Neural network and multiple linear regression to predict school children dimensions for ergonomic school furniture design.

PubMed

Agha, Salah R; Alnahhal, Mohammed J

2012-11-01

The current study investigates the possibility of obtaining the anthropometric dimensions, critical to school furniture design, without measuring all of them. The study first selects some anthropometric dimensions that are easy to measure. Two methods are then used to check if these easy-to-measure dimensions can predict the dimensions critical to the furniture design. These methods are multiple linear regression and neural networks. Each dimension that is deemed necessary to ergonomically design school furniture is expressed as a function of some other measured anthropometric dimensions. Results show that out of the five dimensions needed for chair design, four can be related to other dimensions that can be measured while children are standing. Therefore, the method suggested here would definitely save time and effort and avoid the difficulty of dealing with students while measuring these dimensions. In general, it was found that neural networks perform better than multiple linear regression in the current study. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

NASA Astrophysics Data System (ADS)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

Practical Session: Simple Linear Regression

NASA Astrophysics Data System (ADS)

Clausel, M.; Grégoire, G.

2014-12-01

Two exercises are proposed to illustrate the simple linear regression. The first one is based on the famous Galton's data set on heredity. We use the lm R command and get coefficients estimates, standard error of the error, R2, residuals …In the second example, devoted to data related to the vapor tension of mercury, we fit a simple linear regression, predict values, and anticipate on multiple linear regression. This pratical session is an excerpt from practical exercises proposed by A. Dalalyan at EPNC (see Exercises 1 and 2 of http://certis.enpc.fr/~dalalyan/Download/TP_ENPC_4.pdf).

FAST TRACK PAPER: Non-iterative multiple-attenuation methods: linear inverse solutions to non-linear inverse problems - II. BMG approximation

NASA Astrophysics Data System (ADS)

Ikelle, Luc T.; Osen, Are; Amundsen, Lasse; Shen, Yunqing

2004-12-01

The classical linear solutions to the problem of multiple attenuation, like predictive deconvolution, τ-p filtering, or F-K filtering, are generally fast, stable, and robust compared to non-linear solutions, which are generally either iterative or in the form of a series with an infinite number of terms. These qualities have made the linear solutions more attractive to seismic data-processing practitioners. However, most linear solutions, including predictive deconvolution or F-K filtering, contain severe assumptions about the model of the subsurface and the class of free-surface multiples they can attenuate. These assumptions limit their usefulness. In a recent paper, we described an exception to this assertion for OBS data. We showed in that paper that a linear and non-iterative solution to the problem of attenuating free-surface multiples which is as accurate as iterative non-linear solutions can be constructed for OBS data. We here present a similar linear and non-iterative solution for attenuating free-surface multiples in towed-streamer data. For most practical purposes, this linear solution is as accurate as the non-linear ones.

Simple linear and multivariate regression models.

PubMed

Rodríguez del Águila, M M; Benítez-Parejo, N

2011-01-01

In biomedical research it is common to find problems in which we wish to relate a response variable to one or more variables capable of describing the behaviour of the former variable by means of mathematical models. Regression techniques are used to this effect, in which an equation is determined relating the two variables. While such equations can have different forms, linear equations are the most widely used form and are easy to interpret. The present article describes simple and multiple linear regression models, how they are calculated, and how their applicability assumptions are checked. Illustrative examples are provided, based on the use of the freely accessible R program. Copyright © 2011 SEICAP. Published by Elsevier Espana. All rights reserved.

Relation of Parental Transitions to Boys' Adjustment Problems: I.A. Linear Hypothesis II. Mothers at Risk for Transitions and Unskilled Parenting.

ERIC Educational Resources Information Center

Capaldi, D. M.; Patterson, G. R.

1991-01-01

Examined the adjustment of boys from intact, single-mother, stepfather, and multiple-transition families. Boys who had experienced multiple transitions showed the poorest adjustment. The antisocial mother was most at risk for transitions and unskilled parenting practices, which in turn placed her son at risk for poor adjustment. (BC)

Linear summation of outputs in a balanced network model of motor cortex.

PubMed

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis.

Female Literacy Rate is a Better Predictor of Birth Rate and Infant Mortality Rate in India

PubMed Central

Saurabh, Suman; Sarkar, Sonali; Pandey, Dhruv K.

2013-01-01

Background: Educated women are known to take informed reproductive and healthcare decisions. These result in population stabilization and better infant care reflected by lower birth rates and infant mortality rates (IMRs), respectively. Materials and Methods: Our objective was to study the relationship of male and female literacy rates with crude birth rates (CBRs) and IMRs of the states and union territories (UTs) of India. The data were analyzed using linear regression. CBR and IMR were taken as the dependent variables; while the overall literacy rates, male, and female literacy rates were the independent variables. Results: CBRs were inversely related to literacy rates (slope parameter = −0.402, P < 0.001). On multiple linear regression with male and female literacy rates, a significant inverse relationship emerged between female literacy rate and CBR (slope = −0.363, P < 0.001), while male literacy rate was not significantly related to CBR (P = 0.674). IMR of the states were also inversely related to their literacy rates (slope = −1.254, P < 0.001). Multiple linear regression revealed a significant inverse relationship between IMR and female literacy (slope = −0.816, P = 0.031), whereas male literacy rate was not significantly related (P = 0.630). Conclusion: Female literacy is relatively highly important for both population stabilization and better infant health. PMID:26664840

Effects of Hydrostatic Pressure and Electric Field on the Electron-Related Optical Properties in GaAs Multiple Quantum Well.

PubMed

Ospina, D A; Mora-Ramos, M E; Duque, C A

2017-02-01

The properties of the electronic structure of a finite-barrier semiconductor multiple quantum well are investigated taking into account the effects of the application of a static electric field and hydrostatic pressure. With the information of the allowed quasi-stationary energy states, the coefficients of linear and nonlinear optical absorption and of the relative refractive index change associated to transitions between allowed subbands are calculated with the use of a two-level scheme for the density matrix equation of motion and the rotating wave approximation. It is noticed that the hydrostatic pressure enhances the amplitude of the nonlinear contribution to the optical response of the multiple quantum well, whilst the linear one becomes reduced. Besides, the calculated coefficients are blueshifted due to the increasing of the applied electric field, and shows systematically dependence upon the hydrostatic pressure. The comparison of these results with those related with the consideration of a stationary spectrum of states in the heterostructure-obtained by placing infinite confining barriers at a conveniently far distance-shows essential differences in the pressure-induced effects in the sense of resonant frequency shifting as well as in the variation of the amplitudes of the optical responses.

Genomic prediction based on data from three layer lines using non-linear regression models.

PubMed

Huang, Heyun; Windig, Jack J; Vereijken, Addie; Calus, Mario P L

2014-11-06

Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a multi-trait genomic best linear unbiased prediction (GBLUP) model that modelled trait by line combinations as separate but correlated traits and (2) non-linear models based on kernel learning. These models were compared to conventional linear models for genomic prediction for two lines of brown layer hens (B1 and B2) and one line of white hens (W1). The three lines each had 1004 to 1023 training and 238 to 240 validation animals. Prediction accuracy was evaluated by estimating the correlation between observed phenotypes and predicted breeding values. When the training dataset included only data from the evaluated line, non-linear models yielded at best a similar accuracy as linear models. In some cases, when adding a distantly related line, the linear models showed a slight decrease in performance, while non-linear models generally showed no change in accuracy. When only information from a closely related line was used for training, linear models and non-linear radial basis function (RBF) kernel models performed similarly. The multi-trait GBLUP model took advantage of the estimated genetic correlations between the lines. Combining linear and non-linear models improved the accuracy of multi-line genomic prediction. Linear models and non-linear RBF models performed very similarly for genomic prediction, despite the expectation that non-linear models could deal better with the heterogeneous multi-population data. This heterogeneity of the data can be overcome by modelling trait by line combinations as separate but correlated traits, which avoids the occasional occurrence of large negative accuracies when the evaluated line was not included in the training dataset. Furthermore, when using a multi-line training dataset, non-linear models provided information on the genotype data that was complementary to the linear models, which indicates that the underlying data distributions of the three studied lines were indeed heterogeneous.

Products of multiple Fourier series with application to the multiblade transformation

NASA Technical Reports Server (NTRS)

Kunz, D. L.

1981-01-01

A relatively simple and systematic method for forming the products of multiple Fourier series using tensor like operations is demonstrated. This symbolic multiplication can be performed for any arbitrary number of series, and the coefficients of a set of linear differential equations with periodic coefficients from a rotating coordinate system to a nonrotating system is also demonstrated. It is shown that using Fourier operations to perform this transformation make it easily understood, simple to apply, and generally applicable.

An efficient method for generalized linear multiplicative programming problem with multiplicative constraints.

PubMed

Zhao, Yingfeng; Liu, Sanyang

2016-01-01

We present a practical branch and bound algorithm for globally solving generalized linear multiplicative programming problem with multiplicative constraints. To solve the problem, a relaxation programming problem which is equivalent to a linear programming is proposed by utilizing a new two-phase relaxation technique. In the algorithm, lower and upper bounds are simultaneously obtained by solving some linear relaxation programming problems. Global convergence has been proved and results of some sample examples and a small random experiment show that the proposed algorithm is feasible and efficient.

Highly stable multi-wavelength erbium-doped fiber linear laser based on modal interference

NASA Astrophysics Data System (ADS)

Herrera-Piad, L. A.; Jauregui-Vazquez, D.; Lopez-Dieguez, Y.; Estudillo-Ayala, J. M.; Hernandez-Garcia, J. C.; Sierra-Hernandez, J. M.; Bianchetti, M.; Rojas-Laguna, R.

2018-03-01

We report a linear fiber laser cavity based on an all-fiber Fabry-Perot interferometer and bi-tapered optical fiber for multi-wavelength emission generation. Curvature and strain are used to operate the laser system and the number of lines as well, the emission regions are stronger related to the physical effect applied, due to the phase alteration between the multiple fiber optic modes involved. The original laser emissions present zero wavelength variations, minimal power fluctuations and small spacing mode (1 nm). Additionally, a nonlinear fiber was employed trying to improve the performance of the multiple lasing lines. This system offers a low implementation cost, compactness and good laser parameters.

Comparison study for multiple ionization of carbonyl sulfide by linearly and circularly polarized intense femtosecond laser fields using Coulomb explosion imaging

NASA Astrophysics Data System (ADS)

Ma, Pan; Wang, Chuncheng; Luo, Sizuo; Yu, Xitao; Li, Xiaokai; Wang, Zhenzhen; Hu, Wenhui; Yu, Jiaqi; Yang, Yizhang; Tian, Xu; Cui, Zhonghua; Ding, Dajun

2018-05-01

We studied the relative yields and dissociation dynamics for two- and three-body Coulomb explosion (CE) channels from highly charged carbonyl sulfide molecules in intense laser fields using the CE imaging technique. The electron recollision contributions are evaluated by comparing the relative yields for the multiple ionization process in linearly polarized and circularly polarized (LP and CP) laser fields. The nonsequential multiple ionization is only confirmed for the charge states of 2 to 4 because the energy for further ionization from the inner orbital is much larger than the maximum recollision energy, 3.2U p . The novel deviations of kinetic energy releases distributions between LP and CP pulses are observed for the charge states higher than 4. It can be attributed to the stronger molecular bending in highly charged states before three-body CE with CP light, in which the bending wave packet is initialed by the triple or quartic ionization and spread along their potential curves. Compared to LP light, CP light ionizes a larger fraction of bending molecules in the polarization plane.

Too Much of a Good Thing? How Breadth of Extracurricular Participation Relates to School-Related Affect and Academic Outcomes during Adolescence

ERIC Educational Resources Information Center

Knifsend, Casey A.; Graham, Sandra

2012-01-01

Although adolescents often participate in multiple extracurricular activities, little research has examined how the breadth of activities in which an adolescent is involved relates to school-related affect and academic performance. Relying on a large, multi-ethnic sample (N = 864; 55.9% female), the current study investigated linear and non-linear…

Quantile Regression in the Study of Developmental Sciences

PubMed Central

Petscher, Yaacov; Logan, Jessica A. R.

2014-01-01

Linear regression analysis is one of the most common techniques applied in developmental research, but only allows for an estimate of the average relations between the predictor(s) and the outcome. This study describes quantile regression, which provides estimates of the relations between the predictor(s) and outcome, but across multiple points of the outcome’s distribution. Using data from the High School and Beyond and U.S. Sustained Effects Study databases, quantile regression is demonstrated and contrasted with linear regression when considering models with: (a) one continuous predictor, (b) one dichotomous predictor, (c) a continuous and a dichotomous predictor, and (d) a longitudinal application. Results from each example exhibited the differential inferences which may be drawn using linear or quantile regression. PMID:24329596

Quantile Regression in the Study of Developmental Sciences

ERIC Educational Resources Information Center

Petscher, Yaacov; Logan, Jessica A. R.

2014-01-01

Linear regression analysis is one of the most common techniques applied in developmental research, but only allows for an estimate of the average relations between the predictor(s) and the outcome. This study describes quantile regression, which provides estimates of the relations between the predictor(s) and outcome, but across multiple points of…

The Prediction of Achievement and Time Spent in Instruction in a Self-Paced Individualized Course.

ERIC Educational Resources Information Center

Franklin, Thomas E.

Multiple linear regressions were employed to determine the relative contributions of cognitive and affective variables accounting for variance in college students' achievement and amount of time taken to complete a self-paced, individualized course. Study habits and attitudes (SSHA) made greater relative contributions to explaining total course…

An improved null model for assessing the net effects of multiple stressors on communities.

PubMed

Thompson, Patrick L; MacLennan, Megan M; Vinebrooke, Rolf D

2018-01-01

Ecological stressors (i.e., environmental factors outside their normal range of variation) can mediate each other through their interactions, leading to unexpected combined effects on communities. Determining whether the net effect of stressors is ecologically surprising requires comparing their cumulative impact to a null model that represents the linear combination of their individual effects (i.e., an additive expectation). However, we show that standard additive and multiplicative null models that base their predictions on the effects of single stressors on community properties (e.g., species richness or biomass) do not provide this linear expectation, leading to incorrect interpretations of antagonistic and synergistic responses by communities. We present an alternative, the compositional null model, which instead bases its predictions on the effects of stressors on individual species, and then aggregates them to the community level. Simulations demonstrate the improved ability of the compositional null model to accurately provide a linear expectation of the net effect of stressors. We simulate the response of communities to paired stressors that affect species in a purely additive fashion and compare the relative abilities of the compositional null model and two standard community property null models (additive and multiplicative) to predict these linear changes in species richness and community biomass across different combinations (both positive, negative, or opposite) and intensities of stressors. The compositional model predicts the linear effects of multiple stressors under almost all scenarios, allowing for proper classification of net effects, whereas the standard null models do not. Our findings suggest that current estimates of the prevalence of ecological surprises on communities based on community property null models are unreliable, and should be improved by integrating the responses of individual species to the community level as does our compositional null model. © 2017 John Wiley & Sons Ltd.

Linear summation of outputs in a balanced network model of motor cortex

PubMed Central

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis. PMID:26097452

MultiDK: A Multiple Descriptor Multiple Kernel Approach for Molecular Discovery and Its Application to Organic Flow Battery Electrolytes.

PubMed

Kim, Sungjin; Jinich, Adrián; Aspuru-Guzik, Alán

2017-04-24

We propose a multiple descriptor multiple kernel (MultiDK) method for efficient molecular discovery using machine learning. We show that the MultiDK method improves both the speed and accuracy of molecular property prediction. We apply the method to the discovery of electrolyte molecules for aqueous redox flow batteries. Using multiple-type-as opposed to single-type-descriptors, we obtain more relevant features for machine learning. Following the principle of "wisdom of the crowds", the combination of multiple-type descriptors significantly boosts prediction performance. Moreover, by employing multiple kernels-more than one kernel function for a set of the input descriptors-MultiDK exploits nonlinear relations between molecular structure and properties better than a linear regression approach. The multiple kernels consist of a Tanimoto similarity kernel and a linear kernel for a set of binary descriptors and a set of nonbinary descriptors, respectively. Using MultiDK, we achieve an average performance of r 2 = 0.92 with a test set of molecules for solubility prediction. We also extend MultiDK to predict pH-dependent solubility and apply it to a set of quinone molecules with different ionizable functional groups to assess their performance as flow battery electrolytes.

Early Parallel Activation of Semantics and Phonology in Picture Naming: Evidence from a Multiple Linear Regression MEG Study

PubMed Central

Miozzo, Michele; Pulvermüller, Friedemann; Hauk, Olaf

2015-01-01

The time course of brain activation during word production has become an area of increasingly intense investigation in cognitive neuroscience. The predominant view has been that semantic and phonological processes are activated sequentially, at about 150 and 200–400 ms after picture onset. Although evidence from prior studies has been interpreted as supporting this view, these studies were arguably not ideally suited to detect early brain activation of semantic and phonological processes. We here used a multiple linear regression approach to magnetoencephalography (MEG) analysis of picture naming in order to investigate early effects of variables specifically related to visual, semantic, and phonological processing. This was combined with distributed minimum-norm source estimation and region-of-interest analysis. Brain activation associated with visual image complexity appeared in occipital cortex at about 100 ms after picture presentation onset. At about 150 ms, semantic variables became physiologically manifest in left frontotemporal regions. In the same latency range, we found an effect of phonological variables in the left middle temporal gyrus. Our results demonstrate that multiple linear regression analysis is sensitive to early effects of multiple psycholinguistic variables in picture naming. Crucially, our results suggest that access to phonological information might begin in parallel with semantic processing around 150 ms after picture onset. PMID:25005037

Multiple regression for physiological data analysis: the problem of multicollinearity.

PubMed

Slinker, B K; Glantz, S A

1985-07-01

Multiple linear regression, in which several predictor variables are related to a response variable, is a powerful statistical tool for gaining quantitative insight into complex in vivo physiological systems. For these insights to be correct, all predictor variables must be uncorrelated. However, in many physiological experiments the predictor variables cannot be precisely controlled and thus change in parallel (i.e., they are highly correlated). There is a redundancy of information about the response, a situation called multicollinearity, that leads to numerical problems in estimating the parameters in regression equations; the parameters are often of incorrect magnitude or sign or have large standard errors. Although multicollinearity can be avoided with good experimental design, not all interesting physiological questions can be studied without encountering multicollinearity. In these cases various ad hoc procedures have been proposed to mitigate multicollinearity. Although many of these procedures are controversial, they can be helpful in applying multiple linear regression to some physiological problems.

Predicting musically induced emotions from physiological inputs: linear and neural network models.

PubMed

Russo, Frank A; Vempala, Naresh N; Sandstrom, Gillian M

2013-01-01

Listening to music often leads to physiological responses. Do these physiological responses contain sufficient information to infer emotion induced in the listener? The current study explores this question by attempting to predict judgments of "felt" emotion from physiological responses alone using linear and neural network models. We measured five channels of peripheral physiology from 20 participants-heart rate (HR), respiration, galvanic skin response, and activity in corrugator supercilii and zygomaticus major facial muscles. Using valence and arousal (VA) dimensions, participants rated their felt emotion after listening to each of 12 classical music excerpts. After extracting features from the five channels, we examined their correlation with VA ratings, and then performed multiple linear regression to see if a linear relationship between the physiological responses could account for the ratings. Although linear models predicted a significant amount of variance in arousal ratings, they were unable to do so with valence ratings. We then used a neural network to provide a non-linear account of the ratings. The network was trained on the mean ratings of eight of the 12 excerpts and tested on the remainder. Performance of the neural network confirms that physiological responses alone can be used to predict musically induced emotion. The non-linear model derived from the neural network was more accurate than linear models derived from multiple linear regression, particularly along the valence dimension. A secondary analysis allowed us to quantify the relative contributions of inputs to the non-linear model. The study represents a novel approach to understanding the complex relationship between physiological responses and musically induced emotion.

Adaptive robust fault-tolerant control for linear MIMO systems with unmatched uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Kangkang; Jiang, Bin; Yan, Xing-Gang; Mao, Zehui

2017-10-01

In this paper, two novel fault-tolerant control design approaches are proposed for linear MIMO systems with actuator additive faults, multiplicative faults and unmatched uncertainties. For time-varying multiplicative and additive faults, new adaptive laws and additive compensation functions are proposed. A set of conditions is developed such that the unmatched uncertainties are compensated by actuators in control. On the other hand, for unmatched uncertainties with their projection in unmatched space being not zero, based on a (vector) relative degree condition, additive functions are designed to compensate for the uncertainties from output channels in the presence of actuator faults. The developed fault-tolerant control schemes are applied to two aircraft systems to demonstrate the efficiency of the proposed approaches.

Multiple Input Design for Real-Time Parameter Estimation in the Frequency Domain

NASA Technical Reports Server (NTRS)

Morelli, Eugene

2003-01-01

A method for designing multiple inputs for real-time dynamic system identification in the frequency domain was developed and demonstrated. The designed inputs are mutually orthogonal in both the time and frequency domains, with reduced peak factors to provide good information content for relatively small amplitude excursions. The inputs are designed for selected frequency ranges, and therefore do not require a priori models. The experiment design approach was applied to identify linear dynamic models for the F-15 ACTIVE aircraft, which has multiple control effectors.

Helping Students Assess the Relative Importance of Different Intermolecular Interactions

ERIC Educational Resources Information Center

Jasien, Paul G.

2008-01-01

A semi-quantitative model has been developed to estimate the relative effects of dispersion, dipole-dipole interactions, and H-bonding on the normal boiling points ("T[subscript b]") for a subset of simple organic systems. The model is based upon a statistical analysis using multiple linear regression on a series of straight-chain organic…

Parts-Per-Billion Mass Measurement Accuracy Achieved through the Combination of Multiple Linear Regression and Automatic Gain Control in a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer

PubMed Central

Williams, D. Keith; Muddiman, David C.

2008-01-01

Fourier transform ion cyclotron resonance mass spectrometry has the ability to achieve unprecedented mass measurement accuracy (MMA); MMA is one of the most significant attributes of mass spectrometric measurements as it affords extraordinary molecular specificity. However, due to space-charge effects, the achievable MMA significantly depends on the total number of ions trapped in the ICR cell for a particular measurement. Even through the use of automatic gain control (AGC), the total ion population is not constant between spectra. Multiple linear regression calibration in conjunction with AGC is utilized in these experiments to formally account for the differences in total ion population in the ICR cell between the external calibration spectra and experimental spectra. This ability allows for the extension of dynamic range of the instrument while allowing mean MMA values to remain less than 1 ppm. In addition, multiple linear regression calibration is used to account for both differences in total ion population in the ICR cell as well as relative ion abundance of a given species, which also affords mean MMA values at the parts-per-billion level. PMID:17539605

Chimeras with multiple coherent regions

NASA Astrophysics Data System (ADS)

Ujjwal, Sangeeta Rani; Ramaswamy, Ramakrishna

2013-09-01

We study chimeric states in a coupled phase oscillator system with piecewise linear nonlocal coupling. By modifying the details of the coupling, it is possible to obtain multiple chimeric states with a specified number of coherent regions and with specified phase relationships. The case of a two-component chimera is illustrated and the generalization to arbitrary chimeric configurations is discussed. The phase relations between the two clusters of phase oscillators is described in some detail.

Comparing Multiple-Group Multinomial Log-Linear Models for Multidimensional Skill Distributions in the General Diagnostic Model. Research Report. ETS RR-08-35

ERIC Educational Resources Information Center

Xu, Xueli; von Davier, Matthias

2008-01-01

The general diagnostic model (GDM) utilizes located latent classes for modeling a multidimensional proficiency variable. In this paper, the GDM is extended by employing a log-linear model for multiple populations that assumes constraints on parameters across multiple groups. This constrained model is compared to log-linear models that assume…

Ergonomics study on mobile phones for thumb physiology discomfort

NASA Astrophysics Data System (ADS)

Bendero, J. M. S.; Doon, M. E. R.; Quiogue, K. C. A.; Soneja, L. C.; Ong, N. R.; Sauli, Z.; Vairavan, R.

2017-09-01

The study was conducted on Filipino undergraduate college students and aimed to find out about the significant factors associated with mobile phone usage and its effect on thumb pain.A correlation-prediction analysisand Multiple Linear Regression was adopted and used as the main tool in determining the significant factors and coming up with predictive models on thumb related pain. With the use of the software Statistical Package for the Social Sciences or SPSS in conducting linear regression, 2 significant factors on thumb-related pain (percentage of time using portrait as screen orientation when text messaging, amount of time playing games using one hand in a day) were found.

Prediction of the Main Engine Power of a New Container Ship at the Preliminary Design Stage

NASA Astrophysics Data System (ADS)

Cepowski, Tomasz

2017-06-01

The paper presents mathematical relationships that allow us to forecast the estimated main engine power of new container ships, based on data concerning vessels built in 2005-2015. The presented approximations allow us to estimate the engine power based on the length between perpendiculars and the number of containers the ship will carry. The approximations were developed using simple linear regression and multivariate linear regression analysis. The presented relations have practical application for estimation of container ship engine power needed in preliminary parametric design of the ship. It follows from the above that the use of multiple linear regression to predict the main engine power of a container ship brings more accurate solutions than simple linear regression.

Depressive mood mediates the influence of social support on health-related quality of life in elderly, multimorbid patients

PubMed Central

2014-01-01

Background It is not well established how psychosocial factors like social support and depression affect health-related quality of life in multimorbid and elderly patients. We investigated whether depressive mood mediates the influence of social support on health-related quality of life. Methods Cross-sectional data of 3,189 multimorbid patients from the baseline assessment of the German MultiCare cohort study were used. Mediation was tested using the approach described by Baron and Kenny based on multiple linear regression, and controlling for socioeconomic variables and burden of multimorbidity. Results Mediation analyses confirmed that depressive mood mediates the influence of social support on health-related quality of life (Sobel’s p < 0.001). Multiple linear regression showed that the influence of depressive mood (β = −0.341, p < 0.01) on health-related quality of life is greater than the influence of multimorbidity (β = −0.234, p < 0.01). Conclusion Social support influences health-related quality of life, but this association is strongly mediated by depressive mood. Depression should be taken into consideration in research on multimorbidity, and clinicians should be aware of its importance when caring for multimorbid patients. Trial registration ISRCTN89818205 PMID:24708815

Turbulent Reconnection Rates from Cluster Observations in the Magnetosheath

NASA Technical Reports Server (NTRS)

Wendel, Deirdre

2011-01-01

The role of turbulence in producing fast reconnection rates is an important unresolved question. Scant in situ analyses exist. We apply multiple spacecraft techniques to a case of nonlinear turbulent reconnection in the magnetosheath to test various theoretical results for turbulent reconnection rates. To date, in situ estimates of the contribution of turbulence to reconnection rates have been calculated from an effective electric field derived through linear wave theory. However, estimates of reconnection rates based on fully nonlinear turbulence theories and simulations exist that are amenable to multiple spacecraft analyses. Here we present the linear and nonlinear theories and apply some of the nonlinear rates to Cluster observations of reconnecting, turbulent current sheets in the magnetosheath. We compare the results to the net reconnection rate found from the inflow speed. Ultimately, we intend to test and compare linear and nonlinear estimates of the turbulent contribution to reconnection rates and to measure the relative contributions of turbulence and the Hall effect.

Turbulent Reconnection Rates from Cluster Observations in the Magneto sheath

NASA Technical Reports Server (NTRS)

Wendel, Deirdre

2011-01-01

The role of turbulence in producing fast reconnection rates is an important unresolved question. Scant in situ analyses exist. We apply multiple spacecraft techniques to a case of nonlinear turbulent reconnection in the magnetosheath to test various theoretical results for turbulent reconnection rates. To date, in situ estimates of the contribution of turbulence to reconnection rates have been calculated from an effective electric field derived through linear wave theory. However, estimates of reconnection rates based on fully nonlinear turbulence theories and simulations exist that are amenable to multiple spacecraft analyses. Here we present the linear and nonlinear theories and apply some of the nonlinear rates to Cluster observations of reconnecting, turbulent current sheets in the magnetos heath. We compare the results to the net reconnection rate found from the inflow speed. Ultimately, we intend to test and compare linear and nonlinear estimates of the turbulent contribution to reconnection rates and to measure the relative contributions of turbulence and the Hall effect.

Linearizing an intermodulation radar transmitter by filtering switched tones

NASA Astrophysics Data System (ADS)

Mazzaro, Gregory J.; Sherbondy, Andrew J.; Ranney, Kenneth I.; Sherbondy, Kelly D.; Martone, Anthony F.

2017-05-01

For nonlinear radar, the transmit power required to measure a detectable response from a target is relatively high, and generating that high power is achieved at the cost of linearity. This paper applies the distortion mitigation technique Linearization by Time-Multiplexed Spectrum (LITMUS) to intermodulation radar, a type of nonlinear radar which receives spectral content produced by the mixing of multiple frequencies at a nonlinear target. By implementing LITMUS, an experimental detection system for an intermodulation radar achieves a signal-to-noise ratio up to 20 dB for a total transmit power of approximately 80 mW and nonlinear targets placed at a standoff distance of 2 meters.

Correlates and Predictors of Psychological Distress Among Older Asian Immigrants in California.

PubMed

Chang, Miya; Moon, Ailee

2016-01-01

Psychological distress occurs frequently in older minority immigrants because many have limited social resources and undergo a difficult process related to immigration and acculturation. Despite a rapid increase in the number of Asian immigrants, relatively little research has focused on subgroup mental health comparisons. This study examines the prevalence of psychological distress, and relationship with socio-demographic factors, and health care utilization among older Asian immigrants. Weighted data from Asian immigrants 65 and older from 5 countries (n = 1,028) who participated in the California Health Interview Survey (CHIS) were analyzed descriptively and in multiple linear regressions. The prevalence of psychological distress varied significantly across the 5 ethnic groups, from Filipinos (4.83%) to Chinese (1.64%). General health status, cognitive and physical impairment, and health care utilization are all associated (p < .05) with psychological distress in multiple linear regressions. These findings are similar to those from previous studies. The findings reinforce the need to develop more culturally effective mental health services and outreach programs.

Step-response of a torsional device with multiple discontinuous non-linearities: Formulation of a vibratory experiment

NASA Astrophysics Data System (ADS)

Krak, Michael D.; Dreyer, Jason T.; Singh, Rajendra

2016-03-01

A vehicle clutch damper is intentionally designed to contain multiple discontinuous non-linearities, such as multi-staged springs, clearances, pre-loads, and multi-staged friction elements. The main purpose of this practical torsional device is to transmit a wide range of torque while isolating torsional vibration between an engine and transmission. Improved understanding of the dynamic behavior of the device could be facilitated by laboratory measurement, and thus a refined vibratory experiment is proposed. The experiment is conceptually described as a single degree of freedom non-linear torsional system that is excited by an external step torque. The single torsional inertia (consisting of a shaft and torsion arm) is coupled to ground through parallel production clutch dampers, which are characterized by quasi-static measurements provided by the manufacturer. Other experimental objectives address physical dimensions, system actuation, flexural modes, instrumentation, and signal processing issues. Typical measurements show that the step response of the device is characterized by three distinct non-linear regimes (double-sided impact, single-sided impact, and no-impact). Each regime is directly related to the non-linear features of the device and can be described by peak angular acceleration values. Predictions of a simplified single degree of freedom non-linear model verify that the experiment performs well and as designed. Accordingly, the benchmark measurements could be utilized to validate non-linear models and simulation codes, as well as characterize dynamic parameters of the device including its dissipative properties.

