecting, ordering, and/or counting optional response regulation choices. PMID:24860419

The influence of copper concentration and source on ileal microbiota.

PubMed

Pang, Y; Patterson, J A; Applegate, T J

2009-03-01

Copper is normally supplemented in poultry diets as a growth promotant and antimicrobial. However, there are conflicting reports about the growth benefits and little information about how Cu affects the microbiota in the intestinal tract of poultry. Therefore, in vitro and in vivo experiments were conducted with broilers to determine the effects of Cu source and supplementation on ileal microbiota. The influence of Cu on growth of lactobacilli and Escherichia coli in media inoculated with ileal contents was determined in the first study. When Cu sulfate pentahydrate was supplemented to the cultures, quadratic increases in lactobacilli to graded concentrations of Cu up to 125 mg/kg and quadratic decreases in E. coli up to 250 mg/kg of Cu were observed after 24 h of incubation at 37 degrees C. However, when tribasic Cu chloride (TBCC) was supplemented, neither linear nor quadratic responses to graded concentrations of dietary Cu were observed on number of lactobacilli or number of E. coli. The effects of Cu and Cu source on ileal microbiota and growth performance in broiler chickens were determined in the second study. Bird performance was not affected by Cu source or concentration. The bacterial culture enumeration results revealed that supplementation with 187.5 mg/kg of Cu from Cu sulfate pentahydrate and TBCC had no effect on number of ileal lactobacilli of birds. The denaturing gradient gel electrophoresis analyses of ileal microbial communities revealed that neither Cu supplementation nor source had effects on the number of bacterial species predominant in the ileal digesta or associated with the ileal mucosa. Supplementation with TBCC supplementation significantly increased the similarity coefficients of microbiota in the ileal mucosa compared with cross-products of all individuals. This suggests that TBCC may alter the intestinal microbiota, yet this shift had no effect on bird performance.

Confidence set inference with a prior quadratic bound

NASA Technical Reports Server (NTRS)

Backus, George E.

1988-01-01

In the uniqueness part of a geophysical inverse problem, the observer wants to predict all likely values of P unknown numerical properties z = (z sub 1,...,z sub p) of the earth from measurement of D other numerical properties y(0)=(y sub 1(0),...,y sub D(0)) knowledge of the statistical distribution of the random errors in y(0). The data space Y containing y(0) is D-dimensional, so when the model space X is infinite-dimensional the linear uniqueness problem usually is insoluble without prior information about the correct earth model x. If that information is a quadratic bound on x (e.g., energy or dissipation rate), Bayesian inference (BI) and stochastic inversion (SI) inject spurious structure into x, implied by neither the data nor the quadratic bound. Confidence set inference (CSI) provides an alternative inversion technique free of this objection. CSI is illustrated in the problem of estimating the geomagnetic field B at the core-mantle boundary (CMB) from components of B measured on or above the earth's surface. Neither the heat flow nor the energy bound is strong enough to permit estimation of B(r) at single points on the CMB, but the heat flow bound permits estimation of uniform averages of B(r) over discs on the CMB, and both bounds permit weighted disc-averages with continous weighting kernels. Both bounds also permit estimation of low-degree Gauss coefficients at the CMB. The heat flow bound resolves them up to degree 8 if the crustal field at satellite altitudes must be treated as a systematic error, but can resolve to degree 11 under the most favorable statistical treatment of the crust. These two limits produce circles of confusion on the CMB with diameters of 25 deg and 19 deg respectively.

Population heterogeneity in the salience of multiple risk factors for adolescent delinquency.

PubMed

Lanza, Stephanie T; Cooper, Brittany R; Bray, Bethany C

2014-03-01

To present mixture regression analysis as an alternative to more standard regression analysis for predicting adolescent delinquency. We demonstrate how mixture regression analysis allows for the identification of population subgroups defined by the salience of multiple risk factors. We identified population subgroups (i.e., latent classes) of individuals based on their coefficients in a regression model predicting adolescent delinquency from eight previously established risk indices drawn from the community, school, family, peer, and individual levels. The study included N = 37,763 10th-grade adolescents who participated in the Communities That Care Youth Survey. Standard, zero-inflated, and mixture Poisson and negative binomial regression models were considered. Standard and mixture negative binomial regression models were selected as optimal. The five-class regression model was interpreted based on the class-specific regression coefficients, indicating that risk factors had varying salience across classes of adolescents. Standard regression showed that all risk factors were significantly associated with delinquency. Mixture regression provided more nuanced information, suggesting a unique set of risk factors that were salient for different subgroups of adolescents. Implications for the design of subgroup-specific interventions are discussed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Retro-regression--another important multivariate regression improvement.

PubMed

Randić, M

2001-01-01

We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

[From clinical judgment to linear regression model.

PubMed

Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O

2013-01-01

When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.

Interpretation of commonly used statistical regression models.

PubMed

Kasza, Jessica; Wolfe, Rory

2014-01-01

A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

Dual purpose recovered coagulant from drinking water treatment residuals for adjustment of initial pH and coagulation aid in electrocoagulation process.

PubMed

Jung, Kyung-Won; Ahn, Kyu-Hong

2016-01-01

The present study is focused on the application of recovered coagulant (RC) by acidification from drinking water treatment residuals for both adjusting the initial pH and aiding coagulant in electrocoagulation. To do this, real cotton textile wastewater was used as a target pollutant, and decolorization and chemical oxygen demand (COD) removal efficiency were monitored. A preliminary test indicated that a stainless steel electrode combined with RC significantly accelerated decolorization and COD removal efficiencies, by about 52% and 56%, respectively, even at an operating time of 5 min. A single electrocoagulation system meanwhile requires at least 40 min to attain the similar removal performances. Subsequently, the interactive effect of three independent variables (applied voltage, initial pH, and reaction time) on the response variables (decolorization and COD removal) was evaluated, and these parameters were statistically optimized using the response surface methodology. Analysis of variance showed a high coefficient of determination values (decolorization, R(2) = 0.9925 and COD removal, R(2) = 0.9973) and satisfactory prediction second-order polynomial quadratic regression models. Average decolorization and COD removal of 89.52% and 94.14%, respectively, were achieved, corresponding to 97.8% and 98.1% of the predicted values under statistically optimized conditions. The results suggest that the RC effectively played a dual role of both adjusting the initial pH and aiding coagulant in the electrocoagulation process.

A SEMIPARAMETRIC BAYESIAN MODEL FOR CIRCULAR-LINEAR REGRESSION

EPA Science Inventory

We present a Bayesian approach to regress a circular variable on a linear predictor. The regression coefficients are assumed to have a nonparametric distribution with a Dirichlet process prior. The semiparametric Bayesian approach gives added flexibility to the model and is usefu...

Sinogram restoration in computed tomography with an edge-preserving penalty

PubMed Central

Little, Kevin J.; La Rivière, Patrick J.

2015-01-01

Purpose: With the goal of producing a less computationally intensive alternative to fully iterative penalized-likelihood image reconstruction, our group has explored the use of penalized-likelihood sinogram restoration for transmission tomography. Previously, we have exclusively used a quadratic penalty in our restoration objective function. However, a quadratic penalty does not excel at preserving edges while reducing noise. Here, we derive a restoration update equation for nonquadratic penalties. Additionally, we perform a feasibility study to extend our sinogram restoration method to a helical cone-beam geometry and clinical data. Methods: A restoration update equation for nonquadratic penalties is derived using separable parabolic surrogates (SPS). A method for calculating sinogram degradation coefficients for a helical cone-beam geometry is proposed. Using simulated data, sinogram restorations are performed using both a quadratic penalty and the edge-preserving Huber penalty. After sinogram restoration, Fourier-based analytical methods are used to obtain reconstructions, and resolution-noise trade-offs are investigated. For the fan-beam geometry, a comparison is made to image-domain SPS reconstruction using the Huber penalty. The effects of varying object size and contrast are also investigated. For the helical cone-beam geometry, we investigate the effect of helical pitch (axial movement/rotation). Huber-penalty sinogram restoration is performed on 3D clinical data, and the reconstructed images are compared to those generated with no restoration. Results: We find that by applying the edge-preserving Huber penalty to our sinogram restoration methods, the reconstructed image has a better resolution-noise relationship than an image produced using a quadratic penalty in the sinogram restoration. However, we find that this relatively straightforward approach to edge preservation in the sinogram domain is affected by the physical size of imaged objects in addition to the contrast across the edge. This presents some disadvantages of this method relative to image-domain edge-preserving methods, although the computational burden of the sinogram-domain approach is much lower. For a helical cone-beam geometry, we found applying sinogram restoration in 3D was reasonable and that pitch did not make a significant difference in the general effect of sinogram restoration. The application of Huber-penalty sinogram restoration to clinical data resulted in a reconstruction with less noise while retaining resolution. Conclusions: Sinogram restoration with the Huber penalty is able to provide better resolution-noise performance than restoration with a quadratic penalty. Additionally, sinogram restoration with the Huber penalty is feasible for helical cone-beam CT and can be applied to clinical data. PMID:25735286

Sinogram restoration in computed tomography with an edge-preserving penalty

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

Little, Kevin J., E-mail: little@uchicago.edu; La Rivière, Patrick J.

2015-03-15

Purpose: With the goal of producing a less computationally intensive alternative to fully iterative penalized-likelihood image reconstruction, our group has explored the use of penalized-likelihood sinogram restoration for transmission tomography. Previously, we have exclusively used a quadratic penalty in our restoration objective function. However, a quadratic penalty does not excel at preserving edges while reducing noise. Here, we derive a restoration update equation for nonquadratic penalties. Additionally, we perform a feasibility study to extend our sinogram restoration method to a helical cone-beam geometry and clinical data. Methods: A restoration update equation for nonquadratic penalties is derived using separable parabolic surrogatesmore » (SPS). A method for calculating sinogram degradation coefficients for a helical cone-beam geometry is proposed. Using simulated data, sinogram restorations are performed using both a quadratic penalty and the edge-preserving Huber penalty. After sinogram restoration, Fourier-based analytical methods are used to obtain reconstructions, and resolution-noise trade-offs are investigated. For the fan-beam geometry, a comparison is made to image-domain SPS reconstruction using the Huber penalty. The effects of varying object size and contrast are also investigated. For the helical cone-beam geometry, we investigate the effect of helical pitch (axial movement/rotation). Huber-penalty sinogram restoration is performed on 3D clinical data, and the reconstructed images are compared to those generated with no restoration. Results: We find that by applying the edge-preserving Huber penalty to our sinogram restoration methods, the reconstructed image has a better resolution-noise relationship than an image produced using a quadratic penalty in the sinogram restoration. However, we find that this relatively straightforward approach to edge preservation in the sinogram domain is affected by the physical size of imaged objects in addition to the contrast across the edge. This presents some disadvantages of this method relative to image-domain edge-preserving methods, although the computational burden of the sinogram-domain approach is much lower. For a helical cone-beam geometry, we found applying sinogram restoration in 3D was reasonable and that pitch did not make a significant difference in the general effect of sinogram restoration. The application of Huber-penalty sinogram restoration to clinical data resulted in a reconstruction with less noise while retaining resolution. Conclusions: Sinogram restoration with the Huber penalty is able to provide better resolution-noise performance than restoration with a quadratic penalty. Additionally, sinogram restoration with the Huber penalty is feasible for helical cone-beam CT and can be applied to clinical data.« less

Heavy metal bioaccumulation by Miscanthus sacchariflorus and its potential for removing metals from the Dongting Lake wetlands, China.

PubMed

Yao, Xin; Niu, Yandong; Li, Youzhi; Zou, Dongsheng; Ding, Xiaohui; Bian, Hualin

2018-05-09

Bioaccumulation of five heavy metals (Cd, Cu, Mn, Pb, and Zn) in six plant organs (panicle, leaf, stem, root, rhizome, and bud) of the emergent and perennial plant species, Miscanthus sacchariflorus, were investigated to estimate the plant's potential for accumulating heavy metals in the wetlands of Dongting Lake. We found the highest Cd concentrations in the panicles and leaves; while the highest Cu and Mn were observed in the roots, the highest Pb in the panicles, and the highest Zn in the panicles and buds. In contrast, the lowest Cd concentrations were detected in the stem, roots, and buds; the lowest Cu concentrations in the leaves and stems; the lowest Mn concentrations in the panicles, rhizomes, and buds; the lowest Pb concentrations in the stems; and the lowest Zn concentrations in the leaves, stems, and rhizomes. Mean Cu concentration in the plant showed a positive regression coefficient with plot elevation, soil organic matter content, and soil Cu concentration, whereas it showed a negative regression coefficient with soil moisture and electrolyte leakage. Mean Mn concentration showed positive and negative regression coefficients with soil organic matter and soil moisture, respectively. Mean Pb concentration exhibited positive regression coefficient with plot elevation and soil total P concentration, and Zn concentration showed a positive regression coefficient with soil available P and total P concentrations. However, there was no significant regression coefficient between mean Cd concentration in the plant and the investigated environmental parameters. Stems and roots were the main organs involved in heavy metal accumulation from the environment. The mean quantities of heavy metals accumulated in the plant tissues were 2.2 mg Cd, 86.7 mg Cu, 290.3 mg Mn, 15.9 mg Pb, and 307 mg Zn per square meter. In the Dongting Lake wetlands, 0.7 × 10 3  kg Cd, 22.9 × 10 3  kg Cu, 77.5 × 10 3  kg Mn, 3.1 × 10 3  kg Pb, and 95.9 × 10 3  kg Zn per year were accumulated by aboveground organs and removed from the lake through harvesting for paper manufacture.

Spectral regression and correlation coefficients of some benzaldimines and salicylaldimines in different solvents

NASA Astrophysics Data System (ADS)

Hammud, Hassan H.; Ghannoum, Amer; Masoud, Mamdouh S.

2006-02-01

Sixteen Schiff bases obtained from the condensation of benzaldehyde or salicylaldehyde with various amines (aniline, 4-carboxyaniline, phenylhydrazine, 2,4-dinitrophenylhydrazine, ethylenediamine, hydrazine, o-phenylenediamine and 2,6-pyridinediamine) are studied with UV-vis spectroscopy to observe the effect of solvents, substituents and other structural factors on the spectra. The bands involving different electronic transitions are interpreted. Computerized analysis and multiple regression techniques were applied to calculate the regression and correlation coefficients based on the equation that relates peak position λmax to the solvent parameters that depend on the H-bonding ability, refractive index and dielectric constant of solvents.

Comparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed

USGS Publications Warehouse

Moyer, Douglas; Hirsch, Robert M.; Hyer, Kenneth

2012-01-01

Nutrient and sediment fluxes and changes in fluxes over time are key indicators that water resource managers can use to assess the progress being made in improving the structure and function of the Chesapeake Bay ecosystem. The U.S. Geological Survey collects annual nutrient (nitrogen and phosphorus) and sediment flux data and computes trends that describe the extent to which water-quality conditions are changing within the major Chesapeake Bay tributaries. Two regression-based approaches were compared for estimating annual nutrient and sediment fluxes and for characterizing how these annual fluxes are changing over time. The two regression models compared are the traditionally used ESTIMATOR and the newly developed Weighted Regression on Time, Discharge, and Season (WRTDS). The model comparison focused on answering three questions: (1) What are the differences between the functional form and construction of each model? (2) Which model produces estimates of flux with the greatest accuracy and least amount of bias? (3) How different would the historical estimates of annual flux be if WRTDS had been used instead of ESTIMATOR? One additional point of comparison between the two models is how each model determines trends in annual flux once the year-to-year variations in discharge have been determined. All comparisons were made using total nitrogen, nitrate, total phosphorus, orthophosphorus, and suspended-sediment concentration data collected at the nine U.S. Geological Survey River Input Monitoring stations located on the Susquehanna, Potomac, James, Rappahannock, Appomattox, Pamunkey, Mattaponi, Patuxent, and Choptank Rivers in the Chesapeake Bay watershed. Two model characteristics that uniquely distinguish ESTIMATOR and WRTDS are the fundamental model form and the determination of model coefficients. ESTIMATOR and WRTDS both predict water-quality constituent concentration by developing a linear relation between the natural logarithm of observed constituent concentration and three explanatory variables—the natural log of discharge, time, and season. ESTIMATOR uses two additional explanatory variables—the square of the log of discharge and time-squared. Both models determine coefficients for variables for a series of estimation windows. ESTIMATOR establishes variable coefficients for a series of 9-year moving windows; all observed constituent concentration data within the 9-year window are used to establish each coefficient. Conversely, WRTDS establishes variable coefficients for each combination of discharge and time using only observed concentration data that are similar in time, season, and discharge to the day being estimated. As a result of these distinguishing characteristics, ESTIMATOR reproduces concentration-discharge relations that are closely approximated by a quadratic or linear function with respect to both the log of discharge and time. Conversely, the linear model form of WRTDS coupled with extensive model windowing for each combination of discharge and time allows WRTDS to reproduce observed concentration-discharge relations that are more sinuous in form. Another distinction between ESTIMATOR and WRTDS is the reporting of uncertainty associated with the model estimates of flux and trend. ESTIMATOR quantifies the standard error of prediction associated with the determination of flux and trends. The standard error of prediction enables the determination of the 95-percent confidence intervals for flux and trend as well as the ability to test whether the reported trend is significantly different from zero (where zero equals no trend). Conversely, WRTDS is unable to propagate error through the many (over 5,000) models for unique combinations of flow and time to determine a total standard error. As a result, WRTDS flux estimates are not reported with confidence intervals and a level of significance is not determined for flow-normalized fluxes. The differences between ESTIMATOR and WRTDS, with regard to model form and determination of model coefficients, have an influence on the determination of nutrient and sediment fluxes and associated changes in flux over time as a result of management activities. The comparison between the model estimates of flux and trend was made for combinations of five water-quality constituents at nine River Input Monitoring stations. The major findings with regard to nutrient and sediment fluxes are as follows: (1)WRTDS produced estimates of flux for all combinations that were more accurate, based on reduction in root mean squared error, than flux estimates from ESTIMATOR; (2) for 67 percent of the combinations, WRTDS and ESTIMATOR both produced estimates of flux that were minimally biased compared to observed fluxes(flux bias = tendency to over or underpredict flux observations); however, for 33 percent of the combinations, WRTDS produced estimates of flux that were considerably less biased (by at least 10 percent) than flux estimates from ESTIMATOR; (3) the average percent difference in annual fluxes generated by ESTIMATOR and WRTDS was less than 10 percent at 80 percent of the combinations; and (4) the greatest differences related to flux bias and annual fluxes all occurred for combinations where the pattern in observed concentration-discharge relation was sinuous (two points of inflection) rather than linear or quadratic (zero or one point of inflection). The major findings with regard to trends are as follows: (1) both models produce water-quality trends that have factored in the year-to-year variations in flow; (2) trends in water-quality condition are represented by ESTIMATOR as a trend in flow-adjusted concentration and by WRTDS as a flow normalized flux; (3) for 67 percent of the combinations with trend estimates, the WRTDS trends in flow-normalized flux are in the same direction and magnitude to the ESTIMATOR trends in flow-adjusted concentration, and at the remaining 33 percent the differences in trend magnitude and direction are related to fundamental differences between concentration and flux; and (4) the majority (85 percent) of the total nitrogen, nitrate, and orthophosphorus combinations exhibited long-term (1985 to 2010) trends in WRTDS flow-normalized flux that indicate improvement or reduction in associated flux and the majority (83 percent) of the total phosphorus (from 1985 to 2010) and suspended sediment (from 2001 to 2010) combinations exhibited trends in WRTDS flow-normalized flux that indicate degradation or increases in the flux delivered.

Hypersonic Vehicle Trajectory Optimization and Control

NASA Technical Reports Server (NTRS)

Balakrishnan, S. N.; Shen, J.; Grohs, J. R.