Ergodicity-breaking bifurcations and tunneling in hyperbolic transport models

NASA Astrophysics Data System (ADS)

Giona, M.; Brasiello, A.; Crescitelli, S.

2015-11-01

One of the main differences between parabolic transport, associated with Langevin equations driven by Wiener processes, and hyperbolic models related to generalized Kac equations driven by Poisson processes, is the occurrence in the latter of multiple stable invariant densities (Frobenius multiplicity) in certain regions of the parameter space. This phenomenon is associated with the occurrence in linear hyperbolic balance equations of a typical bifurcation, referred to as the ergodicity-breaking bifurcation, the properties of which are thoroughly analyzed.

MULTIVARIATE LINEAR MIXED MODELS FOR MULTIPLE OUTCOMES. (R824757)

EPA Science Inventory

We propose a multivariate linear mixed (MLMM) for the analysis of multiple outcomes, which generalizes the latent variable model of Sammel and Ryan. The proposed model assumes a flexible correlation structure among the multiple outcomes, and allows a global test of the impact of ...

High-throughput quantitative biochemical characterization of algal biomass by NIR spectroscopy; multiple linear regression and multivariate linear regression analysis.

PubMed

Laurens, L M L; Wolfrum, E J

2013-12-18

One of the challenges associated with microalgal biomass characterization and the comparison of microalgal strains and conversion processes is the rapid determination of the composition of algae. We have developed and applied a high-throughput screening technology based on near-infrared (NIR) spectroscopy for the rapid and accurate determination of algal biomass composition. We show that NIR spectroscopy can accurately predict the full composition using multivariate linear regression analysis of varying lipid, protein, and carbohydrate content of algal biomass samples from three strains. We also demonstrate a high quality of predictions of an independent validation set. A high-throughput 96-well configuration for spectroscopy gives equally good prediction relative to a ring-cup configuration, and thus, spectra can be obtained from as little as 10-20 mg of material. We found that lipids exhibit a dominant, distinct, and unique fingerprint in the NIR spectrum that allows for the use of single and multiple linear regression of respective wavelengths for the prediction of the biomass lipid content. This is not the case for carbohydrate and protein content, and thus, the use of multivariate statistical modeling approaches remains necessary.

Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

Multivariate analysis refers to statistical techniques that simultaneously look at three or more variables in relation to the subjects under investigation with the aim of identifying or clarifying the relationships between them. These techniques have been broadly classified as dependence techniques, which explore the relationship between one or more dependent variables and their independent predictors, and interdependence techniques, that make no such distinction but treat all variables equally in a search for underlying relationships. Multiple linear regression models a situation where a single numerical dependent variable is to be predicted from multiple numerical independent variables. Logistic regression is used when the outcome variable is dichotomous in nature. The log-linear technique models count type of data and can be used to analyze cross-tabulations where more than two variables are included. Analysis of covariance is an extension of analysis of variance (ANOVA), in which an additional independent variable of interest, the covariate, is brought into the analysis. It tries to examine whether a difference persists after "controlling" for the effect of the covariate that can impact the numerical dependent variable of interest. Multivariate analysis of variance (MANOVA) is a multivariate extension of ANOVA used when multiple numerical dependent variables have to be incorporated in the analysis. Interdependence techniques are more commonly applied to psychometrics, social sciences and market research. Exploratory factor analysis and principal component analysis are related techniques that seek to extract from a larger number of metric variables, a smaller number of composite factors or components, which are linearly related to the original variables. Cluster analysis aims to identify, in a large number of cases, relatively homogeneous groups called clusters, without prior information about the groups. The calculation intensive nature of multivariate analysis has so far precluded most researchers from using these techniques routinely. The situation is now changing with wider availability, and increasing sophistication of statistical software and researchers should no longer shy away from exploring the applications of multivariate methods to real-life data sets.

Compensator improvement for multivariable control systems

NASA Technical Reports Server (NTRS)

Mitchell, J. R.; Mcdaniel, W. L., Jr.; Gresham, L. L.

1977-01-01

A theory and the associated numerical technique are developed for an iterative design improvement of the compensation for linear, time-invariant control systems with multiple inputs and multiple outputs. A strict constraint algorithm is used in obtaining a solution of the specified constraints of the control design. The result of the research effort is the multiple input, multiple output Compensator Improvement Program (CIP). The objective of the Compensator Improvement Program is to modify in an iterative manner the free parameters of the dynamic compensation matrix so that the system satisfies frequency domain specifications. In this exposition, the underlying principles of the multivariable CIP algorithm are presented and the practical utility of the program is illustrated with space vehicle related examples.

[Non-linear canonical correlation analysis between anthropometric indicators and multiple metabolic abnormalities].

PubMed

Fu, Xiaoli; Liu, Li; Ping, Zhiguang; Li, Linlin

2013-09-01

To define the general correlation between anthropometric indicators and multiple metabolic abnormalities, and to put forward some particular suggestions for the prevention of multiple metabolic abnormalities. A random cluster sampling was carried out in one county of Henan Province. Questionnaire, physical examination and biochemical tests were admitted to the adult inhabitants. Non-linear canonical correlation analysis (NLCCA) was applied with OVERALS of SPSS 13.0. The coefficients of canonical correlation and multiple correlation were calculated. The plot of centroids labeled by variables showed the correlation among various indicators. In total, 2,914 objects were investigated. It included 1,134 (38.9%) males and 1,780 (61.1%) females (60.0%). The average age was (50.58 +/- 13.70) years old. The fitting result of NLCCA were as follows: the loss of 0.577 accounting for 28.8% of the total variation was relatively small, and indicated that the two sets of variables of this study, namely sets of biochemical indicators (including serum total cholesterol, total triglyceride, high-density lipoprotein cholesterol, low density lipoprotein cholesterol and fasting plasma glucose) and sets of others (including gender, BMI and waist circumference) were closely related and often changed synchronously. Multivariate correlation coefficient showed that internal indicators of the above two sets were closely related respectively and often showed the multiple anomalies of the same set. The diagram of the center of gravity of the association of various indicators showed that the symptoms of metabolic abnormalities increased with age. Women were more liable to have metabolic abnormalities. Overweight and obese people often suffer multiple metabolic disorders. Waist circumference was positively correlated with metabolic abnormalities. (1) Biochemical indicators and anthropometric often change in combination. (2) Much attention should be paid to older people especially middle-aged or older men and older women in primary prevention. (3) Overweight and abdominal obesity can be considered the sensitive predictive indicator of multiple metabolic abnormalities. (4) Nonlinear canonical correlation and center of gravity Figure had the advantage of analyze the correlation between multiple sets of variables.

An Inventory on Rotational Kinematics of a Particle: Unravelling Misconceptions and Pitfalls in Reasoning

ERIC Educational Resources Information Center

Mashood, K. K.; Singh, Vijay A.

2012-01-01

Student difficulties regarding the angular velocity ([image omitted]) and angular acceleration ([image omitted]) of a particle have remained relatively unexplored in contrast to their linear counterparts. We present an inventory comprising multiple choice questions aimed at probing misconceptions and eliciting ill-suited reasoning patterns. The…

Relation of the lunar volcano complexes lying on the identical linear gravity anomaly

NASA Astrophysics Data System (ADS)

Yamamoto, K.; Haruyama, J.; Ohtake, M.; Iwata, T.; Ishihara, Y.

2015-12-01

There are several large-scale volcanic complexes, e.g., Marius Hills, Aristarchus Plateau, Rumker Hills, and Flamsteed area in western Oceanus Procellarum of the lunar nearside. For better understanding of the lunar thermal history, it is important to study these areas intensively. The magmatisms and volcanic eruption mechanisms of these volcanic complexes have been discussed from geophysical and geochemical perspectives using data sets acquired by lunar explorers. In these data sets, precise gravity field data obtained by Gravity Recovery and Interior Laboratory (GRAIL) gives information on mass anomalies below the lunar surface, and useful to estimate location and mass of the embedded magmas. Using GRAIL data, Andrews-Hanna et al. (2014) prepared gravity gradient map of the Moon. They discussed the origin of the quasi-rectangular pattern of narrow linear gravity gradient anomalies located along the border of Oceanus Procellarum and suggested that the underlying dikes played important roles in magma plumbing system. In the gravity gradient map, we found that there are also several small linear gravity gradient anomaly patterns in the inside of the large quasi-rectangular pattern, and that one of the linear anomalies runs through multiple gravity anomalies in the vicinity of Aristarchus, Marius and Flamstead volcano complexes. Our concern is whether the volcanisms of these complexes are caused by common factors or not. To clarify this, we firstly estimated the mass and depth of the embedded magmas as well as the directions of the linear gravity anomalies. The results were interpreted by comparing with the chronological and KREEP distribution maps on the lunar surface. We suggested providing mechanisms of the magma to these regions and finally discussed whether the volcanisms of these multiple volcano complex regions are related with each other or not.

The relationship between health-related fitness and quality of life in postmenopausal women from Southern Taiwan

PubMed Central

Hsu, Wei-Hsiu; Chen, Chi-lung; Kuo, Liang Tseng; Fan, Chun-Hao; Lee, Mel S; Hsu, Robert Wen-Wei

2014-01-01

Background Health-related fitness has been reported to be associated with improved quality of life (QoL) in the elderly. Health-related fitness is comprised of several dimensions that could be enhanced by specific training regimens. It has remained unclear how various dimensions of health-related fitness interact with QoL in postmenopausal women. Objective The purpose of the current study was to investigate the relationship between the dimensions of health-related fitness and QoL in elderly women. Methods A cohort of 408 postmenopausal women in a rural area of Taiwan was prospectively collected. Dimensions of health-related fitness, consisting of muscular strength, balance, cardiorespiratory endurance, flexibility, muscle endurance, and agility, were assessed. QoL was determined using the Short Form Health Survey (SF-36). Differences between age groups (stratified by decades) were calculated using a one-way analysis of variance (ANOVA) and multiple comparisons using a Scheffé test. A Spearman’s correlation analysis was performed to examine differences between QoL and each dimension of fitness. Multiple linear regression with forced-entry procedure was performed to evaluate the effects of health-related fitness. A P-value of <0.05 was considered statistically significant. Results Age-related decreases in health-related fitness were shown for sit-ups, back strength, grip strength, side steps, trunk extension, and agility (P<0.05). An age-related decrease in QoL, specifically in physical functioning, role limitation due to physical problems, and physical component score, was also demonstrated (P<0.05). Multiple linear regression analyses demonstrated that back strength significantly contributed to the physical component of QoL (adjusted beta of 0.268 [P<0.05]). Conclusion Back strength was positively correlated with the physical component of QoL among the examined dimensions of health-related fitness. Health-related fitness, as well as the physical component of QoL, declined with increasing age. PMID:25258526

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

Asymptotic Linear Spectral Statistics for Spiked Hermitian Random Matrices

NASA Astrophysics Data System (ADS)

Passemier, Damien; McKay, Matthew R.; Chen, Yang

2015-07-01

Using the Coulomb Fluid method, this paper derives central limit theorems (CLTs) for linear spectral statistics of three "spiked" Hermitian random matrix ensembles. These include Johnstone's spiked model (i.e., central Wishart with spiked correlation), non-central Wishart with rank-one non-centrality, and a related class of non-central matrices. For a generic linear statistic, we derive simple and explicit CLT expressions as the matrix dimensions grow large. For all three ensembles under consideration, we find that the primary effect of the spike is to introduce an correction term to the asymptotic mean of the linear spectral statistic, which we characterize with simple formulas. The utility of our proposed framework is demonstrated through application to three different linear statistics problems: the classical likelihood ratio test for a population covariance, the capacity analysis of multi-antenna wireless communication systems with a line-of-sight transmission path, and a classical multiple sample significance testing problem.

Discriminative analysis of non-linear brain connectivity for leukoaraiosis with resting-state fMRI

NASA Astrophysics Data System (ADS)

Lai, Youzhi; Xu, Lele; Yao, Li; Wu, Xia

2015-03-01

Leukoaraiosis (LA) describes diffuse white matter abnormalities on CT or MR brain scans, often seen in the normal elderly and in association with vascular risk factors such as hypertension, or in the context of cognitive impairment. The mechanism of cognitive dysfunction is still unclear. The recent clinical studies have revealed that the severity of LA was not corresponding to the cognitive level, and functional connectivity analysis is an appropriate method to detect the relation between LA and cognitive decline. However, existing functional connectivity analyses of LA have been mostly limited to linear associations. In this investigation, a novel measure utilizing the extended maximal information coefficient (eMIC) was applied to construct non-linear functional connectivity in 44 LA subjects (9 dementia, 25 mild cognitive impairment (MCI) and 10 cognitively normal (CN)). The strength of non-linear functional connections for the first 1% of discriminative power increased in MCI compared with CN and dementia, which was opposed to its linear counterpart. Further functional network analysis revealed that the changes of the non-linear and linear connectivity have similar but not completely the same spatial distribution in human brain. In the multivariate pattern analysis with multiple classifiers, the non-linear functional connectivity mostly identified dementia, MCI and CN from LA with a relatively higher accuracy rate than the linear measure. Our findings revealed the non-linear functional connectivity provided useful discriminative power in classification of LA, and the spatial distributed changes between the non-linear and linear measure may indicate the underlying mechanism of cognitive dysfunction in LA.

Multiple Streaming and the Probability Distribution of Density in Redshift Space

NASA Astrophysics Data System (ADS)

Hui, Lam; Kofman, Lev; Shandarin, Sergei F.

2000-07-01

We examine several aspects of redshift distortions by expressing the redshift-space density in terms of the eigenvalues and orientation of the local Lagrangian deformation tensor. We explore the importance of multiple streaming using the Zeldovich approximation (ZA), and compute the average number of streams in both real and redshift space. We find that multiple streaming can be significant in redshift space but negligible in real space, even at moderate values of the linear fluctuation amplitude (σl<~1). Moreover, unlike their real-space counterparts, redshift-space multiple streams can flow past each other with minimal interactions. Such nonlinear redshift-space effects, which are physically distinct from the fingers-of-God due to small-scale virialized motions, might in part explain the well-known departure of redshift distortions from the classic linear prediction by Kaiser, even at relatively large scales where the corresponding density field in real space is well described by linear perturbation theory. We also compute, using the ZA, the probability distribution function (PDF) of the density, as well as S3, in real and redshift space, and compare it with the PDF measured from N-body simulations. The role of caustics in defining the character of the high-density tail is examined. We find that (non-Lagrangian) smoothing, due to both finite resolution or discreteness and small-scale velocity dispersions, is very effective in erasing caustic structures, unless the initial power spectrum is sufficiently truncated.

A simple and selective method for the measurement of azadirachtin and related azadirachtoid levels in fruits and vegetables using liquid chromatography electrospray ionization tandem mass spectrometry.

PubMed

Sarais, Giorgia; Caboni, Pierluigi; Sarritzu, Erika; Russo, Mariateresa; Cabras, Paolo

2008-05-14

Neem-based insecticides containing azadirachtin and related azadirachtoids are widely used in agriculture. Here, we report an analytical method for the rapid and accurate quantification of the insecticide azadirachtin A and B and other azadirachtoids such as salannin, nimbin, and their deacetylated analogues on tomatoes and peaches. Azadirachtoids were extracted from fruits and vegetables with acetonitrile. Using high-performance liquid chromatography/electrospray ionization tandem mass spectrometer, azadirachtoids were selectively detected monitoring the multiple reaction transitions of sodium adduct precursor ions. For azadirachtin A, calibration was linear over a working range of 1-1000 microg/L with r > 0.996. The limit of detection and limit of quantification for azadirachtin A were 0.4 and 0.8 microg/kg, respectively. The presence of interfering compounds in the peach and tomato extracts was evaluated and found to be minimal. Because of the linear behavior, it was concluded that the multiple reaction transitions of sodium adduct ions can be used for analytical purposes, that is, for the identification and quantification of azadirachtin A and B and related azadirachtoids in fruit and vegetable extracts at trace levels.

Linear increases in carbon nanotube density through multiple transfer technique.

PubMed

Shulaker, Max M; Wei, Hai; Patil, Nishant; Provine, J; Chen, Hong-Yu; Wong, H-S P; Mitra, Subhasish

2011-05-11

We present a technique to increase carbon nanotube (CNT) density beyond the as-grown CNT density. We perform multiple transfers, whereby we transfer CNTs from several growth wafers onto the same target surface, thereby linearly increasing CNT density on the target substrate. This process, called transfer of nanotubes through multiple sacrificial layers, is highly scalable, and we demonstrate linear CNT density scaling up to 5 transfers. We also demonstrate that this linear CNT density increase results in an ideal linear increase in drain-source currents of carbon nanotube field effect transistors (CNFETs). Experimental results demonstrate that CNT density can be improved from 2 to 8 CNTs/μm, accompanied by an increase in drain-source CNFET current from 4.3 to 17.4 μA/μm.

Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis

ERIC Educational Resources Information Center

Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.

2006-01-01

Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…

Partitioning sources of variation in vertebrate species richness

USGS Publications Warehouse

Boone, R.B.; Krohn, W.B.

2000-01-01

Aim: To explore biogeographic patterns of terrestrial vertebrates in Maine, USA using techniques that would describe local and spatial correlations with the environment. Location: Maine, USA. Methods: We delineated the ranges within Maine (86,156 km2) of 275 species using literature and expert review. Ranges were combined into species richness maps, and compared to geomorphology, climate, and woody plant distributions. Methods were adapted that compared richness of all vertebrate classes to each environmental correlate, rather than assessing a single explanatory theory. We partitioned variation in species richness into components using tree and multiple linear regression. Methods were used that allowed for useful comparisons between tree and linear regression results. For both methods we partitioned variation into broad-scale (spatially autocorrelated) and fine-scale (spatially uncorrelated) explained and unexplained components. By partitioning variance, and using both tree and linear regression in analyses, we explored the degree of variation in species richness for each vertebrate group that Could be explained by the relative contribution of each environmental variable. Results: In tree regression, climate variation explained richness better (92% of mean deviance explained for all species) than woody plant variation (87%) and geomorphology (86%). Reptiles were highly correlated with environmental variation (93%), followed by mammals, amphibians, and birds (each with 84-82% deviance explained). In multiple linear regression, climate was most closely associated with total vertebrate richness (78%), followed by woody plants (67%) and geomorphology (56%). Again, reptiles were closely correlated with the environment (95%), followed by mammals (73%), amphibians (63%) and birds (57%). Main conclusions: Comparing variation explained using tree and multiple linear regression quantified the importance of nonlinear relationships and local interactions between species richness and environmental variation, identifying the importance of linear relationships between reptiles and the environment, and nonlinear relationships between birds and woody plants, for example. Conservation planners should capture climatic variation in broad-scale designs; temperatures may shift during climate change, but the underlying correlations between the environment and species richness will presumably remain.

Artificial neural networks environmental forecasting in comparison with multiple linear regression technique: From heavy metals to organic micropollutants screening in agricultural soils

NASA Astrophysics Data System (ADS)

Bonelli, Maria Grazia; Ferrini, Mauro; Manni, Andrea

2016-12-01

The assessment of metals and organic micropollutants contamination in agricultural soils is a difficult challenge due to the extensive area used to collect and analyze a very large number of samples. With Dioxins and dioxin-like PCBs measurement methods and subsequent the treatment of data, the European Community advises the develop low-cost and fast methods allowing routing analysis of a great number of samples, providing rapid measurement of these compounds in the environment, feeds and food. The aim of the present work has been to find a method suitable to describe the relations occurring between organic and inorganic contaminants and use the value of the latter in order to forecast the former. In practice, the use of a metal portable soil analyzer coupled with an efficient statistical procedure enables the required objective to be achieved. Compared to Multiple Linear Regression, the Artificial Neural Networks technique has shown to be an excellent forecasting method, though there is no linear correlation between the variables to be analyzed.

Older age, higher perceived disability and depressive symptoms predict the amount and severity of work-related difficulties in persons with multiple sclerosis.

PubMed

Raggi, Alberto; Giovannetti, Ambra Mara; Schiavolin, Silvia; Brambilla, Laura; Brenna, Greta; Confalonieri, Paolo Agostino; Cortese, Francesca; Frangiamore, Rita; Leonardi, Matilde; Mantegazza, Renato Emilio; Moscatelli, Marco; Ponzio, Michela; Torri Clerici, Valentina; Zaratin, Paola; De Torres, Laura

2018-04-16

This cross-sectional study aims to identify the predictors of work-related difficulties in a sample of employed persons with multiple sclerosis as addressed with the Multiple Sclerosis Questionnaire for Job Difficulties. Hierarchical linear regression analysis was conducted to identify predictors of work difficulties: predictors included demographic variables (age, formal education), disease duration and severity, perceived disability and psychological variables (cognitive dysfunction, depression and anxiety). The targets were the questionnaire's overall score and its six subscales. A total of 177 participants (108 females, aged 21-63) were recruited. Age, perceived disability and depression were direct and significant predictors of the questionnaire total score, and the final model explained 43.7% of its variation. The models built on the questionnaire's subscales show that perceived disability and depression were direct and significant predictors of most of its subscales. Our results show that, among patients with multiple sclerosis, those who were older, with higher perceived disability and higher depression symptoms have more and more severe work-related difficulties. The Multiple Sclerosis Questionnaire for Job Difficulties can be fruitfully exploited to plan tailored actions to limit the likelihood of near-future job loss in persons of working age with multiple sclerosis. Implications for rehabilitation Difficulties with work are common among people with multiple sclerosis and are usually addressed in terms of unemployment or job loss. The Multiple Sclerosis Questionnaire for Job Difficulties is a disease-specific questionnaire developed to address the amount and severity of work-related difficulties. We found that work-related difficulties were associated to older age, higher perceived disability and depressive symptoms. Mental health issues and perceived disability should be consistently included in future research targeting work-related difficulties.

Linear Approximation SAR Azimuth Processing Study

NASA Technical Reports Server (NTRS)

Lindquist, R. B.; Masnaghetti, R. K.; Belland, E.; Hance, H. V.; Weis, W. G.

1979-01-01

A segmented linear approximation of the quadratic phase function that is used to focus the synthetic antenna of a SAR was studied. Ideal focusing, using a quadratic varying phase focusing function during the time radar target histories are gathered, requires a large number of complex multiplications. These can be largely eliminated by using linear approximation techniques. The result is a reduced processor size and chip count relative to ideally focussed processing and a correspondingly increased feasibility for spaceworthy implementation. A preliminary design and sizing for a spaceworthy linear approximation SAR azimuth processor meeting requirements similar to those of the SEASAT-A SAR was developed. The study resulted in a design with approximately 1500 IC's, 1.2 cubic feet of volume, and 350 watts of power for a single look, 4000 range cell azimuth processor with 25 meters resolution.

Lichen-based critical loads for atmospheric nitrogen deposition in Western Oregon and Washington forests, USA

Treesearch

Linda H. Geiser; Sarah E. Jovan; Doug A. Glavich; Matthew K. Porter

2010-01-01

Critical loads (CLs) define maximum atmospheric deposition levels apparently preventative of ecosystem harm. We present first nitrogen CLs for northwestern North America's maritime forests. Using multiple linear regression, we related epiphytic-macrolichen community composition to: 1) wet deposition from the National Atmospheric Deposition Program, 2) wet, dry,...

Touch Processing and Social Behavior in ASD

ERIC Educational Resources Information Center

Miguel, Helga O.; Sampaio, Adriana; Martínez-Regueiro, Rocío; Gómez-Guerrero, Lorena; López-Dóriga, Cristina Gutiérrez; Gómez, Sonia; Carracedo, Ángel; Fernández-Prieto, Montse

2017-01-01

Abnormal patterns of touch processing have been linked to core symptoms in ASD. This study examined the relation between tactile processing patterns and social problems in 44 children and adolescents with ASD, aged 6-14 (M = 8.39 ± 2.35). Multiple linear regression indicated significant associations between touch processing and social problems. No…

Identifying Aspects of Parental Involvement that Affect the Academic Achievement of High School Students

ERIC Educational Resources Information Center

Roulette-McIntyre, Ovella; Bagaka's, Joshua G.; Drake, Daniel D.

2005-01-01

This study identified parental practices that relate positively to high school students' academic performance. Parents of 643 high school students participated in the study. Data analysis, using a multiple linear regression model, shows parent-school connection, student gender, and race are significant predictors of student academic performance.…

Cue Reliance in L2 Written Production

ERIC Educational Resources Information Center

Wiechmann, Daniel; Kerz, Elma

2014-01-01

Second language learners reach expert levels in relative cue weighting only gradually. On the basis of ensemble machine learning models fit to naturalistic written productions of German advanced learners of English and expert writers, we set out to reverse engineer differences in the weighting of multiple cues in a clause linearization problem. We…

Association of Alimentary Factors and Nutritional Status with Caries in Children of Leon, Mexico.

PubMed

Guizar, Juan Manuel; Muñoz, Nathalie; Amador, Norma; Garcia, Gabriela

To determine the association between types of food consumed, nutritional status (BMI) and caries in schoolchildren. A cross-sectional study was performed with 224 schoolchildren 6 to 12 years of age. DMFT/ dmft indices, level of oral hygiene, nutritional status as quantified by BMI and types of food consumed were determined in all participants. Data were analysed using multiple linear regression with significance set at p < 0.05. Caries prevalence was 36%. In the multiple linear regression analysis adjusted for BMI, variables related to a higher number of caries were younger age and lower intake of vitamin D, calcium and fiber, with higher consumption of phosphorous and carbohydrates (R2 = 0.30; p < 0.0001 for the model). Sweetened softdrinks and chewy candy were risk factors for higher caries prevalence, while consuming milk and carrots were protectors. Caries in schoolchildren is highly prevalent in this community and is related to younger age and lower intake of vitamin D, calcium and fiber, but a higher consumption of phosphorous and carbohydrates. No relationship was found between caries and nutritional status.

Advanced statistics: linear regression, part II: multiple linear regression.

PubMed

Marill, Keith A

2004-01-01

The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

Fast discovery and visualization of conserved regions in DNA sequences using quasi-alignment

PubMed Central

2013-01-01

Background Next Generation Sequencing techniques are producing enormous amounts of biological sequence data and analysis becomes a major computational problem. Currently, most analysis, especially the identification of conserved regions, relies heavily on Multiple Sequence Alignment and its various heuristics such as progressive alignment, whose run time grows with the square of the number and the length of the aligned sequences and requires significant computational resources. In this work, we present a method to efficiently discover regions of high similarity across multiple sequences without performing expensive sequence alignment. The method is based on approximating edit distance between segments of sequences using p-mer frequency counts. Then, efficient high-throughput data stream clustering is used to group highly similar segments into so called quasi-alignments. Quasi-alignments have numerous applications such as identifying species and their taxonomic class from sequences, comparing sequences for similarities, and, as in this paper, discovering conserved regions across related sequences. Results In this paper, we show that quasi-alignments can be used to discover highly similar segments across multiple sequences from related or different genomes efficiently and accurately. Experiments on a large number of unaligned 16S rRNA sequences obtained from the Greengenes database show that the method is able to identify conserved regions which agree with known hypervariable regions in 16S rRNA. Furthermore, the experiments show that the proposed method scales well for large data sets with a run time that grows only linearly with the number and length of sequences, whereas for existing multiple sequence alignment heuristics the run time grows super-linearly. Conclusion Quasi-alignment-based algorithms can detect highly similar regions and conserved areas across multiple sequences. Since the run time is linear and the sequences are converted into a compact clustering model, we are able to identify conserved regions fast or even interactively using a standard PC. Our method has many potential applications such as finding characteristic signature sequences for families of organisms and studying conserved and variable regions in, for example, 16S rRNA. PMID:24564200

Fast discovery and visualization of conserved regions in DNA sequences using quasi-alignment.

PubMed

Nagar, Anurag; Hahsler, Michael

2013-01-01

Next Generation Sequencing techniques are producing enormous amounts of biological sequence data and analysis becomes a major computational problem. Currently, most analysis, especially the identification of conserved regions, relies heavily on Multiple Sequence Alignment and its various heuristics such as progressive alignment, whose run time grows with the square of the number and the length of the aligned sequences and requires significant computational resources. In this work, we present a method to efficiently discover regions of high similarity across multiple sequences without performing expensive sequence alignment. The method is based on approximating edit distance between segments of sequences using p-mer frequency counts. Then, efficient high-throughput data stream clustering is used to group highly similar segments into so called quasi-alignments. Quasi-alignments have numerous applications such as identifying species and their taxonomic class from sequences, comparing sequences for similarities, and, as in this paper, discovering conserved regions across related sequences. In this paper, we show that quasi-alignments can be used to discover highly similar segments across multiple sequences from related or different genomes efficiently and accurately. Experiments on a large number of unaligned 16S rRNA sequences obtained from the Greengenes database show that the method is able to identify conserved regions which agree with known hypervariable regions in 16S rRNA. Furthermore, the experiments show that the proposed method scales well for large data sets with a run time that grows only linearly with the number and length of sequences, whereas for existing multiple sequence alignment heuristics the run time grows super-linearly. Quasi-alignment-based algorithms can detect highly similar regions and conserved areas across multiple sequences. Since the run time is linear and the sequences are converted into a compact clustering model, we are able to identify conserved regions fast or even interactively using a standard PC. Our method has many potential applications such as finding characteristic signature sequences for families of organisms and studying conserved and variable regions in, for example, 16S rRNA.

Amesos2 and Belos: Direct and Iterative Solvers for Large Sparse Linear Systems

DOE PAGES

Bavier, Eric; Hoemmen, Mark; Rajamanickam, Sivasankaran; ...

2012-01-01

Solvers for large sparse linear systems come in two categories: direct and iterative. Amesos2, a package in the Trilinos software project, provides direct methods, and Belos, another Trilinos package, provides iterative methods. Amesos2 offers a common interface to many different sparse matrix factorization codes, and can handle any implementation of sparse matrices and vectors, via an easy-to-extend C++ traits interface. It can also factor matrices whose entries have arbitrary “Scalar” type, enabling extended-precision and mixed-precision algorithms. Belos includes many different iterative methods for solving large sparse linear systems and least-squares problems. Unlike competing iterative solver libraries, Belos completely decouples themore » algorithms from the implementations of the underlying linear algebra objects. This lets Belos exploit the latest hardware without changes to the code. Belos favors algorithms that solve higher-level problems, such as multiple simultaneous linear systems and sequences of related linear systems, faster than standard algorithms. The package also supports extended-precision and mixed-precision algorithms. Together, Amesos2 and Belos form a complete suite of sparse linear solvers.« less

Simulating first order optical systems—algorithms for and composition of discrete linear canonical transforms

NASA Astrophysics Data System (ADS)

Healy, John J.

2018-01-01

The linear canonical transforms (LCTs) are a parameterised group of linear integral transforms. The LCTs encompass a number of well-known transformations as special cases, including the Fourier transform, fractional Fourier transform, and the Fresnel integral. They relate the scalar wave fields at the input and output of systems composed of thin lenses and free space, along with other quadratic phase systems. In this paper, we perform a systematic search of all algorithms based on up to five stages of magnification, chirp multiplication and Fourier transforms. Based on that search, we propose a novel algorithm, for which we present numerical results. We compare the sampling requirements of three algorithms. Finally, we discuss some issues surrounding the composition of discrete LCTs.

Bayesian dynamical systems modelling in the social sciences.

PubMed

Ranganathan, Shyam; Spaiser, Viktoria; Mann, Richard P; Sumpter, David J T

2014-01-01

Data arising from social systems is often highly complex, involving non-linear relationships between the macro-level variables that characterize these systems. We present a method for analyzing this type of longitudinal or panel data using differential equations. We identify the best non-linear functions that capture interactions between variables, employing Bayes factor to decide how many interaction terms should be included in the model. This method punishes overly complicated models and identifies models with the most explanatory power. We illustrate our approach on the classic example of relating democracy and economic growth, identifying non-linear relationships between these two variables. We show how multiple variables and variable lags can be accounted for and provide a toolbox in R to implement our approach.

Theory of mind and executive function: working-memory capacity and inhibitory control as predictors of false-belief task performance.

PubMed

Mutter, Brigitte; Alcorn, Mark B; Welsh, Marilyn

2006-06-01

This study of the relationship between theory of mind and executive function examined whether on the false-belief task age differences between 3 and 5 ears of age are related to development of working-memory capacity and inhibitory processes. 72 children completed tasks measuring false belief, working memory, and inhibition. Significant age effects were observed for false-belief and working-memory performance, as well as for the false-alarm and perseveration measures of inhibition. A simultaneous multiple linear regression specified the contribution of age, inhibition, and working memory to the prediction of false-belief performance. This model was significant, explaining a total of 36% of the variance. To examine the independent contributions of the working-memory and inhibition variables, after controlling for age, two hierarchical multiple linear regressions were conducted. These multiple regression analyses indicate that working memory and inhibition make small, overlapping contributions to false-belief performance after accounting for age, but that working memory, as measured in this study, is a somewhat better predictor of false-belief understanding than is inhibition.

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.)

The Ability of American Football Helmets to Manage Linear Acceleration With Repeated High-Energy Impacts.

PubMed

Cournoyer, Janie; Post, Andrew; Rousseau, Philippe; Hoshizaki, Blaine

2016-03-01

Football players can receive up to 1400 head impacts per season, averaging 6.3 impacts per practice and 14.3 impacts per game. A decrease in the capacity of a helmet to manage linear acceleration with multiple impacts could increase the risk of traumatic brain injury. To investigate the ability of football helmets to manage linear acceleration with multiple high-energy impacts. Descriptive laboratory study. Laboratory. We collected linear-acceleration data for 100 impacts at 6 locations on 4 helmets of different models currently used in football. Impacts 11 to 20 were compared with impacts 91 to 100 for each of the 6 locations. Linear acceleration was greater after multiple impacts (91-100) than after the first few impacts (11-20) for the front, front-boss, rear, and top locations. However, these differences are not clinically relevant as they do not affect the risk for head injury. American football helmet performance deteriorated with multiple impacts, but this is unlikely to be a factor in head-injury causation during a game or over a season.

Impacts of education level and employment status on health-related quality of life in multiple sclerosis patients.

PubMed

Šabanagić-Hajrić, Selma; Alajbegović, Azra

2015-02-01

To evaluate the impacts of education level and employment status on health-related quality of life (HRQoL) in multiple sclerosis patients. This study included 100 multiple sclerosis patients treated at the Department of Neurology, Clinical Center of the University of Sarajevo. Inclusion criteria were the Expanded Disability Status Scale (EDSS) score between 1.0 and 6.5, age between 18 and 65 years, stable disease on enrollment. Quality of life (QoL) was evaluated by the Multiple Sclerosis Quality of Life-54 questionnaire (MSQoL-54). Mann-Whitney and Kruskal-Wallis test were used for comparisons. Linear regression analyses were performed to evaluate prediction value of educational level and employment status in predicting MSQOL-54 physical and mental composite scores. Full employment status had positive impact on physical health (54.85 vs. 37.90; p les than 0.001) and mental health (59.55 vs. 45.90; p les than 0.001) composite scores. Employment status retained its independent predictability for both physical (r(2)=0.105) and mental (r(2)=0.076) composite scores in linear regression analysis. Patients with college degree had slightly higher median value of physical (49.36 vs. 45.30) and mental health composite score (66.74 vs. 55.62) comparing to others, without statistically significant difference. Employment proved to be an important factor in predicting quality of life in multiple sclerosis patients. Higher education level may determine better QOL but without significant predictive value. Sustained employment and development of vocational rehabilitation programs for MS patients living in the country with high unemployment level is an important factor in improving both physical and mental health outcomes in MS patients.

Multiple Streaming and the Probability Distribution of Density in Redshift Space

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

Hui, Lam; Kofman, Lev; Shandarin, Sergei F.

2000-07-01

We examine several aspects of redshift distortions by expressing the redshift-space density in terms of the eigenvalues and orientation of the local Lagrangian deformation tensor. We explore the importance of multiple streaming using the Zeldovich approximation (ZA), and compute the average number of streams in both real and redshift space. We find that multiple streaming can be significant in redshift space but negligible in real space, even at moderate values of the linear fluctuation amplitude ({sigma}{sub l}(less-or-similar sign)1). Moreover, unlike their real-space counterparts, redshift-space multiple streams can flow past each other with minimal interactions. Such nonlinear redshift-space effects, which aremore » physically distinct from the fingers-of-God due to small-scale virialized motions, might in part explain the well-known departure of redshift distortions from the classic linear prediction by Kaiser, even at relatively large scales where the corresponding density field in real space is well described by linear perturbation theory. We also compute, using the ZA, the probability distribution function (PDF) of the density, as well as S{sub 3}, in real and redshift space, and compare it with the PDF measured from N-body simulations. The role of caustics in defining the character of the high-density tail is examined. We find that (non-Lagrangian) smoothing, due to both finite resolution or discreteness and small-scale velocity dispersions, is very effective in erasing caustic structures, unless the initial power spectrum is sufficiently truncated. (c) 2000 The American Astronomical Society.« less

[Prediction model of health workforce and beds in county hospitals of Hunan by multiple linear regression].

PubMed

Ling, Ru; Liu, Jiawang

2011-12-01

To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.

Circulating levels of perfluoroalkyl substances and prevalent diabetes in the elderly.

PubMed

Lind, Lars; Zethelius, Björn; Salihovic, Samira; van Bavel, Bert; Lind, P Monica

2014-03-01

Several environmental contaminants, such as polychlorinated biphenyls, dioxins, bisphenol A and phthalates, have been linked to diabetes. We therefore investigated whether other kinds of contaminants, perfluoroalkyl substances (PFAS), also called perfluorinated compounds (PFCs), are also associated with diabetes. The Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study investigated 1,016 men and women aged 70 years. Seven PFAS were detected in almost all participant sera by ultra-high performance liquid chromatograph/tandem mass spectrometry. Diabetes was defined as use of hypoglycaemic agents or fasting glucose >7.0 mmol/l. 114 people had diabetes. In the linear analysis, no significant relationships were seen between the seven PFAS and prevalent diabetes. However, inclusion of the quadratic terms of the PFAS revealed a significant non-linear relationship between perfluorononanoic acid (PFNA) and diabetes, even after adjusting for multiple confounders (OR 1.96, 95% CI 1.19, 3.22, p = 0.008 for the linear term and OR 1.25, 95% CI 1.08, 1.44, p = 0.002 for the quadratic term). Perfluorooctanoic acid (PFOA) also showed such a relationship (p = 0.01). PFOA was related to the proinsulin/insulin ratio (a marker of insulin secretion), but none of the PFAS was related to the HOMA-IR (a marker of insulin resistance) following adjustment for multiple confounders. PFNA was related to prevalent diabetes in a non-monotonic fashion in this cross-sectional study, supporting the view that this perfluoroalkyl substance might influence glucose metabolism in humans at the level of exposure seen in the general elderly population.

Life cycle cost optimization of biofuel supply chains under uncertainties based on interval linear programming.

PubMed

Ren, Jingzheng; Dong, Liang; Sun, Lu; Goodsite, Michael Evan; Tan, Shiyu; Dong, Lichun

2015-01-01

The aim of this work was to develop a model for optimizing the life cycle cost of biofuel supply chain under uncertainties. Multiple agriculture zones, multiple transportation modes for the transport of grain and biofuel, multiple biofuel plants, and multiple market centers were considered in this model, and the price of the resources, the yield of grain and the market demands were regarded as interval numbers instead of constants. An interval linear programming was developed, and a method for solving interval linear programming was presented. An illustrative case was studied by the proposed model, and the results showed that the proposed model is feasible for designing biofuel supply chain under uncertainties. Copyright © 2015 Elsevier Ltd. All rights reserved.

Can Multiple "Spatial" Virtual Timelines Convey the Relatedness of Chronological Knowledge across Parallel Domains?

ERIC Educational Resources Information Center

Korallo, Liliya; Foreman, Nigel; Boyd-Davis, Stephen; Moar, Magnus; Coulson, Mark

2012-01-01

Single linear virtual timelines have been used effectively with undergraduates and primary school children to convey the chronological ordering of historical items, improving on PowerPoint and paper/textual displays. In the present study, a virtual environment (VE) consisting of three parallel related timelines (world history and the histories of…

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.

Cactus: An Introduction to Regression

ERIC Educational Resources Information Center

Hyde, Hartley

2008-01-01

When the author first used "VisiCalc," the author thought it a very useful tool when he had the formulas. But how could he design a spreadsheet if there was no known formula for the quantities he was trying to predict? A few months later, the author relates he learned to use multiple linear regression software and suddenly it all clicked into…

Mathematics. Unit 6: A Core Curriculum of Related Instruction for Apprentices.

ERIC Educational Resources Information Center

New York State Education Dept., Albany. Bureau of Occupational and Career Curriculum Development.

The mathematics unit is presented to assist apprentices to acquire a general knowledge of mathematic skills. The unit consists of nine modules: (1) basic addition, subtraction, multiplication, and division; (2) conventional linear measure; (3) using the metric system, (4) steps to take in solving problems, (5) how to calculate areas and volumes,…

Peer Influences on Academic Motivation: Exploring Multiple Methods of Assessing Youths' Most "Influential" Peer Relationships

ERIC Educational Resources Information Center

Molloy, Lauren E.; Gest, Scott D.; Rulison, Kelly L.

2011-01-01

The present study examines the relative role of three distinct types of peer relationships (reciprocated friendships, frequent interactions, and shared group membership) in within-year changes in academic self-concept and engagement before and after the transition to middle school (fifth and seventh grade). In a series of linear regression…

Too much of a good thing? How breadth of extracurricular participation relates to school-related affect and academic outcomes during adolescence.

PubMed

Knifsend, Casey A; Graham, Sandra

2012-03-01

Although adolescents often participate in multiple extracurricular activities, little research has examined how the breadth of activities in which an adolescent is involved relates to school-related affect and academic performance. Relying on a large, multi-ethnic sample (N = 864; 55.9% female), the current study investigated linear and non-linear relationships of 11th grade activity participation in four activity domains (academic/leadership groups, arts activities, clubs, and sports) to adolescents' sense of belonging at school, academic engagement, and grade point average, contemporarily and in 12th grade. Results of multiple regression models revealed curvilinear relationships for sense of belonging at school in 11th and 12th grade, grade point average in 11th grade, and academic engagement in 12th grade. Adolescents who were moderately involved (i.e., in two domains) reported a greater sense of belonging at school in 11th and 12th grade, a higher grade point average in 11th grade, and greater academic engagement in 12th grade, relative to those who were more or less involved. Furthermore, adolescents' sense of belonging at school in 11th grade mediated the relationship of domain participation in 11th grade to academic engagement in 12th grade. This study suggests that involvement in a moderate number of activity domains promotes positive school-related affect and greater academic performance. School policy implications and recommendations are discussed.

Leukocyte telomere length correlates with glucose control in adults with recently diagnosed type 2 diabetes.

PubMed

Rosa, Erica Carine Campos Caldas; Dos Santos, Renan Renato Cruz; Fernandes, Luis Fernando Amarante; Neves, Francisco de Assis Rocha; Coelho, Michella Soares; Amato, Angelica Amorim

2018-01-01

We investigated leukocyte relative telomere length (TL) in patients with type 2 diabetes (T2D) diagnosed for no longer than five years and its association with clinical and biochemical variables. Peripheral blood leukocyte relative TL was investigated in 108 patients with T2D (87 women, 21 men) and 125 (37 women, 88 men) age-matched control subjects with normal glucose tolerance, by quantitative polymerase chain reaction. Multiple linear regression analysis was used to examine the association between relative TL and demographic, anthropometric and biochemical indicators of metabolic control among patients with T2D. Patients with T2D had a median time since diagnosis of 1 year and most were on metformin monotherapy, with satisfactory glucose control determined by HbA1c levels. Median relative TL was not different between patients with T2D and control subjects. However, multiple linear regression analyses showed that relative TL was inversely associated with time since T2D diagnosis, fasting plasma glucose levels and HbA1c levels, but not with HbA1c levels assessed in the preceding 5-12 months, after adjustment for age, sex and body mass index. This study suggests that relative TL is not shorter in patients with recently diagnosed T2D, but is inversely correlated with glucose levels, even among patients with overall satisfactory glucose control. Copyright © 2017 Elsevier B.V. All rights reserved.

Advanced statistics: linear regression, part I: simple linear regression.

PubMed

Marill, Keith A

2004-01-01

Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

Fast linear feature detection using multiple directional non-maximum suppression.

PubMed

Sun, C; Vallotton, P

2009-05-01

The capacity to detect linear features is central to image analysis, computer vision and pattern recognition and has practical applications in areas such as neurite outgrowth detection, retinal vessel extraction, skin hair removal, plant root analysis and road detection. Linear feature detection often represents the starting point for image segmentation and image interpretation. In this paper, we present a new algorithm for linear feature detection using multiple directional non-maximum suppression with symmetry checking and gap linking. Given its low computational complexity, the algorithm is very fast. We show in several examples that it performs very well in terms of both sensitivity and continuity of detected linear features.

An Efficient Spectral Method for Ordinary Differential Equations with Rational Function Coefficients

NASA Technical Reports Server (NTRS)

Coutsias, Evangelos A.; Torres, David; Hagstrom, Thomas

1994-01-01

We present some relations that allow the efficient approximate inversion of linear differential operators with rational function coefficients. We employ expansions in terms of a large class of orthogonal polynomial families, including all the classical orthogonal polynomials. These families obey a simple three-term recurrence relation for differentiation, which implies that on an appropriately restricted domain the differentiation operator has a unique banded inverse. The inverse is an integration operator for the family, and it is simply the tridiagonal coefficient matrix for the recurrence. Since in these families convolution operators (i.e. matrix representations of multiplication by a function) are banded for polynomials, we are able to obtain a banded representation for linear differential operators with rational coefficients. This leads to a method of solution of initial or boundary value problems that, besides having an operation count that scales linearly with the order of truncation N, is computationally well conditioned. Among the applications considered is the use of rational maps for the resolution of sharp interior layers.

Destination bedside: using research findings to visualize optimal unit layouts and health information technology in support of bedside care.

PubMed

Watkins, Nicholas; Kennedy, Mary; Lee, Nelson; O'Neill, Michael; Peavey, Erin; Ducharme, Maria; Padula, Cynthia

2012-05-01

This study explored the impact of unit design and healthcare information technology (HIT) on nursing workflow and patient-centered care (PCC). Healthcare information technology and unit layout-related predictors of nursing workflow and PCC were measured during a 3-phase study involving questionnaires and work sampling methods. Stepwise multiple linear regressions demonstrated several HIT and unit layout-related factors that impact nursing workflow and PCC.

The Elementary Operations of Human Vision Are Not Reducible to Template-Matching

PubMed Central

Neri, Peter

2015-01-01

It is generally acknowledged that biological vision presents nonlinear characteristics, yet linear filtering accounts of visual processing are ubiquitous. The template-matching operation implemented by the linear-nonlinear cascade (linear filter followed by static nonlinearity) is the most widely adopted computational tool in systems neuroscience. This simple model achieves remarkable explanatory power while retaining analytical tractability, potentially extending its reach to a wide range of systems and levels in sensory processing. The extent of its applicability to human behaviour, however, remains unclear. Because sensory stimuli possess multiple attributes (e.g. position, orientation, size), the issue of applicability may be asked by considering each attribute one at a time in relation to a family of linear-nonlinear models, or by considering all attributes collectively in relation to a specified implementation of the linear-nonlinear cascade. We demonstrate that human visual processing can operate under conditions that are indistinguishable from linear-nonlinear transduction with respect to substantially different stimulus attributes of a uniquely specified target signal with associated behavioural task. However, no specific implementation of a linear-nonlinear cascade is able to account for the entire collection of results across attributes; a satisfactory account at this level requires the introduction of a small gain-control circuit, resulting in a model that no longer belongs to the linear-nonlinear family. Our results inform and constrain efforts at obtaining and interpreting comprehensive characterizations of the human sensory process by demonstrating its inescapably nonlinear nature, even under conditions that have been painstakingly fine-tuned to facilitate template-matching behaviour and to produce results that, at some level of inspection, do conform to linear filtering predictions. They also suggest that compliance with linear transduction may be the targeted outcome of carefully crafted nonlinear circuits, rather than default behaviour exhibited by basic components. PMID:26556758

Optimal space communications techniques. [using digital and phase locked systems for signal processing

NASA Technical Reports Server (NTRS)

Schilling, D. L.

1974-01-01

Digital multiplication of two waveforms using delta modulation (DM) is discussed. It is shown that while conventional multiplication of two N bit words requires N2 complexity, multiplication using DM requires complexity which increases linearly with N. Bounds on the signal-to-quantization noise ratio (SNR) resulting from this multiplication are determined and compared with the SNR obtained using standard multiplication techniques. The phase locked loop (PLL) system, consisting of a phase detector, voltage controlled oscillator, and a linear loop filter, is discussed in terms of its design and system advantages. Areas requiring further research are identified.

Aspects of porosity prediction using multivariate linear regression

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

Byrnes, A.P.; Wilson, M.D.

1991-03-01

Highly accurate multiple linear regression models have been developed for sandstones of diverse compositions. Porosity reduction or enhancement processes are controlled by the fundamental variables, Pressure (P), Temperature (T), Time (t), and Composition (X), where composition includes mineralogy, size, sorting, fluid composition, etc. The multiple linear regression equation, of which all linear porosity prediction models are subsets, takes the generalized form: Porosity = C{sub 0} + C{sub 1}(P) + C{sub 2}(T) + C{sub 3}(X) + C{sub 4}(t) + C{sub 5}(PT) + C{sub 6}(PX) + C{sub 7}(Pt) + C{sub 8}(TX) + C{sub 9}(Tt) + C{sub 10}(Xt) + C{sub 11}(PTX) + C{submore » 12}(PXt) + C{sub 13}(PTt) + C{sub 14}(TXt) + C{sub 15}(PTXt). The first four primary variables are often interactive, thus requiring terms involving two or more primary variables (the form shown implies interaction and not necessarily multiplication). The final terms used may also involve simple mathematic transforms such as log X, e{sup T}, X{sup 2}, or more complex transformations such as the Time-Temperature Index (TTI). The X term in the equation above represents a suite of compositional variable and, therefore, a fully expanded equation may include a series of terms incorporating these variables. Numerous published bivariate porosity prediction models involving P (or depth) or Tt (TTI) are effective to a degree, largely because of the high degree of colinearity between p and TTI. However, all such bivariate models ignore the unique contributions of P and Tt, as well as various X terms. These simpler models become poor predictors in regions where colinear relations change, were important variables have been ignored, or where the database does not include a sufficient range or weight distribution for the critical variables.« less

The Impact of Nutritional Interventions beyond the First 2 Years of Life on Linear Growth: A Systematic Review and Meta-Analysis.

PubMed

Roberts, Joseph L; Stein, Aryeh D

2017-03-01

A large body of evidence suggests that the first 1000 d from conception is a critical window in which interventions to address malnutrition will be most effective, but little is known about the impact on linear growth of nutritional interventions in children ≥2 y of age. The aim of this analysis was to evaluate the effectiveness of several nutrition-based interventions, specifically iron, zinc, calcium, iodine, vitamin A, multiple (≥2) micronutrients, protein, and food, at improving growth in children ≥2 y of age. A systematic search of MEDLINE and EMBASE retrieved 7794 articles. A total of 69 studies met prespecified inclusion criteria. Baseline height-for-age z score, age, nutrient dose, and study duration were examined as potential sources of heterogeneity. Zinc (mean effect size: 0.15; 95% CI: 0.06, 0.24), vitamin A (0.05; 95% CI: 0.01, 0.09), multiple micronutrients (0.26; 95% CI: 0.13, 0.39), and protein (0.68; 95% CI: 0.30, 1.05) had significant positive effects on linear growth, with baseline height-for-age z score as a significant inverse predictor of the effect size. Iron, calcium, iodine, and food-based interventions had no significant effect on growth. Age at baseline, study duration, and dose were not related to effect size for any nutrient examined. These findings suggest that zinc, vitamin A, multiple micronutrients, and protein interventions delivered after 24 mo of age can have a positive effect on linear growth, especially in populations that have experienced growth failure. © 2017 American Society for Nutrition.

Vector Potential Generation for Numerical Relativity Simulations

NASA Astrophysics Data System (ADS)

Silberman, Zachary; Faber, Joshua; Adams, Thomas; Etienne, Zachariah; Ruchlin, Ian

2017-01-01

Many different numerical codes are employed in studies of highly relativistic magnetized accretion flows around black holes. Based on the formalisms each uses, some codes evolve the magnetic field vector B, while others evolve the magnetic vector potential A, the two being related by the curl: B=curl(A). Here, we discuss how to generate vector potentials corresponding to specified magnetic fields on staggered grids, a surprisingly difficult task on finite cubic domains. The code we have developed solves this problem in two ways: a brute-force method, whose scaling is nearly linear in the number of grid cells, and a direct linear algebra approach. We discuss the success both algorithms have in generating smooth vector potential configurations and how both may be extended to more complicated cases involving multiple mesh-refinement levels. NSF ACI-1550436

Utilizing the Zero-One Linear Programming Constraints to Draw Multiple Sets of Matched Samples from a Non-Treatment Population as Control Groups for the Quasi-Experimental Design

ERIC Educational Resources Information Center

Li, Yuan H.; Yang, Yu N.; Tompkins, Leroy J.; Modarresi, Shahpar

2005-01-01

The statistical technique, "Zero-One Linear Programming," that has successfully been used to create multiple tests with similar characteristics (e.g., item difficulties, test information and test specifications) in the area of educational measurement, was deemed to be a suitable method for creating multiple sets of matched samples to be…

Natural canopy bridges effectively mitigate tropical forest fragmentation for arboreal mammals.

PubMed

Gregory, Tremaine; Carrasco-Rueda, Farah; Alonso, Alfonso; Kolowski, Joseph; Deichmann, Jessica L

2017-06-20

Linear infrastructure development and resulting habitat fragmentation are expanding in Neotropical forests, and arboreal mammals may be disproportionately impacted by these linear habitat clearings. Maintaining canopy connectivity through preservation of connecting branches (i.e. natural canopy bridges) may help mitigate that impact. Using camera traps, we evaluated crossing rates of a pipeline right-of-way in a control area with no bridges and in a test area where 13 bridges were left by the pipeline construction company. Monitoring all canopy crossing points for a year (7,102 canopy camera nights), we confirmed bridge use by 25 mammal species from 12 families. With bridge use beginning immediately after exposure and increasing over time, use rates were over two orders of magnitude higher than on the ground. We also found a positive relationship between a bridge's use rate and the number of species that used it, suggesting well-used bridges benefit multiple species. Data suggest bridge use may be related to a combination of bridge branch connectivity, multiple connections, connectivity to adjacent forest, and foliage cover. Given the high use rate and minimal cost, we recommend all linear infrastructure projects in forests with arboreal mammal populations include canopy bridges.

Multiple regression technique for Pth degree polynominals with and without linear cross products

NASA Technical Reports Server (NTRS)

Davis, J. W.

1973-01-01

A multiple regression technique was developed by which the nonlinear behavior of specified independent variables can be related to a given dependent variable. The polynomial expression can be of Pth degree and can incorporate N independent variables. Two cases are treated such that mathematical models can be studied both with and without linear cross products. The resulting surface fits can be used to summarize trends for a given phenomenon and provide a mathematical relationship for subsequent analysis. To implement this technique, separate computer programs were developed for the case without linear cross products and for the case incorporating such cross products which evaluate the various constants in the model regression equation. In addition, the significance of the estimated regression equation is considered and the standard deviation, the F statistic, the maximum absolute percent error, and the average of the absolute values of the percent of error evaluated. The computer programs and their manner of utilization are described. Sample problems are included to illustrate the use and capability of the technique which show the output formats and typical plots comparing computer results to each set of input data.

Exploring correlates of diabetes-related stress among adults with Type 1 diabetes in the T1D exchange clinic registry.

PubMed

Boden, Matthew Tyler; Gala, Sasha

2018-04-01

To explore relations between diabetes-related stress and multiple sociodemographic, diabetes health, other health, and treatment-related variables among a large sample of adults with Type 1 Diabetes (T1D). The sample consisted of 10,821 adults (over 18 years old) enrolled in the T1D Exchange Clinic Registry. The T1D Exchange clinic network consists of 67 diabetes clinical centers throughout the United States selected to broadly represent pediatric and adult patients with T1D. Variables were assessed through participant self-report and extraction of clinic chart data. Univariate and multiple linear regression (with simultaneous entry of all predictors) analyses were conducted. Robustly associated with increased diabetes-related stress across analyses were multiple sociodemographic (female [vs. male], native Hawaiian/other Pacific islander [vs. white/Caucasian], decreased age and diabetes duration), diabetes health (higher HbA1c), other health (lower general health, presence of major life stress and depression, less physical activity), and treatment related variables (use of injections/pen or combination injection/pen/pump [vs. pump], use of CGM, increased frequency of missing insulin doses and BG checking, decreased frequency of BG checking prior to bolus, receipt of mental health treatment). We replicated and extended research demonstrating that diabetes-related stress among people with T1D occurs at higher levels among those with particular sociodemographic characteristics and is associated with a range poorer diabetes health and other health variables, and multiple treatment-related variables. The strong incremental prediction of diabetes-related stress by multiple variables in our study suggests that a multi-variable, personalized approach may increase the effectiveness of treatments for diabetes-related stress. Published by Elsevier B.V.

Designing a mixture experiment when the components are subject to a nonlinear multiple-component constraint

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

Piepel, Greg F.; Cooley, Scott K.; Vienna, John D.

This article presents a case study of developing an experimental design for a constrained mixture experiment when the experimental region is defined by single-component constraints (SCCs), linear multiple-component constraints (MCCs), and a nonlinear MCC. Traditional methods and software for designing constrained mixture experiments with SCCs and linear MCCs are not directly applicable because of the nonlinear MCC. A modification of existing methodology to account for the nonlinear MCC was developed and is described in this article. The case study involves a 15-component nuclear waste glass example in which SO3 is one of the components. SO3 has a solubility limit inmore » glass that depends on the composition of the balance of the glass. A goal was to design the experiment so that SO3 would not exceed its predicted solubility limit for any of the experimental glasses. The SO3 solubility limit had previously been modeled by a partial quadratic mixture (PQM) model expressed in the relative proportions of the 14 other components. The PQM model was used to construct a nonlinear MCC in terms of all 15 components. In addition, there were SCCs and linear MCCs. This article discusses the waste glass example and how a layered design was generated to (i) account for the SCCs, linear MCCs, and nonlinear MCC and (ii) meet the goals of the study.« less

Flow Rates Measurement and Uncertainty Analysis in Multiple-Zone Water-Injection Wells from Fluid Temperature Profiles

PubMed Central

Reges, José E. O.; Salazar, A. O.; Maitelli, Carla W. S. P.; Carvalho, Lucas G.; Britto, Ursula J. B.

2016-01-01

This work is a contribution to the development of flow sensors in the oil and gas industry. It presents a methodology to measure the flow rates into multiple-zone water-injection wells from fluid temperature profiles and estimate the measurement uncertainty. First, a method to iteratively calculate the zonal flow rates using the Ramey (exponential) model was described. Next, this model was linearized to perform an uncertainty analysis. Then, a computer program to calculate the injected flow rates from experimental temperature profiles was developed. In the experimental part, a fluid temperature profile from a dual-zone water-injection well located in the Northeast Brazilian region was collected. Thus, calculated and measured flow rates were compared. The results proved that linearization error is negligible for practical purposes and the relative uncertainty increases as the flow rate decreases. The calculated values from both the Ramey and linear models were very close to the measured flow rates, presenting a difference of only 4.58 m³/d and 2.38 m³/d, respectively. Finally, the measurement uncertainties from the Ramey and linear models were equal to 1.22% and 1.40% (for injection zone 1); 10.47% and 9.88% (for injection zone 2). Therefore, the methodology was successfully validated and all objectives of this work were achieved. PMID:27420068

Theory of chromatic noise masking applied to testing linearity of S-cone detection mechanisms.

PubMed

Giulianini, Franco; Eskew, Rhea T

2007-09-01

A method for testing the linearity of cone combination of chromatic detection mechanisms is applied to S-cone detection. This approach uses the concept of mechanism noise, the noise as seen by a postreceptoral neural mechanism, to represent the effects of superposing chromatic noise components in elevating thresholds and leads to a parameter-free prediction for a linear mechanism. The method also provides a test for the presence of multiple linear detectors and off-axis looking. No evidence for multiple linear mechanisms was found when using either S-cone increment or decrement tests. The results for both S-cone test polarities demonstrate that these mechanisms combine their cone inputs nonlinearly.

Impact of pine tip moth attack on loblolly pine

Treesearch

Roy Hedden

1999-01-01

Data on the impact of Nantucket pine tip moth, Rhyacionia frustrana, attack on the height of loblolly pine, Pinus taeda, in the first three growing seasons after planting from three locations in eastern North Carolina (U.S.A.) was used to develop multiple linear regression models relating tree height to tip moth infestation level in each growing season. These models...

Response Rate and Teaching Effectiveness in Institutional Student Evaluation of Teaching: A Multiple Linear Regression Study

ERIC Educational Resources Information Center

Al-Maamari, Faisal

2015-01-01

It is important to consider the question of whether teacher-, course-, and student-related factors affect student ratings of instructors in Student Evaluation of Teaching (SET) in English Language Teaching (ELT). This paper reports on a statistical analysis of SET in two large EFL programmes at a university setting in the Sultanate of Oman. I…

Examining the Influence of Selected Factors on Perceived Co-Op Work-Term Quality from a Student Perspective

ERIC Educational Resources Information Center

Drewery, David; Nevison, Colleen; Pretti, T. Judene; Cormier, Lauren; Barclay, Sage; Pennaforte, Antoine

2016-01-01

This study discusses and tests a conceptual model of co-op work-term quality from a student perspective. Drawing from an earlier exploration of co-op students' perceptions of work-term quality, variables related to role characteristics, interpersonal dynamics, and organizational elements were used in a multiple linear regression analysis to…

Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

NASA Astrophysics Data System (ADS)

Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.