1997-01-01

Two classes of neural networks have been developed for the study of hypersonic vehicle trajectory optimization and control. The first one is called an 'adaptive critic'. The uniqueness and main features of this approach are that: (1) they need no external training; (2) they allow variability of initial conditions; and (3) they can serve as feedback control. This is used to solve a 'free final time' two-point boundary value problem that maximizes the mass at the rocket burn-out while satisfying the pre-specified burn-out conditions in velocity, flightpath angle, and altitude. The second neural network is a recurrent network. An interesting feature of this network formulation is that when its inputs are the coefficients of the dynamics and control matrices, the network outputs are the Kalman sequences (with a quadratic cost function); the same network is also used for identifying the coefficients of the dynamics and control matrices. Consequently, we can use it to control a system whose parameters are uncertain. Numerical results are presented which illustrate the potential of these methods.

Rogue Waves for a (2+1)-Dimensional Coupled Nonlinear Schrödinger System with Variable Coefficients in a Graded-Index Waveguide

NASA Astrophysics Data System (ADS)

Du, Zhong; Tian, Bo; Wu, Xiao-Yu; Yuan, Yu-Qiang

2018-05-01

Studied in this paper is a (2+1)-dimensional coupled nonlinear Schrödinger system with variable coefficients, which describes the propagation of an optical beam inside the two-dimensional graded-index waveguide amplifier with the polarization effects. According to the similarity transformation, we derive the type-I and type-II rogue-wave solutions. We graphically present two types of the rouge wave and discuss the influence of the diffraction parameter on the rogue waves. When the diffraction parameters are exponentially-growing-periodic, exponential, linear and quadratic parameters, we obtain the periodic rogue wave and composite rogue waves respectively. Supported by the National Natural Science Foundation of China under Grant Nos. 11772017, 11272023, and 11471050, by the Fund of State Key Laboratory of Information Photonics and Optical Communications (Beijing University of Posts and Telecommunications), China (IPOC: 2017ZZ05) and by the Fundamental Research Funds for the Central Universities of China under Grant No. 2011BUPTYB02.

Periodic thermodynamics of open quantum systems.

PubMed

Brandner, Kay; Seifert, Udo

2016-06-01

The thermodynamics of quantum systems coupled to periodically modulated heat baths and work reservoirs is developed. By identifying affinities and fluxes, the first and the second law are formulated consistently. In the linear response regime, entropy production becomes a quadratic form in the affinities. Specializing to Lindblad dynamics, we identify the corresponding kinetic coefficients in terms of correlation functions of the unperturbed dynamics. Reciprocity relations follow from symmetries with respect to time reversal. The kinetic coefficients can be split into a classical and a quantum contribution subject to an additional constraint, which follows from a natural detailed balance condition. This constraint implies universal bounds on efficiency and power of quantum heat engines. In particular, we show that Carnot efficiency cannot be reached whenever quantum coherence effects are present, i.e., when the Hamiltonian used for work extraction does not commute with the bare system Hamiltonian. For illustration, we specialize our universal results to a driven two-level system in contact with a heat bath of sinusoidally modulated temperature.

Periodic thermodynamics of open quantum systems

NASA Astrophysics Data System (ADS)

Brandner, Kay; Seifert, Udo

2016-06-01

The thermodynamics of quantum systems coupled to periodically modulated heat baths and work reservoirs is developed. By identifying affinities and fluxes, the first and the second law are formulated consistently. In the linear response regime, entropy production becomes a quadratic form in the affinities. Specializing to Lindblad dynamics, we identify the corresponding kinetic coefficients in terms of correlation functions of the unperturbed dynamics. Reciprocity relations follow from symmetries with respect to time reversal. The kinetic coefficients can be split into a classical and a quantum contribution subject to an additional constraint, which follows from a natural detailed balance condition. This constraint implies universal bounds on efficiency and power of quantum heat engines. In particular, we show that Carnot efficiency cannot be reached whenever quantum coherence effects are present, i.e., when the Hamiltonian used for work extraction does not commute with the bare system Hamiltonian. For illustration, we specialize our universal results to a driven two-level system in contact with a heat bath of sinusoidally modulated temperature.

Limb darkening effect on transit light curves of HAT-P-32b

NASA Astrophysics Data System (ADS)

ćuha, H.; Erdem, A.

2018-02-01

The transit light curve of a transiting exoplanet offers us an opportunity to measure the fractional radius, semi-major axis and orbital inclination of the star-planet system. Precision of those parameters is strongly affected by limb darkening of the host star. In this study, we examine the limb darkening effect on the transit light curves of HAT-P-32b. The transit light curves of HAT-P-32b were observed on three nights at TUBITAK National Observatory with a 100-cm aperture telescope in Bessel R and V filters. The light curves were solved using jktebop code. Linear, square root, logarithmic and quadratic limb darkening laws were taken into account during the analysis. The derived limb darkening coefficients from our observations were then compared with theoretical values given in the literature. We conclude that more sensitive data, such as space based photometric observations, are needed in order to determine the limb darkening coefficients accurately.

The Use of Alternative Regression Methods in Social Sciences and the Comparison of Least Squares and M Estimation Methods in Terms of the Determination of Coefficient

ERIC Educational Resources Information Center

Coskuntuncel, Orkun

2013-01-01

The purpose of this study is two-fold; the first aim being to show the effect of outliers on the widely used least squares regression estimator in social sciences. The second aim is to compare the classical method of least squares with the robust M-estimator using the "determination of coefficient" (R[superscript 2]). For this purpose,…

Theoretical gravity and limb-darkening coefficients for the MOST satellite photometric system

NASA Astrophysics Data System (ADS)

Claret, A.; Dragomir, D.; Matthews, J. M.

2014-07-01

Aims: We present new calculations of limb and gravity-darkening coefficients to be used as input in many fields of stellar physics such as synthetic light curves of double-lined eclipsing binaries and planetary transits, studies of stellar diameters or line profiles in rotating stars. Methods: We compute the limb-darkening coefficients specifically for the photometric system of the satellite MOST (Microvariability and Oscillations in STars). All computations were performed by adopting the least-square method, but for completeness we also performed calculations for the linear and bi-parametric approaches by adopting the flux conservation method. The passband gravity-darkening coefficients y(λ) were computed by adopting a more general differential equation, which also takes the effects of convection into account. Results: We used two stellar atmosphere models: ATLAS (plane-parallel) and PHOENIX (spherical and quasi-spherical). We adopted six laws to describe the specific intensity distribution: linear, quadratic, square root, logarithmic, exponential, and a more general one with four terms. The covered ranges of Teff, log g, metallicities, and microturbulent velocities are (1500-50 000 K, 0-5.5, -5.0-+1.0, 0-8 km s-1), respectively. Tables 2-23 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/567/A3

Self-Consistent Conversion of a Viscous Fluid to Particles and Heavy-Ion Physics Applications

NASA Astrophysics Data System (ADS)

Wolff, Zack J.

The most widely used theoretical framework to model the early stages of a heavy-ion collision is viscous hydrodynamics. Comparing hydrodynamic simulations to heavy-ion data inevitably requires the conversion of the fluid to particles. This conversion, typically done in the Cooper-Frye formalism, is ambiguous for viscous fluids. In this thesis work, self-consistent phase space corrections are calculated by solving the linearized Boltzmann equation. These species-dependent solutions are contrasted with those obtained using the ad-hoc ''democratic Grad'' ansatz typically employed in the literature in which coefficients are independent of particle dynamics. Solutions are calculated analytically for a massless gas and numerically for the general case of a hadron resonance gas. For example, it is found that for a gas of massless particles interacting via isotropic, energy-independent 2 → 2 scatterings, the shear viscous corrections variationally prefer a momentum dependence close to p3/2 rather than the quadratic dependence assumed in the Grad ansatz. The self-consistent phase space distributions are then used to calculate transverse momentum spectra and differential flow coefficients, v n(pT), to study the effects on heavy-ion identified particle observables. Using additive quark model cross sections, it is found that proton flow coefficients are higher than those for pions at moderately high pT in Pb + Pb collisions at LHC, especially for the coefficients v 4 and v6.

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

AllamehZadeh, Mostafa, E-mail: dibaparima@yahoo.com

A Quadratic Neural Networks (QNNs) model has been developed for identifying seismic source classification problem at regional distances using ARMA coefficients determination by Artificial Neural Networks (ANNs). We have devised a supervised neural system to discriminate between earthquakes and chemical explosions with filter coefficients obtained by windowed P-wave phase spectra (15 s). First, we preprocess the recording's signals to cancel out instrumental and attenuation site effects and obtain a compact representation of seismic records. Second, we use a QNNs system to obtain ARMA coefficients for feature extraction in the discrimination problem. The derived coefficients are then applied to the neuralmore » system to train and classification. In this study, we explore the possibility of using single station three-component (3C) covariance matrix traces from a priori-known explosion sites (learning) for automatically recognizing subsequent explosions from the same site. The results have shown that this feature extraction gives the best classifier for seismic signals and performs significantly better than other classification methods. The events have been tested, which include 36 chemical explosions at the Semipalatinsk test site in Kazakhstan and 61 earthquakes (mb = 5.0-6.5) recorded by the Iranian National Seismic Network (INSN). The 100% correct decisions were obtained between site explosions and some of non-site events. The above approach to event discrimination is very flexible as we can combine several 3C stations.« less

Multicollinearity and Regression Analysis

NASA Astrophysics Data System (ADS)

Daoud, Jamal I.

2017-12-01

In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.

QSAR modeling of flotation collectors using principal components extracted from topological indices.

PubMed

Natarajan, R; Nirdosh, Inderjit; Basak, Subhash C; Mills, Denise R

2002-01-01

Several topological indices were calculated for substituted-cupferrons that were tested as collectors for the froth flotation of uranium. The principal component analysis (PCA) was used for data reduction. Seven principal components (PC) were found to account for 98.6% of the variance among the computed indices. The principal components thus extracted were used in stepwise regression analyses to construct regression models for the prediction of separation efficiencies (Es) of the collectors. A two-parameter model with a correlation coefficient of 0.889 and a three-parameter model with a correlation coefficient of 0.913 were formed. PCs were found to be better than partition coefficient to form regression equations, and inclusion of an electronic parameter such as Hammett sigma or quantum mechanically derived electronic charges on the chelating atoms did not improve the correlation coefficient significantly. The method was extended to model the separation efficiencies of mercaptobenzothiazoles (MBT) and aminothiophenols (ATP) used in the flotation of lead and zinc ores, respectively. Five principal components were found to explain 99% of the data variability in each series. A three-parameter equation with correlation coefficient of 0.985 and a two-parameter equation with correlation coefficient of 0.926 were obtained for MBT and ATP, respectively. The amenability of separation efficiencies of chelating collectors to QSAR modeling using PCs based on topological indices might lead to the selection of collectors for synthesis and testing from a virtual database.

Parametric regression model for survival data: Weibull regression model as an example

PubMed Central

2016-01-01

Weibull regression model is one of the most popular forms of parametric regression model that it provides estimate of baseline hazard function, as well as coefficients for covariates. Because of technical difficulties, Weibull regression model is seldom used in medical literature as compared to the semi-parametric proportional hazard model. To make clinical investigators familiar with Weibull regression model, this article introduces some basic knowledge on Weibull regression model and then illustrates how to fit the model with R software. The SurvRegCensCov package is useful in converting estimated coefficients to clinical relevant statistics such as hazard ratio (HR) and event time ratio (ETR). Model adequacy can be assessed by inspecting Kaplan-Meier curves stratified by categorical variable. The eha package provides an alternative method to model Weibull regression model. The check.dist() function helps to assess goodness-of-fit of the model. Variable selection is based on the importance of a covariate, which can be tested using anova() function. Alternatively, backward elimination starting from a full model is an efficient way for model development. Visualization of Weibull regression model after model development is interesting that it provides another way to report your findings. PMID:28149846

Standardized Regression Coefficients as Indices of Effect Sizes in Meta-Analysis

ERIC Educational Resources Information Center

Kim, Rae Seon

2011-01-01

When conducting a meta-analysis, it is common to find many collected studies that report regression analyses, because multiple regression analysis is widely used in many fields. Meta-analysis uses effect sizes drawn from individual studies as a means of synthesizing a collection of results. However, indices of effect size from regression analyses…

The solar wind effect on cosmic rays and solar activity

NASA Technical Reports Server (NTRS)

Fujimoto, K.; Kojima, H.; Murakami, K.

1985-01-01

The relation of cosmic ray intensity to solar wind velocity is investigated, using neutron monitor data from Kiel and Deep River. The analysis shows that the regression coefficient of the average intensity for a time interval to the corresponding average velocity is negative and that the absolute effect increases monotonously with the interval of averaging, tau, that is, from -0.5% per 100km/s for tau = 1 day to -1.1% per 100km/s for tau = 27 days. For tau 27 days the coefficient becomes almost constant independently of the value of tau. The analysis also shows that this tau-dependence of the regression coefficiently is varying with the solar activity.

Seven Wonders of the Ancient and Modern Quadratic World.

ERIC Educational Resources Information Center

Taylor, Sharon E.; Mittag, Kathleen Cage

2001-01-01

Presents four methods for solving a quadratic equation using graphing calculator technology: (1) graphing with the CALC feature; (2) quadratic formula program; (3) table; and (4) solver. Includes a worksheet for a lab activity on factoring quadratic equations. (KHR)

On the time-weighted quadratic sum of linear discrete systems

NASA Technical Reports Server (NTRS)

Jury, E. I.; Gutman, S.

1975-01-01

A method is proposed for obtaining the time-weighted quadratic sum for linear discrete systems. The formula of the weighted quadratic sum is obtained from matrix z-transform formulation. In addition, it is shown that this quadratic sum can be derived in a recursive form for several useful weighted functions. The discussion presented parallels that of MacFarlane (1963) for weighted quadratic integral for linear continuous systems.

Breakfast intake among adults with type 2 diabetes: is bigger better?

PubMed Central

Jarvandi, Soghra; Schootman, Mario; Racette, Susan B.

2015-01-01

Objective To assess the association between breakfast energy and total daily energy intake among individuals with type 2 diabetes. Design Cross-sectional study. Daily energy intake was computed from a 24-h dietary recall. Multiple regression models were used to estimate the association between daily energy intake (dependent variable) and quartiles of energy intake at breakfast (independent variable) expressed as either absolute or relative (% of total daily energy intake) terms. Orthogonal polynomial contrasts were used to test for linear and quadratic trends. Models were controlled for sex, age, race/ethnicity, body mass index, physical activity and smoking. In addition, we used separate multiple regression models to test the effect of quartiles of absolute and relative breakfast energy on intake at lunch, dinner, and snacks. Setting The 1999–2004 National Health and Nutrition Examination Survey (NHANES). Subjects Participants aged ≥ 30 years with self-reported history of diabetes (N = 1,146). Results Daily energy intake increased as absolute breakfast energy intake increased (linear trend, P < 0.0001; quadratic trend, P = 0.02), but decreased as relative breakfast energy intake increased (linear trend, P < 0.0001). In addition, while higher quartiles of absolute breakfast intake had no associations with energy intake at subsequent meals, higher quartiles of relative breakfast intake were associated with lower energy intake during all subsequent meals and snacks (P < 0.05). Conclusions Consuming a breakfast that provided less energy or comprised a greater proportion of daily energy intake was associated with lower total daily energy intake in adults with type 2 diabetes. PMID:25529061

Body mass index and physical fitness in Brazilian adolescents.

PubMed

Lopes, Vitor P; Malina, Robert M; Gomez-Campos, Rossana; Cossio-Bolaños, Marco; Arruda, Miguel de; Hobold, Edilson

2018-05-05

Evaluate the relationship between body mass index and physical fitness in a cross-sectional sample of Brazilian youth. Participants were 3849 adolescents (2027 girls) aged 10-17 years. Weight and height were measured; body mass index was calculated. Physical fitness was evaluated with a multistage 20m shuttle run (cardiovascular endurance), standing long jump (power), and push-ups (upper body strength). Participants were grouped by sex into four age groups: 10-11, 12-13, 14-15, and 16-17 years. Sex-specific ANOVA was used to evaluate differences in each physical fitness item among weight status categories by age group. Relationships between body mass index and each physical fitness item were evaluated with quadratic regression models by age group within each sex. The physical fitness of thin and normal youth was, with few exceptions, significantly better than the physical fitness of overweight and obese youth in each age group by sex. On the other hand, physical fitness performances did not consistently differ, on average, between thin and normal weight and between overweight and obese youths. Results of the quadratic regressions indicated a curvilinear (parabolic) relationship between body mass index and each physical fitness item in most age groups. Better performances were attained by adolescents in the mid-range of the body mass index distribution, while performances of youth at the low and high ends of the body mass index distribution were lower. Relationships between the body mass index and physical fitness were generally nonlinear (parabolic) in youth 10-17 years. Copyright © 2018 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Relationship between aging and T1 relaxation time in deep gray matter: A voxel-based analysis.

PubMed

Okubo, Gosuke; Okada, Tomohisa; Yamamoto, Akira; Fushimi, Yasutaka; Okada, Tsutomu; Murata, Katsutoshi; Togashi, Kaori

2017-09-01

To investigate age-related changes in T 1 relaxation time in deep gray matter structures in healthy volunteers using magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE). In all, 70 healthy volunteers (aged 20-76, mean age 42.6 years) were scanned at 3T magnetic resonance imaging (MRI). A MP2RAGE sequence was employed to quantify T 1 relaxation times. After the spatial normalization of T 1 maps with the diffeomorphic anatomical registration using the exponentiated Lie algebra algorithm, voxel-based regression analysis was conducted. In addition, linear and quadratic regression analyses of regions of interest (ROIs) were also performed. With aging, voxel-based analysis (VBA) revealed significant T 1 value decreases in the ventral-inferior putamen, nucleus accumbens, and amygdala, whereas T 1 values significantly increased in the thalamus and white matter as well (P < 0.05 at cluster level, false discovery rate). ROI analysis revealed that T 1 values in the nucleus accumbens linearly decreased with aging (P = 0.0016), supporting the VBA result. T 1 values in the thalamus (P < 0.0001), substantia nigra (P = 0.0003), and globus pallidus (P < 0.0001) had a best fit to quadratic curves, with the minimum T 1 values observed between 30 and 50 years of age. Age-related changes in T 1 relaxation time vary by location in deep gray matter. 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:724-731. © 2017 International Society for Magnetic Resonance in Medicine.

Least-Squares Data Adjustment with Rank-Deficient Data Covariance Matrices

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

Williams, J.G.

2011-07-01

A derivation of the linear least-squares adjustment formulae is required that avoids the assumption that the covariance matrix of prior parameters can be inverted. Possible proofs are of several kinds, including: (i) extension of standard results for the linear regression formulae, and (ii) minimization by differentiation of a quadratic form of the deviations in parameters and responses. In this paper, the least-squares adjustment equations are derived in both these ways, while explicitly assuming that the covariance matrix of prior parameters is singular. It will be proved that the solutions are unique and that, contrary to statements that have appeared inmore » the literature, the least-squares adjustment problem is not ill-posed. No modification is required to the adjustment formulae that have been used in the past in the case of a singular covariance matrix for the priors. In conclusion: The linear least-squares adjustment formula that has been used in the past is valid in the case of a singular covariance matrix for the covariance matrix of prior parameters. Furthermore, it provides a unique solution. Statements in the literature, to the effect that the problem is ill-posed are wrong. No regularization of the problem is required. This has been proved in the present paper by two methods, while explicitly assuming that the covariance matrix of prior parameters is singular: i) extension of standard results for the linear regression formulae, and (ii) minimization by differentiation of a quadratic form of the deviations in parameters and responses. No modification is needed to the adjustment formulae that have been used in the past. (author)« less

An international age- and gender-controlled model for the Spinal Cord Injury Ability Realization Measurement Index (SCI-ARMI).