2008-04-01

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

Language and hope in schizophrenia-spectrum disorders.

PubMed

Bonfils, Kelsey A; Luther, Lauren; Firmin, Ruth L; Lysaker, Paul H; Minor, Kyle S; Salyers, Michelle P

2016-11-30

Hope is integral to recovery for those with schizophrenia. Considering recent advancements in the examination of clients' lexical qualities, we were interested in how clients' words reflect hope. Using computerized lexical analysis, we examined social, emotion, and future words' relations to hope and its pathways and agency components. Forty-five clients provided detailed narratives about their life and mental illness. Transcripts were analyzed using the Linguistic Inquiry and Word Count program (LIWC), which assigns words to categories (e.g., "anxiety") based on a pre-existing dictionary. Correlations and linear multiple regression were used to examine relationships between lexical qualities and hope. Hope and its subcomponents had significant or trending bivariate correlations in expected directions with several emotion-related word categories (anger and sadness) but were not associated with expected categories such as social words, positive emotions, optimism, achievement, and future words. In linear multiple regressions, no LIWC variable significantly predicted hope agency, but anger words significantly predicted both total hope and hope pathways. Our findings indicate lexical analysis tools can be used to investigate recovery-oriented concepts such as hope, and results may inform clinical practice. Future research should aim to replicate our findings in larger samples. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Differential Dynamic Engagement within 24 SH3 Domain: Peptide Complexes Revealed by Co-Linear Chemical Shift Perturbation Analysis

PubMed Central

Stollar, Elliott J.; Lin, Hong; Davidson, Alan R.; Forman-Kay, Julie D.

2012-01-01

There is increasing evidence for the functional importance of multiple dynamically populated states within single proteins. However, peptide binding by protein-protein interaction domains, such as the SH3 domain, has generally been considered to involve the full engagement of peptide to the binding surface with minimal dynamics and simple methods to determine dynamics at the binding surface for multiple related complexes have not been described. We have used NMR spectroscopy combined with isothermal titration calorimetry to comprehensively examine the extent of engagement to the yeast Abp1p SH3 domain for 24 different peptides. Over one quarter of the domain residues display co-linear chemical shift perturbation (CCSP) behavior, in which the position of a given chemical shift in a complex is co-linear with the same chemical shift in the other complexes, providing evidence that each complex exists as a unique dynamic rapidly inter-converting ensemble. The extent the specificity determining sub-surface of AbpSH3 is engaged as judged by CCSP analysis correlates with structural and thermodynamic measurements as well as with functional data, revealing the basis for significant structural and functional diversity amongst the related complexes. Thus, CCSP analysis can distinguish peptide complexes that may appear identical in terms of general structure and percent peptide occupancy but have significant local binding differences across the interface, affecting their ability to transmit conformational change across the domain and resulting in functional differences. PMID:23251481

INTRODUCTION TO A COMBINED MULTIPLE LINEAR REGRESSION AND ARMA MODELING APPROACH FOR BEACH BACTERIA PREDICTION

EPA Science Inventory

Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...

Ranking Forestry Investments With Parametric Linear Programming

Treesearch

Paul A. Murphy

1976-01-01

Parametric linear programming is introduced as a technique for ranking forestry investments under multiple constraints; it combines the advantages of simple tanking and linear programming as capital budgeting tools.

Fuzzy adaptive interacting multiple model nonlinear filter for integrated navigation sensor fusion.

PubMed

Tseng, Chien-Hao; Chang, Chih-Wen; Jwo, Dah-Jing

2011-01-01

In this paper, the application of the fuzzy interacting multiple model unscented Kalman filter (FUZZY-IMMUKF) approach to integrated navigation processing for the maneuvering vehicle is presented. The unscented Kalman filter (UKF) employs a set of sigma points through deterministic sampling, such that a linearization process is not necessary, and therefore the errors caused by linearization as in the traditional extended Kalman filter (EKF) can be avoided. The nonlinear filters naturally suffer, to some extent, the same problem as the EKF for which the uncertainty of the process noise and measurement noise will degrade the performance. As a structural adaptation (model switching) mechanism, the interacting multiple model (IMM), which describes a set of switching models, can be utilized for determining the adequate value of process noise covariance. The fuzzy logic adaptive system (FLAS) is employed to determine the lower and upper bounds of the system noise through the fuzzy inference system (FIS). The resulting sensor fusion strategy can efficiently deal with the nonlinear problem for the vehicle navigation. The proposed FUZZY-IMMUKF algorithm shows remarkable improvement in the navigation estimation accuracy as compared to the relatively conventional approaches such as the UKF and IMMUKF.

Influence of age on the correlations of hematological and biochemical variables with the stability of erythrocyte membrane in relation to sodium dodecyl sulfate.

PubMed

de Freitas, Mariana V; Marquez-Bernardes, Liandra F; de Arvelos, Letícia R; Paraíso, Lara F; Gonçalves E Oliveira, Ana Flávia M; Mascarenhas Netto, Rita de C; Neto, Morun Bernardino; Garrote-Filho, Mario S; de Souza, Paulo César A; Penha-Silva, Nilson

2014-10-01

To evaluate the influence of age on the relationships between biochemical and hematological variables and stability of erythrocyte membrane in relation to the sodium dodecyl sulfate (SDS) in population of 105 female volunteers between 20 and 90 years. The stability of RBC membrane was determined by non-linear regression of the dependency of the absorbance of hemoglobin released as a function of SDS concentration, represented by the half-transition point of the curve (D50) and the variation in the concentration of the detergent to promote lysis (dD). There was an age-dependent increase in the membrane stability in relation to SDS. Analyses by multiple linear regression showed that this stability increase is significantly related to the hematological variable red cell distribution width (RDW) and the biochemical variables blood albumin and cholesterol. The positive association between erythrocyte stability and RDW may reflect one possible mechanism involved in the clinical meaning of this hematological index.

Multiple solution of linear algebraic systems by an iterative method with recomputed preconditioner in the analysis of microstrip structures

NASA Astrophysics Data System (ADS)

Ahunov, Roman R.; Kuksenko, Sergey P.; Gazizov, Talgat R.

2016-06-01

A multiple solution of linear algebraic systems with dense matrix by iterative methods is considered. To accelerate the process, the recomputing of the preconditioning matrix is used. A priory condition of the recomputing based on change of the arithmetic mean of the current solution time during the multiple solution is proposed. To confirm the effectiveness of the proposed approach, the numerical experiments using iterative methods BiCGStab and CGS for four different sets of matrices on two examples of microstrip structures are carried out. For solution of 100 linear systems the acceleration up to 1.6 times, compared to the approach without recomputing, is obtained.

Health related quality of life in parents of six to eight year old children with Down syndrome.

PubMed

Marchal, Jan Pieter; Maurice-Stam, Heleen; Hatzmann, Janneke; van Trotsenburg, A S Paul; Grootenhuis, Martha A

2013-11-01

Raising a child with Down syndrome (DS) has been found to be associated with lowered health related quality of life (HRQoL) in the domains cognitive functioning, social functioning, daily activities and vitality. We aimed to explore which socio-demographics, child functioning and psychosocial variables were related to these HRQoL domains in parents of children with DS. Parents of 98 children with DS completed the TNO-AZL adult quality of life questionnaire (TAAQOL) and a questionnaire assessing socio-demographic, child functioning and psychosocial predictors. Using multiple linear regression analyses for each category of predictors, we selected relevant predictors for the final models. The final multiple linear regression models revealed that cognitive functioning was best predicted by the sleep of the child (β=.29, p<.01) and by the parent having given up a hobby (β=-.29, p<.01), social functioning by the quality of the partner relation (β=.34, p<.001), daily activities by the parent having to care for an ill friend or family member (β=-.31, p<.01), and vitality by the parent having enough personal time (β=.32, p<.01). Overall, psychosocial variables rather than socio-demographics or child functioning showed most consistent and powerful relations to the HRQoL domains of cognitive functioning, social functioning, daily activities and vitality. These psychosocial variables mainly related to social support and time pressure. Systematic screening of parents to detect problems timely, and interventions targeting the supportive network and the demands in time are recommended. Copyright © 2013 Elsevier Ltd. All rights reserved.

Does linear separability really matter? Complex visual search is explained by simple search

PubMed Central

Vighneshvel, T.; Arun, S. P.

2013-01-01

Visual search in real life involves complex displays with a target among multiple types of distracters, but in the laboratory, it is often tested using simple displays with identical distracters. Can complex search be understood in terms of simple searches? This link may not be straightforward if complex search has emergent properties. One such property is linear separability, whereby search is hard when a target cannot be separated from its distracters using a single linear boundary. However, evidence in favor of linear separability is based on testing stimulus configurations in an external parametric space that need not be related to their true perceptual representation. We therefore set out to assess whether linear separability influences complex search at all. Our null hypothesis was that complex search performance depends only on classical factors such as target-distracter similarity and distracter homogeneity, which we measured using simple searches. Across three experiments involving a variety of artificial and natural objects, differences between linearly separable and nonseparable searches were explained using target-distracter similarity and distracter heterogeneity. Further, simple searches accurately predicted complex search regardless of linear separability (r = 0.91). Our results show that complex search is explained by simple search, refuting the widely held belief that linear separability influences visual search. PMID:24029822

A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants

ERIC Educational Resources Information Center

Cooper, Paul D.

2010-01-01

A new procedure using a student-friendly least-squares multiple linear-regression technique utilizing a function within Microsoft Excel is described that enables students to calculate molecular constants from the vibronic spectrum of iodine. This method is advantageous pedagogically as it calculates molecular constants for ground and excited…

Sparse matrix multiplications for linear scaling electronic structure calculations in an atom-centered basis set using multiatom blocks.

PubMed

Saravanan, Chandra; Shao, Yihan; Baer, Roi; Ross, Philip N; Head-Gordon, Martin

2003-04-15

A sparse matrix multiplication scheme with multiatom blocks is reported, a tool that can be very useful for developing linear-scaling methods with atom-centered basis functions. Compared to conventional element-by-element sparse matrix multiplication schemes, efficiency is gained by the use of the highly optimized basic linear algebra subroutines (BLAS). However, some sparsity is lost in the multiatom blocking scheme because these matrix blocks will in general contain negligible elements. As a result, an optimal block size that minimizes the CPU time by balancing these two effects is recovered. In calculations on linear alkanes, polyglycines, estane polymers, and water clusters the optimal block size is found to be between 40 and 100 basis functions, where about 55-75% of the machine peak performance was achieved on an IBM RS6000 workstation. In these calculations, the blocked sparse matrix multiplications can be 10 times faster than a standard element-by-element sparse matrix package. Copyright 2003 Wiley Periodicals, Inc. J Comput Chem 24: 618-622, 2003

Degree-of-Freedom Strengthened Cascade Array for DOD-DOA Estimation in MIMO Array Systems.

PubMed

Yao, Bobin; Dong, Zhi; Zhang, Weile; Wang, Wei; Wu, Qisheng

2018-05-14

In spatial spectrum estimation, difference co-array can provide extra degrees-of-freedom (DOFs) for promoting parameter identifiability and parameter estimation accuracy. For the sake of acquiring as more DOFs as possible with a given number of physical sensors, we herein design a novel sensor array geometry named cascade array. This structure is generated by systematically connecting a uniform linear array (ULA) and a non-uniform linear array, and can provide more DOFs than some exist array structures but less than the upper-bound indicated by minimum redundant array (MRA). We further apply this cascade array into multiple input multiple output (MIMO) array systems, and propose a novel joint direction of departure (DOD) and direction of arrival (DOA) estimation algorithm, which is based on a reduced-dimensional weighted subspace fitting technique. The algorithm is angle auto-paired and computationally efficient. Theoretical analysis and numerical simulations prove the advantages and effectiveness of the proposed array structure and the related algorithm.

GPU-based relative fuzzy connectedness image segmentation

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

Zhuge Ying; Ciesielski, Krzysztof C.; Udupa, Jayaram K.

2013-01-15

Purpose:Recently, clinical radiological research and practice are becoming increasingly quantitative. Further, images continue to increase in size and volume. For quantitative radiology to become practical, it is crucial that image segmentation algorithms and their implementations are rapid and yield practical run time on very large data sets. The purpose of this paper is to present a parallel version of an algorithm that belongs to the family of fuzzy connectedness (FC) algorithms, to achieve an interactive speed for segmenting large medical image data sets. Methods: The most common FC segmentations, optimizing an Script-Small-L {sub {infinity}}-based energy, are known as relative fuzzymore » connectedness (RFC) and iterative relative fuzzy connectedness (IRFC). Both RFC and IRFC objects (of which IRFC contains RFC) can be found via linear time algorithms, linear with respect to the image size. The new algorithm, P-ORFC (for parallel optimal RFC), which is implemented by using NVIDIA's Compute Unified Device Architecture (CUDA) platform, considerably improves the computational speed of the above mentioned CPU based IRFC algorithm. Results: Experiments based on four data sets of small, medium, large, and super data size, achieved speedup factors of 32.8 Multiplication-Sign , 22.9 Multiplication-Sign , 20.9 Multiplication-Sign , and 17.5 Multiplication-Sign , correspondingly, on the NVIDIA Tesla C1060 platform. Although the output of P-ORFC need not precisely match that of IRFC output, it is very close to it and, as the authors prove, always lies between the RFC and IRFC objects. Conclusions: A parallel version of a top-of-the-line algorithm in the family of FC has been developed on the NVIDIA GPUs. An interactive speed of segmentation has been achieved, even for the largest medical image data set. Such GPU implementations may play a crucial role in automatic anatomy recognition in clinical radiology.« less

Tail mean and related robust solution concepts

NASA Astrophysics Data System (ADS)

Ogryczak, Włodzimierz

2014-01-01

Robust optimisation might be viewed as a multicriteria optimisation problem where objectives correspond to the scenarios although their probabilities are unknown or imprecise. The simplest robust solution concept represents a conservative approach focused on the worst-case scenario results optimisation. A softer concept allows one to optimise the tail mean thus combining performances under multiple worst scenarios. We show that while considering robust models allowing the probabilities to vary only within given intervals, the tail mean represents the robust solution for only upper bounded probabilities. For any arbitrary intervals of probabilities the corresponding robust solution may be expressed by the optimisation of appropriately combined mean and tail mean criteria thus remaining easily implementable with auxiliary linear inequalities. Moreover, we use the tail mean concept to develope linear programming implementable robust solution concepts related to risk averse optimisation criteria.

Non-linear molecular pattern classification using molecular beacons with multiple targets.

PubMed

Lee, In-Hee; Lee, Seung Hwan; Park, Tai Hyun; Zhang, Byoung-Tak

2013-12-01

In vitro pattern classification has been highlighted as an important future application of DNA computing. Previous work has demonstrated the feasibility of linear classifiers using DNA-based molecular computing. However, complex tasks require non-linear classification capability. Here we design a molecular beacon that can interact with multiple targets and experimentally shows that its fluorescent signals form a complex radial-basis function, enabling it to be used as a building block for non-linear molecular classification in vitro. The proposed method was successfully applied to solving artificial and real-world classification problems: XOR and microRNA expression patterns. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Multiple imputation of rainfall missing data in the Iberian Mediterranean context

NASA Astrophysics Data System (ADS)

Miró, Juan Javier; Caselles, Vicente; Estrela, María José

2017-11-01

Given the increasing need for complete rainfall data networks, in recent years have been proposed diverse methods for filling gaps in observed precipitation series, progressively more advanced that traditional approaches to overcome the problem. The present study has consisted in validate 10 methods (6 linear, 2 non-linear and 2 hybrid) that allow multiple imputation, i.e., fill at the same time missing data of multiple incomplete series in a dense network of neighboring stations. These were applied for daily and monthly rainfall in two sectors in the Júcar River Basin Authority (east Iberian Peninsula), which is characterized by a high spatial irregularity and difficulty of rainfall estimation. A classification of precipitation according to their genetic origin was applied as pre-processing, and a quantile-mapping adjusting as post-processing technique. The results showed in general a better performance for the non-linear and hybrid methods, highlighting that the non-linear PCA (NLPCA) method outperforms considerably the Self Organizing Maps (SOM) method within non-linear approaches. On linear methods, the Regularized Expectation Maximization method (RegEM) was the best, but far from NLPCA. Applying EOF filtering as post-processing of NLPCA (hybrid approach) yielded the best results.

Relative importance of multiple scattering by air molecules and aerosols in forming the atmospheric path radiance in the visible and near-infrared parts of the spectrum.

PubMed

Antoine, D; Morel, A

1998-04-20

Single and multiple scattering by molecules or by atmospheric aerosols only (homogeneous scattering), and heterogeneous scattering by aerosols and molecules, are recorded in Monte Carlo simulations. It is shown that heterogeneous scattering (1) always contributes significantly to the path reflectance (rho(path)), (2) is realized at the expense of homogeneous scattering, (3) decreases when aerosols are absorbing, and (4) introduces deviations in the spectral dependencies of reflectances compared with the Rayleigh exponent and the aerosol angstrom exponent. The ratio of rho(path) to the Rayleigh reflectance for an aerosol-free atmosphere is linearly related to the aerosol optical thickness. This result provides a basis for a new scheme for atmospheric correction of remotely sensed ocean color observations.

Multiple origins of linear dunes on Earth and Titan

USGS Publications Warehouse

Rubin, David M.; Hesp, Patrick A.

2009-01-01

Dunes with relatively long and parallel crests are classified as linear dunes. On Earth, they form in at least two environmental settings: where winds of bimodal direction blow across loose sand, and also where single-direction winds blow over sediment that is locally stabilized, be it through vegetation, sediment cohesion or topographic shelter from the winds. Linear dunes have also been identified on Titan, where they are thought to form in loose sand. Here we present evidence that in the Qaidam Basin, China, linear dunes are found downwind of transverse dunes owing to higher cohesiveness in the downwind sediments, which contain larger amounts of salt and mud. We also present a compilation of other settings where sediment stabilization has been reported to produce linear dunes. We suggest that in this dune-forming process, loose sediment accumulates on the dunes and is stabilized; the stable dune then functions as a topographic shelter, which induces the deposition of sediments downwind. We conclude that a model in which Titan's dunes formed similarly in cohesive sediments cannot be ruled out by the existing data.

A method for fitting regression splines with varying polynomial order in the linear mixed model.

PubMed

Edwards, Lloyd J; Stewart, Paul W; MacDougall, James E; Helms, Ronald W

2006-02-15

The linear mixed model has become a widely used tool for longitudinal analysis of continuous variables. The use of regression splines in these models offers the analyst additional flexibility in the formulation of descriptive analyses, exploratory analyses and hypothesis-driven confirmatory analyses. We propose a method for fitting piecewise polynomial regression splines with varying polynomial order in the fixed effects and/or random effects of the linear mixed model. The polynomial segments are explicitly constrained by side conditions for continuity and some smoothness at the points where they join. By using a reparameterization of this explicitly constrained linear mixed model, an implicitly constrained linear mixed model is constructed that simplifies implementation of fixed-knot regression splines. The proposed approach is relatively simple, handles splines in one variable or multiple variables, and can be easily programmed using existing commercial software such as SAS or S-plus. The method is illustrated using two examples: an analysis of longitudinal viral load data from a study of subjects with acute HIV-1 infection and an analysis of 24-hour ambulatory blood pressure profiles.

Predicting hearing thresholds and occupational hearing loss with multiple-frequency auditory steady-state responses.

PubMed

Hsu, Ruey-Fen; Ho, Chi-Kung; Lu, Sheng-Nan; Chen, Shun-Sheng

2010-10-01

An objective investigation is needed to verify the existence and severity of hearing impairments resulting from work-related, noise-induced hearing loss in arbitration of medicolegal aspects. We investigated the accuracy of multiple-frequency auditory steady-state responses (Mf-ASSRs) between subjects with sensorineural hearing loss (SNHL) with and without occupational noise exposure. Cross-sectional study. Tertiary referral medical centre. Pure-tone audiometry and Mf-ASSRs were recorded in 88 subjects (34 patients had occupational noise-induced hearing loss [NIHL], 36 patients had SNHL without noise exposure, and 18 volunteers were normal controls). Inter- and intragroup comparisons were made. A predicting equation was derived using multiple linear regression analysis. ASSRs and pure-tone thresholds (PTTs) showed a strong correlation for all subjects (r = .77 ≈ .94). The relationship is demonstrated by the equationThe differences between the ASSR and PTT were significantly higher for the NIHL group than for the subjects with non-noise-induced SNHL (p < .001). Mf-ASSR is a promising tool for objectively evaluating hearing thresholds. Predictive value may be lower in subjects with occupational hearing loss. Regardless of carrier frequencies, the severity of hearing loss affects the steady-state response. Moreover, the ASSR may assist in detecting noise-induced injury of the auditory pathway. A multiple linear regression equation to accurately predict thresholds was shown that takes into consideration all effect factors.

Solving a mixture of many random linear equations by tensor decomposition and alternating minimization.

DOT National Transportation Integrated Search

2016-09-01

We consider the problem of solving mixed random linear equations with k components. This is the noiseless setting of mixed linear regression. The goal is to estimate multiple linear models from mixed samples in the case where the labels (which sample...

Multiple pass laser amplifier system

DOEpatents

Brueckner, Keith A.; Jorna, Siebe; Moncur, N. Kent

1977-01-01

A laser amplification method for increasing the energy extraction efficiency from laser amplifiers while reducing the energy flux that passes through a flux limited system which includes apparatus for decomposing a linearly polarized light beam into multiple components, passing the components through an amplifier in delayed time sequence and recombining the amplified components into an in phase linearly polarized beam.

Statistical linearization for multi-input/multi-output nonlinearities

NASA Technical Reports Server (NTRS)

Lin, Ching-An; Cheng, Victor H. L.

1991-01-01

Formulas are derived for the computation of the random input-describing functions for MIMO nonlinearities; these straightforward and rigorous derivations are based on the optimal mean square linear approximation. The computations involve evaluations of multiple integrals. It is shown that, for certain classes of nonlinearities, multiple-integral evaluations are obviated and the computations are significantly simplified.

What Is Wrong with ANOVA and Multiple Regression? Analyzing Sentence Reading Times with Hierarchical Linear Models

ERIC Educational Resources Information Center

Richter, Tobias

2006-01-01

Most reading time studies using naturalistic texts yield data sets characterized by a multilevel structure: Sentences (sentence level) are nested within persons (person level). In contrast to analysis of variance and multiple regression techniques, hierarchical linear models take the multilevel structure of reading time data into account. They…

Some Applied Research Concerns Using Multiple Linear Regression Analysis.

ERIC Educational Resources Information Center

Newman, Isadore; Fraas, John W.

The intention of this paper is to provide an overall reference on how a researcher can apply multiple linear regression in order to utilize the advantages that it has to offer. The advantages and some concerns expressed about the technique are examined. A number of practical ways by which researchers can deal with such concerns as…

Tornado outbreak variability follows Taylor's power law of fluctuation scaling and increases dramatically with severity.

PubMed

Tippett, Michael K; Cohen, Joel E

2016-02-29

Tornadoes cause loss of life and damage to property each year in the United States and around the world. The largest impacts come from 'outbreaks' consisting of multiple tornadoes closely spaced in time. Here we find an upward trend in the annual mean number of tornadoes per US tornado outbreak for the period 1954-2014. Moreover, the variance of this quantity is increasing more than four times as fast as the mean. The mean and variance of the number of tornadoes per outbreak vary according to Taylor's power law of fluctuation scaling (TL), with parameters that are consistent with multiplicative growth. Tornado-related atmospheric proxies show similar power-law scaling and multiplicative growth. Path-length-integrated tornado outbreak intensity also follows TL, but with parameters consistent with sampling variability. The observed TL power-law scaling of outbreak severity means that extreme outbreaks are more frequent than would be expected if mean and variance were independent or linearly related.

Tornado outbreak variability follows Taylor's power law of fluctuation scaling and increases dramatically with severity

PubMed Central

Tippett, Michael K.; Cohen, Joel E.

2016-01-01

Tornadoes cause loss of life and damage to property each year in the United States and around the world. The largest impacts come from ‘outbreaks' consisting of multiple tornadoes closely spaced in time. Here we find an upward trend in the annual mean number of tornadoes per US tornado outbreak for the period 1954–2014. Moreover, the variance of this quantity is increasing more than four times as fast as the mean. The mean and variance of the number of tornadoes per outbreak vary according to Taylor's power law of fluctuation scaling (TL), with parameters that are consistent with multiplicative growth. Tornado-related atmospheric proxies show similar power-law scaling and multiplicative growth. Path-length-integrated tornado outbreak intensity also follows TL, but with parameters consistent with sampling variability. The observed TL power-law scaling of outbreak severity means that extreme outbreaks are more frequent than would be expected if mean and variance were independent or linearly related. PMID:26923210

Tornado outbreak variability follows Taylor's power law of fluctuation scaling and increases dramatically with severity

NASA Astrophysics Data System (ADS)

Tippett, Michael K.; Cohen, Joel E.

2016-02-01

Tornadoes cause loss of life and damage to property each year in the United States and around the world. The largest impacts come from `outbreaks' consisting of multiple tornadoes closely spaced in time. Here we find an upward trend in the annual mean number of tornadoes per US tornado outbreak for the period 1954-2014. Moreover, the variance of this quantity is increasing more than four times as fast as the mean. The mean and variance of the number of tornadoes per outbreak vary according to Taylor's power law of fluctuation scaling (TL), with parameters that are consistent with multiplicative growth. Tornado-related atmospheric proxies show similar power-law scaling and multiplicative growth. Path-length-integrated tornado outbreak intensity also follows TL, but with parameters consistent with sampling variability. The observed TL power-law scaling of outbreak severity means that extreme outbreaks are more frequent than would be expected if mean and variance were independent or linearly related.

The use of artificial neural networks and multiple linear regression to predict rate of medical waste generation

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

Jahandideh, Sepideh; Jahandideh, Samad; Asadabadi, Ebrahim Barzegari

2009-11-15

Prediction of the amount of hospital waste production will be helpful in the storage, transportation and disposal of hospital waste management. Based on this fact, two predictor models including artificial neural networks (ANNs) and multiple linear regression (MLR) were applied to predict the rate of medical waste generation totally and in different types of sharp, infectious and general. In this study, a 5-fold cross-validation procedure on a database containing total of 50 hospitals of Fars province (Iran) were used to verify the performance of the models. Three performance measures including MAR, RMSE and R{sup 2} were used to evaluate performancemore » of models. The MLR as a conventional model obtained poor prediction performance measure values. However, MLR distinguished hospital capacity and bed occupancy as more significant parameters. On the other hand, ANNs as a more powerful model, which has not been introduced in predicting rate of medical waste generation, showed high performance measure values, especially 0.99 value of R{sup 2} confirming the good fit of the data. Such satisfactory results could be attributed to the non-linear nature of ANNs in problem solving which provides the opportunity for relating independent variables to dependent ones non-linearly. In conclusion, the obtained results showed that our ANN-based model approach is very promising and may play a useful role in developing a better cost-effective strategy for waste management in future.« less

Refractive Status at Birth: Its Relation to Newborn Physical Parameters at Birth and Gestational Age

PubMed Central

Varghese, Raji Mathew; Sreenivas, Vishnubhatla; Puliyel, Jacob Mammen; Varughese, Sara

2009-01-01

Background Refractive status at birth is related to gestational age. Preterm babies have myopia which decreases as gestational age increases and term babies are known to be hypermetropic. This study looked at the correlation of refractive status with birth weight in term and preterm babies, and with physical indicators of intra-uterine growth such as the head circumference and length of the baby at birth. Methods All babies delivered at St. Stephens Hospital and admitted in the nursery were eligible for the study. Refraction was performed within the first week of life. 0.8% tropicamide with 0.5% phenylephrine was used to achieve cycloplegia and paralysis of accommodation. 599 newborn babies participated in the study. Data pertaining to the right eye is utilized for all the analyses except that for anisometropia where the two eyes were compared. Growth parameters were measured soon after birth. Simple linear regression analysis was performed to see the association of refractive status, (mean spherical equivalent (MSE), astigmatism and anisometropia) with each of the study variables, namely gestation, length, weight and head circumference. Subsequently, multiple linear regression was carried out to identify the independent predictors for each of the outcome parameters. Results Simple linear regression showed a significant relation between all 4 study variables and refractive error but in multiple regression only gestational age and weight were related to refractive error. The partial correlation of weight with MSE adjusted for gestation was 0.28 and that of gestation with MSE adjusted for weight was 0.10. Birth weight had a higher correlation to MSE than gestational age. Conclusion This is the first study to look at refractive error against all these growth parameters, in preterm and term babies at birth. It would appear from this study that birth weight rather than gestation should be used as criteria for screening for refractive error, especially in developing countries where the incidence of intrauterine malnutrition is higher. PMID:19214228

Time-resolved flow reconstruction with indirect measurements using regression models and Kalman-filtered POD ROM

NASA Astrophysics Data System (ADS)

Leroux, Romain; Chatellier, Ludovic; David, Laurent

2018-01-01

This article is devoted to the estimation of time-resolved particle image velocimetry (TR-PIV) flow fields using a time-resolved point measurements of a voltage signal obtained by hot-film anemometry. A multiple linear regression model is first defined to map the TR-PIV flow fields onto the voltage signal. Due to the high temporal resolution of the signal acquired by the hot-film sensor, the estimates of the TR-PIV flow fields are obtained with a multiple linear regression method called orthonormalized partial least squares regression (OPLSR). Subsequently, this model is incorporated as the observation equation in an ensemble Kalman filter (EnKF) applied on a proper orthogonal decomposition reduced-order model to stabilize it while reducing the effects of the hot-film sensor noise. This method is assessed for the reconstruction of the flow around a NACA0012 airfoil at a Reynolds number of 1000 and an angle of attack of {20}°. Comparisons with multi-time delay-modified linear stochastic estimation show that both the OPLSR and EnKF combined with OPLSR are more accurate as they produce a much lower relative estimation error, and provide a faithful reconstruction of the time evolution of the velocity flow fields.

Flow behaviour and constitutive modelling of a ferritic stainless steel at elevated temperatures

NASA Astrophysics Data System (ADS)

Zhao, Jingwei; Jiang, Zhengyi; Zu, Guoqing; Du, Wei; Zhang, Xin; Jiang, Laizhu

2016-05-01

The flow behaviour of a ferritic stainless steel (FSS) was investigated by a Gleeble 3500 thermal-mechanical test simulator over the temperature range of 900-1100 °C and strain rate range of 1-50 s-1. Empirical and phenomenological constitutive models were established, and a comparative study was made on the predictability of them. The results indicate that the flow stress decreases with increasing the temperature and decreasing the strain rate. High strain rate may cause a drop in flow stress after a peak value due to the adiabatic heating. The Zener-Hollomon parameter depends linearly on the flow stress, and decreases with raising the temperature and reducing the strain rate. Significant deviations occur in the prediction of flow stress by the Johnson-Cook (JC) model, indicating that the JC model cannot accurately track the flow behaviour of the FSS during hot deformation. Both the multiple-linear and the Arrhenius-type models can track the flow behaviour very well under the whole hot working conditions, and have much higher accuracy in predicting the flow behaviour than that of the JC model. The multiple-linear model is recommended in the current work due to its simpler structure and less time needed for solving the equations relative to the Arrhenius-type model.

A simplified calculation procedure for mass isotopomer distribution analysis (MIDA) based on multiple linear regression.

PubMed

Fernández-Fernández, Mario; Rodríguez-González, Pablo; García Alonso, J Ignacio

2016-10-01

We have developed a novel, rapid and easy calculation procedure for Mass Isotopomer Distribution Analysis based on multiple linear regression which allows the simultaneous calculation of the precursor pool enrichment and the fraction of newly synthesized labelled proteins (fractional synthesis) using linear algebra. To test this approach, we used the peptide RGGGLK as a model tryptic peptide containing three subunits of glycine. We selected glycine labelled in two 13 C atoms ( 13 C 2 -glycine) as labelled amino acid to demonstrate that spectral overlap is not a problem in the proposed methodology. The developed methodology was tested first in vitro by changing the precursor pool enrichment from 10 to 40% of 13 C 2 -glycine. Secondly, a simulated in vivo synthesis of proteins was designed by combining the natural abundance RGGGLK peptide and 10 or 20% 13 C 2 -glycine at 1 : 1, 1 : 3 and 3 : 1 ratios. Precursor pool enrichments and fractional synthesis values were calculated with satisfactory precision and accuracy using a simple spreadsheet. This novel approach can provide a relatively rapid and easy means to measure protein turnover based on stable isotope tracers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Relation of Environmental characteristics to the composition of aquatic assemblages along a gradient of urban land use in New Jersey, 1996-98

USGS Publications Warehouse

Kennen, Jonathan G.; Ayers, Mark A.

2002-01-01

Community data from 36 watersheds were used to evaluate the response of fish, invertebrate, and algal assemblages in New Jersey streams to environmental characteristics along a gradient of urban land use that ranged from 3 to 96 percent. Aquatic assemblages were sampled at 36 sites during 1996-98, and more than 400 environmental attributes at multiple spatial scales were summarized. Data matrices were reduced to 43, 170, and 103 species of fish, invertebrates, and algae, respectively, by means of a predetermined joint frequency and relative abundance approach. White sucker (Catostomus commersoni) and Tessellated darter (Etheostoma olmstedi) were the most abundant fishes, accounting for more than 20 and 17 percent, respectively, of the mean abundance. Net-spinning caddisflies (Hydropsychidae) were the most commonly occurring benthic invertebrates and were found at all but one of the 36 sampling sites. Blue-green (for example, Calothrix sp. and Oscillatoria sp.) and green (for example, Protoderma viride) algae were the most widely distrib-uted algae; however, more than 81 percent of the algal taxa collected were diatoms. Principal-component and correlation analyses were used to reduce the dimensionality of the environmental data. Multiple linear regression analysis of extracted ordination axes then was used to develop models that expressed effects of increasing urban land use on the structure of aquatic assemblages. Significant environmental variables identified by using multiple linear regression analysis then were included in a direct gradient analysis. Partial canonical correspondence analysis of relativized abundance data was used to restrict further the effects of residual natural variability, and to identify relations among the environmental variables and the structure of fish, invertebrate, and algal assemblages along an urban land-use gradient. Results of this approach, combined with the results of the multiple linear regression analyses, were used to identify human population density (311-37,594 persons/km2), amount and type of impervious surface cover (0.12-1,350 km2), nutrient concentrations (for example, 0.01-0.29 mg/L of phosphorus), hydrologic instability (for example, 100-8,955 ft3/s for 2-year peak flow), the amount of forest and wetlands in a basin (0.01-6.25 km2), and substrate quality (0-87 percent cobble substrate) as variables that are highly correlated with aquatic-assemblage structure. Species distributions in ordination space clearly indicate that tolerant species are more abundant in the streams impaired by urbanization and sensitive taxa are more closely associated with the least impaired basins. The distinct differences in aquatic assemblages along the urban land-use gradient demonstrate the deleterious effects of urbanization on assemblage structure and indicate that conserving landscape attributes that mitigate anthropogenic influences (for example, stormwater-management practices emphasizing infiltration and preservation of existing forests, wetlands, and riparian corridors) will help to maintain the relative abundance of sensitive taxa. Complementary multiple linear regression models indicate that aquatic community indices were correlated with many of the anthropogenic factors that were found to be significant along the urban land-use gradient. These indices appear to be effective in differentiating the moderately and severely impaired streams from the minimally impaired streams. Evaluation of disturbance thresholds for aquatic assemblages indicates that moderate to severe impairment is detectable in New Jersey streams when impervious surface cover in the drainage basin reaches approximately 18 percent.

Stochastic Swift-Hohenberg Equation with Degenerate Linear Multiplicative Noise

NASA Astrophysics Data System (ADS)

Hernández, Marco; Ong, Kiah Wah

2018-03-01

We study the dynamic transition of the Swift-Hohenberg equation (SHE) when linear multiplicative noise acting on a finite set of modes of the dominant linear flow is introduced. Existence of a stochastic flow and a local stochastic invariant manifold for this stochastic form of SHE are both addressed in this work. We show that the approximate reduced system corresponding to the invariant manifold undergoes a stochastic pitchfork bifurcation, and obtain numerical evidence suggesting that this picture is a good approximation for the full system as well.

A methodology based on reduced complexity algorithm for system applications using microprocessors

NASA Technical Reports Server (NTRS)

Yan, T. Y.; Yao, K.

1988-01-01

The paper considers a methodology on the analysis and design of a minimum mean-square error criterion linear system incorporating a tapped delay line (TDL) where all the full-precision multiplications in the TDL are constrained to be powers of two. A linear equalizer based on the dispersive and additive noise channel is presented. This microprocessor implementation with optimized power of two TDL coefficients achieves a system performance comparable to the optimum linear equalization with full-precision multiplications for an input data rate of 300 baud.

Equivalent Linearization Analysis of Geometrically Nonlinear Random Vibrations Using Commercial Finite Element Codes

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Muravyov, Alexander A.

2002-01-01

Two new equivalent linearization implementations for geometrically nonlinear random vibrations are presented. Both implementations are based upon a novel approach for evaluating the nonlinear stiffness within commercial finite element codes and are suitable for use with any finite element code having geometrically nonlinear static analysis capabilities. The formulation includes a traditional force-error minimization approach and a relatively new version of a potential energy-error minimization approach, which has been generalized for multiple degree-of-freedom systems. Results for a simply supported plate under random acoustic excitation are presented and comparisons of the displacement root-mean-square values and power spectral densities are made with results from a nonlinear time domain numerical simulation.

A simple white noise analysis of neuronal light responses.

PubMed

Chichilnisky, E J

2001-05-01

A white noise technique is presented for estimating the response properties of spiking visual system neurons. The technique is simple, robust, efficient and well suited to simultaneous recordings from multiple neurons. It provides a complete and easily interpretable model of light responses even for neurons that display a common form of response nonlinearity that precludes classical linear systems analysis. A theoretical justification of the technique is presented that relies only on elementary linear algebra and statistics. Implementation is described with examples. The technique and the underlying model of neural responses are validated using recordings from retinal ganglion cells, and in principle are applicable to other neurons. Advantages and disadvantages of the technique relative to classical approaches are discussed.

Lower back pain in nurses working in home care: linked to work-family conflict, emotional dissonance, and appreciation?

PubMed

Elfering, Achim; Häfliger, Evelyne; Celik, Zehra; Grebner, Simone

2018-07-01

In industrial countries home care services for elderly people living in the community are growing rapidly. Home care nursing is intensive and the nurses often suffer from musculoskeletal pain. Time pressure and job control are job-related factors linked to the risk of experiencing lower back pain (LBP) and LBP-related work impairment. This survey investigated whether work-family conflict (WFC), emotional dissonance and being appreciated at work have incremental predictive value. Responses were obtained from 125 home care nurses (63% response rate). Multiple linear regression showed that emotional dissonance and being appreciated at work predicted LBP intensity and LBP-related disability independently of time pressure and job control. WFC was not a predictor of LBP-related disability in multiple regression analyses despite a zero-order correlation with it. Redesigning the working pattern of home care nurses to reduce the emotional demands and improve appreciation of their work might reduce the incidence of LBP in this group.

Birthweight Related Factors in Northwestern Iran: Using Quantile Regression Method.

PubMed

Fallah, Ramazan; Kazemnejad, Anoshirvan; Zayeri, Farid; Shoghli, Alireza

2015-11-18

Birthweight is one of the most important predicting indicators of the health status in adulthood. Having a balanced birthweight is one of the priorities of the health system in most of the industrial and developed countries. This indicator is used to assess the growth and health status of the infants. The aim of this study was to assess the birthweight of the neonates by using quantile regression in Zanjan province. This analytical descriptive study was carried out using pre-registered (March 2010 - March 2012) data of neonates in urban/rural health centers of Zanjan province using multiple-stage cluster sampling. Data were analyzed using multiple linear regressions andquantile regression method and SAS 9.2 statistical software. From 8456 newborn baby, 4146 (49%) were female. The mean age of the mothers was 27.1±5.4 years. The mean birthweight of the neonates was 3104 ± 431 grams. Five hundred and seventy-three patients (6.8%) of the neonates were less than 2500 grams. In all quantiles, gestational age of neonates (p<0.05), weight and educational level of the mothers (p<0.05) showed a linear significant relationship with the i of the neonates. However, sex and birth rank of the neonates, mothers age, place of residence (urban/rural) and career were not significant in all quantiles (p>0.05). This study revealed the results of multiple linear regression and quantile regression were not identical. We strictly recommend the use of quantile regression when an asymmetric response variable or data with outliers is available.

Birthweight Related Factors in Northwestern Iran: Using Quantile Regression Method

PubMed Central

Fallah, Ramazan; Kazemnejad, Anoshirvan; Zayeri, Farid; Shoghli, Alireza

2016-01-01

Introduction: Birthweight is one of the most important predicting indicators of the health status in adulthood. Having a balanced birthweight is one of the priorities of the health system in most of the industrial and developed countries. This indicator is used to assess the growth and health status of the infants. The aim of this study was to assess the birthweight of the neonates by using quantile regression in Zanjan province. Methods: This analytical descriptive study was carried out using pre-registered (March 2010 - March 2012) data of neonates in urban/rural health centers of Zanjan province using multiple-stage cluster sampling. Data were analyzed using multiple linear regressions andquantile regression method and SAS 9.2 statistical software. Results: From 8456 newborn baby, 4146 (49%) were female. The mean age of the mothers was 27.1±5.4 years. The mean birthweight of the neonates was 3104 ± 431 grams. Five hundred and seventy-three patients (6.8%) of the neonates were less than 2500 grams. In all quantiles, gestational age of neonates (p<0.05), weight and educational level of the mothers (p<0.05) showed a linear significant relationship with the i of the neonates. However, sex and birth rank of the neonates, mothers age, place of residence (urban/rural) and career were not significant in all quantiles (p>0.05). Conclusion: This study revealed the results of multiple linear regression and quantile regression were not identical. We strictly recommend the use of quantile regression when an asymmetric response variable or data with outliers is available. PMID:26925889

On using the Multiple Signal Classification algorithm to study microbaroms

NASA Astrophysics Data System (ADS)

Marcillo, O. E.; Blom, P. S.; Euler, G. G.

2016-12-01

Multiple Signal Classification (MUSIC) (Schmidt, 1986) is a well-known high-resolution algorithm used in array processing for parameter estimation. We report on the application of MUSIC to infrasonic array data in a study of the structure of microbaroms. Microbaroms can be globally observed and display energy centered around 0.2 Hz. Microbaroms are an infrasonic signal generated by the non-linear interaction of ocean surface waves that radiate into the ocean and atmosphere as well as the solid earth in the form of microseisms. Microbaroms sources are dynamic and, in many cases, distributed in space and moving in time. We assume that the microbarom energy detected by an infrasonic array is the result of multiple sources (with different back-azimuths) in the same bandwidth and apply the MUSIC algorithm accordingly to recover the back-azimuth and trace velocity of the individual components. Preliminary results show that the multiple component assumption in MUSIC allows one to resolve the fine structure in the microbarom band that can be related to multiple ocean surface phenomena.

Multi-Target Angle Tracking Algorithm for Bistatic Multiple-Input Multiple-Output (MIMO) Radar Based on the Elements of the Covariance Matrix.

PubMed

Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo

2018-03-07

In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar.

Heavy quark energy loss in nuclear medium

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

Zhang, Benr-Wei; Wang, Enke; Wang, Xin-Nian

2003-09-16

Multiple scattering, modified fragmentation functions and radiative energy loss of a heavy quark propagating in a nuclear medium are investigated in perturbative QCD. Because of the quark mass dependence of the gluon formation time, the medium size dependence of heavy quark energy loss is found to change from a linear to a quadratic form when the initial energy and momentum scale are increased relative to the quark mass. The radiative energy loss is also significantly suppressed relative to a light quark due to the suppression of collinear gluon emission by a heavy quark.

A Quantitative and Combinatorial Approach to Non-Linear Meanings of Multiplication

ERIC Educational Resources Information Center

Tillema, Erik; Gatza, Andrew

2016-01-01

We provide a conceptual analysis of how combinatorics problems have the potential to support students to establish non-linear meanings of multiplication (NLMM). The problems we analyze we have used in a series of studies with 6th, 8th, and 10th grade students. We situate the analysis in prior work on students' quantitative and multiplicative…

Non-linear quantitative structure-activity relationship for adenine derivatives as competitive inhibitors of adenosine deaminase

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

Sadat Hayatshahi, Sayyed Hamed; Abdolmaleki, Parviz; Safarian, Shahrokh

2005-12-16

Logistic regression and artificial neural networks have been developed as two non-linear models to establish quantitative structure-activity relationships between structural descriptors and biochemical activity of adenosine based competitive inhibitors, toward adenosine deaminase. The training set included 24 compounds with known k {sub i} values. The models were trained to solve two-class problems. Unlike the previous work in which multiple linear regression was used, the highest of positive charge on the molecules was recognized to be in close relation with their inhibition activity, while the electric charge on atom N1 of adenosine was found to be a poor descriptor. Consequently, themore » previously developed equation was improved and the newly formed one could predict the class of 91.66% of compounds correctly. Also optimized 2-3-1 and 3-4-1 neural networks could increase this rate to 95.83%.« less

Rural-urban analyses of health-related quality of life among people with multiple sclerosis.

PubMed

Buchanan, Robert J; Zhu, Li; Schiffer, Randolph; Radin, Dagmar; James, Wesley

2008-01-01

Health-related quality of life (HRQOL) is a multi-dimensional construct including aspects of life quality or function that are affected by physical health and symptoms, psychosocial factors, and psychiatric conditions. HRQOL gives a broader measure of the burden of disease than physical impairment or disability levels. To identify factors associated with HRQOL among people with multiple sclerosis (MS) utilizing the SF-8 Health Survey. Data presented in this study were collected in a survey of 1,518 people with MS living in all 50 states. The survey sample was randomly selected from the database of the National Multiple Sclerosis Society, using ZIP codes to recruit the survey sample. A multiple linear regression model was employed to analyze the survey data, with the Physical Component Summary and the Mental Component Summary of the SF-8 the dependent variables. Independent variables were demographic characteristics, MS-disease characteristics, and health services utilized. People with MS in rural areas tended to report lower physically related HRQOL. Worsening MS symptoms were associated with reduced physical and mental dimensions of HRQOL. In addition, people with MS who received a diagnosis of depression tended to have reduced physical and mental dimensions of HRQOL. Receiving MS care at an MS clinic was associated with better physically related HRQOL, while having a neurologist as principal care physician was associated with better mental-related HRQOL. The challenge is to increase the access that people living with MS in rural areas have to MS-focused specialty care.

Analysis of Slope Limiters on Irregular Grids

NASA Technical Reports Server (NTRS)

Berger, Marsha; Aftosmis, Michael J.

2005-01-01

This paper examines the behavior of flux and slope limiters on non-uniform grids in multiple dimensions. Many slope limiters in standard use do not preserve linear solutions on irregular grids impacting both accuracy and convergence. We rewrite some well-known limiters to highlight their underlying symmetry, and use this form to examine the proper - ties of both traditional and novel limiter formulations on non-uniform meshes. A consistent method of handling stretched meshes is developed which is both linearity preserving for arbitrary mesh stretchings and reduces to common limiters on uniform meshes. In multiple dimensions we analyze the monotonicity region of the gradient vector and show that the multidimensional limiting problem may be cast as the solution of a linear programming problem. For some special cases we present a new directional limiting formulation that preserves linear solutions in multiple dimensions on irregular grids. Computational results using model problems and complex three-dimensional examples are presented, demonstrating accuracy, monotonicity and robustness.

A gradient in cortical pathology in multiple sclerosis by in vivo quantitative 7 T imaging

PubMed Central

Louapre, Céline; Govindarajan, Sindhuja T.; Giannì, Costanza; Nielsen, A. Scott; Cohen-Adad, Julien; Sloane, Jacob; Kinkel, Revere P.

2015-01-01

We used a surface-based analysis of T2* relaxation rates at 7 T magnetic resonance imaging, which allows sampling quantitative T2* throughout the cortical width, to map in vivo the spatial distribution of intracortical pathology in multiple sclerosis. Ultra-high resolution quantitative T2* maps were obtained in 10 subjects with clinically isolated syndrome/early multiple sclerosis (≤3 years disease duration), 18 subjects with relapsing-remitting multiple sclerosis (≥4 years disease duration), 13 subjects with secondary progressive multiple sclerosis, and in 17 age-matched healthy controls. Quantitative T2* maps were registered to anatomical cortical surfaces for sampling T2* at 25%, 50% and 75% depth from the pial surface. Differences in laminar quantitative T2* between each patient group and controls were assessed using general linear model (P < 0.05 corrected for multiple comparisons). In all 41 multiple sclerosis cases, we tested for associations between laminar quantitative T2*, neurological disability, Multiple Sclerosis Severity Score, cortical thickness, and white matter lesions. In patients, we measured, T2* in intracortical lesions and in the intracortical portion of leukocortical lesions visually detected on 7 T scans. Cortical lesional T2* was compared with patients’ normal-appearing cortical grey matter T2* (paired t-test) and with mean cortical T2* in controls (linear regression using age as nuisance factor). Subjects with multiple sclerosis exhibited relative to controls, independent from cortical thickness, significantly increased T2*, consistent with cortical myelin and iron loss. In early disease, T2* changes were focal and mainly confined at 25% depth, and in cortical sulci. In later disease stages T2* changes involved deeper cortical laminae, multiple cortical areas and gyri. In patients, T2* in intracortical and leukocortical lesions was increased compared with normal-appearing cortical grey matter (P < 10−10 and P < 10−7), and mean cortical T2* in controls (P < 10−5 and P < 10−6). In secondary progressive multiple sclerosis, T2* in normal-appearing cortical grey matter was significantly increased relative to controls (P < 0.001). Laminar T2* changes may, thus, result from cortical pathology within and outside focal cortical lesions. Neurological disability and Multiple Sclerosis Severity Score correlated each with the degree of laminar quantitative T2* changes, independently from white matter lesions, the greatest association being at 25% depth, while they did not correlate with cortical thickness and volume. These findings demonstrate a gradient in the expression of cortical pathology throughout stages of multiple sclerosis, which was associated with worse disability and provides in vivo evidence for the existence of a cortical pathological process driven from the pial surface. PMID:25681411

Spacecraft Formation Flying Maneuvers Using Linear-Quadratic Regulation with No Radial Axis Inputs

NASA Technical Reports Server (NTRS)

Starin, Scott R.; Yedavalli, R. K.; Sparks, Andrew G.; Bauer, Frank H. (Technical Monitor)

2001-01-01

Regarding multiple spacecraft formation flying, the observation has been made that control thrust need only be applied coplanar to the local horizon to achieve complete controllability of a two-satellite (leader-follower) formation. A formulation of orbital dynamics using the state of one satellite relative to another is used. Without the need for thrust along the radial (zenith-nadir) axis of the relative reference frame ' propulsion system simplifications and weight reduction may be accomplished. Several linear-quadratic regulators (LQR) are explored and compared based on performance measures likely to be important to many missions, but not directly optimized in the LQR designs. Maneuver simulations are performed using commercial ODE solvers to propagate the Keplerian dynamics of a controlled satellite relative to an uncontrolled leader. These short maneuver simulations demonstrate the capacity of the controller to perform changes from one formation geometry to another. This work focusses on formations in which the controlled satellite has a relative trajectory which projects onto the local horizon of the uncontrolled satellite as a circle. This formation has potential uses for distributed remote sensing systems.

Simulated bi-SQUID Arrays Performing Direction Finding

DTIC Science & Technology

2015-09-01

First, we applied the multiple signal classification ( MUSIC ) algorithm on linearly polarized signals. We included multiple signals in the output...both of the same frequency and different fre- quencies. Next, we explored a modified MUSIC algorithm called dimensionality reduction MUSIC (DR- MUSIC ... MUSIC algorithm is able to determine the AoA from the simulated SQUID data for linearly polarized signals. The MUSIC algorithm could accurately find

Estimate the contribution of incubation parameters influence egg hatchability using multiple linear regression analysis

PubMed Central

Khalil, Mohamed H.; Shebl, Mostafa K.; Kosba, Mohamed A.; El-Sabrout, Karim; Zaki, Nesma

2016-01-01

Aim: This research was conducted to determine the most affecting parameters on hatchability of indigenous and improved local chickens’ eggs. Materials and Methods: Five parameters were studied (fertility, early and late embryonic mortalities, shape index, egg weight, and egg weight loss) on four strains, namely Fayoumi, Alexandria, Matrouh, and Montazah. Multiple linear regression was performed on the studied parameters to determine the most influencing one on hatchability. Results: The results showed significant differences in commercial and scientific hatchability among strains. Alexandria strain has the highest significant commercial hatchability (80.70%). Regarding the studied strains, highly significant differences in hatching chick weight among strains were observed. Using multiple linear regression analysis, fertility made the greatest percent contribution (71.31%) to hatchability, and the lowest percent contributions were made by shape index and egg weight loss. Conclusion: A prediction of hatchability using multiple regression analysis could be a good tool to improve hatchability percentage in chickens. PMID:27651666

A non-linear regression analysis program for describing electrophysiological data with multiple functions using Microsoft Excel.

PubMed

Brown, Angus M

2006-04-01

The objective of this present study was to demonstrate a method for fitting complex electrophysiological data with multiple functions using the SOLVER add-in of the ubiquitous spreadsheet Microsoft Excel. SOLVER minimizes the difference between the sum of the squares of the data to be fit and the function(s) describing the data using an iterative generalized reduced gradient method. While it is a straightforward procedure to fit data with linear functions, and we have previously demonstrated a method of non-linear regression analysis of experimental data based upon a single function, it is more complex to fit data with multiple functions, usually requiring specialized expensive computer software. In this paper we describe an easily understood program for fitting experimentally acquired data, in this case the stimulus-evoked compound action potential from the mouse optic nerve, with multiple Gaussian functions. The program is flexible and can be applied to describe data with a wide variety of user-input functions.

Adaptive receiver structures for asynchronous CDMA systems

NASA Astrophysics Data System (ADS)

Rapajic, Predrag B.; Vucetic, Branka S.

1994-05-01

Adaptive linear and decision feedback receiver structures for coherent demodulation in asynchronous code division multiple access (CDMA) systems are considered. It is assumed that the adaptive receiver has no knowledge of the signature waveforms and timing of other users. The receiver is trained by a known training sequence prior to data transmission and continuously adjusted by an adaptive algorithm during data transmission. The proposed linear receiver is as simple as a standard single-user detector receiver consisting of a matched filter with constant coefficients, but achieves essential advantages with respect to timing recovery, multiple access interference elimination, near/far effect, narrowband and frequency-selective fading interference suppression, and user privacy. An adaptive centralized decision feedback receiver has the same advantages of the linear receiver but, in addition, achieves a further improvement in multiple access interference cancellation at the expense of higher complexity. The proposed receiver structures are tested by simulation over a channel with multipath propagation, multiple access interference, narrowband interference, and additive white Gaussian noise.

Multiple imputation of covariates by fully conditional specification: Accommodating the substantive model

PubMed Central

Seaman, Shaun R; White, Ian R; Carpenter, James R

2015-01-01

Missing covariate data commonly occur in epidemiological and clinical research, and are often dealt with using multiple imputation. Imputation of partially observed covariates is complicated if the substantive model is non-linear (e.g. Cox proportional hazards model), or contains non-linear (e.g. squared) or interaction terms, and standard software implementations of multiple imputation may impute covariates from models that are incompatible with such substantive models. We show how imputation by fully conditional specification, a popular approach for performing multiple imputation, can be modified so that covariates are imputed from models which are compatible with the substantive model. We investigate through simulation the performance of this proposal, and compare it with existing approaches. Simulation results suggest our proposal gives consistent estimates for a range of common substantive models, including models which contain non-linear covariate effects or interactions, provided data are missing at random and the assumed imputation models are correctly specified and mutually compatible. Stata software implementing the approach is freely available. PMID:24525487

A new adaptive multiple modelling approach for non-linear and non-stationary systems

NASA Astrophysics Data System (ADS)

Chen, Hao; Gong, Yu; Hong, Xia

2016-07-01

This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.

Robust control of a parallel hybrid drivetrain with a CVT

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

Mayer, T.; Schroeder, D.

1996-09-01

In this paper the design of a robust control system for a parallel hybrid drivetrain is presented. The drivetrain is based on a continuously variable transmission (CVT) and is therefore a highly nonlinear multiple-input-multiple-output system (MIMO-System). Input-Output-Linearization offers the possibility of linearizing and of decoupling the system. Since for example the vehicle mass varies with the load and the efficiency of the gearbox depends strongly on the actual working point, an exact linearization of the plant will mostly fail. Therefore a robust control algorithm based on sliding mode is used to control the drivetrain.

Effects of multiple predator species on green treefrog (Hyla cinerea) tadpoles

USGS Publications Warehouse

Gunzburger, M.S.; Travis, J.

2005-01-01

Prey species that occur across a range of habitats may be exposed to variable communities of multiple predator species across habitats. Predicting the combined effects of multiple predators can be complex. Many experiments evaluating the effects of multiple predators on prey confound either variation in predator density with predator identity or variation in relative predator frequency with overall predation rates. We develop a new experimental design of factorial predator combinations that maintains a constant expected predation rate, under the null hypothesis of additive predator effects. We implement this design to evaluate the combined effects of three predator species (bass, aeshnid and libellulid odonate naiads) on mortality rate of a prey species, Hyla cinerea (Schneider, 1799) tadpoles, that occurs across a range of aquatic habitats. Two predator treatments (libellulid and aeshnid + libellulid) resulted in lower tadpole mortality than any of the other predator treatments. Variation in tadpole mortality across treatments was not related to coarse variation in microhabitat use, but was likely due to intraguild predation, which occurred in all predator treatments. Hyla cinerea tadpoles have constant, low survival values when exposed to many different combinations of predator species, and predation rate probably increases linearly with predator density.

Inelastic compaction, dilation and hysteresis of sandstones under hydrostatic conditions

NASA Astrophysics Data System (ADS)

Shalev, Eyal; Lyakhovsky, Vladimir; Ougier-Simonin, Audrey; Hamiel, Yariv; Zhu, Wenlu

2014-05-01

Sandstones display non-linear and inelastic behaviour such as hysteresis when subjected to cyclic loading. We present three hydrostatic compaction experiments with multiple loading-unloading cycles on Berea and Darley Dale sandstones and explain their hysteretic behaviour using non-linear inelastic compaction and dilation. Each experiment included eight to nine loading-unloading cycles with increasing maximum pressure in each subsequent cycle. Different pressure-volumetric strain relations during loading and unloading were observed. During the first cycles, under relatively low pressures, not all of the volumetric strain is recovered at the end of each cycle whereas at the last cycles, under relatively high pressures, the strain is recovered and the pressure-volumetric strain hysteresis loops are closed. The observed pressure-volumetric strain relations are non-linear and the effective bulk modulus of the sandstones changes between cycles. Observations are modelled with two inelastic deformation processes: irreversible compaction caused by changes in grain packing and recoverable compaction associated with grain contact adhesion, frictional sliding on grains or frictional sliding on cracks. The irreversible compaction is suggested to reflect rearrangement of grains into a more compact mode as the maximum pressure increases. Our model describes the `inelastic compaction envelope' in which sandstone sample will follow during hydrostatic loading. Irreversible compaction occurs when pressure is greater than a threshold value defined by the `inelastic compaction envelope'.

Hurricane Katrina’s Impact on the Mental Health of Adolescent Female Offenders

PubMed Central

Robertson, Angela A.; Morse, David T.; Baird-Thomas, Connie

2008-01-01

Exposure to multiple traumatic events and high rates of mental health problems are common among juvenile offenders. This study draws on Conservation of Resources (COR) stress theory to examine the impact of a specific trauma, Hurricane Katrina, relative to other adverse life events on the mental health of female adolescent offenders in Mississippi. Teenage girls (N = 258, 69% African American) were recruited from 4 juvenile detention centers and the state training school. Participants were interviewed about the occurrence and timing of adverse life events and hurricane-related experiences and completed a self-administered mental health assessment. Hierarchical linear regression models were used to identify predictors of anxiety and depression. Pre-hurricane family stressors, pre-hurricane traumatic events, hurricane-related property damage, and receipt of hurricane-related financial assistance significantly predicted symptoms of anxiety and depression. Findings support COR theory. Family stressors had the greatest influence on symptoms of anxiety and depression, highlighting the need for family-based services that address the multiple, inter-related problems and challenges in the lives of female juvenile offenders. PMID:19296263

Longitudinal mathematics development of students with learning disabilities and students without disabilities: a comparison of linear, quadratic, and piecewise linear mixed effects models.