PubMed

Scivoletto, Giorgio; Glass, Clive; Anderson, Kim D; Galili, Tal; Benjamin, Yoav; Front, Lilach; Aidinoff, Elena; Bluvshtein, Vadim; Itzkovich, Malka; Aito, Sergio; Baroncini, Ilaria; Benito-Penalva, Jesùs; Castellano, Simona; Osman, Aheed; Silva, Pedro; Catz, Amiram

2015-01-01

Background. A quadratic formula of the Spinal Cord Injury Ability Realization Measurement Index (SCI-ARMI) has previously been published. This formula was based on a model of Spinal Cord Independence Measure (SCIM95), the 95th percentile of the SCIM III values, which correspond with the American Spinal Injury Association Motor Scores (AMS) of SCI patients. Objective. To further develop the original formula. Setting. Spinal cord injury centers from 6 countries and the Statistical Laboratory, Tel-Aviv University, Israel. Methods. SCIM95 of 661 SCI patients was modeled, using a quantile regression with or without adjustment for age and gender, to calculate SCI-ARMI values. SCI-ARMI gain during rehabilitation and its correlations were examined. Results. A new quadratic SCIM95 model was created. This resembled the previously published model, which yielded similar SCIM95 values in all the countries, after adjustment for age and gender. Without this adjustment, however, only 86% of the non-Israeli SCIM III observations were lower than those SCIM95 values (P < .0001). Adding the variables age and gender to the new model affected the SCIM95 value significantly (P < .04). Adding country information did not add a significant effect (P > .1). SCI-ARMI gain was positive (38.8 ± 22 points, P < .0001) and correlated weakly with admission age and AMS. Conclusions. The original quadratic SCI-ARMI formula is valid for an international population after adjustment for age and gender. The new formula considers more factors that affect functional ability following SCI. © The Author(s) 2014.

Interpretation of the Coefficients in the Fit y = at + bx + c

ERIC Educational Resources Information Center

Farnsworth, David L.

2006-01-01

The goals of this note are to derive formulas for the coefficients a and b in the least-squares regression plane y = at + bx + c for observations (t[subscript]i,x[subscript]i,y[subscript]i), i = 1, 2, ..., n, and to present meanings for the coefficients a and b. In this note, formulas for the coefficients a and b in the least-squares fit are…

THE EFFECTIVENESS OF QUADRATS FOR MEASURING VASCULAR PLANT DIVERSITY

EPA Science Inventory

Quadrats are widely used for measuring characteristics of vascular plant communities. It is well recognized that quadrat size affects measurements of frequency and cover. The ability of quadrats of varying sizes to adequately measure diversity has not been established. An exha...

Investigating the Performance of Alternate Regression Weights by Studying All Possible Criteria in Regression Models with a Fixed Set of Predictors

ERIC Educational Resources Information Center

Waller, Niels; Jones, Jeff

2011-01-01

We describe methods for assessing all possible criteria (i.e., dependent variables) and subsets of criteria for regression models with a fixed set of predictors, x (where x is an n x 1 vector of independent variables). Our methods build upon the geometry of regression coefficients (hereafter called regression weights) in n-dimensional space. For a…

Neither fixed nor random: weighted least squares meta-regression.

PubMed

Stanley, T D; Doucouliagos, Hristos

2017-03-01

Our study revisits and challenges two core conventional meta-regression estimators: the prevalent use of 'mixed-effects' or random-effects meta-regression analysis and the correction of standard errors that defines fixed-effects meta-regression analysis (FE-MRA). We show how and explain why an unrestricted weighted least squares MRA (WLS-MRA) estimator is superior to conventional random-effects (or mixed-effects) meta-regression when there is publication (or small-sample) bias that is as good as FE-MRA in all cases and better than fixed effects in most practical applications. Simulations and statistical theory show that WLS-MRA provides satisfactory estimates of meta-regression coefficients that are practically equivalent to mixed effects or random effects when there is no publication bias. When there is publication selection bias, WLS-MRA always has smaller bias than mixed effects or random effects. In practical applications, an unrestricted WLS meta-regression is likely to give practically equivalent or superior estimates to fixed-effects, random-effects, and mixed-effects meta-regression approaches. However, random-effects meta-regression remains viable and perhaps somewhat preferable if selection for statistical significance (publication bias) can be ruled out and when random, additive normal heterogeneity is known to directly affect the 'true' regression coefficient. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Interpreting Bivariate Regression Coefficients: Going beyond the Average

ERIC Educational Resources Information Center

Halcoussis, Dennis; Phillips, G. Michael

2010-01-01

Statistics, econometrics, investment analysis, and data analysis classes often review the calculation of several types of averages, including the arithmetic mean, geometric mean, harmonic mean, and various weighted averages. This note shows how each of these can be computed using a basic regression framework. By recognizing when a regression model…

Beyond Multiple Regression: Using Commonality Analysis to Better Understand R[superscript 2] Results

ERIC Educational Resources Information Center

Warne, Russell T.

2011-01-01

Multiple regression is one of the most common statistical methods used in quantitative educational research. Despite the versatility and easy interpretability of multiple regression, it has some shortcomings in the detection of suppressor variables and for somewhat arbitrarily assigning values to the structure coefficients of correlated…

Precision Efficacy Analysis for Regression.

ERIC Educational Resources Information Center

Brooks, Gordon P.

When multiple linear regression is used to develop a prediction model, sample size must be large enough to ensure stable coefficients. If the derivation sample size is inadequate, the model may not predict well for future subjects. The precision efficacy analysis for regression (PEAR) method uses a cross- validity approach to select sample sizes…

The non-avian theropod quadrate I: standardized terminology with an overview of the anatomy and function

PubMed Central

Araújo, Ricardo; Mateus, Octávio

2015-01-01

The quadrate of reptiles and most other tetrapods plays an important morphofunctional role by allowing the articulation of the mandible with the cranium. In Theropoda, the morphology of the quadrate is particularly complex and varies importantly among different clades of non-avian theropods, therefore conferring a strong taxonomic potential. Inconsistencies in the notation and terminology used in discussions of the theropod quadrate anatomy have been noticed, including at least one instance when no less than eight different terms were given to the same structure. A standardized list of terms and notations for each quadrate anatomical entity is proposed here, with the goal of facilitating future descriptions of this important cranial bone. In addition, an overview of the literature on quadrate function and pneumaticity in non-avian theropods is presented, along with a discussion of the inferences that could be made from this research. Specifically, the quadrate of the large majority of non-avian theropods is akinetic but the diagonally oriented intercondylar sulcus of the mandibular articulation allowed both rami of the mandible to move laterally when opening the mouth in many of theropods. Pneumaticity of the quadrate is also present in most averostran clades and the pneumatic chamber—invaded by the quadrate diverticulum of the mandibular arch pneumatic system—was connected to one or several pneumatic foramina on the medial, lateral, posterior, anterior or ventral sides of the quadrate. PMID:26401455

40 CFR 53.34 - Test procedure for methods for PM10 and Class I methods for PM2.5.

Code of Federal Regulations, 2011 CFR

2011-07-01

... linear regression parameters (slope, intercept, and correlation coefficient) describing the relationship... correlation coefficient. (2) To pass the test for comparability, the slope, intercept, and correlation...

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

PubMed

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

2012-01-01

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

Data Mining Methods Applied to Flight Operations Quality Assurance Data: A Comparison to Standard Statistical Methods

NASA Technical Reports Server (NTRS)

Stolzer, Alan J.; Halford, Carl

2007-01-01

In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.

Predicting Air Permeability of Handloom Fabrics: A Comparative Analysis of Regression and Artificial Neural Network Models

NASA Astrophysics Data System (ADS)

Mitra, Ashis; Majumdar, Prabal Kumar; Bannerjee, Debamalya

2013-03-01

This paper presents a comparative analysis of two modeling methodologies for the prediction of air permeability of plain woven handloom cotton fabrics. Four basic fabric constructional parameters namely ends per inch, picks per inch, warp count and weft count have been used as inputs for artificial neural network (ANN) and regression models. Out of the four regression models tried, interaction model showed very good prediction performance with a meager mean absolute error of 2.017 %. However, ANN models demonstrated superiority over the regression models both in terms of correlation coefficient and mean absolute error. The ANN model with 10 nodes in the single hidden layer showed very good correlation coefficient of 0.982 and 0.929 and mean absolute error of only 0.923 and 2.043 % for training and testing data respectively.

Improvement of Storm Forecasts Using Gridded Bayesian Linear Regression for Northeast United States

NASA Astrophysics Data System (ADS)

Yang, J.; Astitha, M.; Schwartz, C. S.

2017-12-01

Bayesian linear regression (BLR) is a post-processing technique in which regression coefficients are derived and used to correct raw forecasts based on pairs of observation-model values. This study presents the development and application of a gridded Bayesian linear regression (GBLR) as a new post-processing technique to improve numerical weather prediction (NWP) of rain and wind storm forecasts over northeast United States. Ten controlled variables produced from ten ensemble members of the National Center for Atmospheric Research (NCAR) real-time prediction system are used for a GBLR model. In the GBLR framework, leave-one-storm-out cross-validation is utilized to study the performances of the post-processing technique in a database composed of 92 storms. To estimate the regression coefficients of the GBLR, optimization procedures that minimize the systematic and random error of predicted atmospheric variables (wind speed, precipitation, etc.) are implemented for the modeled-observed pairs of training storms. The regression coefficients calculated for meteorological stations of the National Weather Service are interpolated back to the model domain. An analysis of forecast improvements based on error reductions during the storms will demonstrate the value of GBLR approach. This presentation will also illustrate how the variances are optimized for the training partition in GBLR and discuss the verification strategy for grid points where no observations are available. The new post-processing technique is successful in improving wind speed and precipitation storm forecasts using past event-based data and has the potential to be implemented in real-time.

Correlation and prediction of dynamic human isolated joint strength from lean body mass

NASA Technical Reports Server (NTRS)

Pandya, Abhilash K.; Hasson, Scott M.; Aldridge, Ann M.; Maida, James C.; Woolford, Barbara J.

1992-01-01

A relationship between a person's lean body mass and the amount of maximum torque that can be produced with each isolated joint of the upper extremity was investigated. The maximum dynamic isolated joint torque (upper extremity) on 14 subjects was collected using a dynamometer multi-joint testing unit. These data were reduced to a table of coefficients of second degree polynomials, computed using a least squares regression method. All the coefficients were then organized into look-up tables, a compact and convenient storage/retrieval mechanism for the data set. Data from each joint, direction and velocity, were normalized with respect to that joint's average and merged into files (one for each curve for a particular joint). Regression was performed on each one of these files to derive a table of normalized population curve coefficients for each joint axis, direction, and velocity. In addition, a regression table which included all upper extremity joints was built which related average torque to lean body mass for an individual. These two tables are the basis of the regression model which allows the prediction of dynamic isolated joint torques from an individual's lean body mass.

Relationship of extinction coefficient, air pollution, and meteorological parameters in an urban area during 2007 to 2009.

PubMed

Sabetghadam, Samaneh; Ahmadi-Givi, Farhang

2014-01-01

Light extinction, which is the extent of attenuation of light signal for every distance traveled by light in the absence of special weather conditions (e.g., fog and rain), can be expressed as the sum of scattering and absorption effects of aerosols. In this paper, diurnal and seasonal variations of the extinction coefficient are investigated for the urban areas of Tehran from 2007 to 2009. Cases of visibility impairment that were concurrent with reports of fog, mist, precipitation, or relative humidity above 90% are filtered. The mean value and standard deviation of daily extinction are 0.49 and 0.39 km(-1), respectively. The average is much higher than that in many other large cities in the world, indicating the rather poor air quality over Tehran. The extinction coefficient shows obvious diurnal variations in each season, with a peak in the morning that is more pronounced in the wintertime. Also, there is a very slight increasing trend in the annual variations of atmospheric extinction coefficient, which suggests that air quality has regressed since 2007. The horizontal extinction coefficient decreased from January to July in each year and then increased between July and December, with the maximum value in the winter. Diurnal variation of extinction is often associated with small values for low relative humidity (RH), but increases significantly at higher RH. Annual correlation analysis shows that there is a positive correlation between the extinction coefficient and RH, CO, PM10, SO2, and NO2 concentration, while negative correlation exists between the extinction and T, WS, and O3, implying their unfavorable impact on extinction variation. The extinction budget was derived from multiple regression equations using the regression coefficients. On average, 44% of the extinction is from suspended particles, 3% is from air molecules, about 5% is from NO2 absorption, 0.35% is from RH, and approximately 48% is unaccounted for, which may represent errors in the data as well as contribution of other atmospheric constituents omitted from the analysis. Stronger regression equation is achieved in the summer, meaning that the extinction is more predictable in this season using pollutant concentrations.

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

Cerebrospinal fluid norepinephrine and cognition in subjects across the adult age span

PubMed Central

Wang, Lucy Y.; Murphy, Richard R.; Hanscom, Brett; Li, Ge; Millard, Steven P.; Petrie, Eric C.; Galasko, Douglas R.; Sikkema, Carl; Raskind, Murray A.; Wilkinson, Charles W.; Peskind, Elaine R.

2013-01-01

Adequate central nervous system noradrenergic activity enhances cognition, but excessive noradrenergic activity may have adverse effects on cognition. Previous studies have also demonstrated that noradrenergic activity is higher in older than younger adults. We aimed to determine relationships between cerebrospinal fluid (CSF) norepinephrine (NE) concentration and cognitive performance by using data from a CSF bank that includes samples from 258 cognitively normal participants aged 21–100 years. After adjusting for age, gender, education, and ethnicity, higher CSF NE levels (units of 100 pg/mL) are associated with poorer performance on tests of attention, processing speed, and executive function (Trail Making A: regression coefficient 1.5, standard error [SE] 0.77, p = 0.046; Trail Making B: regression coefficient 5.0, SE 2.2, p = 0.024; Stroop Word-Color Interference task: regression coefficient 6.1, SE 2.0, p = 0.003). Findings are consistent with the earlier literature relating excess noradrenergic activity with cognitive impairment. PMID:23639207

Cerebrospinal fluid norepinephrine and cognition in subjects across the adult age span.

PubMed

Wang, Lucy Y; Murphy, Richard R; Hanscom, Brett; Li, Ge; Millard, Steven P; Petrie, Eric C; Galasko, Douglas R; Sikkema, Carl; Raskind, Murray A; Wilkinson, Charles W; Peskind, Elaine R

2013-10-01

Adequate central nervous system noradrenergic activity enhances cognition, but excessive noradrenergic activity may have adverse effects on cognition. Previous studies have also demonstrated that noradrenergic activity is higher in older than younger adults. We aimed to determine relationships between cerebrospinal fluid (CSF) norepinephrine (NE) concentration and cognitive performance by using data from a CSF bank that includes samples from 258 cognitively normal participants aged 21-100 years. After adjusting for age, gender, education, and ethnicity, higher CSF NE levels (units of 100 pg/mL) are associated with poorer performance on tests of attention, processing speed, and executive function (Trail Making A: regression coefficient 1.5, standard error [SE] 0.77, p = 0.046; Trail Making B: regression coefficient 5.0, SE 2.2, p = 0.024; Stroop Word-Color Interference task: regression coefficient 6.1, SE 2.0, p = 0.003). Findings are consistent with the earlier literature relating excess noradrenergic activity with cognitive impairment. Published by Elsevier Inc.

A classical mechanics model for the interpretation of piezoelectric property data

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

Bell, Andrew J., E-mail: a.j.bell@leeds.ac.uk

2015-12-14

In order to provide a means of understanding, the relationship between the primary electromechanical coefficients and simple crystal chemistry parameters for piezoelectric materials, a static analysis of a 3 atom, dipolar molecule has been undertaken to derive relationships for elastic compliance s{sup E}, dielectric permittivity ε{sup X}, and piezoelectric charge coefficient d in terms of an effective ionic charge and two inter-atomic force constants. The relationships demonstrate the mutual interdependence of the three coefficients, in keeping with experimental evidence from a large dataset of commercial piezoelectric materials. It is shown that the electromechanical coupling coefficient k is purely an expressionmore » of the asymmetry in the two force constants or bond compliances. The treatment is extended to show that the quadratic electrostriction relation between strain and polarization, in both centrosymmetric and non-centrosymmetric systems, is due to the presence of a non-zero 2nd order term in the bond compliance. Comparison with experimental data explains the counter-intuitive, positive correlation of k with s{sup E} and ε{sup X} and supports the proposition that high piezoelectric activity in single crystals is dominated by large compliance coupled with asymmetry in the sub-cell force constants. However, the analysis also shows that in polycrystalline materials, the dielectric anisotropy of the constituent crystals can be more important for attaining large charge coefficients. The model provides a completely new methodology for the interpretation of piezoelectric and electrostrictive property data and suggests methods for rapid screening for high activity in candidate piezoelectric materials, both experimentally and by novel interrogation of ab initio calculations.« less

Environmental and genetic effects on weight and visual score traits at postweaning in Suffolk sheep.

PubMed

Nascimento, Bárbara Mazetti; Somavilla, Adriana Luiza; Dias, Laila Talarico; Teixeira, Rodrigo de Almeida

2014-10-01

This study aimed to investigate the following environmental effects in Suffolk lambing: contemporary groups, type of birth, and age of animal and age of dam at lambing on conformation (C), precocity (P), musculature (M), and body weight at postweaning (W), and the heritability coefficients and genetic correlations among these traits. Contemporary groups, type of birth, and age of animal and age of dam at lambing were significant for W. For C, all the effects studied were significant, except linear and quadratic effects of age of the animal. For P, all effects studied were significant, except the quadratic effect of age of the animal. For M, the effects of contemporary group, type of birth, and the linear effect of the age of the animal were significant. Heritability estimates were 0.07 ± 0.03, 0.14 ± 0.03, 0.09 ± 0.03, and 0.11 ± 0.03 for C, P, M, and W, respectively, indicating a positive low response for direct selection. Estimates of genetic correlations among the visual scores (C, P, and M) and W were moderate to highly favorable and positive, ranging from 0.48 to 0.90. These results indicate that selection for visual scores will increase body weight.

Income Inequality and Happiness: An Inverted U-Shaped Curve.

PubMed

Yu, Zonghuo; Wang, Fei

2017-01-01

Numerous studies agree that income inequality, rather than absolute income, is an important predictor of happiness. However, its specific role has been controversial. We argue that income inequality and happiness should exhibit an inverted U-shaped relationship due to the dynamic competing process between two effects: when income inequality is relatively low, the signal effect will be the dominating factor, in which individuals feel happy because they consider income inequality as a signal of social mobility and expect upward mobility; however, if income inequality level increases beyond a critical point, the jealousy effect will become the dominating factor, in which individuals tend to be unhappy because they are disillusioned about the prospect of upward mobility and jealous of their wealthier peers. This hypothesis is tested in a longitudinal dataset on the United States and a cross-national dataset on several European countries. In both datasets, the Gini coefficient (a common index of a society's income inequality) and its quadratic term were significant predictors of personal happiness. Further examinations of the quadratic relationships showed that the signal effect was only presented in the European data, while the jealousy effect was presented in both datasets. These findings shed new light on our understanding of the relationship between income inequality and personal happiness.

Income Inequality and Happiness: An Inverted U-Shaped Curve

PubMed Central

Yu, Zonghuo; Wang, Fei

2017-01-01

Numerous studies agree that income inequality, rather than absolute income, is an important predictor of happiness. However, its specific role has been controversial. We argue that income inequality and happiness should exhibit an inverted U-shaped relationship due to the dynamic competing process between two effects: when income inequality is relatively low, the signal effect will be the dominating factor, in which individuals feel happy because they consider income inequality as a signal of social mobility and expect upward mobility; however, if income inequality level increases beyond a critical point, the jealousy effect will become the dominating factor, in which individuals tend to be unhappy because they are disillusioned about the prospect of upward mobility and jealous of their wealthier peers. This hypothesis is tested in a longitudinal dataset on the United States and a cross-national dataset on several European countries. In both datasets, the Gini coefficient (a common index of a society’s income inequality) and its quadratic term were significant predictors of personal happiness. Further examinations of the quadratic relationships showed that the signal effect was only presented in the European data, while the jealousy effect was presented in both datasets. These findings shed new light on our understanding of the relationship between income inequality and personal happiness. PMID:29225588

The sea state bias in altimeter estimates of sea level from collinear analysis of TOPEX data

NASA Technical Reports Server (NTRS)

Chelton, Dudley B.