PubMed

Kohli, Nidhi; Sullivan, Amanda L; Sadeh, Shanna; Zopluoglu, Cengiz

2015-04-01

Effective instructional planning and intervening rely heavily on accurate understanding of students' growth, but relatively few researchers have examined mathematics achievement trajectories, particularly for students with special needs. We applied linear, quadratic, and piecewise linear mixed-effects models to identify the best-fitting model for mathematics development over elementary and middle school and to ascertain differences in growth trajectories of children with learning disabilities relative to their typically developing peers. The analytic sample of 2150 students was drawn from the Early Childhood Longitudinal Study - Kindergarten Cohort, a nationally representative sample of United States children who entered kindergarten in 1998. We first modeled students' mathematics growth via multiple mixed-effects models to determine the best fitting model of 9-year growth and then compared the trajectories of students with and without learning disabilities. Results indicate that the piecewise linear mixed-effects model captured best the functional form of students' mathematics trajectories. In addition, there were substantial achievement gaps between students with learning disabilities and students with no disabilities, and their trajectories differed such that students without disabilities progressed at a higher rate than their peers who had learning disabilities. The results underscore the need for further research to understand how to appropriately model students' mathematics trajectories and the need for attention to mathematics achievement gaps in policy. Copyright © 2015 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Stochastic resonance in a fractional oscillator driven by multiplicative quadratic noise

NASA Astrophysics Data System (ADS)

Ren, Ruibin; Luo, Maokang; Deng, Ke

2017-02-01

Stochastic resonance of a fractional oscillator subject to an external periodic field as well as to multiplicative and additive noise is investigated. The fluctuations of the eigenfrequency are modeled as the quadratic function of the trichotomous noise. Applying the moment equation method and Shapiro-Loginov formula, we obtain the exact expression of the complex susceptibility and related stability criteria. Theoretical analysis and numerical simulations indicate that the spectral amplification (SPA) depends non-monotonicly both on the external driving frequency and the parameters of the quadratic noise. In addition, the investigations into fractional stochastic systems have suggested that both the noise parameters and the memory effect can induce the phenomenon of stochastic multi-resonance (SMR), which is previously reported and believed to be absent in the case of the multiplicative noise with only a linear term.

Work related stress and blood glucose levels.

PubMed

Sancini, A; Ricci, S; Tomei, F; Sacco, C; Pacchiarotti, A; Nardone, N; Ricci, P; Suppi, A; De Cesare, D P; Anzelmo, V; Giubilati, R; Pimpinella, B; Rosati, M V; Tomei, G

2017-01-01

The aim of the study is to evaluate work-related subjective stress in a group of workers on a major Italian company in the field of healthcare through the administration of a valid "questionnaire-tool indicator" (HSE Indicator Tool), and to analyze any correlation between stress levels taken from questionnaire scores and blood glucose values. We studied a final sample consisting of 241 subjects with different tasks. The HSE questionnaire - made up of 35 items (divided into 7 organizational dimensions) with 5 possible answers - has been distributed to all the subjects in occasion of the health surveillance examinations provided by law. The questionnaire was then analyzed using its specific software to process the results related to the 7 dimensions. These results were compared using the Pearson correlation and multiple linear regression with the blood glucose values obtained from each subject. From the analysis of the data the following areas resulted critical, in other words linked to an intermediate (yellow area) or high (red area) condition of stress: sustain from managers, sustain from colleagues, quality of relationships and professional changes. A significant positive correlation (p <0.05) between the mean values of all critical areas and the concentrations of glucose values have been highlighted with the correlation index of Pearson. Multiple linear regression confirmed these findings, showing that the critical dimensions resulting from the questionnaire were the significant variables that can increase the levels of blood glucose. The preliminary results indicate that perceived work stress can be statistically associated with increased levels of blood glucose.

A time-domain decomposition iterative method for the solution of distributed linear quadratic optimal control problems

NASA Astrophysics Data System (ADS)

Heinkenschloss, Matthias

2005-01-01

We study a class of time-domain decomposition-based methods for the numerical solution of large-scale linear quadratic optimal control problems. Our methods are based on a multiple shooting reformulation of the linear quadratic optimal control problem as a discrete-time optimal control (DTOC) problem. The optimality conditions for this DTOC problem lead to a linear block tridiagonal system. The diagonal blocks are invertible and are related to the original linear quadratic optimal control problem restricted to smaller time-subintervals. This motivates the application of block Gauss-Seidel (GS)-type methods for the solution of the block tridiagonal systems. Numerical experiments show that the spectral radii of the block GS iteration matrices are larger than one for typical applications, but that the eigenvalues of the iteration matrices decay to zero fast. Hence, while the GS method is not expected to convergence for typical applications, it can be effective as a preconditioner for Krylov-subspace methods. This is confirmed by our numerical tests.A byproduct of this research is the insight that certain instantaneous control techniques can be viewed as the application of one step of the forward block GS method applied to the DTOC optimality system.

Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

NASA Astrophysics Data System (ADS)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2017-04-01

This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

Forest management and economics

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

Buongiorno, J.; Gilless, J.K.

1987-01-01

This volume provides a survey of quantitative methods, guiding the reader through formulation and analysis of models that address forest management problems. The authors use simple mathematics, graphics, and short computer programs to explain each method. Emphasizing applications, they discuss linear, integer, dynamic, and goal programming; simulation; network modeling; and econometrics, as these relate to problems of determining economic harvest schedules in even-aged and uneven-aged forests, the evaluation of forest policies, multiple-objective decision making, and more.

Modified Hyperspheres Algorithm to Trace Homotopy Curves of Nonlinear Circuits Composed by Piecewise Linear Modelled Devices

PubMed Central

Vazquez-Leal, H.; Jimenez-Fernandez, V. M.; Benhammouda, B.; Filobello-Nino, U.; Sarmiento-Reyes, A.; Ramirez-Pinero, A.; Marin-Hernandez, A.; Huerta-Chua, J.

2014-01-01

We present a homotopy continuation method (HCM) for finding multiple operating points of nonlinear circuits composed of devices modelled by using piecewise linear (PWL) representations. We propose an adaptation of the modified spheres path tracking algorithm to trace the homotopy trajectories of PWL circuits. In order to assess the benefits of this proposal, four nonlinear circuits composed of piecewise linear modelled devices are analysed to determine their multiple operating points. The results show that HCM can find multiple solutions within a single homotopy trajectory. Furthermore, we take advantage of the fact that homotopy trajectories are PWL curves meant to replace the multidimensional interpolation and fine tuning stages of the path tracking algorithm with a simple and highly accurate procedure based on the parametric straight line equation. PMID:25184157

Mental ability and psychological work performance in Chinese workers.

PubMed

Zhong, Fei; Yano, Eiji; Lan, Yajia; Wang, Mianzhen; Wang, Zhiming; Wang, Xiaorong

2006-10-01

This study was to explore the relationship among mental ability, occupational stress, and psychological work performance in Chinese workers, and to identify relevant modifiers of mental ability and psychological work performance. Psychological Stress Intensity (PSI), psychological work performance, and mental ability (Mental Function Index, MFI) were determined among 485 Chinese workers (aged 33 to 62 yr, 65% of men) with varied work occupations. Occupational Stress Questionnaire (OSQ) and mental ability with 3 tests (including immediate memory, digit span, and cipher decoding) were used. The relationship between mental ability and psychological work performance was analyzed with multiple linear regression approach. PSI, MFI, or psychological work performance were significantly different among different work types and educational level groups (p<0.01). Multiple linear regression analysis showed that MFI was significantly related to gender, age, educational level, and work type. Higher MFI and lower PSI predicted a better psychological work performance, even after adjusted for gender, age, educational level, and work type. The study suggests that occupational stress and low mental ability are important predictors for poor psychological work performance, which is modified by both gender and educational level.

Prediction of octanol-water partition coefficients of organic compounds by multiple linear regression, partial least squares, and artificial neural network.

PubMed

Golmohammadi, Hassan

2009-11-30

A quantitative structure-property relationship (QSPR) study was performed to develop models those relate the structure of 141 organic compounds to their octanol-water partition coefficients (log P(o/w)). A genetic algorithm was applied as a variable selection tool. Modeling of log P(o/w) of these compounds as a function of theoretically derived descriptors was established by multiple linear regression (MLR), partial least squares (PLS), and artificial neural network (ANN). The best selected descriptors that appear in the models are: atomic charge weighted partial positively charged surface area (PPSA-3), fractional atomic charge weighted partial positive surface area (FPSA-3), minimum atomic partial charge (Qmin), molecular volume (MV), total dipole moment of molecule (mu), maximum antibonding contribution of a molecule orbital in the molecule (MAC), and maximum free valency of a C atom in the molecule (MFV). The result obtained showed the ability of developed artificial neural network to prediction of partition coefficients of organic compounds. Also, the results revealed the superiority of ANN over the MLR and PLS models. Copyright 2009 Wiley Periodicals, Inc.

Systematic Analysis of Absorbed Anti-Inflammatory Constituents and Metabolites of Sarcandra glabra in Rat Plasma Using Ultra-High-Pressure Liquid Chromatography Coupled with Linear Trap Quadrupole Orbitrap Mass Spectrometry.

PubMed

Li, Xiong; Zhao, Jin; Liu, Jianxing; Li, Geng; Zhao, Ya; Zeng, Xing

2016-01-01

Ultra-high-pressure liquid chromatography (UHPLC) was coupled with linear ion trap quadrupole Orbitrap mass spectrometry (LTQ-Orbitrap) and was used for the first time to systematically analyze the absorbed components and metabolites in rat plasma after oral administration of the water extract of Sarcandra glabra. This extract is a well-known Chinese herbal medicine for the treatment of inflammation and immunity related diseases. The anti-inflammatory activities of the absorbed components were evaluated by measuring nitric oxide (NO) production and proinflammatory genes expression in lipopolysaccharide (LPS)-stimulated murine RAW 264.7 macrophages. As a result, 54 components in Sarcandra glabra were detected in dosed rat plasma, and 36 of them were positively identified. Moreover, 23 metabolites were characterized and their originations were traced. Furthermore, 20 of the 24 studied components showed anti-inflammatory activities. These results provide evidence that this method efficiency detected constituents in plasma based on the anti-inflammatory mechanism of multiple components and would be a useful technique for screening multiple targets for natural medicine research.

Patterns of adverse childhood experiences and substance use among young adults: A latent class analysis.

PubMed

Shin, Sunny H; McDonald, Shelby Elaine; Conley, David

2018-03-01

Adverse childhood experiences (ACEs) have been strongly linked with subsequent substance use. The aim of this study was to investigate how different patterns of ACEs influence substance use in young adulthood. Using a community sample of young individuals (N=336; ages 18-25), we performed latent class analyses (LCA) to identify homogenous groups of young people with similar patterns of ACEs. Exposure to ACEs incorporates 13 childhood adversities including childhood maltreatment, household dysfunction, and community violence. Multiple linear and logistic regression models were used in an effort to examine the associations between ACEs classes and four young adult outcomes such as alcohol-related problems, current tobacco use, drug dependence symptoms, and psychological distress. LCA identified four heterogeneous classes of young people distinguished by different patterns of ACEs exposure: Low ACEs (56%), Household Dysfunction/Community Violence (14%), Emotional ACEs (14%), and High/Multiple ACEs (16%). Multiple regression analyses found that compared to those in the Low ACEs class, young adults in the High/Multiple ACEs class reported more alcohol-related problems, current tobacco use, and psychological symptoms, controlling for sociodemographic characteristics and common risk factors for substance use such as peer substance use. Our findings confirm that for many young people, ACEs occur as multiple rather than single experiences. The results of this research suggest that exposure to poly-victimization during childhood is particularly related to substance use during young adulthood. Copyright © 2017 Elsevier Ltd. All rights reserved.

Role of multiparton interactions on J /ψ production in p +p collisions at LHC energies

NASA Astrophysics Data System (ADS)

Thakur, Dhananjaya; De, Sudipan; Sahoo, Raghunath; Dansana, Soumya

2018-05-01

The production mechanism of quarkonia states in hadronic collisions is still to be understood by the scientific community. In high-multiplicity p +p collisions, underlying event observables are of major interest. The multiparton interactions (MPIs) are underlying event observables, in which several interactions occur at the partonic level in a single p +p event. This leads to dependence of particle production on event multiplicity. If the MPI occurs in a harder scale, there will be a correlation between the yield of quarkonia and total charged-particle multiplicity. The ALICE experiment at the LHC in p +p collisions at √{s }=7 and 13 TeV has observed an approximate linear increase of relative J /ψ yield, (d/NJ /ψ/d y ⟨d NJ /ψ/d y ⟩ ), with relative charged-particle multiplicity density, (d/Nch/d y ⟨d Nch/d y ⟩ ). In our present work, we have performed a comprehensive study of the production of charmonia as a function of charged-particle multiplicity in p +p collisions at LHC energies using the perturbative QCD-inspired multiparton interaction model, pythia8 tune 4C, with and without the color reconnection scheme. A detailed multiplicity and energy-dependent study is performed to understand the effects of MPI on J /ψ production. The ratio of ψ (2 S ) to J /ψ is also studied as a function of charged-particle multiplicity at LHC energies.

Multiple Equilibria Associated with Response of the ITCZ to Seasonal SST Forcing

NASA Technical Reports Server (NTRS)

Chao, Winston C.

1998-01-01

Supported by numerical experiment results, the abrupt change of the location of the intertropical convergence zone (ITCZ), from the equatorial trough flow regime to the monsoon trough flow regime is interpreted as a subcritical instability. The existence of these multiple quasi-equilibria is due to the balance of two "forces" on the ITCZ: one toward the equator, due to the earth's rotation, has a nonlinear latitudinal dependence; and the other toward the latitude of the sea surface (or ground) temperature peak has a relatively linear latitudinal dependence. This work pivots on the finding that the ITCZ and Hadley circulation can still exist without the pole-to-equator gradient of radiative-convective equilibrium temperature.

Multiple ionization of C 60 in collisions with 2.33 MeV/u O-ions and giant plasmon excitation

NASA Astrophysics Data System (ADS)

Kelkar, A. H.; Kadhane, U.; Misra, D.; Kumar, Ajay; Tribedi, L. C.

2007-03-01

Single and multiple ionization of C60 in collisions with fast (v = 9.7 a.u.) Oq+ ions have been studied. Relative cross sections for production of C 601+ to C 604+ have been measured. The intensity ratios of double-to-single ionization agree very well with a model based on giant dipole plasmon resonance (GDPR). Almost linear increasing trend of the yields of single and double ionizations with projectile charge state is well reproduced by the single and double plasmon excitation mechanisms. The observed charge state independence of triple and quadruple ionization is in sharp contrast to the GDPR model.

Estimation of aboveground biomass in Mediterranean forests by statistical modelling of ASTER fraction images

NASA Astrophysics Data System (ADS)

Fernández-Manso, O.; Fernández-Manso, A.; Quintano, C.

2014-09-01

Aboveground biomass (AGB) estimation from optical satellite data is usually based on regression models of original or synthetic bands. To overcome the poor relation between AGB and spectral bands due to mixed-pixels when a medium spatial resolution sensor is considered, we propose to base the AGB estimation on fraction images from Linear Spectral Mixture Analysis (LSMA). Our study area is a managed Mediterranean pine woodland (Pinus pinaster Ait.) in central Spain. A total of 1033 circular field plots were used to estimate AGB from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) optical data. We applied Pearson correlation statistics and stepwise multiple regression to identify suitable predictors from the set of variables of original bands, fraction imagery, Normalized Difference Vegetation Index and Tasselled Cap components. Four linear models and one nonlinear model were tested. A linear combination of ASTER band 2 (red, 0.630-0.690 μm), band 8 (short wave infrared 5, 2.295-2.365 μm) and green vegetation fraction (from LSMA) was the best AGB predictor (Radj2=0.632, the root-mean-squared error of estimated AGB was 13.3 Mg ha-1 (or 37.7%), resulting from cross-validation), rather than other combinations of the above cited independent variables. Results indicated that using ASTER fraction images in regression models improves the AGB estimation in Mediterranean pine forests. The spatial distribution of the estimated AGB, based on a multiple linear regression model, may be used as baseline information for forest managers in future studies, such as quantifying the regional carbon budget, fuel accumulation or monitoring of management practices.

Properties of a novel linear sulfur response mode in a multiple flame photometric detector.

PubMed

Clark, Adrian G; Thurbide, Kevin B

2014-01-24

A new linear sulfur response mode was established in the multiple flame photometric detector (mFPD) by monitoring HSO* emission in the red spectral region above 600nm. Optimal conditions for this mode were found by using a 750nm interference filter and oxygen flows to the worker flames of this device that were about 10mL/min larger than those used for monitoring quadratic S2* emission. By employing these parameters, this mode provided a linear response over about 4 orders of magnitude, with a detection limit near 5.8×10(-11)gS/s and a selectivity of sulfur over carbon of about 3.5×10(3). Specifically, the minimum detectable masses for 10 different sulfur analytes investigated ranged from 0.4 to 3.6ng for peak half-widths spanning 4-6s. The response toward ten different sulfur compounds was examined and produced an average reproducibility of 1.7% RSD (n=10) and an average equimolarity value of 1.0±0.1. In contrast to this, a conventional single flame S2* mode comparatively yielded respective values of 6.7% RSD (n=10) and 1.1±0.4. HSO* emission in the mFPD was also found to be relatively much less affected by response quenching due to hydrocarbons compared to a conventional single flame S2* emission mode. Results indicate that this new alternative linear mFPD response mode could be beneficial for sulfur monitoring applications. Copyright © 2013 Elsevier B.V. All rights reserved.

An inventory on rotational kinematics of a particle: unravelling misconceptions and pitfalls in reasoning

NASA Astrophysics Data System (ADS)

Mashood, K. K.; Singh, Vijay A.

2012-09-01

Student difficulties regarding the angular velocity (\\vec{\\omega }) and angular acceleration (\\vec{\\alpha }) of a particle have remained relatively unexplored in contrast to their linear counterparts. We present an inventory comprising multiple choice questions aimed at probing misconceptions and eliciting ill-suited reasoning patterns. The development of the inventory was based on interactions with students, teachers and experts. We report misconceptions, some of which are parallel to those found earlier in linear kinematics. Fixations with inappropriate prototypes were uncovered. Many students and even teachers mistakenly assume that all rotational motion is necessarily circular. A persistent notion that the direction of \\vec{\\omega } and \\vec{\\alpha } should be ‘along’ the motion exists. Instances of indiscriminate usage of equations were identified.

Bayesian analysis of non-linear differential equation models with application to a gut microbial ecosystem.

PubMed

Lawson, Daniel J; Holtrop, Grietje; Flint, Harry

2011-07-01

Process models specified by non-linear dynamic differential equations contain many parameters, which often must be inferred from a limited amount of data. We discuss a hierarchical Bayesian approach combining data from multiple related experiments in a meaningful way, which permits more powerful inference than treating each experiment as independent. The approach is illustrated with a simulation study and example data from experiments replicating the aspects of the human gut microbial ecosystem. A predictive model is obtained that contains prediction uncertainty caused by uncertainty in the parameters, and we extend the model to capture situations of interest that cannot easily be studied experimentally. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Single-Photon-Sensitive HgCdTe Avalanche Photodiode Detector

NASA Technical Reports Server (NTRS)

Huntington, Andrew

2013-01-01

The purpose of this program was to develop single-photon-sensitive short-wavelength infrared (SWIR) and mid-wavelength infrared (MWIR) avalanche photodiode (APD) receivers based on linear-mode HgCdTe APDs, for application by NASA in light detection and ranging (lidar) sensors. Linear-mode photon-counting APDs are desired for lidar because they have a shorter pixel dead time than Geiger APDs, and can detect sequential pulse returns from multiple objects that are closely spaced in range. Linear-mode APDs can also measure photon number, which Geiger APDs cannot, adding an extra dimension to lidar scene data for multi-photon returns. High-gain APDs with low multiplication noise are required for efficient linear-mode detection of single photons because of APD gain statistics -- a low-excess-noise APD will generate detectible current pulses from single photon input at a much higher rate of occurrence than will a noisy APD operated at the same average gain. MWIR and LWIR electron-avalanche HgCdTe APDs have been shown to operate in linear mode at high average avalanche gain (M > 1000) without excess multiplication noise (F = 1), and are therefore very good candidates for linear-mode photon counting. However, detectors fashioned from these narrow-bandgap alloys require aggressive cooling to control thermal dark current. Wider-bandgap SWIR HgCdTe APDs were investigated in this program as a strategy to reduce detector cooling requirements.

Chaotic examination

NASA Astrophysics Data System (ADS)

Bildirici, Melike; Sonustun, Fulya Ozaksoy; Sonustun, Bahri

2018-01-01

In the regards of chaos theory, new concepts such as complexity, determinism, quantum mechanics, relativity, multiple equilibrium, complexity, (continuously) instability, nonlinearity, heterogeneous agents, irregularity were widely questioned in economics. It is noticed that linear models are insufficient for analyzing unpredictable, irregular and noncyclical oscillations of economies, and for predicting bubbles, financial crisis, business cycles in financial markets. Therefore, economists gave great consequence to use appropriate tools for modelling non-linear dynamical structures and chaotic behaviors of the economies especially in macro and the financial economy. In this paper, we aim to model the chaotic structure of exchange rates (USD-TL and EUR-TL). To determine non-linear patterns of the selected time series, daily returns of the exchange rates were tested by BDS during the period from January 01, 2002 to May 11, 2017 which covers after the era of the 2001 financial crisis. After specifying the non-linear structure of the selected time series, it was aimed to examine the chaotic characteristic for the selected time period by Lyapunov Exponents. The findings verify the existence of the chaotic structure of the exchange rate returns in the analyzed time period.

Formation of template-switching artifacts by linear amplification.

PubMed

Chakravarti, Dhrubajyoti; Mailander, Paula C

2008-07-01

Linear amplification is a method of synthesizing single-stranded DNA from either a single-stranded DNA or one strand of a double-stranded DNA. In this protocol, molecules of a single primer DNA are extended by multiple rounds of DNA synthesis at high temperature using thermostable DNA polymerases. Although linear amplification generates the intended full-length single-stranded product, it is more efficient over single-stranded templates than double-stranded templates. We analyzed linear amplification over single- or double-stranded mouse H-ras DNA (exon 1-2 region). The single-stranded H-ras template yielded only the intended product. However, when the double-stranded template was used, additional artifact products were observed. Increasing the concentration of the double-stranded template produced relatively higher amounts of these artifact products. One of the artifact DNA bands could be mapped and analyzed by sequencing. It contained three template-switching products. These DNAs were formed by incomplete DNA strand extension over the template strand, followed by switching to the complementary strand at a specific Ade nucleotide within a putative hairpin sequence, from which DNA synthesis continued over the complementary strand.

Socio-economic factors associated with infant mortality in Italy: an ecological study.

PubMed

Dallolio, Laura; Di Gregori, Valentina; Lenzi, Jacopo; Franchino, Giuseppe; Calugi, Simona; Domenighetti, Gianfranco; Fantini, Maria Pia

2012-08-16

One issue that continues to attract the attention of public health researchers is the possible relationship in high-income countries between income, income inequality and infant mortality (IM). The aim of this study was to assess the associations between IM and major socio-economic determinants in Italy. Associations between infant mortality rates in the 20 Italian regions (2006-2008) and the Gini index of income inequality, mean household income, percentage of women with at least 8 years of education, and percentage of unemployed aged 15-64 years were assessed using Pearson correlation coefficients. Univariate linear regression and multiple stepwise linear regression analyses were performed to determine the magnitude and direction of the effect of the four socio-economic variables on IM. The Gini index and the total unemployment rate showed a positive strong correlation with IM (r = 0.70; p < 0.001 and r = 0.84; p < 0.001 respectively), mean household income showed a strong negative correlation (r = -0.78; p < 0.001), while female educational attainment presented a weak negative correlation (r = -0.45; p < 0.05). Using a multiple stepwise linear regression model, only unemployment rate was independently associated with IM (b = 0.15, p < 0.001). In Italy, a high-income country where health care is universally available, variations in IM were strongly associated with relative and absolute income and unemployment rate. These results suggest that in Italy IM is not only related to income distribution, as demonstrated for other developed countries, but also to economic factors such as absolute income and unemployment. In order to reduce IM and the existing inequalities, the challenge for Italian decision makers is to promote economic growth and enhance employment levels.

Trends in bullying victimization by gender among U.S. high school students.

PubMed

Pontes, Nancy M H; Ayres, Cynthia G; Lewandowski, Carla; Pontes, Manuel C F

2018-06-01

This research used four consecutive waves of data from the National Youth Risk Behavior Survey (YRBS) conducted by the Centers for Disease Control (CDC), to estimate linear time trends by gender in the prevalence of school and electronic bullying victimization among U.S. high school students (N = 61,042). Dependent variables were student self-reported school bullying victimization and electronic bullying victimization during the previous 12 months. Independent variables used to estimate multiple logistic regression models by gender were survey year, race/ethnicity, and grade level. Results showed the prevalence of school bullying increased significantly among females from 2009 (21.2%) to 2015 (24.8%), linear trend OR = 1.08 [1.04, 1.12]; and decreased significantly among males from 2009 (18.7%) to 2015 (15.8%), linear trend OR = 0.93 [0.89, 0.98]. Prevalence of electronic bullying was unchanged between 2011 to 2015 among both male and female students. Asian race, relative to White race, was associated with significantly lower rates of both school and electronic bullying victimization among females, but not males. The incidence of school and electronic bullying victimization was significantly lower among Black and Hispanic students, but not among multiple-race students, regardless of student gender. Healthy People 2020 set a goal to reduce school bullying victimization 10% by 2019. As of 2015, school bullying victimization decreased significantly among males (16% decrease); it significantly increased among females (17% increase). Future research should explore underlying factors related to these divergent trends, and develop effective strategies to reverse the alarming rise in female school bullying victimization. © 2018 Wiley Periodicals, Inc.

Minimizing energy dissipation of matrix multiplication kernel on Virtex-II

NASA Astrophysics Data System (ADS)

Choi, Seonil; Prasanna, Viktor K.; Jang, Ju-wook

2002-07-01

In this paper, we develop energy-efficient designs for matrix multiplication on FPGAs. To analyze the energy dissipation, we develop a high-level model using domain-specific modeling techniques. In this model, we identify architecture parameters that significantly affect the total energy (system-wide energy) dissipation. Then, we explore design trade-offs by varying these parameters to minimize the system-wide energy. For matrix multiplication, we consider a uniprocessor architecture and a linear array architecture to develop energy-efficient designs. For the uniprocessor architecture, the cache size is a parameter that affects the I/O complexity and the system-wide energy. For the linear array architecture, the amount of storage per processing element is a parameter affecting the system-wide energy. By using maximum amount of storage per processing element and minimum number of multipliers, we obtain a design that minimizes the system-wide energy. We develop several energy-efficient designs for matrix multiplication. For example, for 6×6 matrix multiplication, energy savings of upto 52% for the uniprocessor architecture and 36% for the linear arrary architecture is achieved over an optimized library for Virtex-II FPGA from Xilinx.

Linear and Nonlinear Thinking: A Multidimensional Model and Measure

ERIC Educational Resources Information Center

Groves, Kevin S.; Vance, Charles M.

2015-01-01

Building upon previously developed and more general dual-process models, this paper provides empirical support for a multidimensional thinking style construct comprised of linear thinking and multiple dimensions of nonlinear thinking. A self-report assessment instrument (Linear/Nonlinear Thinking Style Profile; LNTSP) is presented and…

Scattering properties of alumina particle clusters with different radius of monomers in aerocraft plume

NASA Astrophysics Data System (ADS)

Li, Jingying; Bai, Lu; Wu, Zhensen; Guo, Lixin; Gong, Yanjun

2017-11-01

In this paper, diffusion limited aggregation (DLA) algorithm is improved to generate the alumina particle cluster with different radius of monomers in the plume. Scattering properties of these alumina clusters are solved by the multiple sphere T matrix method (MSTM). The effect of the number and radius of monomers on the scattering properties of clusters of alumina particles is discussed. The scattering properties of two types of alumina particle clusters are compared, one has different radius of monomers that follows lognormal probability distribution, another has the same radius of monomers that equals the mean of lognormal probability distribution. The result show that the scattering phase functions and linear polarization degrees of these two types of alumina particle clusters are of great differences. For the alumina clusters with different radius of monomers, the forward scatterings are bigger and the linear polarization degree has multiple peaks. Moreover, the vary of their scattering properties do not have strong correlative with the change of number of monomers. For larger booster motors, 25-38% of the plume being condensed alumina. The alumina can scatter radiation from other sources present in the plume and effect on radiation transfer characteristics of plume. In addition, the shape, size distribution and refractive index of the particles in the plume are estimated by linear polarization degree. Therefore, accurate scattering properties calculation is very important to decrease the deviation in the related research.

Comparison of two-concentration with multi-concentration linear regressions: Retrospective data analysis of multiple regulated LC-MS bioanalytical projects.

PubMed

Musuku, Adrien; Tan, Aimin; Awaiye, Kayode; Trabelsi, Fethi

2013-09-01

Linear calibration is usually performed using eight to ten calibration concentration levels in regulated LC-MS bioanalysis because a minimum of six are specified in regulatory guidelines. However, we have previously reported that two-concentration linear calibration is as reliable as or even better than using multiple concentrations. The purpose of this research is to compare two-concentration with multiple-concentration linear calibration through retrospective data analysis of multiple bioanalytical projects that were conducted in an independent regulated bioanalytical laboratory. A total of 12 bioanalytical projects were randomly selected: two validations and two studies for each of the three most commonly used types of sample extraction methods (protein precipitation, liquid-liquid extraction, solid-phase extraction). When the existing data were retrospectively linearly regressed using only the lowest and the highest concentration levels, no extra batch failure/QC rejection was observed and the differences in accuracy and precision between the original multi-concentration regression and the new two-concentration linear regression are negligible. Specifically, the differences in overall mean apparent bias (square root of mean individual bias squares) are within the ranges of -0.3% to 0.7% and 0.1-0.7% for the validations and studies, respectively. The differences in mean QC concentrations are within the ranges of -0.6% to 1.8% and -0.8% to 2.5% for the validations and studies, respectively. The differences in %CV are within the ranges of -0.7% to 0.9% and -0.3% to 0.6% for the validations and studies, respectively. The average differences in study sample concentrations are within the range of -0.8% to 2.3%. With two-concentration linear regression, an average of 13% of time and cost could have been saved for each batch together with 53% of saving in the lead-in for each project (the preparation of working standard solutions, spiking, and aliquoting). Furthermore, examples are given as how to evaluate the linearity over the entire concentration range when only two concentration levels are used for linear regression. To conclude, two-concentration linear regression is accurate and robust enough for routine use in regulated LC-MS bioanalysis and it significantly saves time and cost as well. Copyright © 2013 Elsevier B.V. All rights reserved.

Investigation of Sunspot Area Varying with Sunspot Number

NASA Astrophysics Data System (ADS)

Li, K. J.; Li, F. Y.; Zhang, J.; Feng, W.

2016-11-01

The statistical relationship between sunspot area (SA) and sunspot number (SN) is investigated through analysis of their daily observation records from May 1874 to April 2015. For a total of 1607 days, representing 3 % of the total interval considered, either SA or SN had a value of zero while the other parameter did not. These occurrences most likely reflect the report of short-lived spots by a single observatory and subsequent averaging of zero values over multiple stations. The main results obtained are as follows: i) The number of spotless days around the minimum of a solar cycle is statistically negatively correlated with the maximum strength of solar activity of that cycle. ii) The probability distribution of SA generally decreases monotonically with SA, but the distribution of SN generally increases first, then it decreases as a whole. The different probability distribution of SA and SN should strengthen their non-linear relation, and the correction factor [k] in the definition of SN may be one of the factors that cause the non-linearity. iii) The non-linear relation of SA and SN indeed exists statistically, and it is clearer during the maximum epoch of a solar cycle.