1994-01-01

The wind speed and significant wave height (H(sub 1/3)) dependencies of the sea state bias in altimeter estimates of sea level, expressed in the form (Delta)h(sub SSB) = bH(sub 1/3), are examined from least squares analysis of 21 cycles of collinear TOPEX data. The bias coefficient b is found to increase in magnitude with increasing wind speed up to about 12 m/s and decrease monotonically in magnitude with increasing H(sub 1/3). A parameterization of b as a quadratic function of wind speed only, as in the formation used to produce the TOPEX geophysical data records (GDRs), is significantly better than a parameterization purely in terms of H(sub 1/3). However, a four-parameter combined wind speed and wave height formulation for b (quadratic in wind speed plus linear in H(sub 1/3)) significantly improves the accuracy of the sea state bias correction. The GDR formulation in terms of wind speed only should therefore be expanded to account for a wave height dependence of b. An attempt to quantify the accuracy of the sea state bias correction (Delta)h(sub SSB) concludes that the uncertainty is a disconcertingly large 1% of H(sub 1/3).

Development of a nearshore oscillating surge wave energy converter with variable geometry

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

Tom, N. M.; Lawson, M. J.; Yu, Y. H.

This paper presents an analysis of a novel wave energy converter concept that combines an oscillating surge wave energy converter (OSWEC) with control surfaces. The control surfaces allow for a variable device geometry that enables the hydrodynamic properties to be adapted with respect to structural loading, absorption range and power-take-off capability. The device geometry is adjusted on a sea state-to-sea state time scale and combined with wave-to-wave manipulation of the power take-off (PTO) to provide greater control over the capture efficiency, capacity factor, and design loads. This work begins with a sensitivity study of the hydrodynamic coefficients with respect tomore » device width, support structure thickness, and geometry. A linear frequency domain analysis is used to evaluate device performance in terms of absorbed power, foundation loads, and PTO torque. Previous OSWEC studies included nonlinear hydrodynamics, in response a nonlinear model that includes a quadratic viscous damping torque that was linearized via the Lorentz linearization. Inclusion of the quadratic viscous torque led to construction of an optimization problem that incorporated motion and PTO constraints. Results from this study found that, when transitioning from moderate-to-large sea states the novel OSWEC was capable of reducing structural loads while providing a near constant power output.« less

Modeling the pressure-strain correlation of turbulence: An invariant dynamical systems approach

NASA Technical Reports Server (NTRS)

Speziale, Charles G.; Sarkar, Sutanu; Gatski, Thomas B.

1990-01-01

The modeling of the pressure-strain correlation of turbulence is examined from a basic theoretical standpoint with a view toward developing improved second-order closure models. Invariance considerations along with elementary dynamical systems theory are used in the analysis of the standard hierarchy of closure models. In these commonly used models, the pressure-strain correlation is assumed to be a linear function of the mean velocity gradients with coefficients that depend algebraically on the anisotropy tensor. It is proven that for plane homogeneous turbulent flows the equilibrium structure of this hierarchy of models is encapsulated by a relatively simple model which is only quadratically nonlinear in the anisotropy tensor. This new quadratic model - the SSG model - is shown to outperform the Launder, Reece, and Rodi model (as well as more recent models that have a considerably more complex nonlinear structure) in a variety of homogeneous turbulent flows. Some deficiencies still remain for the description of rotating turbulent shear flows that are intrinsic to this general hierarchy of models and, hence, cannot be overcome by the mere introduction of more complex nonlinearities. It is thus argued that the recent trend of adding substantially more complex nonlinear terms containing the anisotropy tensor may be of questionable value in the modeling of the pressure-strain correlation. Possible alternative approaches are discussed briefly.

Modelling the pressure-strain correlation of turbulence - An invariant dynamical systems approach

NASA Technical Reports Server (NTRS)

Speziale, Charles G.; Sarkar, Sutanu; Gatski, Thomas B.

1991-01-01

The modeling of the pressure-strain correlation of turbulence is examined from a basic theoretical standpoint with a view toward developing improved second-order closure models. Invariance considerations along with elementary dynamical systems theory are used in the analysis of the standard hierarchy of closure models. In these commonly used models, the pressure-strain correlation is assumed to be a linear function of the mean velocity gradients with coefficients that depend algebraically on the anisotropy tensor. It is proven that for plane homogeneous turbulent flows the equilibrium structure of this hierarchy of models is encapsulated by a relatively simple model which is only quadratically nonlinear in the anisotropy tensor. This new quadratic model - the SSG model - is shown to outperform the Launder, Reece, and Rodi model (as well as more recent models that have a considerably more complex nonlinear structure) in a variety of homogeneous turbulent flows. Some deficiencies still remain for the description of rotating turbulent shear flows that are intrinsic to this general hierarchy of models and, hence, cannot be overcome by the mere introduction of more complex nonlinearities. It is thus argued that the recent trend of adding substantially more complex nonlinear terms containing the anisotropy tensor may be of questionable value in the modeling of the pressure-strain correlation. Possible alternative approaches are discussed briefly.

The kinematic advantage of electric cars

NASA Astrophysics Data System (ADS)

Meyn, Jan-Peter

2015-11-01

Acceleration of a common car with with a turbocharged diesel engine is compared to the same type with an electric motor in terms of kinematics. Starting from a state of rest, the electric car reaches a distant spot earlier than the diesel car, even though the latter has a better specification for engine power and average acceleration from 0 to 100 km h-1. A three phase model of acceleration as a function of time fits the data of the electric car accurately. The first phase is a quadratic growth of acceleration in time. It is shown that the tenfold higher coefficient for the first phase accounts for most of the kinematic advantage of the electric car.

Nanostructured Anodic Multilayer Dielectric Stacked Metal-Insulator-Metal Capacitors.

PubMed

Karthik, R; Kannadassan, D; Baghini, Maryam Shojaei; Mallick, P S

2015-12-01

This paper presents the fabrication of Al2O3/TiO2/Al2O3 metal-insulator-metal (MIM) capacitor using anodization technique. High capacitance density of > 3.5 fF/μm2, low quadratic voltage coefficient of capacitance of < 115 ppm/V2 and a low leakage current density of 4.457 x 10(-11) A/cm2 at 3 V are achieved which are suitable for analog and mixed signal applications. We found that the anodization voltage played a major role in electrical and structural properties of the thin film. This work suggests that the anodization method can offer crystalline multilayer dielectric stack required for high performance MIM capacitor.

Analytic regularization of uniform cubic B-spline deformation fields.

PubMed

Shackleford, James A; Yang, Qi; Lourenço, Ana M; Shusharina, Nadya; Kandasamy, Nagarajan; Sharp, Gregory C

2012-01-01

Image registration is inherently ill-posed, and lacks a unique solution. In the context of medical applications, it is desirable to avoid solutions that describe physically unsound deformations within the patient anatomy. Among the accepted methods of regularizing non-rigid image registration to provide solutions applicable to medical practice is the penalty of thin-plate bending energy. In this paper, we develop an exact, analytic method for computing the bending energy of a three-dimensional B-spline deformation field as a quadratic matrix operation on the spline coefficient values. Results presented on ten thoracic case studies indicate the analytic solution is between 61-1371x faster than a numerical central differencing solution.

Geometry creation for MCNP by Sabrina and XSM

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

Van Riper, K.A.

The Monte Carlo N-Particle transport code MCNP is based on a surface description of 3-dimensional geometry. Cells are defined in terms of boolean operations on signed quadratic surfaces. MCNP geometry is entered as a card image file containing coefficients of the surface equations and a list of surfaces and operators describing cells. Several programs are available to assist in creation of the geometry specification, among them Sabrina and the new ``Smart Editor`` code XSM. We briefly describe geometry creation in Sabrina and then discuss XSM in detail. XSM is under development; our discussion is based on the state of XSMmore » as of January 1, 1994.« less

Ride comfort control in large flexible aircraft. M.S. Thesis

NASA Technical Reports Server (NTRS)

Warren, M. E.

1971-01-01

The problem of ameliorating the discomfort of passengers on a large air transport subject to flight disturbances is examined. The longitudinal dynamics of the aircraft, including effects of body flexing, are developed in terms of linear, constant coefficient differential equations in state variables. A cost functional, penalizing the rigid body displacements and flexure accelerations over the surface of the aircraft is formulated as a quadratic form. The resulting control problem, to minimize the cost subject to the state equation constraints, is of a class whose solutions are well known. The feedback gains for the optimal controller are calculated digitally, and the resulting autopilot is simulated on an analog computer and its performance evaluated.

A denoising algorithm for CT image using low-rank sparse coding

NASA Astrophysics Data System (ADS)

Lei, Yang; Xu, Dong; Zhou, Zhengyang; Wang, Tonghe; Dong, Xue; Liu, Tian; Dhabaan, Anees; Curran, Walter J.; Yang, Xiaofeng

2018-03-01

We propose a denoising method of CT image based on low-rank sparse coding. The proposed method constructs an adaptive dictionary of image patches and estimates the sparse coding regularization parameters using the Bayesian interpretation. A low-rank approximation approach is used to simultaneously construct the dictionary and achieve sparse representation through clustering similar image patches. A variable-splitting scheme and a quadratic optimization are used to reconstruct CT image based on achieved sparse coefficients. We tested this denoising technology using phantom, brain and abdominal CT images. The experimental results showed that the proposed method delivers state-of-art denoising performance, both in terms of objective criteria and visual quality.

[Study on optimization of formulation of Danggui Liuhuang effervescent granules].

PubMed

Zheng, Ping; Meng, Li-Juan; Sun, Guo-Ping; Wang, Wen-Zhong

2011-03-01

To optimize the formulation of Danggui Liuhuang effervescent granules. By means of quadratic regression rotation-orthogonal combination design, the effect of the proper proportion between citric acid and sodium bicarbonate, as well as the proper quantity of polyethylene glycol 6000 and sodium cyclamate on the dissolubility and pH of effervescent granules was studied. The best formulation was as follows: citric acid: sodium bicarbonate = 0.75: 1, the percentage of polyethylene glycol 6000 and cyclamate was 3.25% and 0.89%, respectively. The dissolubility and pH of the effervescent granules are better and the taste is satisfactory.

Determining Sample Size for Accurate Estimation of the Squared Multiple Correlation Coefficient.

ERIC Educational Resources Information Center

Algina, James; Olejnik, Stephen

2000-01-01

Discusses determining sample size for estimation of the squared multiple correlation coefficient and presents regression equations that permit determination of the sample size for estimating this parameter for up to 20 predictor variables. (SLD)

Estimating population size with correlated sampling unit estimates

Treesearch

David C. Bowden; Gary C. White; Alan B. Franklin; Joseph L. Ganey

2003-01-01

Finite population sampling theory is useful in estimating total population size (abundance) from abundance estimates of each sampled unit (quadrat). We develop estimators that allow correlated quadrat abundance estimates, even for quadrats in different sampling strata. Correlated quadrat abundance estimates based on mark–recapture or distance sampling methods occur...

Quadratic soliton self-reflection at a quadratically nonlinear interface

NASA Astrophysics Data System (ADS)

Jankovic, Ladislav; Kim, Hongki; Stegeman, George; Carrasco, Silvia; Torner, Lluis; Katz, Mordechai

2003-11-01

The reflection of bulk quadratic solutions incident onto a quadratically nonlinear interface in periodically poled potassium titanyl phosphate was observed. The interface consisted of the boundary between two quasi-phase-matched regions displaced from each other by a half-period. At high intensities and small angles of incidence the soliton is reflected.

Self-Replicating Quadratics

ERIC Educational Resources Information Center

Withers, Christopher S.; Nadarajah, Saralees

2012-01-01

We show that there are exactly four quadratic polynomials, Q(x) = x [superscript 2] + ax + b, such that (x[superscript 2] + ax + b) (x[superscript 2] - ax + b) = (x[superscript 4] + ax[superscript 2] + b). For n = 1, 2, ..., these quadratic polynomials can be written as the product of N = 2[superscript n] quadratic polynomials in x[superscript…

Facial convective heat exchange coefficients in cold and windy environments estimated from human experiments

NASA Astrophysics Data System (ADS)

Ben Shabat, Yael; Shitzer, Avraham

2012-07-01

Facial heat exchange convection coefficients were estimated from experimental data in cold and windy ambient conditions applicable to wind chill calculations. Measured facial temperature datasets, that were made available to this study, originated from 3 separate studies involving 18 male and 6 female subjects. Most of these data were for a -10°C ambient environment and wind speeds in the range of 0.2 to 6 m s-1. Additional single experiments were for -5°C, 0°C and 10°C environments and wind speeds in the same range. Convection coefficients were estimated for all these conditions by means of a numerical facial heat exchange model, applying properties of biological tissues and a typical facial diameter of 0.18 m. Estimation was performed by adjusting the guessed convection coefficients in the computed facial temperatures, while comparing them to measured data, to obtain a satisfactory fit ( r 2 > 0.98, in most cases). In one of the studies, heat flux meters were additionally used. Convection coefficients derived from these meters closely approached the estimated values for only the male subjects. They differed significantly, by about 50%, when compared to the estimated female subjects' data. Regression analysis was performed for just the -10°C ambient temperature, and the range of experimental wind speeds, due to the limited availability of data for other ambient temperatures. The regressed equation was assumed in the form of the equation underlying the "new" wind chill chart. Regressed convection coefficients, which closely duplicated the measured data, were consistently higher than those calculated by this equation, except for one single case. The estimated and currently used convection coefficients are shown to diverge exponentially from each other, as wind speed increases. This finding casts considerable doubts on the validity of the convection coefficients that are used in the computation of the "new" wind chill chart and their applicability to humans in cold and windy environments.

Facial convective heat exchange coefficients in cold and windy environments estimated from human experiments.

PubMed

Ben Shabat, Yael; Shitzer, Avraham

2012-07-01

Facial heat exchange convection coefficients were estimated from experimental data in cold and windy ambient conditions applicable to wind chill calculations. Measured facial temperature datasets, that were made available to this study, originated from 3 separate studies involving 18 male and 6 female subjects. Most of these data were for a -10°C ambient environment and wind speeds in the range of 0.2 to 6 m s(-1). Additional single experiments were for -5°C, 0°C and 10°C environments and wind speeds in the same range. Convection coefficients were estimated for all these conditions by means of a numerical facial heat exchange model, applying properties of biological tissues and a typical facial diameter of 0.18 m. Estimation was performed by adjusting the guessed convection coefficients in the computed facial temperatures, while comparing them to measured data, to obtain a satisfactory fit (r(2) > 0.98, in most cases). In one of the studies, heat flux meters were additionally used. Convection coefficients derived from these meters closely approached the estimated values for only the male subjects. They differed significantly, by about 50%, when compared to the estimated female subjects' data. Regression analysis was performed for just the -10°C ambient temperature, and the range of experimental wind speeds, due to the limited availability of data for other ambient temperatures. The regressed equation was assumed in the form of the equation underlying the "new" wind chill chart. Regressed convection coefficients, which closely duplicated the measured data, were consistently higher than those calculated by this equation, except for one single case. The estimated and currently used convection coefficients are shown to diverge exponentially from each other, as wind speed increases. This finding casts considerable doubts on the validity of the convection coefficients that are used in the computation of the "new" wind chill chart and their applicability to humans in cold and windy environments.

Comparison of regression coefficient and GIS-based methodologies for regional estimates of forest soil carbon stocks.

PubMed

Campbell, J Elliott; Moen, Jeremie C; Ney, Richard A; Schnoor, Jerald L

2008-03-01

Estimates of forest soil organic carbon (SOC) have applications in carbon science, soil quality studies, carbon sequestration technologies, and carbon trading. Forest SOC has been modeled using a regression coefficient methodology that applies mean SOC densities (mass/area) to broad forest regions. A higher resolution model is based on an approach that employs a geographic information system (GIS) with soil databases and satellite-derived landcover images. Despite this advancement, the regression approach remains the basis of current state and federal level greenhouse gas inventories. Both approaches are analyzed in detail for Wisconsin forest soils from 1983 to 2001, applying rigorous error-fixing algorithms to soil databases. Resulting SOC stock estimates are 20% larger when determined using the GIS method rather than the regression approach. Average annual rates of increase in SOC stocks are 3.6 and 1.0 million metric tons of carbon per year for the GIS and regression approaches respectively.

Radon-222 concentrations in ground water and soil gas on Indian reservations in Wisconsin

USGS Publications Warehouse

DeWild, John F.; Krohelski, James T.

1995-01-01

For sites with wells finished in the sand and gravel aquifer, the coefficient of determination (R2) of the regression of concentration of radon-222 in ground water as a function of well depth is 0.003 and the significance level is 0.32, which indicates that there is not a statistically significant relation between radon-222 concentrations in ground water and well depth. The coefficient of determination of the regression of radon-222 in ground water and soil gas is 0.19 and the root mean square error of the regression line is 271 picocuries per liter. Even though the significance level (0.036) indicates a statistical relation, the root mean square error of the regression is so large that the regression equation would not give reliable predictions. Because of an inadequate number of samples, similar statistical analyses could not be performed for sites with wells finished in the crystalline and sedimentary bedrock aquifers.

Modeling Group Differences in OLS and Orthogonal Regression: Implications for Differential Validity Studies

ERIC Educational Resources Information Center

Kane, Michael T.; Mroch, Andrew A.

2010-01-01

In evaluating the relationship between two measures across different groups (i.e., in evaluating "differential validity") it is necessary to examine differences in correlation coefficients and in regression lines. Ordinary least squares (OLS) regression is the standard method for fitting lines to data, but its criterion for optimal fit…

Incremental Net Effects in Multiple Regression

ERIC Educational Resources Information Center

Lipovetsky, Stan; Conklin, Michael

2005-01-01

A regular problem in regression analysis is estimating the comparative importance of the predictors in the model. This work considers the 'net effects', or shares of the predictors in the coefficient of the multiple determination, which is a widely used characteristic of the quality of a regression model. Estimation of the net effects can be a…

Simple and multiple linear regression: sample size considerations.

PubMed

Hanley, James A

2016-11-01

The suggested "two subjects per variable" (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression. This article distinguishes two of the major uses of regression models that imply very different sample size considerations, neither served well by the 2SPV rule. The first is etiological research, which contrasts mean Y levels at differing "exposure" (X) values and thus tends to focus on a single regression coefficient, possibly adjusted for confounders. The second research genre guides clinical practice. It addresses Y levels for individuals with different covariate patterns or "profiles." It focuses on the profile-specific (mean) Y levels themselves, estimating them via linear compounds of regression coefficients and covariates. By drawing on long-established closed-form variance formulae that lie beneath the standard errors in multiple regression, and by rearranging them for heuristic purposes, one arrives at quite intuitive sample size considerations for both research genres. Copyright © 2016 Elsevier Inc. All rights reserved.

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

USGS Publications Warehouse

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-01-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

NASA Astrophysics Data System (ADS)

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-12-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

Multi-threshold de-noising of electrical imaging logging data based on the wavelet packet transform

NASA Astrophysics Data System (ADS)

Xie, Fang; Xiao, Chengwen; Liu, Ruilin; Zhang, Lili

2017-08-01

A key problem of effectiveness evaluation for fractured-vuggy carbonatite reservoir is how to accurately extract fracture and vug information from electrical imaging logging data. Drill bits quaked during drilling and resulted in rugged surfaces of borehole walls and thus conductivity fluctuations in electrical imaging logging data. The occurrence of the conductivity fluctuations (formation background noise) directly affects the fracture/vug information extraction and reservoir effectiveness evaluation. We present a multi-threshold de-noising method based on wavelet packet transform to eliminate the influence of rugged borehole walls. The noise is present as fluctuations in button-electrode conductivity curves and as pockmarked responses in electrical imaging logging static images. The noise has responses in various scales and frequency ranges and has low conductivity compared with fractures or vugs. Our de-noising method is to decompose the data into coefficients with wavelet packet transform on a quadratic spline basis, then shrink high-frequency wavelet packet coefficients in different resolutions with minimax threshold and hard-threshold function, and finally reconstruct the thresholded coefficients. We use electrical imaging logging data collected from fractured-vuggy Ordovician carbonatite reservoir in Tarim Basin to verify the validity of the multi-threshold de-noising method. Segmentation results and extracted parameters are shown as well to prove the effectiveness of the de-noising procedure.