Modeling thermal sensation in a Mediterranean climate—a comparison of linear and ordinal models

NASA Astrophysics Data System (ADS)

Pantavou, Katerina; Lykoudis, Spyridon

2014-08-01

A simple thermo-physiological model of outdoor thermal sensation adjusted with psychological factors is developed aiming to predict thermal sensation in Mediterranean climates. Microclimatic measurements simultaneously with interviews on personal and psychological conditions were carried out in a square, a street canyon and a coastal location of the greater urban area of Athens, Greece. Multiple linear and ordinal regression were applied in order to estimate thermal sensation making allowance for all the recorded parameters or specific, empirically selected, subsets producing so-called extensive and empirical models, respectively. Meteorological, thermo-physiological and overall models - considering psychological factors as well - were developed. Predictions were improved when personal and psychological factors were taken into account as compared to meteorological models. The model based on ordinal regression reproduced extreme values of thermal sensation vote more adequately than the linear regression one, while the empirical model produced satisfactory results in relation to the extensive model. The effects of adaptation and expectation on thermal sensation vote were introduced in the models by means of the exposure time, season and preference related to air temperature and irradiation. The assessment of thermal sensation could be a useful criterion in decision making regarding public health, outdoor spaces planning and tourism.

DYGABCD: A program for calculating linear A, B, C, and D matrices from a nonlinear dynamic engine simulation

NASA Technical Reports Server (NTRS)

Geyser, L. C.

1978-01-01

A digital computer program, DYGABCD, was developed that generates linearized, dynamic models of simulated turbofan and turbojet engines. DYGABCD is based on an earlier computer program, DYNGEN, that is capable of calculating simulated nonlinear steady-state and transient performance of one- and two-spool turbojet engines or two- and three-spool turbofan engines. Most control design techniques require linear system descriptions. For multiple-input/multiple-output systems such as turbine engines, state space matrix descriptions of the system are often desirable. DYGABCD computes the state space matrices commonly referred to as the A, B, C, and D matrices required for a linear system description. The report discusses the analytical approach and provides a users manual, FORTRAN listings, and a sample case.

Transmit Designs for the MIMO Broadcast Channel With Statistical CSI

NASA Astrophysics Data System (ADS)

Wu, Yongpeng; Jin, Shi; Gao, Xiqi; McKay, Matthew R.; Xiao, Chengshan

2014-09-01

We investigate the multiple-input multiple-output broadcast channel with statistical channel state information available at the transmitter. The so-called linear assignment operation is employed, and necessary conditions are derived for the optimal transmit design under general fading conditions. Based on this, we introduce an iterative algorithm to maximize the linear assignment weighted sum-rate by applying a gradient descent method. To reduce complexity, we derive an upper bound of the linear assignment achievable rate of each receiver, from which a simplified closed-form expression for a near-optimal linear assignment matrix is derived. This reveals an interesting construction analogous to that of dirty-paper coding. In light of this, a low complexity transmission scheme is provided. Numerical examples illustrate the significant performance of the proposed low complexity scheme.

Non-linear wave-particle interactions and fast ion loss induced by multiple Alfvén eigenmodes in the DIII-D tokamak

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

Chen, Xi; Kramer, Gerrit J.; Heidbrink, William W.

2014-05-21

A new non-linear feature has been observed in fast-ion loss from tokamak plasmas in the form of oscillations at the sum, difference and second harmonic frequencies of two independent Alfvén eigenmodes (AEs). Full orbit calculations and analytic theory indicate this non-linearity is due to coupling of fast-ion orbital response as it passes through each AE — a change in wave-particle phase k • r by one mode alters the force exerted by the next. Furthermore, the loss measurement is of barely confined, non-resonant particles, while similar non-linear interactions can occur between well-confined particles and multiple AEs leading to enhanced fast-ionmore » transport.« less

Statistical experiments using the multiple regression research for prediction of proper hardness in areas of phosphorus cast-iron brake shoes manufacturing

NASA Astrophysics Data System (ADS)

Kiss, I.; Cioată, V. G.; Ratiu, S. A.; Rackov, M.; Penčić, M.

2018-01-01

Multivariate research is important in areas of cast-iron brake shoes manufacturing, because many variables interact with each other simultaneously. This article focuses on expressing the multiple linear regression model related to the hardness assurance by the chemical composition of the phosphorous cast irons destined to the brake shoes, having in view that the regression coefficients will illustrate the unrelated contributions of each independent variable towards predicting the dependent variable. In order to settle the multiple correlations between the hardness of the cast-iron brake shoes, and their chemical compositions several regression equations has been proposed. Is searched a mathematical solution which can determine the optimum chemical composition for the hardness desirable values. Starting from the above-mentioned affirmations two new statistical experiments are effectuated related to the values of Phosphorus [P], Manganese [Mn] and Silicon [Si]. Therefore, the regression equations, which describe the mathematical dependency between the above-mentioned elements and the hardness, are determined. As result, several correlation charts will be revealed.

Spatial and Temporal Scaling of Thermal Infrared Remote Sensing Data

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Goel, Narendra S.

1995-01-01

Although remote sensing has a central role to play in the acquisition of synoptic data obtained at multiple spatial and temporal scales to facilitate our understanding of local and regional processes as they influence the global climate, the use of thermal infrared (TIR) remote sensing data in this capacity has received only minimal attention. This results from some fundamental challenges that are associated with employing TIR data collected at different space and time scales, either with the same or different sensing systems, and also from other problems that arise in applying a multiple scaled approach to the measurement of surface temperatures. In this paper, we describe some of the more important problems associated with using TIR remote sensing data obtained at different spatial and temporal scales, examine why these problems appear as impediments to using multiple scaled TIR data, and provide some suggestions for future research activities that may address these problems. We elucidate the fundamental concept of scale as it relates to remote sensing and explore how space and time relationships affect TIR data from a problem-dependency perspective. We also describe how linearity and non-linearity observation versus parameter relationships affect the quantitative analysis of TIR data. Some insight is given on how the atmosphere between target and sensor influences the accurate measurement of surface temperatures and how these effects will be compounded in analyzing multiple scaled TIR data. Last, we describe some of the challenges in modeling TIR data obtained at different space and time scales and discuss how multiple scaled TIR data can be used to provide new and important information for measuring and modeling land-atmosphere energy balance processes.

A Constrained Linear Estimator for Multiple Regression

ERIC Educational Resources Information Center

Davis-Stober, Clintin P.; Dana, Jason; Budescu, David V.

2010-01-01

"Improper linear models" (see Dawes, Am. Psychol. 34:571-582, "1979"), such as equal weighting, have garnered interest as alternatives to standard regression models. We analyze the general circumstances under which these models perform well by recasting a class of "improper" linear models as "proper" statistical models with a single predictor. We…

Multivariate Linear Regression and CART Regression Analysis of TBM Performance at Abu Hamour Phase-I Tunnel

NASA Astrophysics Data System (ADS)

Jakubowski, J.; Stypulkowski, J. B.; Bernardeau, F. G.

2017-12-01

The first phase of the Abu Hamour drainage and storm tunnel was completed in early 2017. The 9.5 km long, 3.7 m diameter tunnel was excavated with two Earth Pressure Balance (EPB) Tunnel Boring Machines from Herrenknecht. TBM operation processes were monitored and recorded by Data Acquisition and Evaluation System. The authors coupled collected TBM drive data with available information on rock mass properties, cleansed, completed with secondary variables and aggregated by weeks and shifts. Correlations and descriptive statistics charts were examined. Multivariate Linear Regression and CART regression tree models linking TBM penetration rate (PR), penetration per revolution (PPR) and field penetration index (FPI) with TBM operational and geotechnical characteristics were performed for the conditions of the weak/soft rock of Doha. Both regression methods are interpretable and the data were screened with different computational approaches allowing enriched insight. The primary goal of the analysis was to investigate empirical relations between multiple explanatory and responding variables, to search for best subsets of explanatory variables and to evaluate the strength of linear and non-linear relations. For each of the penetration indices, a predictive model coupling both regression methods was built and validated. The resultant models appeared to be stronger than constituent ones and indicated an opportunity for more accurate and robust TBM performance predictions.

A Common Mechanism for Resistance to Oxime Reactivation of Acetylcholinesterase Inhibited by Organophosphorus Compounds

DTIC Science & Technology

2013-01-01

application of the Hammett equation with the constants rph in the chemistry of organophosphorus compounds, Russ. Chem. Rev. 38 (1969) 795–811. [13...of oximes and OP compounds and the ability of oximes to reactivate OP- inhibited AChE. Multiple linear regression equations were analyzed using...phosphonate pairs, 21 oxime/ phosphoramidate pairs and 12 oxime/phosphate pairs. The best linear regression equation resulting from multiple regression anal

Pleiotropy Analysis of Quantitative Traits at Gene Level by Multivariate Functional Linear Models

PubMed Central

Wang, Yifan; Liu, Aiyi; Mills, James L.; Boehnke, Michael; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Xiong, Momiao; Wu, Colin O.; Fan, Ruzong

2015-01-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks’s Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. PMID:25809955

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

PubMed

Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

2015-05-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

Wavelet regression model in forecasting crude oil price

NASA Astrophysics Data System (ADS)

Hamid, Mohd Helmie; Shabri, Ani

2017-05-01

This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

New nonlinear control algorithms for multiple robot arms

NASA Technical Reports Server (NTRS)

Tarn, T. J.; Bejczy, A. K.; Yun, X.

1988-01-01

Multiple coordinated robot arms are modeled by considering the arms as closed kinematic chains and as a force-constrained mechanical system working on the same object simultaneously. In both formulations, a novel dynamic control method is discussed. It is based on feedback linearization and simultaneous output decoupling technique. By applying a nonlinear feedback and a nonlinear coordinate transformation, the complicated model of the multiple robot arms in either formulation is converted into a linear and output decoupled system. The linear system control theory and optimal control theory are used to design robust controllers in the task space. The first formulation has the advantage of automatically handling the coordination and load distribution among the robot arms. In the second formulation, it was found that by choosing a general output equation it became possible simultaneously to superimpose the position and velocity error feedback with the force-torque error feedback in the task space.

Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model.

PubMed

Seaman, Shaun R; Hughes, Rachael A

2018-06-01

Estimating the parameters of a regression model of interest is complicated by missing data on the variables in that model. Multiple imputation is commonly used to handle these missing data. Joint model multiple imputation and full-conditional specification multiple imputation are known to yield imputed data with the same asymptotic distribution when the conditional models of full-conditional specification are compatible with that joint model. We show that this asymptotic equivalence of imputation distributions does not imply that joint model multiple imputation and full-conditional specification multiple imputation will also yield asymptotically equally efficient inference about the parameters of the model of interest, nor that they will be equally robust to misspecification of the joint model. When the conditional models used by full-conditional specification multiple imputation are linear, logistic and multinomial regressions, these are compatible with a restricted general location joint model. We show that multiple imputation using the restricted general location joint model can be substantially more asymptotically efficient than full-conditional specification multiple imputation, but this typically requires very strong associations between variables. When associations are weaker, the efficiency gain is small. Moreover, full-conditional specification multiple imputation is shown to be potentially much more robust than joint model multiple imputation using the restricted general location model to mispecification of that model when there is substantial missingness in the outcome variable.

Method and system for knowledge discovery using non-linear statistical analysis and a 1st and 2nd tier computer program

DOEpatents

Hively, Lee M [Philadelphia, TN

2011-07-12

The invention relates to a method and apparatus for simultaneously processing different sources of test data into informational data and then processing different categories of informational data into knowledge-based data. The knowledge-based data can then be communicated between nodes in a system of multiple computers according to rules for a type of complex, hierarchical computer system modeled on a human brain.

Variables associated with health-related quality of life in a Brazilian sample of patients from a tertiary outpatient clinic for depression and anxiety disorders.

PubMed

Schwab, Bianca; Daniel, Heloisa Silveira; Lutkemeyer, Carine; Neves, João Arthur Lange Lins; Zilli, Louise Nassif; Guarnieri, Ricardo; Diaz, Alexandre Paim; Michels, Ana Maria Maykot Prates

2015-01-01

Health-related quality of life (HRQOL) assessment tools have been broadly used in the medical context. These tools are used to measure the subjective impact of the disease on patients. The objective of this study was to evaluate the variables associated with HRQOL in a Brazilian sample of patients followed up in a tertiary outpatient clinic for depression and anxiety disorders. Cross-sectional study. Independent variables were those included in a sociodemographic questionnaire and the Hospital Anxiety and Depression Scale (HADS) scores. Dependent variables were those included in the short version of the World Health Organization Quality of Life (WHOQOL-BREF) and the scores for its subdomains (overall quality of life and general health, physical health, psychological health, social relationships, and environment). A multiple linear regression analysis was used to find the variables independently associated with each outcome. Seventy-five adult patients were evaluated. After multiple linear regression analysis, the HADS scores were associated with all outcomes, except social relationships (p = 0.08). Female gender was associated with poor total scores, as well as psychological health and environment. Unemployment was associated with poor physical health. Identifying the factors associated with HRQOL and recognizing that depression and anxiety are major factors are essential to improve the care of patients.

Artificial Neural Networks: A Novel Approach to Analysing the Nutritional Ecology of a Blowfly Species, Chrysomya megacephala

PubMed Central

Bianconi, André; Zuben, Cláudio J. Von; Serapião, Adriane B. de S.; Govone, José S.

2010-01-01

Bionomic features of blowflies may be clarified and detailed by the deployment of appropriate modelling techniques such as artificial neural networks, which are mathematical tools widely applied to the resolution of complex biological problems. The principal aim of this work was to use three well-known neural networks, namely Multi-Layer Perceptron (MLP), Radial Basis Function (RBF), and Adaptive Neural Network-Based Fuzzy Inference System (ANFIS), to ascertain whether these tools would be able to outperform a classical statistical method (multiple linear regression) in the prediction of the number of resultant adults (survivors) of experimental populations of Chrysomya megacephala (F.) (Diptera: Calliphoridae), based on initial larval density (number of larvae), amount of available food, and duration of immature stages. The coefficient of determination (R2) derived from the RBF was the lowest in the testing subset in relation to the other neural networks, even though its R2 in the training subset exhibited virtually a maximum value. The ANFIS model permitted the achievement of the best testing performance. Hence this model was deemed to be more effective in relation to MLP and RBF for predicting the number of survivors. All three networks outperformed the multiple linear regression, indicating that neural models could be taken as feasible techniques for predicting bionomic variables concerning the nutritional dynamics of blowflies. PMID:20569135

Drug use, mental health and problems related to crime and violence: cross-sectional study1

PubMed Central

Claro, Heloísa Garcia; de Oliveira, Márcia Aparecida Ferreira; Bourdreaux, Janet Titus; Fernandes, Ivan Filipe de Almeida Lopes; Pinho, Paula Hayasi; Tarifa, Rosana Ribeiro

2015-01-01

Objective: to investigate the correlation between disorders related to the use of alcohol and other drugs and symptoms of mental disorders, problems related to crime and violence and to age and gender. Methods: cross-sectional descriptive study carried out with 128 users of a Psychosocial Care Center for Alcohol and other Drugs, in the city of São Paulo, interviewed by means of the instrument entitled Global Appraisal of Individual Needs - Short Screener. Univariate and multiple linear regression models were used to verify the correlation between the variables. Results: using univariate regression models, internalizing and externalizing symptoms and problems related to crime/violence proved significant and were included in the multiple model, in which only the internalizing symptoms and problems related to crime and violence remained significant. Conclusions: there is a correlation between the severity of problems related to alcohol use and severity of mental health symptoms and crime and violence in the study sample. The results emphasize the need for an interdisciplinary and intersectional character of attention to users of alcohol and other drugs, since they live in a socially vulnerable environment. PMID:26626010

Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control.

PubMed

Brunton, Steven L; Brunton, Bingni W; Proctor, Joshua L; Kutz, J Nathan

2016-01-01

In this wIn this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system. Dominant terms in the Koopman expansion are typically computed using dynamic mode decomposition (DMD). DMD uses linear measurements of the state variables, and it has recently been shown that this may be too restrictive for nonlinear systems. Choosing the right nonlinear observable functions to form an invariant subspace where it is possible to obtain linear reduced-order models, especially those that are useful for control, is an open challenge. Here, we investigate the choice of observable functions for Koopman analysis that enable the use of optimal linear control techniques on nonlinear problems. First, to include a cost on the state of the system, as in linear quadratic regulator (LQR) control, it is helpful to include these states in the observable subspace, as in DMD. However, we find that this is only possible when there is a single isolated fixed point, as systems with multiple fixed points or more complicated attractors are not globally topologically conjugate to a finite-dimensional linear system, and cannot be represented by a finite-dimensional linear Koopman subspace that includes the state. We then present a data-driven strategy to identify relevant observable functions for Koopman analysis by leveraging a new algorithm to determine relevant terms in a dynamical system by ℓ1-regularized regression of the data in a nonlinear function space; we also show how this algorithm is related to DMD. Finally, we demonstrate the usefulness of nonlinear observable subspaces in the design of Koopman operator optimal control laws for fully nonlinear systems using techniques from linear optimal control.ork, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system. Dominant terms in the Koopman expansion are typically computed using dynamic mode decomposition (DMD). DMD uses linear measurements of the state variables, and it has recently been shown that this may be too restrictive for nonlinear systems. Choosing the right nonlinear observable functions to form an invariant subspace where it is possible to obtain linear reduced-order models, especially those that are useful for control, is an open challenge. Here, we investigate the choice of observable functions for Koopman analysis that enable the use of optimal linear control techniques on nonlinear problems. First, to include a cost on the state of the system, as in linear quadratic regulator (LQR) control, it is helpful to include these states in the observable subspace, as in DMD. However, we find that this is only possible when there is a single isolated fixed point, as systems with multiple fixed points or more complicated attractors are not globally topologically conjugate to a finite-dimensional linear system, and cannot be represented by a finite-dimensional linear Koopman subspace that includes the state. We then present a data-driven strategy to identify relevant observable functions for Koopman analysis by leveraging a new algorithm to determine relevant terms in a dynamical system by ℓ1-regularized regression of the data in a nonlinear function space; we also show how this algorithm is related to DMD. Finally, we demonstrate the usefulness of nonlinear observable subspaces in the design of Koopman operator optimal control laws for fully nonlinear systems using techniques from linear optimal control.

Evaluation of Relationship between Trunk Muscle Endurance and Static Balance in Male Students

PubMed Central

Barati, Amirhossein; SafarCherati, Afsaneh; Aghayari, Azar; Azizi, Faeze; Abbasi, Hamed

2013-01-01

Purpose Fatigue of trunk muscle contributes to spinal instability over strenuous and prolonged physical tasks and therefore may lead to injury, however from a performance perspective, relation between endurance efficient core muscles and optimal balance control has not been well-known. The purpose of this study was to examine the relationship of trunk muscle endurance and static balance. Methods Fifty male students inhabitant of Tehran university dormitory (age 23.9±2.4, height 173.0±4.5 weight 70.7±6.3) took part in the study. Trunk muscle endurance was assessed using Sørensen test of trunk extensor endurance, trunk flexor endurance test, side bridge endurance test and static balance was measured using single-limb stance test. A multiple linear regression analysis was applied to test if the trunk muscle endurance measures significantly predicted the static balance. Results There were positive correlations between static balance level and trunk flexor, extensor and lateral endurance measures (Pearson correlation test, r=0.80 and P<0.001; r=0.71 and P<0.001; r=0.84 and P<0.001, respectively). According to multiple regression analysis for variables predicting static balance, the linear combination of trunk muscle endurance measures was significantly related to the static balance (F (3,46) = 66.60, P<0.001). Endurance of trunk flexor, extensor and lateral muscles were significantly associated with the static balance level. The regression model which included these factors had the sample multiple correlation coefficient of 0.902, indicating that approximately 81% of the variance of the static balance is explained by the model. Conclusion There is a significant relationship between trunk muscle endurance and static balance. PMID:24800004

Shared Dosimetry Error in Epidemiological Dose-Response Analyses

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

Stram, Daniel O.; Preston, Dale L.; Sokolnikov, Mikhail

2015-03-23

Radiation dose reconstruction systems for large-scale epidemiological studies are sophisticated both in providing estimates of dose and in representing dosimetry uncertainty. For example, a computer program was used by the Hanford Thyroid Disease Study to provide 100 realizations of possible dose to study participants. The variation in realizations reflected the range of possible dose for each cohort member consistent with the data on dose determinates in the cohort. Another example is the Mayak Worker Dosimetry System 2013 which estimates both external and internal exposures and provides multiple realizations of "possible" dose history to workers given dose determinants. This paper takesmore » up the problem of dealing with complex dosimetry systems that provide multiple realizations of dose in an epidemiologic analysis. In this paper we derive expected scores and the information matrix for a model used widely in radiation epidemiology, namely the linear excess relative risk (ERR) model that allows for a linear dose response (risk in relation to radiation) and distinguishes between modifiers of background rates and of the excess risk due to exposure. We show that treating the mean dose for each individual (calculated by averaging over the realizations) as if it was true dose (ignoring both shared and unshared dosimetry errors) gives asymptotically unbiased estimates (i.e. the score has expectation zero) and valid tests of the null hypothesis that the ERR slope β is zero. Although the score is unbiased the information matrix (and hence the standard errors of the estimate of β) is biased for β≠0 when ignoring errors in dose estimates, and we show how to adjust the information matrix to remove this bias, using the multiple realizations of dose. Use of these methods for several studies, including the Mayak Worker Cohort and the U.S. Atomic Veterans Study, is discussed.« less

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions.

PubMed

Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael

2015-11-26

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field.

An improved multiple flame photometric detector for gas chromatography.

PubMed

Clark, Adrian G; Thurbide, Kevin B

2015-11-20

An improved multiple flame photometric detector (mFPD) is introduced, based upon interconnecting fluidic channels within a planar stainless steel (SS) plate. Relative to the previous quartz tube mFPD prototype, the SS mFPD provides a 50% reduction in background emission levels, an orthogonal analytical flame, and easier more sensitive operation. As a result, sulfur response in the SS mFPD spans 4 orders of magnitude, yields a minimum detectable limit near 9×10(-12)gS/s, and has a selectivity approaching 10(4) over carbon. The device also exhibits exceptionally large resistance to hydrocarbon response quenching. Additionally, the SS mFPD uniquely allows analyte emission monitoring in the multiple worker flames for the first time. The findings suggest that this mode can potentially further improve upon the analytical flame response of sulfur (both linear HSO, and quadratic S2) and also phosphorus. Of note, the latter is nearly 20-fold stronger in S/N in the collective worker flames response and provides 6 orders of linearity with a detection limit of about 2.0×10(-13)gP/s. Overall, the results indicate that this new SS design notably improves the analytical performance of the mFPD and can provide a versatile and beneficial monitoring tool for gas chromatography. Copyright © 2015 Elsevier B.V. All rights reserved.

Linear mixed-effects models to describe individual tree crown width for China-fir in Fujian Province, southeast China.

PubMed

Hao, Xu; Yujun, Sun; Xinjie, Wang; Jin, Wang; Yao, Fu

2015-01-01

A multiple linear model was developed for individual tree crown width of Cunninghamia lanceolata (Lamb.) Hook in Fujian province, southeast China. Data were obtained from 55 sample plots of pure China-fir plantation stands. An Ordinary Linear Least Squares (OLS) regression was used to establish the crown width model. To adjust for correlations between observations from the same sample plots, we developed one level linear mixed-effects (LME) models based on the multiple linear model, which take into account the random effects of plots. The best random effects combinations for the LME models were determined by the Akaike's information criterion, the Bayesian information criterion and the -2logarithm likelihood. Heteroscedasticity was reduced by three residual variance functions: the power function, the exponential function and the constant plus power function. The spatial correlation was modeled by three correlation structures: the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)], and the compound symmetry structure (CS). Then, the LME model was compared to the multiple linear model using the absolute mean residual (AMR), the root mean square error (RMSE), and the adjusted coefficient of determination (adj-R2). For individual tree crown width models, the one level LME model showed the best performance. An independent dataset was used to test the performance of the models and to demonstrate the advantage of calibrating LME models.

Linearized inversion of multiple scattering seismic energy

NASA Astrophysics Data System (ADS)

Aldawood, Ali; Hoteit, Ibrahim; Zuberi, Mohammad

2014-05-01

Internal multiples deteriorate the quality of the migrated image obtained conventionally by imaging single scattering energy. So, imaging seismic data with the single-scattering assumption does not locate multiple bounces events in their actual subsurface positions. However, imaging internal multiples properly has the potential to enhance the migrated image because they illuminate zones in the subsurface that are poorly illuminated by single scattering energy such as nearly vertical faults. Standard migration of these multiples provides subsurface reflectivity distributions with low spatial resolution and migration artifacts due to the limited recording aperture, coarse sources and receivers sampling, and the band-limited nature of the source wavelet. The resultant image obtained by the adjoint operator is a smoothed depiction of the true subsurface reflectivity model and is heavily masked by migration artifacts and the source wavelet fingerprint that needs to be properly deconvolved. Hence, we proposed a linearized least-square inversion scheme to mitigate the effect of the migration artifacts, enhance the spatial resolution, and provide more accurate amplitude information when imaging internal multiples. The proposed algorithm uses the least-square image based on single-scattering assumption as a constraint to invert for the part of the image that is illuminated by internal scattering energy. Then, we posed the problem of imaging double-scattering energy as a least-square minimization problem that requires solving the normal equation of the following form: GTGv = GTd, (1) where G is a linearized forward modeling operator that predicts double-scattered seismic data. Also, GT is a linearized adjoint operator that image double-scattered seismic data. Gradient-based optimization algorithms solve this linear system. Hence, we used a quasi-Newton optimization technique to find the least-square minimizer. In this approach, an estimate of the Hessian matrix that contains curvature information is modified at every iteration by a low-rank update based on gradient changes at every step. At each iteration, the data residual is imaged using GT to determine the model update. Application of the linearized inversion to synthetic data to image a vertical fault plane demonstrate the effectiveness of this methodology to properly delineate the vertical fault plane and give better amplitude information than the standard migrated image using the adjoint operator that takes into account internal multiples. Thus, least-square imaging of multiple scattering enhances the spatial resolution of the events illuminated by internal scattering energy. It also deconvolves the source signature and helps remove the fingerprint of the acquisition geometry. The final image is obtained by the superposition of the least-square solution based on single scattering assumption and the least-square solution based on double scattering assumption.

Multi-channel spatialization systems for audio signals

NASA Technical Reports Server (NTRS)

Begault, Durand R. (Inventor)

1993-01-01

Synthetic head related transfer functions (HRTF's) for imposing reprogrammable spatial cues to a plurality of audio input signals included, for example, in multiple narrow-band audio communications signals received simultaneously are generated and stored in interchangeable programmable read only memories (PROM's) which store both head related transfer function impulse response data and source positional information for a plurality of desired virtual source locations. The analog inputs of the audio signals are filtered and converted to digital signals from which synthetic head related transfer functions are generated in the form of linear phase finite impulse response filters. The outputs of the impulse response filters are subsequently reconverted to analog signals, filtered, mixed, and fed to a pair of headphones.

Multi-channel spatialization system for audio signals

NASA Technical Reports Server (NTRS)

Begault, Durand R. (Inventor)

1995-01-01

Synthetic head related transfer functions (HRTF's) for imposing reprogramable spatial cues to a plurality of audio input signals included, for example, in multiple narrow-band audio communications signals received simultaneously are generated and stored in interchangeable programmable read only memories (PROM's) which store both head related transfer function impulse response data and source positional information for a plurality of desired virtual source locations. The analog inputs of the audio signals are filtered and converted to digital signals from which synthetic head related transfer functions are generated in the form of linear phase finite impulse response filters. The outputs of the impulse response filters are subsequently reconverted to analog signals, filtered, mixed and fed to a pair of headphones.

Time-dependent Fracture Behaviour of Polyampholyte Hydrogels

NASA Astrophysics Data System (ADS)

Sun, Tao Lin; Luo, Feng; Nakajima, Tasuku; Kurokawa, Takayuki; Gong, Jian Ping

Recently, we report that polyampholytes, polymers bearing randomly dispersed cationic and anionic repeat groups, form tough and self-healing hydrogels with excellent multiple mechanical functions. The randomness makes ionic bonds with a wide distribution of strength, via inter and intra chain complexation. As the breaking and reforming of ionic bonds are time dependent, the hydrogels exhibit rate dependent mechanical behaviour. We systematically studied the tearing energy by tearing test with various tearing velocity under different temperature, and the linear viscoelastic behaviour over a wide range of frequency and temperature. Results have shown that the tearing energy markedly increase with the crack velocity and decrease with the measured temperature. In accordance with the prediction of Williams, Landel, and Ferry (WLF) rate-temperature equivalence, a master curve of tearing energy dependence of crack velocity can be well constructed using the same shift factor from the linear viscoelastic data. The scaling relation of tearing energy as a function of crack velocity can be predicted well by the rheological data according to the developed linear fracture mechanics.

Nonlinear ionic transport through microstructured solid electrolytes: homogenization estimates

NASA Astrophysics Data System (ADS)

Curto Sillamoni, Ignacio J.; Idiart, Martín I.

2016-10-01

We consider the transport of multiple ionic species by diffusion and migration through microstructured solid electrolytes in the presence of strong electric fields. The assumed constitutive relations for the constituent phases follow from convex energy and dissipation potentials which guarantee thermodynamic consistency. The effective response is heuristically deduced from a multi-scale convergence analysis of the relevant field equations. The resulting homogenized response involves an effective dissipation potential per species. Each potential is mathematically akin to that of a standard nonlinear heterogeneous conductor. A ‘linear-comparison’ homogenization technique is then used to generate estimates for these nonlinear potentials in terms of available estimates for corresponding linear conductors. By way of example, use is made of the Maxwell-Garnett and effective-medium linear approximations to generate estimates for two-phase systems with power-law dissipation. Explicit formulas are given for some limiting cases. In the case of threshold-type behavior, the estimates exhibit non-analytical dilute limits and seem to be consistent with fields localized in low energy paths.

Electronically Tunable Differential Integrator: Linear Voltage Controlled Quadrature Oscillator.

PubMed

Nandi, Rabindranath; Pattanayak, Sandhya; Venkateswaran, Palaniandavar; Das, Sagarika

2015-01-01

A new electronically tunable differential integrator (ETDI) and its extension to voltage controlled quadrature oscillator (VCQO) design with linear tuning law are proposed; the active building block is a composite current feedback amplifier with recent multiplication mode current conveyor (MMCC) element. Recently utilization of two different kinds of active devices to form a composite building block is being considered since it yields a superior functional element suitable for improved quality circuit design. The integrator time constant (τ) and the oscillation frequency (ω o ) are tunable by the control voltage (V) of the MMCC block. Analysis indicates negligible phase error (θ e ) for the integrator and low active ω o -sensitivity relative to the device parasitic capacitances. Satisfactory experimental verifications on electronic tunability of some wave shaping applications by the integrator and a double-integrator feedback loop (DIFL) based sinusoid oscillator with linear f o variation range of 60 KHz~1.8 MHz at low THD of 2.1% are verified by both simulation and hardware tests.