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

Kuchinskii, E. Z., E-mail: kuchinsk@iep.uran.ru; Kuleeva, N. A.; Sadovskii, M. V., E-mail: sadovski@iep.uran.ru

We derive a Ginzburg–Landau (GL) expansion in the disordered attractive Hubbard model within the combined Nozieres–Schmitt-Rink and DMFT+Σ approximation. Restricting ourselves to the homogeneous expansion, we analyze the disorder dependence of GL expansion coefficients for a wide range of attractive potentials U, from the weak BCS coupling region to the strong-coupling limit, where superconductivity is described by Bose–Einstein condensation (BEC) of preformed Cooper pairs. We show that for the a semielliptic “bare” density of states of the conduction band, the disorder influence on the GL coefficients A and B before quadratic and quartic terms of the order parameter, as wellmore » as on the specific heat discontinuity at the superconducting transition, is of a universal nature at any strength of the attractive interaction and is related only to the general widening of the conduction band by disorder. In general, disorder growth increases the values of the coefficients A and B, leading either to a suppression of the specific heat discontinuity (in the weak-coupling limit), or to its significant growth (in the strong-coupling region). However, this behavior actually confirms the validity of the generalized Anderson theorem, because the disorder dependence of the superconducting transition temperature T{sub c}, is also controlled only by disorder widening of the conduction band (density of states).« less

Fishing in the Amazonian forest: a gendered social network puzzle

PubMed Central

Díaz-Reviriego, I.; Fernández-Llamazares, Á.; Howard, P.L; Molina, JL; Reyes-García, V

2016-01-01

We employ social network analysis (SNA) to describe the structure of subsistence fishing social networks and to explore the relation between fishers’ emic perceptions of fishing expertise and their position in networks. Participant observation and quantitative methods were employed among the Tsimane’ Amerindians of the Bolivian Amazonia. A multiple regression quadratic assignment procedure was used to explore the extent to which gender, kinship, and age homophilies influence the formation of fishing networks. Logistic regressions were performed to determine the association between the fishers’ expertise, their socio-demographic identities, and network centrality. We found that fishing networks are gendered and that there is a positive association between fishers’ expertise and centrality in networks, an association that is more striking for women than for men. We propose that a social network perspective broadens understanding of the relations that shape the intracultural distribution of fishing expertise as well as natural resource access and use. PMID:28479670

Fishing in the Amazonian forest: a gendered social network puzzle.

PubMed

Díaz-Reviriego, I; Fernández-Llamazares, Á; Howard, P L; Molina, J L; Reyes-García, V

2017-01-01

We employ social network analysis (SNA) to describe the structure of subsistence fishing social networks and to explore the relation between fishers' emic perceptions of fishing expertise and their position in networks. Participant observation and quantitative methods were employed among the Tsimane' Amerindians of the Bolivian Amazonia. A multiple regression quadratic assignment procedure was used to explore the extent to which gender, kinship, and age homophilies influence the formation of fishing networks. Logistic regressions were performed to determine the association between the fishers' expertise, their socio-demographic identities, and network centrality. We found that fishing networks are gendered and that there is a positive association between fishers' expertise and centrality in networks, an association that is more striking for women than for men. We propose that a social network perspective broadens understanding of the relations that shape the intracultural distribution of fishing expertise as well as natural resource access and use.

Orthogonality preserving infinite dimensional quadratic stochastic operators

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

Akın, Hasan; Mukhamedov, Farrukh

In the present paper, we consider a notion of orthogonal preserving nonlinear operators. We introduce π-Volterra quadratic operators finite and infinite dimensional settings. It is proved that any orthogonal preserving quadratic operator on finite dimensional simplex is π-Volterra quadratic operator. In infinite dimensional setting, we describe all π-Volterra operators in terms orthogonal preserving operators.

Effects of acceleration in the Gz axis on human cardiopulmonary responses to exercise.

PubMed

Bonjour, Julien; Bringard, Aurélien; Antonutto, Guglielmo; Capelli, Carlo; Linnarsson, Dag; Pendergast, David R; Ferretti, Guido

2011-12-01

The aim of this paper was to develop a model from experimental data allowing a prediction of the cardiopulmonary responses to steady-state submaximal exercise in varying gravitational environments, with acceleration in the G(z) axis (a (g)) ranging from 0 to 3 g. To this aim, we combined data from three different experiments, carried out at Buffalo, at Stockholm and inside the Mir Station. Oxygen consumption, as expected, increased linearly with a (g). In contrast, heart rate increased non-linearly with a (g), whereas stroke volume decreased non-linearly: both were described by quadratic functions. Thus, the relationship between cardiac output and a (g) was described by a fourth power regression equation. Mean arterial pressure increased with a (g) non linearly, a relation that we interpolated again with a quadratic function. Thus, total peripheral resistance varied linearly with a (g). These data led to predict that maximal oxygen consumption would decrease drastically as a (g) is increased. Maximal oxygen consumption would become equal to resting oxygen consumption when a (g) is around 4.5 g, thus indicating the practical impossibility for humans to stay and work on the biggest Planets of the Solar System.

Physiological responses to daily light exposure

NASA Astrophysics Data System (ADS)

Yang, Yefeng; Yu, Yonghua; Yang, Bo; Zhou, Hong; Pan, Jinming

2016-04-01

Long daylength artificial light exposure associates with disorders, and a potential physiological mechanism has been proposed. However, previous studies have examined no more than three artificial light treatments and limited metabolic parameters, which have been insufficient to demonstrate mechanical responses. Here, comprehensive physiological response curves were established and the physiological mechanism was strengthened. Chicks were illuminated for 12, 14, 16, 18, 20, or 22 h periods each day. A quadratic relationship between abdominal adipose weight (AAW) and light period suggested that long-term or short-term light exposure could decrease the amount of AAW. Quantitative relationships between physiological parameters and daily light period were also established in this study. The relationships between triglycerides (TG), cholesterol (TC), glucose (GLU), phosphorus (P) levels and daily light period could be described by quadratic regression models. TG levels, AAW, and BW positively correlated with each other, suggesting long-term light exposure significantly increased AAW by increasing TG thus resulting in greater BW. A positive correlation between blood triiodothyronine (T3) levels and BW suggested that daily long-term light exposure increased BW by thyroid hormone secretion. Though the molecular pathway remains unknown, these results suggest a comprehensive physiological mechanism through which light exposure affects growth.

An empirical study of statistical properties of variance partition coefficients for multi-level logistic regression models

USGS Publications Warehouse

Li, Ji; Gray, B.R.; Bates, D.M.

2008-01-01

Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.

Interquantile Shrinkage in Regression Models

PubMed Central

Jiang, Liewen; Wang, Huixia Judy; Bondell, Howard D.

2012-01-01

Conventional analysis using quantile regression typically focuses on fitting the regression model at different quantiles separately. However, in situations where the quantile coefficients share some common feature, joint modeling of multiple quantiles to accommodate the commonality often leads to more efficient estimation. One example of common features is that a predictor may have a constant effect over one region of quantile levels but varying effects in other regions. To automatically perform estimation and detection of the interquantile commonality, we develop two penalization methods. When the quantile slope coefficients indeed do not change across quantile levels, the proposed methods will shrink the slopes towards constant and thus improve the estimation efficiency. We establish the oracle properties of the two proposed penalization methods. Through numerical investigations, we demonstrate that the proposed methods lead to estimations with competitive or higher efficiency than the standard quantile regression estimation in finite samples. Supplemental materials for the article are available online. PMID:24363546

Contribution of Monomeric Anthocyanins to the Color of Young Red Wine: Statistical and Experimental Approaches.

PubMed

Han, Fu Liang; Li, Zheng; Xu, Yan

2015-12-01

Monomeric anthocyanin contributions to young red wine color were investigated using partial least square regression (PLSR) and aqueous alcohol solutions in this study. Results showed that the correlation between the anthocyanin concentration and the solution color fitted in a quadratic regression rather than linear or cubic regression. Malvidin-3-O-glucoside was estimated to show the highest contribution to young red wine color according to its concentration in wine, whereas peonidin-3-O-glucoside in its concentration contributed the least. The PLSR suggested that delphinidin-3-O-glucoside and peonidin-3-O-glucoside under the same concentration resulted in a stronger color of young red wine compared with malvidin-3-O-glucoside. These estimates were further confirmed by their color in aqueous alcohol solutions. These results suggested that delphinidin-3-O-glucoside and peonidin-3-O-glucoside were primary anthocyanins to enhance young red wine color by increasing their concentrations. This study could provide an alternative approach to improve young red wine color by adjusting anthocyanin composition and concentration. © 2015 Institute of Food Technologists®

Relationship between chemical composition of native forage and nutrient digestibility by Tibetan sheep on the Qinghai-Tibetan Plateau.

PubMed

Yang, Chuntao; Gao, Peng; Hou, Fujiang; Yan, Tianhai; Chang, Shenghua; Chen, Xianjiang; Wang, Zhaofeng

2018-04-02

To better utilize native pasture at the high altitude region, three-consecutive-year feeding experiments and a total of seven metabolism trials were conducted to evaluate the impact of three forage stages of maturity on the chemical composition, nutrient digestibility, and energy metabolism of native forage in Tibetan sheep on the Qinghai-Tibetan Plateau (QTP). Forages were harvested from June to July, August to October, and November to December of 2011 to 2013, corresponding to the vegetative, bloom, and senescent stages of the annual forages. Twenty male Tibetan sheep were selected for each study and fed native forage ad libitum. The digestibility of DM, OM, CP, NDF, ADF, DE, DE/GE, and ME/GE were greatest (P < 0.01) from the vegetative stage, intermediate (P < 0.01) from the bloom stage, and least (P < 0.01) from the senescent stage. Nutrient digestibility and energy parameters correlated positively (linear, 0.422 to 0.778; quadratic, 0.568 to 0.815; P < 0.01) with the CP content of forage but correlated negatively with the content of NDF (linear, 0.343 to 0.689; quadratic, 0.444 to 0.777; P ≤ 0.02), ADF (linear, 0.563 to 0.766; quadratic, 0.582 to 0.770; P < 0.01), and ether extract (EE, linear, 0.283 to 0.574; quadratic, 0.366 to 0.718; P ≤ 0.04) of forage. For each predicted variable, the prediction of DMI expressed as grams per kilogram of BW (g/kg BW·d) yielded a greater R2 value (0.677 to 0.761 vs. 0.616 to 0.711) compared with the equations of DMI expressed as g/kg metabolic BW by step-wise regression. The results suggest that parameters of forage CP, NDF, and ADF content were most closely related to nutrient digestibility. Contrary to previous studies, in this study, ADF content had a greater linear relationship (0.766 vs. 0.563 to 0.732) with OM digestibility than the other parameters of nutrient digestibility. The quadratic relationship between forage CP content and CP digestibility indicates that when forage CP content exceeds the peak point (9.7% DM in the present study), increasing forage CP content could decrease CP digestibility when Tibetan sheep were offered native forage alone on the QTP. Additionally, using the forage CP, EE, NDF, and ADF content to predict DMI (g/kg BW·d) yielded the best fit equation for Tibetan sheep living in the northeast portion of the QTP.

Uncertainty Analysis for a Jet Flap Airfoil

NASA Technical Reports Server (NTRS)

Green, Lawrence L.; Cruz, Josue

2006-01-01

An analysis of variance (ANOVA) study was performed to quantify the potential uncertainties of lift and pitching moment coefficient calculations from a computational fluid dynamics code, relative to an experiment, for a jet flap airfoil configuration. Uncertainties due to a number of factors including grid density, angle of attack and jet flap blowing coefficient were examined. The ANOVA software produced a numerical model of the input coefficient data, as functions of the selected factors, to a user-specified order (linear, 2-factor interference, quadratic, or cubic). Residuals between the model and actual data were also produced at each of the input conditions, and uncertainty confidence intervals (in the form of Least Significant Differences or LSD) for experimental, computational, and combined experimental / computational data sets were computed. The LSD bars indicate the smallest resolvable differences in the functional values (lift or pitching moment coefficient) attributable solely to changes in independent variable, given just the input data points from selected data sets. The software also provided a collection of diagnostics which evaluate the suitability of the input data set for use within the ANOVA process, and which examine the behavior of the resultant data, possibly suggesting transformations which should be applied to the data to reduce the LSD. The results illustrate some of the key features of, and results from, the uncertainty analysis studies, including the use of both numerical (continuous) and categorical (discrete) factors, the effects of the number and range of the input data points, and the effects of the number of factors considered simultaneously.

Remote sensing of PM2.5 from ground-based optical measurements

NASA Astrophysics Data System (ADS)

Li, S.; Joseph, E.; Min, Q.

2014-12-01

Remote sensing of particulate matter concentration with aerodynamic diameter smaller than 2.5 um(PM2.5) by using ground-based optical measurements of aerosols is investigated based on 6 years of hourly average measurements of aerosol optical properties, PM2.5, ceilometer backscatter coefficients and meteorological factors from Howard University Beltsville Campus facility (HUBC). The accuracy of quantitative retrieval of PM2.5 using aerosol optical depth (AOD) is limited due to changes in aerosol size distribution and vertical distribution. In this study, ceilometer backscatter coefficients are used to provide vertical information of aerosol. It is found that the PM2.5-AOD ratio can vary largely for different aerosol vertical distributions. The ratio is also sensitive to mode parameters of bimodal lognormal aerosol size distribution when the geometric mean radius for the fine mode is small. Using two Angstrom exponents calculated at three wavelengths of 415, 500, 860nm are found better representing aerosol size distributions than only using one Angstrom exponent. A regression model is proposed to assess the impacts of different factors on the retrieval of PM2.5. Compared to a simple linear regression model, the new model combining AOD and ceilometer backscatter can prominently improve the fitting of PM2.5. The contribution of further introducing Angstrom coefficients is apparent. Using combined measurements of AOD, ceilometer backscatter, Angstrom coefficients and meteorological parameters in the regression model can get a correlation coefficient of 0.79 between fitted and expected PM2.5.

Correcting bias in the rational polynomial coefficients of satellite imagery using thin-plate smoothing splines

NASA Astrophysics Data System (ADS)

Shen, Xiang; Liu, Bin; Li, Qing-Quan

2017-03-01

The Rational Function Model (RFM) has proven to be a viable alternative to the rigorous sensor models used for geo-processing of high-resolution satellite imagery. Because of various errors in the satellite ephemeris and instrument calibration, the Rational Polynomial Coefficients (RPCs) supplied by image vendors are often not sufficiently accurate, and there is therefore a clear need to correct the systematic biases in order to meet the requirements of high-precision topographic mapping. In this paper, we propose a new RPC bias-correction method using the thin-plate spline modeling technique. Benefiting from its excellent performance and high flexibility in data fitting, the thin-plate spline model has the potential to remove complex distortions in vendor-provided RPCs, such as the errors caused by short-period orbital perturbations. The performance of the new method was evaluated by using Ziyuan-3 satellite images and was compared against the recently developed least-squares collocation approach, as well as the classical affine-transformation and quadratic-polynomial based methods. The results show that the accuracies of the thin-plate spline and the least-squares collocation approaches were better than the other two methods, which indicates that strong non-rigid deformations exist in the test data because they cannot be adequately modeled by simple polynomial-based methods. The performance of the thin-plate spline method was close to that of the least-squares collocation approach when only a few Ground Control Points (GCPs) were used, and it improved more rapidly with an increase in the number of redundant observations. In the test scenario using 21 GCPs (some of them located at the four corners of the scene), the correction residuals of the thin-plate spline method were about 36%, 37%, and 19% smaller than those of the affine transformation method, the quadratic polynomial method, and the least-squares collocation algorithm, respectively, which demonstrates that the new method can be more effective at removing systematic biases in vendor-supplied RPCs.

Genetic structured antedependence and random regression models applied to the longitudinal feed conversion ratio in growing Large White pigs.

PubMed

Huynh-Tran, V H; Gilbert, H; David, I

2017-11-01

The objective of the present study was to compare a random regression model, usually used in genetic analyses of longitudinal data, with the structured antedependence (SAD) model to study the longitudinal feed conversion ratio (FCR) in growing Large White pigs and to propose criteria for animal selection when used for genetic evaluation. The study was based on data from 11,790 weekly FCR measures collected on 1,186 Large White male growing pigs. Random regression (RR) using orthogonal polynomial Legendre and SAD models was used to estimate genetic parameters and predict FCR-based EBV for each of the 10 wk of the test. The results demonstrated that the best SAD model (1 order of antedependence of degree 2 and a polynomial of degree 2 for the innovation variance for the genetic and permanent environmental effects, i.e., 12 parameters) provided a better fit for the data than RR with a quadratic function for the genetic and permanent environmental effects (13 parameters), with Bayesian information criteria values of -10,060 and -9,838, respectively. Heritabilities with the SAD model were higher than those of RR over the first 7 wk of the test. Genetic correlations between weeks were higher than 0.68 for short intervals between weeks and decreased to 0.08 for the SAD model and -0.39 for RR for the longest intervals. These differences in genetic parameters showed that, contrary to the RR approach, the SAD model does not suffer from border effect problems and can handle genetic correlations that tend to 0. Summarized breeding values were proposed for each approach as linear combinations of the individual weekly EBV weighted by the coefficients of the first or second eigenvector computed from the genetic covariance matrix of the additive genetic effects. These summarized breeding values isolated EBV trajectories over time, capturing either the average general value or the slope of the trajectory. Finally, applying the SAD model over a reduced period of time suggested that similar selection choices would result from the use of the records from the first 8 wk of the test. To conclude, the SAD model performed well for the genetic evaluation of longitudinal phenotypes.

Quadratic Optimisation with One Quadratic Equality Constraint

DTIC Science & Technology

2010-06-01

This report presents a theoretical framework for minimising a quadratic objective function subject to a quadratic equality constraint. The first part of the report gives a detailed algorithm which computes the global minimiser without calling special nonlinear optimisation solvers. The second part of the report shows how the developed theory can be applied to solve the time of arrival geolocation problem.

Spatially resolved regression analysis of pre-treatment FDG, FLT and Cu-ATSM PET from post-treatment FDG PET: an exploratory study

PubMed Central

Bowen, Stephen R; Chappell, Richard J; Bentzen, Søren M; Deveau, Michael A; Forrest, Lisa J; Jeraj, Robert

2012-01-01

Purpose To quantify associations between pre-radiotherapy and post-radiotherapy PET parameters via spatially resolved regression. Materials and methods Ten canine sinonasal cancer patients underwent PET/CT scans of [18F]FDG (FDGpre), [18F]FLT (FLTpre), and [61Cu]Cu-ATSM (Cu-ATSMpre). Following radiotherapy regimens of 50 Gy in 10 fractions, veterinary patients underwent FDG PET/CT scans at three months (FDGpost). Regression of standardized uptake values in baseline FDGpre, FLTpre and Cu-ATSMpre tumour voxels to those in FDGpost images was performed for linear, log-linear, generalized-linear and mixed-fit linear models. Goodness-of-fit in regression coefficients was assessed by R2. Hypothesis testing of coefficients over the patient population was performed. Results Multivariate linear model fits of FDGpre to FDGpost were significantly positive over the population (FDGpost~0.17 FDGpre, p=0.03), and classified slopes of RECIST non-responders and responders to be different (0.37 vs. 0.07, p=0.01). Generalized-linear model fits related FDGpre to FDGpost by a linear power law (FDGpost~FDGpre0.93, p<0.001). Univariate mixture model fits of FDGpre improved R2 from 0.17 to 0.52. Neither baseline FLT PET nor Cu-ATSM PET uptake contributed statistically significant multivariate regression coefficients. Conclusions Spatially resolved regression analysis indicates that pre-treatment FDG PET uptake is most strongly associated with three-month post-treatment FDG PET uptake in this patient population, though associations are histopathology-dependent. PMID:22682748

Line shape parameters of air-broadened water vapor transitions in the ν 1 and ν 3 spectral region

DOE PAGES

Malathy Devi, V.; Gamache, Robert R.; Vispoel, Bastien; ...

2017-11-26

A Bruker IFS-120HR Fourier transform spectrometer located at the Pacific Northwest National Laboratory (PNNL) in Richland, Washington was used to record a series of spectra of pure H 2O and air-broadened H 2O in the regions of the ν 1 and ν 3 bands (3450–4000 cm -1) at different pressures, temperatures and volume mixing ratios of H 2O in air. Eighteen high-resolution, high signal-to-noise (S/N) ratio absorption spectra were recorded at T = 268, 296 and 353 K using two temperature-controlled absorption cells with path lengths of 9.906(1) and 19.95(1) cm. Furthermore, the resolution of the spectra recorded with themore » 9.906 cm and 19.95 cm absorption cells was 0.006 and 0.008 cm -1, respectively. A multispectrum nonlinear least squares fitting technique was employed to fit all the eighteen spectra simultaneously to retrieve 313 accurate line positions, 315 intensities, 229 Lorentz air-broadened half-width and 213 air-shift coefficients and their temperature dependences (136 for air-broadened width and 128 for air-shift coefficients, respectively). Room temperature self-broadened half-width coefficients for 209 transitions and self-shift coefficients for 106 transitions were also measured. Line mixing coefficients were experimentally determined for isolated sets of 10 transition pairs for H 2O-air and 8 transition pairs for H 2O-H 2O using the off-diagonal relaxation matrix element formalism, and 85 quadratic speed dependence parameters were measured. Modified Complex Robert-Bonamy (MCRB) calculations of self-, and air-broadened (from N 2- and O 2-broadening) half-width and air-shift coefficients, and temperature dependence exponents of air-broadened half-width coefficients are made. Finally, the measurements and calculations are compared with each other and with similar parameters reported in the literature.« less

Line shape parameters of air-broadened water vapor transitions in the ν1 and ν3 spectral region

NASA Astrophysics Data System (ADS)

Malathy Devi, V.; Gamache, Robert R.; Vispoel, Bastien; Renaud, Candice L.; Chris Benner, D.; Smith, Mary Ann H.; Blake, Thomas A.; Sams, Robert L.

2018-06-01

A Bruker IFS-120HR Fourier transform spectrometer located at the Pacific Northwest National Laboratory (PNNL) in Richland, Washington was used to record a series of spectra of pure H2O and air-broadened H2O in the regions of the ν1 and ν3 bands (3450-4000 cm-1) at different pressures, temperatures and volume mixing ratios of H2O in air. Eighteen high-resolution, high signal-to-noise (S/N) ratio absorption spectra were recorded at T = 268, 296 and 353 K using two temperature-controlled absorption cells with path lengths of 9.906(1) and 19.95(1) cm. The resolution of the spectra recorded with the 9.906 cm and 19.95 cm absorption cells was 0.006 and 0.008 cm-1, respectively. A multispectrum nonlinear least squares fitting technique was employed to fit all the eighteen spectra simultaneously to retrieve 313 accurate line positions, 315 intensities, 229 Lorentz air-broadened half-width and 213 air-shift coefficients and their temperature dependences (136 for air-broadened width and 128 for air-shift coefficients, respectively). Room temperature self-broadened half-width coefficients for 209 transitions and self-shift coefficients for 106 transitions were also measured. Line mixing coefficients were experimentally determined for isolated sets of 10 transition pairs for H2O-air and 8 transition pairs for H2O-H2O using the off-diagonal relaxation matrix element formalism, and 85 quadratic speed dependence parameters were measured. Modified Complex Robert-Bonamy (MCRB) calculations of self-, and air-broadened (from N2- and O2-broadening) half-width and air-shift coefficients, and temperature dependence exponents of air-broadened half-width coefficients are made. The measurements and calculations are compared with each other and with similar parameters reported in the literature.

Line shape parameters of air-broadened water vapor transitions in the ν 1 and ν 3 spectral region

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

Malathy Devi, V.; Gamache, Robert R.; Vispoel, Bastien

A Bruker IFS-120HR Fourier transform spectrometer located at the Pacific Northwest National Laboratory (PNNL) in Richland, Washington was used to record a series of spectra of pure H 2O and air-broadened H 2O in the regions of the ν 1 and ν 3 bands (3450–4000 cm -1) at different pressures, temperatures and volume mixing ratios of H 2O in air. Eighteen high-resolution, high signal-to-noise (S/N) ratio absorption spectra were recorded at T = 268, 296 and 353 K using two temperature-controlled absorption cells with path lengths of 9.906(1) and 19.95(1) cm. Furthermore, the resolution of the spectra recorded with themore » 9.906 cm and 19.95 cm absorption cells was 0.006 and 0.008 cm -1, respectively. A multispectrum nonlinear least squares fitting technique was employed to fit all the eighteen spectra simultaneously to retrieve 313 accurate line positions, 315 intensities, 229 Lorentz air-broadened half-width and 213 air-shift coefficients and their temperature dependences (136 for air-broadened width and 128 for air-shift coefficients, respectively). Room temperature self-broadened half-width coefficients for 209 transitions and self-shift coefficients for 106 transitions were also measured. Line mixing coefficients were experimentally determined for isolated sets of 10 transition pairs for H 2O-air and 8 transition pairs for H 2O-H 2O using the off-diagonal relaxation matrix element formalism, and 85 quadratic speed dependence parameters were measured. Modified Complex Robert-Bonamy (MCRB) calculations of self-, and air-broadened (from N 2- and O 2-broadening) half-width and air-shift coefficients, and temperature dependence exponents of air-broadened half-width coefficients are made. Finally, the measurements and calculations are compared with each other and with similar parameters reported in the literature.« less

The curvilinear effects of sexual orientation on young adult substance use.

PubMed

Parnes, Jamie E; Rahm-Knigge, Ryan L; Conner, Bradley T

2017-03-01

Alcohol, tobacco, and marijuana are commonly used by adolescents and linked with harmful health-related outcomes (e.g. injury, dependence). Moreover, heavy episodic (binge) drinking predicts more severe consequences. When examined by sexual orientation, highest rates of substance use have been found among bisexual individuals, with lower use at either end of the spectrum. When examined also by sex, this curvilinear trend is maintained among women but not men. These substance use patterns were identified using group differences (i.e. heterosexual vs. bisexual vs. homosexual). However, evidence suggests that sexual orientation is a continuous, not categorical, variable. This study examined the hypotheses that sexual orientation and commonly used substances (heavy episodic drinking, tobacco, marijuana) would have a quadratic relation among women, but not among men. Six negative binomial regressions tested study hypotheses using data from 7372 participants. Results indicated that sexual orientation had a quadratic relation with heavy episodic drinking, tobacco use, and marijuana use among women, as hypothesized. Additionally, a quadratic relation was found between marijuana use and sexual orientation among men. These findings indicate that women identifying as having mixed sexual orientation are at higher risk than women at either end of the sexual orientation continuum for substance use and related negative outcomes. For men, this is only true for marijuana use and resultant negative consequences. This observed increased use may relate to coping with increased stressors, which has been linked to more problematic use. By better understanding LBG identities and behaviors, clinicians and researchers will be more adept at identifying risk factors and better understanding the nuances across the sexual orientation spectrum. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evolution of deep gray matter volume across the human lifespan.

PubMed

Narvacan, Karl; Treit, Sarah; Camicioli, Richard; Martin, Wayne; Beaulieu, Christian

2017-08-01

Magnetic resonance imaging of subcortical gray matter structures, which mediate behavior, cognition and the pathophysiology of several diseases, is crucial for establishing typical maturation patterns across the human lifespan. This single site study examines T1-weighted MPRAGE images of 3 healthy cohorts: (i) a cross-sectional cohort of 406 subjects aged 5-83 years; (ii) a longitudinal neurodevelopment cohort of 84 subjects scanned twice approximately 4 years apart, aged 5-27 years at first scan; and (iii) a longitudinal aging cohort of 55 subjects scanned twice approximately 3 years apart, aged 46-83 years at first scan. First scans from longitudinal subjects were included in the cross-sectional analysis. Age-dependent changes in thalamus, caudate, putamen, globus pallidus, nucleus accumbens, hippocampus, and amygdala volumes were tested with Poisson, quadratic, and linear models in the cross-sectional cohort, and quadratic and linear models in the longitudinal cohorts. Most deep gray matter structures best fit to Poisson regressions in the cross-sectional cohort and quadratic curves in the young longitudinal cohort, whereas the volume of all structures except the caudate and globus pallidus decreased linearly in the longitudinal aging cohort. Males had larger volumes than females for all subcortical structures, but sex differences in trajectories of change with age were not significant. Within subject analysis showed that 65%-80% of 13-17 year olds underwent a longitudinal decrease in volume between scans (∼4 years apart) for the putamen, globus pallidus, and hippocampus, suggesting unique developmental processes during adolescence. This lifespan study of healthy participants will form a basis for comparison to neurological and psychiatric disorders. Hum Brain Mapp 38:3771-3790, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Bootstrap Methods: A Very Leisurely Look.

ERIC Educational Resources Information Center

Hinkle, Dennis E.; Winstead, Wayland H.

The Bootstrap method, a computer-intensive statistical method of estimation, is illustrated using a simple and efficient Statistical Analysis System (SAS) routine. The utility of the method for generating unknown parameters, including standard errors for simple statistics, regression coefficients, discriminant function coefficients, and factor…

Hidden supersymmetry and quadratic deformations of the space-time conformal superalgebra

NASA Astrophysics Data System (ADS)

Yates, L. A.; Jarvis, P. D.

2018-04-01

We analyze the structure of the family of quadratic superalgebras, introduced in Jarvis et al (2011 J. Phys. A: Math. Theor. 44 235205), for the quadratic deformations of N  =  1 space-time conformal supersymmetry. We characterize in particular the ‘zero-step’ modules for this case. In such modules, the odd generators vanish identically, and the quadratic superalgebra is realized on a single irreducible representation of the even subalgebra (which is a Lie algebra). In the case under study, the quadratic deformations of N  =  1 space-time conformal supersymmetry, it is shown that each massless positive energy unitary irreducible representation (in the standard classification of Mack), forms such a zero-step module, for an appropriate parameter choice amongst the quadratic family (with vanishing central charge). For these massless particle multiplets therefore, quadratic supersymmetry is unbroken, in that the supersymmetry generators annihilate all physical states (including the vacuum state), while at the same time, superpartners do not exist.

Linear state feedback, quadratic weights, and closed loop eigenstructures. M.S. Thesis

NASA Technical Reports Server (NTRS)

Thompson, P. M.

1979-01-01

Results are given on the relationships between closed loop eigenstructures, state feedback gain matrices of the linear state feedback problem, and quadratic weights of the linear quadratic regulator. Equations are derived for the angles of general multivariable root loci and linear quadratic optimal root loci, including angles of departure and approach. The generalized eigenvalue problem is used for the first time to compute angles of approach. Equations are also derived to find the sensitivity of closed loop eigenvalues and the directional derivatives of closed loop eigenvectors (with respect to a scalar multiplying the feedback gain matrix or the quadratic control weight). An equivalence class of quadratic weights that produce the same asymptotic eigenstructure is defined, sufficient conditions to be in it are given, a canonical element is defined, and an algorithm to find it is given. The behavior of the optimal root locus in the nonasymptotic region is shown to be different for quadratic weights with the same asymptotic properties.

Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials.

PubMed

Mota, L F M; Martins, P G M A; Littiere, T O; Abreu, L R A; Silva, M A; Bonafé, C M

2018-04-01

The objective was to estimate (co)variance functions using random regression models (RRM) with Legendre polynomials, B-spline function and multi-trait models aimed at evaluating genetic parameters of growth traits in meat-type quail. A database containing the complete pedigree information of 7000 meat-type quail was utilized. The models included the fixed effects of contemporary group and generation. Direct additive genetic and permanent environmental effects, considered as random, were modeled using B-spline functions considering quadratic and cubic polynomials for each individual segment, and Legendre polynomials for age. Residual variances were grouped in four age classes. Direct additive genetic and permanent environmental effects were modeled using 2 to 4 segments and were modeled by Legendre polynomial with orders of fit ranging from 2 to 4. The model with quadratic B-spline adjustment, using four segments for direct additive genetic and permanent environmental effects, was the most appropriate and parsimonious to describe the covariance structure of the data. The RRM using Legendre polynomials presented an underestimation of the residual variance. Lesser heritability estimates were observed for multi-trait models in comparison with RRM for the evaluated ages. In general, the genetic correlations between measures of BW from hatching to 35 days of age decreased as the range between the evaluated ages increased. Genetic trend for BW was positive and significant along the selection generations. The genetic response to selection for BW in the evaluated ages presented greater values for RRM compared with multi-trait models. In summary, RRM using B-spline functions with four residual variance classes and segments were the best fit for genetic evaluation of growth traits in meat-type quail. In conclusion, RRM should be considered in genetic evaluation of breeding programs.

Importance of physical and hydraulic characteristics to unionid mussels: A retrospective analysis in a reach of large river

USGS Publications Warehouse

Zigler, S.J.; Newton, T.J.; Steuer, J.J.; Bartsch, M.R.; Sauer, J.S.

2008-01-01

Interest in understanding physical and hydraulic factors that might drive distribution and abundance of freshwater mussels has been increasing due to their decline throughout North America. We assessed whether the spatial distribution of unionid mussels could be predicted from physical and hydraulic variables in a reach of the Upper Mississippi River. Classification and regression tree (CART) models were constructed using mussel data compiled from various sources and explanatory variables derived from GIS coverages. Prediction success of CART models for presence-absence of mussels ranged from 71 to 76% across three gears (brail, sled-dredge, and dive-quadrat) and 51% of the deviance in abundance. Models were largely driven by shear stress and substrate stability variables, but interactions with simple physical variables, especially slope, were also important. Geospatial models, which were based on tree model results, predicted few mussels in poorly connected backwater areas (e.g., floodplain lakes) and the navigation channel, whereas main channel border areas with high geomorphic complexity (e.g., river bends, islands, side channel entrances) and small side channels were typically favorable to mussels. Moreover, bootstrap aggregation of discharge-specific regression tree models of dive-quadrat data indicated that variables measured at low discharge were about 25% more predictive (PMSE = 14.8) than variables measured at median discharge (PMSE = 20.4) with high discharge (PMSE = 17.1) variables intermediate. This result suggests that episodic events such as droughts and floods were important in structuring mussel distributions. Although the substantial mussel and ancillary data in our study reach is unusual, our approach to develop exploratory statistical and geospatial models should be useful even when data are more limited. ?? 2007 Springer Science+Business Media B.V.

Determination of Strength Exercise Intensities Based on the Load-Power-Velocity Relationship

PubMed Central

Jandačka, Daniel; Beremlijski, Petr

2011-01-01

The velocity of movement and applied load affect the production of mechanical power output and subsequently the extent of the adaptation stimulus in strength exercises. We do not know of any known function describing the relationship of power and velocity and load in the bench press exercise. The objective of the study is to find a function modeling of the relationship of relative velocity, relative load and mechanical power output for the bench press exercise and to determine the intensity zones of the exercise for specifically focused strength training of soccer players. Fifteen highly trained soccer players at the start of a competition period were studied. The subjects of study performed bench presses with the load of 0, 10, 30, 50, 70 and 90% of the predetermined one repetition maximum with maximum possible speed of movement. The mean measured power and velocity for each load (kg) were used to develop a multiple linear regression function which describes the quadratic relationship between the ratio of power (W) to maximum power (W) and the ratios of the load (kg) to one repetition maximum (kg) and the velocity (m•s−1) to maximal velocity (m•s−1). The quadratic function of two variables that modeled the searched relationship explained 74% of measured values in the acceleration phase and 75% of measured values from the entire extent of the positive power movement in the lift. The optimal load for reaching maximum power output suitable for the dynamics effort strength training was 40% of one repetition maximum, while the optimal mean velocity would be 75% of maximal velocity. Moreover, four zones: maximum power, maximum velocity, velocity-power and strength-power were determined on the basis of the regression function. PMID:23486484

Determination of strength exercise intensities based on the load-power-velocity relationship.

PubMed

Jandačka, Daniel; Beremlijski, Petr

2011-06-01

The velocity of movement and applied load affect the production of mechanical power output and subsequently the extent of the adaptation stimulus in strength exercises. We do not know of any known function describing the relationship of power and velocity and load in the bench press exercise. The objective of the study is to find a function modeling of the relationship of relative velocity, relative load and mechanical power output for the bench press exercise and to determine the intensity zones of the exercise for specifically focused strength training of soccer players. Fifteen highly trained soccer players at the start of a competition period were studied. The subjects of study performed bench presses with the load of 0, 10, 30, 50, 70 and 90% of the predetermined one repetition maximum with maximum possible speed of movement. The mean measured power and velocity for each load (kg) were used to develop a multiple linear regression function which describes the quadratic relationship between the ratio of power (W) to maximum power (W) and the ratios of the load (kg) to one repetition maximum (kg) and the velocity (m•s(-1)) to maximal velocity (m•s(-1)). The quadratic function of two variables that modeled the searched relationship explained 74% of measured values in the acceleration phase and 75% of measured values from the entire extent of the positive power movement in the lift. The optimal load for reaching maximum power output suitable for the dynamics effort strength training was 40% of one repetition maximum, while the optimal mean velocity would be 75% of maximal velocity. Moreover, four zones: maximum power, maximum velocity, velocity-power and strength-power were determined on the basis of the regression function.

Simulation-extrapolation method to address errors in atomic bomb survivor dosimetry on solid cancer and leukaemia mortality risk estimates, 1950-2003.

PubMed

Allodji, Rodrigue S; Schwartz, Boris; Diallo, Ibrahima; Agbovon, Césaire; Laurier, Dominique; de Vathaire, Florent

2015-08-01

Analyses of the Life Span Study (LSS) of Japanese atomic bombing survivors have routinely incorporated corrections for additive classical measurement errors using regression calibration. Recently, several studies reported that the efficiency of the simulation-extrapolation method (SIMEX) is slightly more accurate than the simple regression calibration method (RCAL). In the present paper, the SIMEX and RCAL methods have been used to address errors in atomic bomb survivor dosimetry on solid cancer and leukaemia mortality risk estimates. For instance, it is shown that using the SIMEX method, the ERR/Gy is increased by an amount of about 29 % for all solid cancer deaths using a linear model compared to the RCAL method, and the corrected EAR 10(-4) person-years at 1 Gy (the linear terms) is decreased by about 8 %, while the corrected quadratic term (EAR 10(-4) person-years/Gy(2)) is increased by about 65 % for leukaemia deaths based on a linear-quadratic model. The results with SIMEX method are slightly higher than published values. The observed differences were probably due to the fact that with the RCAL method the dosimetric data were partially corrected, while all doses were considered with the SIMEX method. Therefore, one should be careful when comparing the estimated risks and it may be useful to use several correction techniques in order to obtain a range of corrected estimates, rather than to rely on a single technique. This work will enable to improve the risk estimates derived from LSS data, and help to make more reliable the development of radiation protection standards.

Radiation dose and cataract surgery incidence in atomic bomb survivors, 1986-2005.

PubMed

Neriishi, Kazuo; Nakashima, Eiji; Akahoshi, Masazumi; Hida, Ayumi; Grant, Eric J; Masunari, Naomi; Funamoto, Sachiyo; Minamoto, Atsushi; Fujiwara, Saeko; Shore, Roy E

2012-10-01

To examine the incidence of clinically important cataracts in relation to lens radiation doses between 0 and approximately 3 Gy to address risks at relatively low brief doses. Informed consent was obtained, and human subjects procedures were approved by the ethical committee at the Radiation Effects Research Foundation. Cataract surgery incidence was documented for 6066 atomic bomb survivors during 1986-2005. Sixteen risk factors for cataract, such as smoking, hypertension, and corticosteroid use, were not confounders of the radiation effect on the basis of Cox regression analysis. Radiation dose-response analyses were performed for cataract surgery incidence by using Poisson regression analysis, adjusting for demographic variables and diabetes mellitus, and results were expressed as the excess relative risk (ERR) and the excess absolute risk (EAR) (ie, measures of how much radiation multiplies [ERR] or adds to [EAR] the risk in the unexposed group). Of 6066 atomic bomb survivors, 1028 underwent a first cataract surgery during 1986-2005. The estimated threshold dose was 0.50 Gy (95% confidence interval [CI]: 0.10 Gy, 0.95 Gy) for the ERR model and 0.45 Gy (95% CI: 0.10 Gy, 1.05 Gy) for the EAR model. A linear-quadratic test for upward curvature did not show a significant quadratic effect for either the ERR or EAR model. The linear ERR model for a 70-year-old individual, exposed at age 20 years, showed a 0.32 (95% CI: 0.09, 0.53) [corrected] excess risk at 1 Gy. The ERR was highest for those who were young at exposure. These data indicate a radiation effect for vision-impairing cataracts at doses less than 1 Gy. The evidence suggests that dose standards for protection of the eye from brief radiation exposures should be 0.5 Gy or less. © RSNA, 2012.

HIV health center affiliation networks of black men who have sex with men: disentangling fragmented patterns of HIV prevention service utilization.

PubMed

Schneider, John A; Walsh, Tim; Cornwell, Benjamin; Ostrow, David; Michaels, Stuart; Laumann, Edward O

2012-08-01

In the United States, black men who have sex with men (BMSM) are at highest risk for HIV infection and are at high risk for limited health service utilization. We describe HIV health center (HHC) affiliation network patterns and their potential determinants among urban BMSM. The Men's Assessment of Social and Risk Network instrument was used to elicit HHC utilization, as reported by study respondents recruited through respondent-driven sampling. In 2010, 204 BMSM were systematically recruited from diverse venues in Chicago, IL. A 2-mode data set was constructed that included study participants and 9 diverse HHCs. Associations between individual-level characteristics and HHC utilization were analyzed using Multiple Regression Quadratic Assignment Procedure. Visualization analyses included computation of HHC centrality and faction membership. High utilization of HHCs (45.9%-70.3%) was evident among BMSM, 44.4% who were HIV infected. Multiple Regression Quadratic Assignment Procedure revealed that age, social network size, and HIV status were associated with HHC affiliation patterns (coeff., 0.13-0.27; all P < 0.05). With the exception of one HHC, HHCs offering HIV prevention services to HIV-infected participants occupied peripheral positions within the network of health centers. High-risk HIV-uninfected participants affiliated most with an HHC that offers only treatment services. Subcategories of BMSM in this sample affiliated with HHCs that may not provide appropriate HIV prevention services. Using 2-mode data, public health authorities may be better able to match prevention services to BMSM need; in particular, HIV prevention services for high-risk HIV-uninfected men and HIV "prevention for positives" services for HIV-infected men.

Body mass index and motor coordination: Non-linear relationships in children 6-10 years.

PubMed

Lopes, V P; Malina, R M; Maia, J A R; Rodrigues, L P

2018-05-01

Given the concern for health-related consequences of an elevated body mass index (BMI; obesity), the potential consequences of a low BMI in children are often overlooked. The purpose was to evaluate the relationship between the BMI across its entire spectrum and motor coordination (MC) in children 6-10 years. Height, weight, and MC (Körperkoordinationstest für Kinder, KTK test battery) were measured in 1,912 boys and 1,826 girls of 6-10 years of age. BMI (kg/m 2 ) was calculated. KTK scores for each of the four tests were also converted to a motor quotient (MQ). One-way ANOVA was used to test differences in the BMI, individual test items, and MQ among boys and girls within age groups. Sex-specific quadratic regressions of individual KTK items and the MQ on the BMI were calculated. Girls and boys were also classified into four weight status groups using International Obesity Task Force criteria: thin, normal, overweight, and obese. Differences in specific test items and MQ between weight status groups were evaluated by age group in each sex. Thirty-one percent of the sample was overweight or obese, whereas 5% was thin. On average, normal weight children had the highest MQ in both sexes across the age range with few exceptions. Overweight/obese children had a lower MQ than normal weight and thin children. The quadratic regression lines generally presented an inverted parabolic relationship between the BMI and MC and suggested a decrease in MC with an increase in the BMI. In general, BMI shows a curvilinear, inverted parabolic relationship with MC in children 6-10 years. © 2018 John Wiley & Sons Ltd.

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

Dierauf, Timothy; Kurtz, Sarah; Riley, Evan

This paper provides a recommended method for evaluating the AC capacity of a photovoltaic (PV) generating station. It also presents companion guidance on setting the facilitys capacity guarantee value. This is a principles-based approach that incorporates plant fundamental design parameters such as loss factors, module coefficients, and inverter constraints. This method has been used to prove contract guarantees for over 700 MW of installed projects. The method is transparent, and the results are deterministic. In contrast, current industry practices incorporate statistical regression where the empirical coefficients may only characterize the collected data. Though these methods may work well when extrapolationmore » is not required, there are other situations where the empirical coefficients may not adequately model actual performance.This proposed Fundamentals Approach method provides consistent results even where regression methods start to lose fidelity.« less

Optimization of process parameters for extrusion cooking of low amylose rice flour blended with seeded banana and carambola pomace for development of minerals and fiber rich breakfast cereal.

PubMed

Borah, Anjan; Lata Mahanta, Charu; Kalita, Dipankar

2016-01-01

The low-amylose rice flour, seeded banana (Musa balbisiana, ABB) and carambola (Averrhoa carambola L.) pomace blends were extruded to prepare ready to eat breakfast cereal in a single-screw extruder. Response surface methodology using a central composite design was used to evaluate effect of independent variables, namely blend ratio (80:10:10 - 60:30:10 of low-amylose rice flour, seeded banana and carambola pomace), screw speed (200 - 400 rpm), barrel temperature (90 - 130 (°)C) and feed moisture content (9 - 21 g/100 g, wet basis) on product responses. Quadratic polynomial equations were also obtained by multiple regression analysis. The predicted models were adequate based on lack-of-fit test and coefficient of determination obtained. The feed moisture content had critical effect on all response variables. The compromised optimal conditions obtained by numerical integration for development of extrudates were: screw speed of 350 rpm, barrel temperature of 120 (°)C, feed moisture content of 12 g/100 g and 65:25:10 of blend ratio of feed. In the optimized condition low-amylose rice blend is found to have better physicochemical properties (water absorption index of 481.79 g/100 g; water solubility index of 44.13 g/100 g) and dietary fiber content of 21.35 g/100 g respectively. The developed breakfast cereal showed considerable amount of minerals (Mg and K) and overall acceptability was found to be 7.8.

Three-factor response surface optimization of nano-emulsion formation using a microfluidizer.

PubMed

Sadeghpour Galooyak, Saeed; Dabir, Bahram

2015-05-01

Emulsification of sunflower oil in water by microfluidization was studied. Response surface methodology (RSM) and the central composite design (CCD) were applied to determine the effects of certain process parameters on performance of the apparatus for optimization of nano-emulsion fabrication. Influence of pressure, oil content and number of passes on the disruption of emulsions was studied. Quadratic multiple regression models were chosen for two available responses, namely Sauter mean diameter (SMD) and Polydispersity index (PdI). Analysis of variance (ANOVA) showed a high coefficient of determination (R(2)) value for both responses, confirming adjustment of the models with experimental data. The SMD and the PdI decreased as the pressure of emulsification increased from 408 to 762.3 bar for the oil content of 5 vol% and from 408 to 854.4 bar for the oil content of 13 vol%, and thereafter, increasing the pressure up to 952 bar led to increasing the both responses. The results implied that laminar elongational flow is the alternative disruption mechanism in addition to inertia in turbulence flow, especially at low treatment pressures. Both of responses improved with increase in number of passes from 2 to 4 cycles. The oil content depicted low effect on responses; however, interaction of this parameter with other regressors pointed remarkable impact. Also, the effect of pressure on Kolmogorov micro-scale was studied. The results implied that Kolmogorov equation did not take into account the over-processing and was applicable only for disruption of droplets in the inertial turbulent flow.

A New Test of Linear Hypotheses in OLS Regression under Heteroscedasticity of Unknown Form

ERIC Educational Resources Information Center

Cai, Li; Hayes, Andrew F.

2008-01-01

When the errors in an ordinary least squares (OLS) regression model are heteroscedastic, hypothesis tests involving the regression coefficients can have Type I error rates that are far from the nominal significance level. Asymptotically, this problem can be rectified with the use of a heteroscedasticity-consistent covariance matrix (HCCM)…

[Long-term outcome analysis of subjective and objective parameters after breast reduction in 159 cases: Patients judge differently from plastic surgeons].

PubMed

Osinga, Rik; Babst, Doris; Bodmer, Elvira S; Link, Bjoern C; Fritsche, Elmar; Hug, Urs

2017-12-01

This work assessed both subjective and objective postoperative parameters after breast reduction surgery and compared between patients and plastic surgeons. After an average postoperative observation period of 6.7 ± 2.7 (2 - 13) years, 159 out of 259 patients (61 %) were examined. The mean age at the time of surgery was 37 ± 14 (15 - 74) years. The postoperative anatomy of the breast and other anthropometric parameters were measured in cm with the patient in an upright position. The visual analogue scale (VAS) values for symmetry, size, shape, type of scar and overall satisfaction both from the patient's and from four plastic surgeons' perspectives were assessed and compared. Patients rated the postoperative result significantly better than surgeons. Good subjective ratings by patients for shape, symmetry and sensitivity correlated with high scores for overall assessment. Shape had the strongest influence on overall satisfaction (regression coefficient 0.357; p < 0.001), followed by symmetry (regression coefficient 0.239; p < 0.001) and sensitivity (regression coefficient 0.109; p = 0.040) of the breast. The better the subjective rating for symmetry by the patient, the smaller the measured difference of the jugulum-mamillary distance between left and right (regression coefficient -0.773; p = 0.002) and the smaller the difference in height of the lowest part of the breast between left and right (regression coefficient -0.465; p = 0.035). There was no significant correlation between age, weight, height, BMI, resected weight of the breast, postoperative breast size or type of scar with overall satisfaction. After breast reduction surgery, long-term outcome is rated significantly better by patients than by plastic surgeons. Good subjective ratings by patients for shape, symmetry and sensitivity correlated with high scores for overall assessment. Shape had the strongest influence on overall satisfaction, followed by symmetry and sensitivity of the breast. Postoperative size of the breast, resection weight, type of scar, age or BMI was not of significant influence. Symmetry was the only assessed subjective parameter of this study that could be objectified by postoperative measurements. Georg Thieme Verlag KG Stuttgart · New York.

Belief in complementary and alternative medicine is related to age and paranormal beliefs in adults.

PubMed

Van den Bulck, Jan; Custers, Kathleen

2010-04-01

The use of complementary and alternative medicine (CAM) is widespread, even among people who use conventional medicine. Positive beliefs about CAM are common among physicians and medical students. Little is known about the beliefs regarding CAM among the general public. Among science students, belief in CAM was predicted by belief in the paranormal. In a cross-sectional study, 712 randomly selected adults (>18 years old) responded to the CAM Health Belief Questionnaire (CHBQ) and a paranormal beliefs scale. CAM beliefs were very prevalent in this sample of adult Flemish men and women. Zero-order correlations indicated that belief in CAM was associated with age (r = 0.173 P < 0.001) level of education (r = -0.079 P = 0.039) social desirability (r = -0.119 P = 0.002) and paranormal belief (r = 0.365 P < 0.001). In a multivariate model, two variables predicted CAM beliefs. Support for CAM increased with age (regression coefficient: 0.01; 95% confidence interval (CI): 0.006 to 0.014), but the strongest relationship existed between support for CAM and beliefs in the paranormal. Paranormal beliefs accounted for 14% of the variance of the CAM beliefs (regression coefficient: 0.376; 95%: CI 0.30-0.44). The level of education (regression coefficient: 0.06; 95% CI: -0.014-0.129) and social desirability (regression coefficient: -0.023; 95% CI: -0.048-0.026) did not make a significant contribution to the explained variance (<0.1%, P = 0.867). Support of CAM was very prevalent in this Flemish adult population. CAM beliefs were strongly associated with paranormal beliefs.

Characteristics of low-slope streams that affect O2 transfer rates

USGS Publications Warehouse

Parker, Gene W.; Desimone, Leslie A.

1991-01-01

Multiple-regression techniques were used to derive the reaeration coefficients estimating equation for low sloped streams: K2 = 3.83 MBAS-0.41 SL0.20 H-0.76, where K2 is the reaeration coefficient in base e units per day; MBAS is the methylene blue active substances concentration in milligrams per liter; SL is the water-surface slope in foot per foot; and H is the mean-flow depth in feet. Fourteen hydraulic, physical, and water-quality characteristics were regressed against 29 measured-reaeration coefficients for low-sloped (water surface slopes less than 0.002 foot per foot) streams in Massachusetts and New York. Reaeration coefficients measured from May 1985 to October 1988 ranged from 0.2 to 11.0 base e units per day for 29 low-sloped tracer studies. Concentration of methylene blue active substances is significant because it is thought to be an indicator of concentration of surfactants which could change the surface tension at the air-water interface.

Atomic-layer-deposited Al2O3-HfO2-Al2O3 dielectrics for metal-insulator-metal capacitor applications

NASA Astrophysics Data System (ADS)

Ding, Shi-Jin; Zhu, Chunxiang; Li, Ming-Fu; Zhang, David Wei

2005-08-01

Atomic-layer-deposited Al2O3-HfO2-Al2O3 dielectrics have been investigated to replace conventional silicon oxide and nitride for radio frequency and analog metal-insulator-metal capacitors applications. In the case of 1-nm-Al2O3, sufficiently good electrical performances are achieved, including a high dielectric constant of ˜17, a small dissipation factor of 0.018 at 100kHz, an extremely low leakage current of 7.8×10-9A/cm2 at 1MV/cm and 125°C, perfect voltage coefficients of capacitance (74ppm/V2 and 10ppm/V). The quadratic voltage coefficient of capacitance decreases with the applied frequency due to the change of relaxation time with different carrier mobility in insulator, and correlates with the dielectric composition and thickness, which is of intrinsic property owing to electric field polarization. Furthermore, the conduction mechanism of the AHA dielectrics is also discussed, indicating the Schottky emission dominated at room temperature.

Moderation analysis using a two-level regression model.

PubMed

Yuan, Ke-Hai; Cheng, Ying; Maxwell, Scott

2014-10-01

Moderation analysis is widely used in social and behavioral research. The most commonly used model for moderation analysis is moderated multiple regression (MMR) in which the explanatory variables of the regression model include product terms, and the model is typically estimated by least squares (LS). This paper argues for a two-level regression model in which the regression coefficients of a criterion variable on predictors are further regressed on moderator variables. An algorithm for estimating the parameters of the two-level model by normal-distribution-based maximum likelihood (NML) is developed. Formulas for the standard errors (SEs) of the parameter estimates are provided and studied. Results indicate that, when heteroscedasticity exists, NML with the two-level model gives more efficient and more accurate parameter estimates than the LS analysis of the MMR model. When error variances are homoscedastic, NML with the two-level model leads to essentially the same results as LS with the MMR model. Most importantly, the two-level regression model permits estimating the percentage of variance of each regression coefficient that is due to moderator variables. When applied to data from General Social Surveys 1991, NML with the two-level model identified a significant moderation effect of race on the regression of job prestige on years of education while LS with the MMR model did not. An R package is also developed and documented to facilitate the application of the two-level model.

Engine With Regression and Neural Network Approximators Designed

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Hopkins, Dale A.

2001-01-01

At the NASA Glenn Research Center, the NASA engine performance program (NEPP, ref. 1) and the design optimization testbed COMETBOARDS (ref. 2) with regression and neural network analysis-approximators have been coupled to obtain a preliminary engine design methodology. The solution to a high-bypass-ratio subsonic waverotor-topped turbofan engine, which is shown in the preceding figure, was obtained by the simulation depicted in the following figure. This engine is made of 16 components mounted on two shafts with 21 flow stations. The engine is designed for a flight envelope with 47 operating points. The design optimization utilized both neural network and regression approximations, along with the cascade strategy (ref. 3). The cascade used three algorithms in sequence: the method of feasible directions, the sequence of unconstrained minimizations technique, and sequential quadratic programming. The normalized optimum thrusts obtained by the three methods are shown in the following figure: the cascade algorithm with regression approximation is represented by a triangle, a circle is shown for the neural network solution, and a solid line indicates original NEPP results. The solutions obtained from both approximate methods lie within one standard deviation of the benchmark solution for each operating point. The simulation improved the maximum thrust by 5 percent. The performance of the linear regression and neural network methods as alternate engine analyzers was found to be satisfactory for the analysis and operation optimization of air-breathing propulsion engines (ref. 4).

Simulation of Alfvén eigenmode bursts using a hybrid code for nonlinear magnetohydrodynamics and energetic particles

NASA Astrophysics Data System (ADS)

Todo, Y.; Berk, H. L.; Breizman, B. N.

2012-03-01

A hybrid simulation code for nonlinear magnetohydrodynamics (MHD) and energetic-particle dynamics has been extended to simulate recurrent bursts of Alfvén eigenmodes by implementing the energetic-particle source, collisions and losses. The Alfvén eigenmode bursts with synchronization of multiple modes and beam ion losses at each burst are successfully simulated with nonlinear MHD effects for the physics condition similar to a reduced simulation for a TFTR experiment (Wong et al 1991 Phys. Rev. Lett. 66 1874, Todo et al 2003 Phys. Plasmas 10 2888). It is demonstrated with a comparison between nonlinear MHD and linear MHD simulation results that the nonlinear MHD effects significantly reduce both the saturation amplitude of the Alfvén eigenmodes and the beam ion losses. Two types of time evolution are found depending on the MHD dissipation coefficients, namely viscosity, resistivity and diffusivity. The Alfvén eigenmode bursts take place for higher dissipation coefficients with roughly 10% drop in stored beam energy and the maximum amplitude of the dominant magnetic fluctuation harmonic δBm/n/B ~ 5 × 10-3 at the mode peak location inside the plasma. Quadratic dependence of beam ion loss rate on magnetic fluctuation amplitude is found for the bursting evolution in the nonlinear MHD simulation. For lower dissipation coefficients, the amplitude of the Alfvén eigenmodes is at steady levels δBm/n/B ~ 2 × 10-3 and the beam ion losses take place continuously. The beam ion pressure profiles are similar among the different dissipation coefficients, and the stored beam energy is higher for higher dissipation coefficients.

Measurement of effective air diffusion coefficients for trichloroethene in undisturbed soil cores.

PubMed

Bartelt-Hunt, Shannon L; Smith, James A

2002-06-01

In this study, we measure effective diffusion coefficients for trichloroethene in undisturbed soil samples taken from Picatinny Arsenal, New Jersey. The measured effective diffusion coefficients ranged from 0.0053 to 0.0609 cm2/s over a range of air-filled porosity of 0.23-0.49. The experimental data were compared to several previously published relations that predict diffusion coefficients as a function of air-filled porosity and porosity. A multiple linear regression analysis was developed to determine if a modification of the exponents in Millington's [Science 130 (1959) 100] relation would better fit the experimental data. The literature relations appeared to generally underpredict the effective diffusion coefficient for the soil cores studied in this work. Inclusion of a particle-size distribution parameter, d10, did not significantly improve the fit of the linear regression equation. The effective diffusion coefficient and porosity data were used to recalculate estimates of diffusive flux through the subsurface made in a previous study performed at the field site. It was determined that the method of calculation used in the previous study resulted in an underprediction of diffusive flux from the subsurface. We conclude that although Millington's [Science 130 (1959) 100] relation works well to predict effective diffusion coefficients in homogeneous soils with relatively uniform particle-size distributions, it may be inaccurate for many natural soils with heterogeneous structure and/or non-uniform particle-size distributions.

Smooth Scalar-on-Image Regression via Spatial Bayesian Variable Selection

PubMed Central

Goldsmith, Jeff; Huang, Lei; Crainiceanu, Ciprian M.

2013-01-01

We develop scalar-on-image regression models when images are registered multidimensional manifolds. We propose a fast and scalable Bayes inferential procedure to estimate the image coefficient. The central idea is the combination of an Ising prior distribution, which controls a latent binary indicator map, and an intrinsic Gaussian Markov random field, which controls the smoothness of the nonzero coefficients. The model is fit using a single-site Gibbs sampler, which allows fitting within minutes for hundreds of subjects with predictor images containing thousands of locations. The code is simple and is provided in less than one page in the Appendix. We apply this method to a neuroimaging study where cognitive outcomes are regressed on measures of white matter microstructure at every voxel of the corpus callosum for hundreds of subjects. PMID:24729670

Scaling Laws for the Multidimensional Burgers Equation with Quadratic External Potential

NASA Astrophysics Data System (ADS)

Leonenko, N. N.; Ruiz-Medina, M. D.

2006-07-01

The reordering of the multidimensional exponential quadratic operator in coordinate-momentum space (see X. Wang, C.H. Oh and L.C. Kwek (1998). J. Phys. A.: Math. Gen. 31:4329-4336) is applied to derive an explicit formulation of the solution to the multidimensional heat equation with quadratic external potential and random initial conditions. The solution to the multidimensional Burgers equation with quadratic external potential under Gaussian strongly dependent scenarios is also obtained via the Hopf-Cole transformation. The limiting distributions of scaling solutions to the multidimensional heat and Burgers equations with quadratic external potential are then obtained under such scenarios.

Nanostructured bilayer anodic TiO2/Al2O3 metal-insulator-metal capacitor.

PubMed

Karthik, R; Kannadassan, D; Baghini, Maryam Shojaei; Mallick, P S

2013-10-01

This paper presents the fabrication of high performance bilayer TiO2/Al2O3 Metal-Insulator-Metal capacitor using anodization technique. A high capacitance density of 7 fF/microm2, low quadratic voltage coefficient of capacitance of 150 ppm/V2 and a low leakage current density of 9.1 nA/cm2 at 3 V are achieved which are suitable for Analog and Mixed signal applications. The influence of anodization voltage on structural and electrical properties of dielectric stack is studied in detail. At higher anodization voltages, we have observed the transformation of amorphous to crystalline state of TiO2/Al2O3 and improvement of electrical properties.

Viscous magnetoresistance of correlated electron liquids

NASA Astrophysics Data System (ADS)

Levchenko, Alex; Xie, Hong-Yi; Andreev, A. V.

2017-03-01

We develop a theory of magnetoresistance of two-dimensional electron systems in a smooth disorder potential in the hydrodynamic regime. Our theory applies to two-dimensional semiconductor structures with strongly correlated carriers when the mean free path due to electron-electron collisions is sufficiently short. The dominant contribution to magnetoresistance arises from the modification of the flow pattern by the Lorentz force, rather than the magnetic field dependence of the kinetic coefficients of the electron liquid. The resulting magnetoresistance is positive and quadratic at weak fields. Although the resistivity is governed by both the viscosity and thermal conductivity of the electron fluid, the magnetoresistance is controlled by the viscosity only. This enables the extraction of viscosity of the electron liquid from magnetotransport measurements.

Using Land Surface Phenology to Detect Land Use Change in the Northern Great Plains

NASA Astrophysics Data System (ADS)

Nguyen, L. H.; Henebry, G. M.

2017-12-01

The Northern Great Plains of the US have been undergoing many types of land cover / land use change over the past two decades, including expansion of irrigation, conversion of grassland to cropland, biofuels production, urbanization, and fossil fuel mining. Much of the literature on these changes has relied on post-classification change detection based on a limited number of observations per year. Here we demonstrate an approach to characterize land dynamics through land surface phenology (LSP) by synergistic use of image time series at two scales. Our study areas include regions of interest (ROIs) across the Northern Great Plains located within Landsat path overlap zones to boost the number of valid observations (free of clouds or snow) each year. We first compute accumulated growing degree-days (AGDD) from MODIS 8-day composites of land surface temperature (MOD11A2 and MYD11A2). Using Landsat Collection 1 surface reflectance-derived vegetation indices (NDVI, EVI), we then fit at each pixel a downward convex quadratic model linking the vegetation index to each year's progression of AGDD. This quadratic equation exhibits linearity in a mathematical sense; thus, the fitted models can be linearly mixed and unmixed using a set of LSP endmembers (defined by the fitted parameter coefficients of the quadratic model) that represent "pure" land cover types with distinct seasonal patterns found within the region, such as winter wheat, spring wheat, maize, soybean, sunflower, hay/pasture/grassland, developed/built-up, among others. Information about land cover corresponding to each endmember are provided by the NLCD (National Land Cover Dataset) and CDL (Cropland Data Layer). We use linear unmixing to estimate the likely proportion of each LSP endmember within particular areas stratified by latitude. By tracking the proportions over the 2001-2011 period, we can quantify various types of land transitions in the Northern Great Plains.

The Geometry of Enhancement in Multiple Regression

ERIC Educational Resources Information Center

Waller, Niels G.

2011-01-01

In linear multiple regression, "enhancement" is said to occur when R[superscript 2] = b[prime]r greater than r[prime]r, where b is a p x 1 vector of standardized regression coefficients and r is a p x 1 vector of correlations between a criterion y and a set of standardized regressors, x. When p = 1 then b [is congruent to] r and…

A Comparison between the Use of Beta Weights and Structure Coefficients in Interpreting Regression Results

ERIC Educational Resources Information Center

Tong, Fuhui

2006-01-01

Background: An extensive body of researches has favored the use of regression over other parametric analyses that are based on OVA. In case of noteworthy regression results, researchers tend to explore magnitude of beta weights for the respective predictors. Purpose: The purpose of this paper is to examine both beta weights and structure…

Remote-sensing data processing with the multivariate regression analysis method for iron mineral resource potential mapping: a case study in the Sarvian area, central Iran

NASA Astrophysics Data System (ADS)

Mansouri, Edris; Feizi, Faranak; Jafari Rad, Alireza; Arian, Mehran

2018-03-01

This paper uses multivariate regression to create a mathematical model for iron skarn exploration in the Sarvian area, central Iran, using multivariate regression for mineral prospectivity mapping (MPM). The main target of this paper is to apply multivariate regression analysis (as an MPM method) to map iron outcrops in the northeastern part of the study area in order to discover new iron deposits in other parts of the study area. Two types of multivariate regression models using two linear equations were employed to discover new mineral deposits. This method is one of the reliable methods for processing satellite images. ASTER satellite images (14 bands) were used as unique independent variables (UIVs), and iron outcrops were mapped as dependent variables for MPM. According to the results of the probability value (p value), coefficient of determination value (R2) and adjusted determination coefficient (Radj2), the second regression model (which consistent of multiple UIVs) fitted better than other models. The accuracy of the model was confirmed by iron outcrops map and geological observation. Based on field observation, iron mineralization occurs at the contact of limestone and intrusive rocks (skarn type).

Estimation Methods for Non-Homogeneous Regression - Minimum CRPS vs Maximum Likelihood

NASA Astrophysics Data System (ADS)

Gebetsberger, Manuel; Messner, Jakob W.; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Non-homogeneous regression models are widely used to statistically post-process numerical weather prediction models. Such regression models correct for errors in mean and variance and are capable to forecast a full probability distribution. In order to estimate the corresponding regression coefficients, CRPS minimization is performed in many meteorological post-processing studies since the last decade. In contrast to maximum likelihood estimation, CRPS minimization is claimed to yield more calibrated forecasts. Theoretically, both scoring rules used as an optimization score should be able to locate a similar and unknown optimum. Discrepancies might result from a wrong distributional assumption of the observed quantity. To address this theoretical concept, this study compares maximum likelihood and minimum CRPS estimation for different distributional assumptions. First, a synthetic case study shows that, for an appropriate distributional assumption, both estimation methods yield to similar regression coefficients. The log-likelihood estimator is slightly more efficient. A real world case study for surface temperature forecasts at different sites in Europe confirms these results but shows that surface temperature does not always follow the classical assumption of a Gaussian distribution. KEYWORDS: ensemble post-processing, maximum likelihood estimation, CRPS minimization, probabilistic temperature forecasting, distributional regression models

The consequences of ignoring measurement invariance for path coefficients in structural equation models

PubMed Central

Guenole, Nigel; Brown, Anna

2014-01-01

We report a Monte Carlo study examining the effects of two strategies for handling measurement non-invariance – modeling and ignoring non-invariant items – on structural regression coefficients between latent variables measured with item response theory models for categorical indicators. These strategies were examined across four levels and three types of non-invariance – non-invariant loadings, non-invariant thresholds, and combined non-invariance on loadings and thresholds – in simple, partial, mediated and moderated regression models where the non-invariant latent variable occupied predictor, mediator, and criterion positions in the structural regression models. When non-invariance is ignored in the latent predictor, the focal group regression parameters are biased in the opposite direction to the difference in loadings and thresholds relative to the referent group (i.e., lower loadings and thresholds for the focal group lead to overestimated regression parameters). With criterion non-invariance, the focal group regression parameters are biased in the same direction as the difference in loadings and thresholds relative to the referent group. While unacceptable levels of parameter bias were confined to the focal group, bias occurred at considerably lower levels of ignored non-invariance than was previously recognized in referent and focal groups. PMID:25278911

How many stakes are required to measure the mass balance of a glacier?

USGS Publications Warehouse

Fountain, A.G.; Vecchia, A.

1999-01-01

Glacier mass balance is estimated for South Cascade Glacier and Maclure Glacier using a one-dimensional regression of mass balance with altitude as an alternative to the traditional approach of contouring mass balance values. One attractive feature of regression is that it can be applied to sparse data sets where contouring is not possible and can provide an objective error of the resulting estimate. Regression methods yielded mass balance values equivalent to contouring methods. The effect of the number of mass balance measurements on the final value for the glacier showed that sample sizes as small as five stakes provided reasonable estimates, although the error estimates were greater than for larger sample sizes. Different spatial patterns of measurement locations showed no appreciable influence on the final value as long as different surface altitudes were intermittently sampled over the altitude range of the glacier. Two different regression equations were examined, a quadratic, and a piecewise linear spline, and comparison of results showed little sensitivity to the type of equation. These results point to the dominant effect of the gradient of mass balance with altitude of alpine glaciers compared to transverse variations. The number of mass balance measurements required to determine the glacier balance appears to be scale invariant for small glaciers and five to ten stakes are sufficient.

Atmospheric refraction errors in laser ranging systems

NASA Technical Reports Server (NTRS)

Gardner, C. S.; Rowlett, J. R.

1976-01-01

The effects of horizontal refractivity gradients on the accuracy of laser ranging systems were investigated by ray tracing through three dimensional refractivity profiles. The profiles were generated by performing a multiple regression on measurements from seven or eight radiosondes, using a refractivity model which provided for both linear and quadratic variations in the horizontal direction. The range correction due to horizontal gradients was found to be an approximately sinusoidal function of azimuth having a minimum near 0 deg azimuth and a maximum near 180 deg azimuth. The peak to peak variation was approximately 5 centimeters at 10 deg elevation and decreased to less than 1 millimeter at 80 deg elevation.

Association of sense of coherence and supernatural beliefs with death anxiety and death depression among Romanian cancer patients.

PubMed

Postolică, Roxana; Enea, Violeta; Dafinoiu, Ion; Petrov, Iuliana; Azoicăi, Doina

2018-02-02

The aim of this cross-sectional study was to examine the association of supernatural beliefs and sense of coherence with death anxiety and death depression in a Romanian sample of cancer patients. We found support for the terror management theory worldview defence hypothesis postulating the presence of a curvilinear relation between death anxiety and supernatural beliefs among cancer patients. Results conformed to an inverted U-shape quadratic regression, indicating that cancer patients who scored moderately on supernatural beliefs were afraid of death the most, while death anxiety was lowest for the extreme atheists and extreme believers in supernatural entities.

Crime prediction modeling

NASA Technical Reports Server (NTRS)

1971-01-01

A study of techniques for the prediction of crime in the City of Los Angeles was conducted. Alternative approaches to crime prediction (causal, quasicausal, associative, extrapolative, and pattern-recognition models) are discussed, as is the environment within which predictions were desired for the immediate application. The decision was made to use time series (extrapolative) models to produce the desired predictions. The characteristics of the data and the procedure used to choose equations for the extrapolations are discussed. The usefulness of different functional forms (constant, quadratic, and exponential forms) and of different parameter estimation techniques (multiple regression and multiple exponential smoothing) are compared, and the quality of the resultant predictions is assessed.

Linear regression metamodeling as a tool to summarize and present simulation model results.

PubMed

Jalal, Hawre; Dowd, Bryan; Sainfort, François; Kuntz, Karen M

2013-10-01

Modelers lack a tool to systematically and clearly present complex model results, including those from sensitivity analyses. The objective was to propose linear regression metamodeling as a tool to increase transparency of decision analytic models and better communicate their results. We used a simplified cancer cure model to demonstrate our approach. The model computed the lifetime cost and benefit of 3 treatment options for cancer patients. We simulated 10,000 cohorts in a probabilistic sensitivity analysis (PSA) and regressed the model outcomes on the standardized input parameter values in a set of regression analyses. We used the regression coefficients to describe measures of sensitivity analyses, including threshold and parameter sensitivity analyses. We also compared the results of the PSA to deterministic full-factorial and one-factor-at-a-time designs. The regression intercept represented the estimated base-case outcome, and the other coefficients described the relative parameter uncertainty in the model. We defined simple relationships that compute the average and incremental net benefit of each intervention. Metamodeling produced outputs similar to traditional deterministic 1-way or 2-way sensitivity analyses but was more reliable since it used all parameter values. Linear regression metamodeling is a simple, yet powerful, tool that can assist modelers in communicating model characteristics and sensitivity analyses.

Geometric Approaches to Quadratic Equations from Other Times and Places.

ERIC Educational Resources Information Center

Allaire, Patricia R.; Bradley, Robert E.

2001-01-01

Focuses on geometric solutions of quadratic problems. Presents a collection of geometric techniques from ancient Babylonia, classical Greece, medieval Arabia, and early modern Europe to enhance the quadratic equation portion of an algebra course. (KHR)

Employing the Gini coefficient to measure participation inequality in treatment-focused Digital Health Social Networks.

PubMed

van Mierlo, Trevor; Hyatt, Douglas; Ching, Andrew T

2016-01-01

Digital Health Social Networks (DHSNs) are common; however, there are few metrics that can be used to identify participation inequality. The objective of this study was to investigate whether the Gini coefficient, an economic measure of statistical dispersion traditionally used to measure income inequality, could be employed to measure DHSN inequality. Quarterly Gini coefficients were derived from four long-standing DHSNs. The combined data set included 625,736 posts that were generated from 15,181 actors over 18,671 days. The range of actors (8-2323), posts (29-28,684), and Gini coefficients (0.15-0.37) varied. Pearson correlations indicated statistically significant associations between number of actors and number of posts (0.527-0.835, p  < .001), and Gini coefficients and number of posts (0.342-0.725, p  < .001). However, the association between Gini coefficient and number of actors was only statistically significant for the addiction networks (0.619 and 0.276, p  < .036). Linear regression models had positive but mixed R 2 results (0.333-0.527). In all four regression models, the association between Gini coefficient and posts was statistically significant ( t  = 3.346-7.381, p  < .002). However, unlike the Pearson correlations, the association between Gini coefficient and number of actors was only statistically significant in the two mental health networks ( t  = -4.305 and -5.934, p  < .000). The Gini coefficient is helpful in measuring shifts in DHSN inequality. However, as a standalone metric, the Gini coefficient does not indicate optimal numbers or ratios of actors to posts, or effective network engagement. Further, mixed-methods research investigating quantitative performance metrics is required.

Twenty-year trends in cardiovascular risk factors in India and influence of educational status.

PubMed

Gupta, Rajeev; Guptha, Soneil; Gupta, V P; Agrawal, Aachu; Gaur, Kiran; Deedwania, Prakash C

2012-12-01

Urban middle-socioeconomic status (SES) subjects have high burden of cardiovascular risk factors in low-income countries. To determine secular trends in risk factors among this population and to correlate risks with educational status we performed epidemiological studies in India. Five cross-sectional studies were performed in middle-SES urban locations in Jaipur, India from years 1992 to 2010. Cluster sampling was performed. Subjects (men, women) aged 20-59 years evaluated were 712 (459, 253) in 1992-94, 558 (286, 272) in 1999-2001, 374 (179, 195) in 2002-03, 887 (414, 473) in 2004-05, and 530 (324, 206) in 2009-10. Data were obtained by history, anthropometry, and fasting blood glucose and lipids estimation. Response rates varied from 55 to 75%. Mean values and risk factor prevalence were determined. Secular trends were identified using quadratic and log-linear regression and chi-squared for trend. Across the studies, there was high prevalence of overweight, hypertension, and lipid abnormalities. Age- and sex-adjusted trends showed significant increases in mean body mass index (BMI), fasting glucose, total cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides (quadratic and log-linear regression, p < 0.001). Systolic blood pressure (BP) decreased while insignificant changes were observed for waist-hip ratio and low-density lipoprotein (LDL) cholesterol. Categorical trends showed increase in overweight and decrease in smoking (p < 0.05); insignificant changes were observed in truncal obesity, hypertension, hypercholesterolaemia, and diabetes. Adjustment for educational status attenuated linear trends in BMI and total and LDL cholesterol and accentuated trends in systolic BP, glucose, and HDL cholesterol. There was significant association of an increase in education with decline in smoking and an increase in overweight (two-line regression p < 0.05). In Indian urban middle-SES subjects there is high prevalence of cardiovascular risk factors. Over a 20-year period BMI and overweight increased, smoking and systolic BP decreased, and truncal obesity, hypercholesterolaemia, and diabetes remained stable. Increasing educational status attenuated trends for systolic BP, glucose and HDL cholesterol, and BMI.

Migrating husbands and changing cardiovascular risk factors in the wife: a cross sectional study in Asian Indian women.

PubMed

Gupta, Rajeev; Gupta, Rajiv; Agrawal, Aachu; Misra, Anoop; Guptha, Soneil; Pandey, Ravindra M; Misra, Puneet; Vikram, Naval K; Dey, Sanjit; Rao, Shobha; Menon, V Usha; Kamalamma, N; Revathi, K; Mathur, Beena; Sharma, Vinita

2012-10-01

The authors studied the influence of migration of husband on cardiovascular risk factors in Asian Indian women. Population-based studies in women aged 35-70 years were performed in four urban and five rural locations. 4608 (rural 2604 and urban 2004) of the targeted 8000 (57%) were enrolled. Demographic details, lifestyle factors, anthropometry, fasting glucose and cholesterol were measured. Multivariate logistic and quadratic regression was performed to compare influence of migration and its duration on prevalence of risk factors. Details of migration were available in 4573 women (rural 2267, rural-urban migrants 455, urban 1552 and urban-rural migrants 299). Majority were married, and illiteracy was high. Median (interquartile) duration of residence in urban locations among rural-urban migrants was 9 (4-18) years and in rural areas for urban-rural migrants 23 (18-30) years. In rural, rural-urban migrants, urban and urban-rural migrants, age-adjusted prevalence (%) of risk factors was tobacco use 41.9, 22.7, 18.8 and 38.1; sedentary lifestyle 69.7, 82.0, 79.9 and 74.6; high-fat diet 33.3, 54.2, 66.1 and 61.1; overweight 21.3, 42.7, 46.3 and 29.7; large waist 8.5, 38.5, 29.2 and 29.2; hypertension 30.4, 49.4, 47.7 and 38.4; hypercholesterolaemia 14.4, 31.3, 26.6 and 9.1 and diabetes 3.9, 15.8, 14.9 and 8.4, respectively (p<0.001). In rural-urban migrants, there was a significant correlation of duration of migration with waist size, waist-to-hip ratio and systolic blood pressure (quadratic regression, p<0.001). Association of risk factors with migration remained significant, though attenuated, after adjustment for socioeconomic, lifestyle and obesity variables (logistic regression, p<0.01). Compared with rural women, rural-urban migrants and urban have significantly greater cardiometabolic risk factors. Prevalence is lower in urban-rural migrants. There is significant correlation of duration of migration with obesity and blood pressure. Differences are attenuated after adjusting for social and lifestyle variables.