Nonlinear Dynamic Models in Advanced Life Support

NASA Technical Reports Server (NTRS)

Jones, Harry

2002-01-01

To facilitate analysis, ALS systems are often assumed to be linear and time invariant, but they usually have important nonlinear and dynamic aspects. Nonlinear dynamic behavior can be caused by time varying inputs, changes in system parameters, nonlinear system functions, closed loop feedback delays, and limits on buffer storage or processing rates. Dynamic models are usually cataloged according to the number of state variables. The simplest dynamic models are linear, using only integration, multiplication, addition, and subtraction of the state variables. A general linear model with only two state variables can produce all the possible dynamic behavior of linear systems with many state variables, including stability, oscillation, or exponential growth and decay. Linear systems can be described using mathematical analysis. Nonlinear dynamics can be fully explored only by computer simulations of models. Unexpected behavior is produced by simple models having only two or three state variables with simple mathematical relations between them. Closed loop feedback delays are a major source of system instability. Exceeding limits on buffer storage or processing rates forces systems to change operating mode. Different equilibrium points may be reached from different initial conditions. Instead of one stable equilibrium point, the system may have several equilibrium points, oscillate at different frequencies, or even behave chaotically, depending on the system inputs and initial conditions. The frequency spectrum of an output oscillation may contain harmonics and the sums and differences of input frequencies, but it may also contain a stable limit cycle oscillation not related to input frequencies. We must investigate the nonlinear dynamic aspects of advanced life support systems to understand and counter undesirable behavior.

A class of stochastic optimization problems with one quadratic & several linear objective functions and extended portfolio selection model

NASA Astrophysics Data System (ADS)

Xu, Jiuping; Li, Jun

2002-09-01

In this paper a class of stochastic multiple-objective programming problems with one quadratic, several linear objective functions and linear constraints has been introduced. The former model is transformed into a deterministic multiple-objective nonlinear programming model by means of the introduction of random variables' expectation. The reference direction approach is used to deal with linear objectives and results in a linear parametric optimization formula with a single linear objective function. This objective function is combined with the quadratic function using the weighted sums. The quadratic problem is transformed into a linear (parametric) complementary problem, the basic formula for the proposed approach. The sufficient and necessary conditions for (properly, weakly) efficient solutions and some construction characteristics of (weakly) efficient solution sets are obtained. An interactive algorithm is proposed based on reference direction and weighted sums. Varying the parameter vector on the right-hand side of the model, the DM can freely search the efficient frontier with the model. An extended portfolio selection model is formed when liquidity is considered as another objective to be optimized besides expectation and risk. The interactive approach is illustrated with a practical example.

E-beam generated holographic masks for optical vector-matrix multiplication

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Case, S. K.

1981-01-01

An optical vector matrix multiplication scheme that encodes the matrix elements as a holographic mask consisting of linear diffraction gratings is proposed. The binary, chrome on glass masks are fabricated by e-beam lithography. This approach results in a fairly simple optical system that promises both large numerical range and high accuracy. A partitioned computer generated hologram mask was fabricated and tested. This hologram was diagonally separated outputs, compact facets and symmetry about the axis. The resultant diffraction pattern at the output plane is shown. Since the grating fringes are written at 45 deg relative to the facet boundaries, the many on-axis sidelobes from each output are seen to be diagonally separated from the adjacent output signals.

Assessment of unconstrained cerebrovascular reactivity marker for large age-range FMRI studies.

PubMed

Kannurpatti, Sridhar S; Motes, Michael A; Biswal, Bharat B; Rypma, Bart

2014-01-01

Breath hold (BH), a commonly used task to measure cerebrovascular reactivity (CVR) in fMRI studies varies in outcome among individuals due to subject-physiology and/or BH-inspiration/expiration differences (i.e., performance). In prior age-related fMRI studies, smaller task-related BOLD response variability is observed among younger than older individuals. Also, a linear CVR versus task relationship exists in younger individuals which maybe useful to test the accuracy of CVR responses in older groups. Hence we hypothesized that subject-related physiological and/or BH differences, if present, may compromise CVR versus task linearity in older individuals. To test the hypothesis, empirical BH versus task relationships from motor and cognitive areas were obtained in younger (mean age = 26 years) and older (mean age = 58 years) human subjects. BH versus task linearity was observed only in the younger group, confirming our hypothesis. Further analysis indicated BH responses and its variability to be similar in both younger and older groups, suggesting that BH may not accurately represent CVR in a large age range. Using the resting state fluctuation of amplitude (RSFA) as an unconstrained alternative to BH, subject-wise correspondence between BH and RSFA was tested. Correlation between BH versus RSFA was significant within the motor but was not significant in the cognitive areas in the younger and was completely disrupted in both areas in the older subjects indicating that BH responses are constrained by subject-related physiology and/or performance-related differences. Contrasting BH to task, RSFA-task relationships were independent of age accompanied by age-related increases in CVR variability as measured by RSFA, not observed with BH. Together the results obtained indicate that RSFA accurately represents CVR in any age range avoiding multiple and yet unknown physiologic and task-related pitfalls of BH.

Ultrasensitive surveillance of sensors and processes

DOEpatents

Wegerich, Stephan W.; Jarman, Kristin K.; Gross, Kenneth C.

2001-01-01

A method and apparatus for monitoring a source of data for determining an operating state of a working system. The method includes determining a sensor (or source of data) arrangement associated with monitoring the source of data for a system, activating a method for performing a sequential probability ratio test if the data source includes a single data (sensor) source, activating a second method for performing a regression sequential possibility ratio testing procedure if the arrangement includes a pair of sensors (data sources) with signals which are linearly or non-linearly related; activating a third method for performing a bounded angle ratio test procedure if the sensor arrangement includes multiple sensors and utilizing at least one of the first, second and third methods to accumulate sensor signals and determining the operating state of the system.

Ultrasensitive surveillance of sensors and processes

DOEpatents

Wegerich, Stephan W.; Jarman, Kristin K.; Gross, Kenneth C.

1999-01-01

A method and apparatus for monitoring a source of data for determining an operating state of a working system. The method includes determining a sensor (or source of data) arrangement associated with monitoring the source of data for a system, activating a method for performing a sequential probability ratio test if the data source includes a single data (sensor) source, activating a second method for performing a regression sequential possibility ratio testing procedure if the arrangement includes a pair of sensors (data sources) with signals which are linearly or non-linearly related; activating a third method for performing a bounded angle ratio test procedure if the sensor arrangement includes multiple sensors and utilizing at least one of the first, second and third methods to accumulate sensor signals and determining the operating state of the system.

Nonlinear aeroservoelastic analysis of a controlled multiple-actuated-wing model with free-play

NASA Astrophysics Data System (ADS)

Huang, Rui; Hu, Haiyan; Zhao, Yonghui

2013-10-01

In this paper, the effects of structural nonlinearity due to free-play in both leading-edge and trailing-edge outboard control surfaces on the linear flutter control system are analyzed for an aeroelastic model of three-dimensional multiple-actuated-wing. The free-play nonlinearities in the control surfaces are modeled theoretically by using the fictitious mass approach. The nonlinear aeroelastic equations of the presented model can be divided into nine sub-linear modal-based aeroelastic equations according to the different combinations of deflections of the leading-edge and trailing-edge outboard control surfaces. The nonlinear aeroelastic responses can be computed based on these sub-linear aeroelastic systems. To demonstrate the effects of nonlinearity on the linear flutter control system, a single-input and single-output controller and a multi-input and multi-output controller are designed based on the unconstrained optimization techniques. The numerical results indicate that the free-play nonlinearity can lead to either limit cycle oscillations or divergent motions when the linear control system is implemented.

Theory and investigation of acoustic multiple-input multiple-output systems based on spherical arrays in a room.

PubMed

Morgenstern, Hai; Rafaely, Boaz; Zotter, Franz

2015-11-01

Spatial attributes of room acoustics have been widely studied using microphone and loudspeaker arrays. However, systems that combine both arrays, referred to as multiple-input multiple-output (MIMO) systems, have only been studied to a limited degree in this context. These systems can potentially provide a powerful tool for room acoustics analysis due to the ability to simultaneously control both arrays. This paper offers a theoretical framework for the spatial analysis of enclosed sound fields using a MIMO system comprising spherical loudspeaker and microphone arrays. A system transfer function is formulated in matrix form for free-field conditions, and its properties are studied using tools from linear algebra. The system is shown to have unit-rank, regardless of the array types, and its singular vectors are related to the directions of arrival and radiation at the microphone and loudspeaker arrays, respectively. The formulation is then generalized to apply to rooms, using an image source method. In this case, the rank of the system is related to the number of significant reflections. The paper ends with simulation studies, which support the developed theory, and with an extensive reflection analysis of a room impulse response, using the platform of a MIMO system.

Assembly and Architecture of Biogenesis of Lysosome-related Organelles Complex-1 (BLOC-1)*

PubMed Central

Lee, Hyung Ho; Nemecek, Daniel; Schindler, Christina; Smith, William J.; Ghirlando, Rodolfo; Steven, Alasdair C.; Bonifacino, Juan S.; Hurley, James H.

2012-01-01

BLOC-1 (biogenesis of lysosome-related organelles complex-1) is critical for melanosome biogenesis and has also been implicated in neurological function and disease. We show that BLOC-1 is an elongated complex that contains one copy each of the eight subunits pallidin, Cappuccino, dysbindin, Snapin, Muted, BLOS1, BLOS2, and BLOS3. The complex appears as a linear chain of eight globular domains, ∼300 Å long and ∼30 Å in diameter. The individual domains are flexibly connected such that the linear chain undergoes bending by as much as 45°. Two stable subcomplexes were defined, pallidin-Cappuccino-BLOS1 and dysbindin-Snapin-BLOS2. Both subcomplexes are 1:1:1 heterotrimers that form extended structures as indicated by their hydrodynamic properties. The two subcomplexes appear to constitute flexible units within the larger BLOC-1 chain, an arrangement conducive to simultaneous interactions with multiple BLOC-1 partners in the course of tubular endosome biogenesis and sorting. PMID:22203680

Statistical Methods for Generalized Linear Models with Covariates Subject to Detection Limits.

PubMed

Bernhardt, Paul W; Wang, Huixia J; Zhang, Daowen

2015-05-01

Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we consider statistical methods for dealing with multiple predictors subject to detection limits within the context of generalized linear models. We investigate and adapt several conventional methods and develop a new multiple imputation approach for analyzing data sets with predictors censored due to detection limits. We establish the consistency and asymptotic normality of the proposed multiple imputation estimator and suggest a computationally simple and consistent variance estimator. We also demonstrate that the conditional mean imputation method often leads to inconsistent estimates in generalized linear models, while several other methods are either computationally intensive or lead to parameter estimates that are biased or more variable compared to the proposed multiple imputation estimator. In an extensive simulation study, we assess the bias and variability of different approaches within the context of a logistic regression model and compare variance estimation methods for the proposed multiple imputation estimator. Lastly, we apply several methods to analyze the data set from a recently-conducted GenIMS study.

Residents' engagement in everyday activities and its association with thriving in nursing homes.

PubMed

Björk, Sabine; Lindkvist, Marie; Wimo, Anders; Juthberg, Christina; Bergland, Ådel; Edvardsson, David

2017-08-01

To describe the prevalence of everyday activity engagement for older people in nursing homes and the extent to which engagement in everyday activities is associated with thriving. Research into residents' engagement in everyday activities in nursing homes has focused primarily on associations with quality of life and prevention and management of neuropsychiatric symptoms. However, the mere absence of symptoms does not necessarily guarantee experiences of well-being. The concept of thriving encapsulates and explores experiences of well-being in relation to the place where a person lives. A cross-sectional survey. A national survey of 172 Swedish nursing homes (2013-2014). Resident (n = 4831) symptoms, activities and thriving were assessed by staff using a study survey based on established questionnaires. Descriptive statistics, simple and multiple linear regression, and linear stepwise multiple regression were performed. The most commonly occurring everyday activities were receiving hugs and physical touch, talking to relatives/friends and receiving visitors, having conversation with staff not related to care and grooming. The least commonly occurring everyday activities were going to the cinema, participating in an educational program, visiting a restaurant and doing everyday chores. Positive associations were found between activity engagement and thriving, where engagement in an activity program, dressing nicely and spending time with someone the resident likes had the strongest positive association with resident thriving. Engagement in everyday activities can support personhood and thriving and can be conceptualized and implemented as nursing interventions to enable residents to thrive in nursing homes. © 2017 John Wiley & Sons Ltd.

Coexistence and local μ-stability of multiple equilibrium points for memristive neural networks with nonmonotonic piecewise linear activation functions and unbounded time-varying delays.

PubMed

Nie, Xiaobing; Zheng, Wei Xing; Cao, Jinde

2016-12-01

In this paper, the coexistence and dynamical behaviors of multiple equilibrium points are discussed for a class of memristive neural networks (MNNs) with unbounded time-varying delays and nonmonotonic piecewise linear activation functions. By means of the fixed point theorem, nonsmooth analysis theory and rigorous mathematical analysis, it is proven that under some conditions, such n-neuron MNNs can have 5 n equilibrium points located in ℜ n , and 3 n of them are locally μ-stable. As a direct application, some criteria are also obtained on the multiple exponential stability, multiple power stability, multiple log-stability and multiple log-log-stability. All these results reveal that the addressed neural networks with activation functions introduced in this paper can generate greater storage capacity than the ones with Mexican-hat-type activation function. Numerical simulations are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Digital processing of array seismic recordings

USGS Publications Warehouse

Ryall, Alan; Birtill, John

1962-01-01

This technical letter contains a brief review of the operations which are involved in digital processing of array seismic recordings by the methods of velocity filtering, summation, cross-multiplication and integration, and by combinations of these operations (the "UK Method" and multiple correlation). Examples are presented of analyses by the several techniques on array recordings which were obtained by the U.S. Geological Survey during chemical and nuclear explosions in the western United States. Seismograms are synthesized using actual noise and Pn-signal recordings, such that the signal-to-noise ratio, onset time and velocity of the signal are predetermined for the synthetic record. These records are then analyzed by summation, cross-multiplication, multiple correlation and the UK technique, and the results are compared. For all of the examples presented, analysis by the non-linear techniques of multiple correlation and cross-multiplication of the traces on an array recording are preferred to analyses by the linear operations involved in summation and the UK Method.

The isoform A of reticulon-4 (Nogo-A) in cerebrospinal fluid of primary brain tumor patients: influencing factors.

PubMed

Koper, Olga Martyna; Kamińska, Joanna; Milewska, Anna; Sawicki, Karol; Mariak, Zenon; Kemona, Halina; Matowicka-Karna, Joanna

2018-05-18

The influence of isoform A of reticulon-4 (Nogo-A), also known as neurite outgrowth inhibitor, on primary brain tumor development was reported. Therefore the aim was the evaluation of Nogo-A concentrations in cerebrospinal fluid (CSF) and serum of brain tumor patients compared with non-tumoral individuals. All serum results, except for two cases, obtained both in brain tumors and non-tumoral individuals, were below the lower limit of ELISA detection. Cerebrospinal fluid Nogo-A concentrations were significantly lower in primary brain tumor patients compared to non-tumoral individuals. The univariate linear regression analysis found that if white blood cell count increases by 1 × 10 3 /μL, the mean cerebrospinal fluid Nogo-A concentration value decreases 1.12 times. In the model of multiple linear regression analysis predictor variables influencing cerebrospinal fluid Nogo-A concentrations included: diagnosis, sex, and sodium level. The mean cerebrospinal fluid Nogo-A concentration value was 1.9 times higher for women in comparison to men. In the astrocytic brain tumor group higher sodium level occurs with lower cerebrospinal fluid Nogo-A concentrations. We found the opposite situation in non-tumoral individuals. Univariate linear regression analysis revealed, that cerebrospinal fluid Nogo-A concentrations change in relation to white blood cell count. In the created model of multiple linear regression analysis we found, that within predictor variables influencing CSF Nogo-A concentrations were diagnosis, sex, and sodium level. Results may be relevant to the search for cerebrospinal fluid biomarkers and potential therapeutic targets in primary brain tumor patients. Nogo-A concentrations were tested by means of enzyme-linked immunosorbent assay (ELISA).

Commentary on the statistical properties of noise and its implication on general linear models in functional near-infrared spectroscopy.

PubMed

Huppert, Theodore J

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of light to measure changes in cerebral blood oxygenation levels. In the majority of NIRS functional brain studies, analysis of this data is based on a statistical comparison of hemodynamic levels between a baseline and task or between multiple task conditions by means of a linear regression model: the so-called general linear model. Although these methods are similar to their implementation in other fields, particularly for functional magnetic resonance imaging, the specific application of these methods in fNIRS research differs in several key ways related to the sources of noise and artifacts unique to fNIRS. In this brief communication, we discuss the application of linear regression models in fNIRS and the modifications needed to generalize these models in order to deal with structured (colored) noise due to systemic physiology and noise heteroscedasticity due to motion artifacts. The objective of this work is to present an overview of these noise properties in the context of the linear model as it applies to fNIRS data. This work is aimed at explaining these mathematical issues to the general fNIRS experimental researcher but is not intended to be a complete mathematical treatment of these concepts.

BIODEGRADATION PROBABILITY PROGRAM (BIODEG)

EPA Science Inventory

The Biodegradation Probability Program (BIODEG) calculates the probability that a chemical under aerobic conditions with mixed cultures of microorganisms will biodegrade rapidly or slowly. It uses fragment constants developed using multiple linear and non-linear regressions and d...

The Use of Linear Programming for Prediction.

ERIC Educational Resources Information Center

Schnittjer, Carl J.

The purpose of the study was to develop a linear programming model to be used for prediction, test the accuracy of the predictions, and compare the accuracy with that produced by curvilinear multiple regression analysis. (Author)

The Climate Response to Stratospheric Aerosol Geoengineering Can Be Tailored Using Multiple Injection Locations

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

MacMartin, Douglas G.; Kravitz, Ben; Tilmes, Simone

The climate response to geoengineering with stratospheric aerosols has the potential to be designed to achieve some chosen objectives. By injecting different amounts of SO2 at multiple different latitudes, the spatial pattern of aerosol optical depth (AOD) can be partially controlled. We use simulations from the fully-coupled whole-atmosphere chemistry-climate model CESM1(WACCM), to demonstrate that three spatial degrees of freedom of AOD can be achieved by appropriately combining injection at different locations: an approximately spatially-uniform AOD distribution, the relative difference in AOD between Northern and Southern hemispheres, and the relative AOD in high versus low latitudes. For forcing levels that yieldmore » 1–2°C cooling, the AOD and surface temperature response are sufficiently linear in this model so that many climate effects can be predicted from single-latitude injection simulations. Optimized injection at multiple locations is predicted to improve compensation of CO2-forced climate change, relative to a case using only equatorial aerosol injection. The additional degrees of freedom can be used, for example, to balance interhemispheric temperature differences and the equator to pole temperature difference in addition to the global mean temperature; this is projected in this model to reduce the mean-square error in temperature compensation by 30%.« less

A method for computing ion energy distributions for multifrequency capacitive discharges

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

Wu, Alan C. F.; Lieberman, M. A.; Verboncoeur, J. P.

2007-03-01

The ion energy distribution (IED) at a surface is an important parameter for processing in multiple radio frequency driven capacitive discharges. An analytical model is developed for the IED in a low pressure discharge based on a linear transfer function that relates the time-varying sheath voltage to the time-varying ion energy response at the surface. This model is in good agreement with particle-in-cell simulations over a wide range of single, dual, and triple frequency driven capacitive discharge excitations.

A Comparison of Variable Selection Criteria for Multiple Linear Regression: A Second Simulation Study

DTIC Science & Technology

1993-03-01

statistical mathe- matics, began in the late 1800’s when Sir Francis Galton first attempted to use practical mathematical techniques to investigate the...randomly collected (sampled) many pairs of parent/child height mea- surements (data), Galton observed that for a given parent- height average, the...ty only Maximum Adjusted R2 will be discussed. However, Maximum Adjusted R’ and Minimum MSE test exactly the same 2.thing. Adjusted R is related to R

Comparing methods of analysing datasets with small clusters: case studies using four paediatric datasets.

PubMed

Marston, Louise; Peacock, Janet L; Yu, Keming; Brocklehurst, Peter; Calvert, Sandra A; Greenough, Anne; Marlow, Neil

2009-07-01

Studies of prematurely born infants contain a relatively large percentage of multiple births, so the resulting data have a hierarchical structure with small clusters of size 1, 2 or 3. Ignoring the clustering may lead to incorrect inferences. The aim of this study was to compare statistical methods which can be used to analyse such data: generalised estimating equations, multilevel models, multiple linear regression and logistic regression. Four datasets which differed in total size and in percentage of multiple births (n = 254, multiple 18%; n = 176, multiple 9%; n = 10 098, multiple 3%; n = 1585, multiple 8%) were analysed. With the continuous outcome, two-level models produced similar results in the larger dataset, while generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) produced divergent estimates using the smaller dataset. For the dichotomous outcome, most methods, except generalised least squares multilevel modelling (ML GH 'xtlogit' in Stata) gave similar odds ratios and 95% confidence intervals within datasets. For the continuous outcome, our results suggest using multilevel modelling. We conclude that generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) should be used with caution when the dataset is small. Where the outcome is dichotomous and there is a relatively large percentage of non-independent data, it is recommended that these are accounted for in analyses using logistic regression with adjusted standard errors or multilevel modelling. If, however, the dataset has a small percentage of clusters greater than size 1 (e.g. a population dataset of children where there are few multiples) there appears to be less need to adjust for clustering.

The Multiple Correspondence Analysis Method and Brain Functional Connectivity: Its Application to the Study of the Non-linear Relationships of Motor Cortex and Basal Ganglia.

PubMed

Rodriguez-Sabate, Clara; Morales, Ingrid; Sanchez, Alberto; Rodriguez, Manuel

2017-01-01

The complexity of basal ganglia (BG) interactions is often condensed into simple models mainly based on animal data and that present BG in closed-loop cortico-subcortical circuits of excitatory/inhibitory pathways which analyze the incoming cortical data and return the processed information to the cortex. This study was aimed at identifying functional relationships in the BG motor-loop of 24 healthy-subjects who provided written, informed consent and whose BOLD-activity was recorded by MRI methods. The analysis of the functional interaction between these centers by correlation techniques and multiple linear regression showed non-linear relationships which cannot be suitably addressed with these methods. The multiple correspondence analysis (MCA), an unsupervised multivariable procedure which can identify non-linear interactions, was used to study the functional connectivity of BG when subjects were at rest. Linear methods showed different functional interactions expected according to current BG models. MCA showed additional functional interactions which were not evident when using lineal methods. Seven functional configurations of BG were identified with MCA, two involving the primary motor and somatosensory cortex, one involving the deepest BG (external-internal globus pallidum, subthalamic nucleus and substantia nigral), one with the input-output BG centers (putamen and motor thalamus), two linking the input-output centers with other BG (external pallidum and subthalamic nucleus), and one linking the external pallidum and the substantia nigral. The results provide evidence that the non-linear MCA and linear methods are complementary and should be best used in conjunction to more fully understand the nature of functional connectivity of brain centers.

Impact of Learning Styles on Air Force Technical Training: Multiple and Linear Imagery in the Presentation of a Comparative Visual Location Task to Visual and Haptic Subjects. Interim Report for Period January 1977-January 1978.

ERIC Educational Resources Information Center

Ausburn, Floyd B.

A U.S. Air Force study was designed to develop instruction based on the supplantation theory, in which tasks are performed (supplanted) for individuals who are unable to perform them due to their cognitive style. The study examined the effects of linear and multiple imagery in presenting a task requiring visual comparison and location to…

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

PubMed

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

Analysis and prediction of flow from local source in a river basin using a Neuro-fuzzy modeling tool.

PubMed

Aqil, Muhammad; Kita, Ichiro; Yano, Akira; Nishiyama, Soichi

2007-10-01

Traditionally, the multiple linear regression technique has been one of the most widely used models in simulating hydrological time series. However, when the nonlinear phenomenon is significant, the multiple linear will fail to develop an appropriate predictive model. Recently, neuro-fuzzy systems have gained much popularity for calibrating the nonlinear relationships. This study evaluated the potential of a neuro-fuzzy system as an alternative to the traditional statistical regression technique for the purpose of predicting flow from a local source in a river basin. The effectiveness of the proposed identification technique was demonstrated through a simulation study of the river flow time series of the Citarum River in Indonesia. Furthermore, in order to provide the uncertainty associated with the estimation of river flow, a Monte Carlo simulation was performed. As a comparison, a multiple linear regression analysis that was being used by the Citarum River Authority was also examined using various statistical indices. The simulation results using 95% confidence intervals indicated that the neuro-fuzzy model consistently underestimated the magnitude of high flow while the low and medium flow magnitudes were estimated closer to the observed data. The comparison of the prediction accuracy of the neuro-fuzzy and linear regression methods indicated that the neuro-fuzzy approach was more accurate in predicting river flow dynamics. The neuro-fuzzy model was able to improve the root mean square error (RMSE) and mean absolute percentage error (MAPE) values of the multiple linear regression forecasts by about 13.52% and 10.73%, respectively. Considering its simplicity and efficiency, the neuro-fuzzy model is recommended as an alternative tool for modeling of flow dynamics in the study area.

Alcohol Availability and Intimate Partner Violence Among US Couples

PubMed Central

McKinney, Christy M.; Caetano, Raul; Harris, Theodore Robert; Ebama, Malembe S.

2008-01-01

Objectives We examined the relation between alcohol outlet density (the number of alcohol outlets per capita by zip code) and male-to-female partner violence (MFPV) or female-to-male partner violence (FMPV). We also investigated whether binge drinking or the presence of alcohol-related problems altered the relationship between alcohol outlet density and MFPV or FMPV. Methods We linked individual and couple sociodemographic and behavioral data from a 1995 national population-based sample of 1,597 couples to alcohol outlet data and 1990 US Census sociodemographic information. We used logistic regression for survey data to estimate unadjusted and adjusted odds ratios between alcohol outlet density and MFPV or FMPV along with 95% confidence intervals (CIs) and p-values. We used a design-based Wald test to derive a p-value for multiplicative interaction to assess the role of binge drinking and alcohol-related problems. Results In adjusted analysis, an increase of one alcohol outlet per 10,000 persons was associated with a 1.03-fold increased risk of MFPV (p-value for linear trend = 0.01) and a 1.011-fold increased risk of FMPV (p-value for linear trend = 0.48). An increase of 10 alcohol outlets per 10,000 persons was associated with 34% and 12% increased risk of MFPV and FMPV respectively, though the CI for the association with FMPV was compatible with no increased risk. The relationship between alcohol outlet density and MFPV was stronger among couples reporting alcohol-related problems than those reporting no problems (p-value for multiplicative interaction = 0.01). Conclusions We found that as alcohol outlet density increases so does the risk of MFPV and that this relationship may differ for couples who do and do not report alcohol-related problems. Given that MFPV accounts for the majority of injuries related to intimate partner violence, policy makers may wish to carefully consider the potential benefit of limiting alcohol outlet density to reduce MFPV and its adverse consequences. PMID:18976345

Alcohol availability and intimate partner violence among US couples.

PubMed

McKinney, Christy M; Caetano, Raul; Harris, Theodore Robert; Ebama, Malembe S

2009-01-01

We examined the relation between alcohol outlet density (the number of alcohol outlets per capita by zip code) and male-to-female partner violence (MFPV) or female-to-male partner violence (FMPV). We also investigated whether binge drinking or the presence of alcohol-related problems altered the relationship between alcohol outlet density and MFPV or FMPV. We linked individual and couple sociodemographic and behavioral data from a 1995 national population-based sample of 1,597 couples to alcohol outlet data and 1990 US Census sociodemographic information. We used logistic regression for survey data to estimate unadjusted and adjusted odds ratios between alcohol outlet density and MFPV or FMPV along with 95% confidence intervals (CIs) and p-values. We used a design-based Wald test to derive a p-value for multiplicative interaction to assess the role of binge drinking and alcohol-related problems. In adjusted analysis, an increase of one alcohol outlet per 10,000 persons was associated with a 1.03-fold increased risk of MFPV (p-value for linear trend = 0.01) and a 1.011-fold increased risk of FMPV (p-value for linear trend = 0.48). An increase of 10 alcohol outlets per 10,000 persons was associated with 34% and 12% increased risk of MFPV and FMPV respectively, though the CI for the association with FMPV was compatible with no increased risk. The relationship between alcohol outlet density and MFPV was stronger among couples reporting alcohol-related problems than those reporting no problems (p-value for multiplicative interaction = 0.01). We found that as alcohol outlet density increases so does the risk of MFPV and that this relationship may differ for couples who do and do not report alcohol-related problems. Given that MFPV accounts for the majority of injuries related to intimate partner violence, policy makers may wish to carefully consider the potential benefit of limiting alcohol outlet density to reduce MFPV and its adverse consequences.

Response Strength in Extreme Multiple Schedules

PubMed Central

McLean, Anthony P; Grace, Randolph C; Nevin, John A

2012-01-01

Four pigeons were trained in a series of two-component multiple schedules. Reinforcers were scheduled with random-interval schedules. The ratio of arranged reinforcer rates in the two components was varied over 4 log units, a much wider range than previously studied. When performance appeared stable, prefeeding tests were conducted to assess resistance to change. Contrary to the generalized matching law, logarithms of response ratios in the two components were not a linear function of log reinforcer ratios, implying a failure of parameter invariance. Over a 2 log unit range, the function appeared linear and indicated undermatching, but in conditions with more extreme reinforcer ratios, approximate matching was observed. A model suggested by McLean (1991), originally for local contrast, predicts these changes in sensitivity to reinforcer ratios somewhat better than models by Herrnstein (1970) and by Williams and Wixted (1986). Prefeeding tests of resistance to change were conducted at each reinforcer ratio, and relative resistance to change was also a nonlinear function of log reinforcer ratios, again contrary to conclusions from previous work. Instead, the function suggests that resistance to change in a component may be determined partly by the rate of reinforcement and partly by the ratio of reinforcers to responses. PMID:22287804

Multiple Use One-Sided Hypotheses Testing in Univariate Linear Calibration

NASA Technical Reports Server (NTRS)

Krishnamoorthy, K.; Kulkarni, Pandurang M.; Mathew, Thomas

1996-01-01

Consider a normally distributed response variable, related to an explanatory variable through the simple linear regression model. Data obtained on the response variable, corresponding to known values of the explanatory variable (i.e., calibration data), are to be used for testing hypotheses concerning unknown values of the explanatory variable. We consider the problem of testing an unlimited sequence of one sided hypotheses concerning the explanatory variable, using the corresponding sequence of values of the response variable and the same set of calibration data. This is the situation of multiple use of the calibration data. The tests derived in this context are characterized by two types of uncertainties: one uncertainty associated with the sequence of values of the response variable, and a second uncertainty associated with the calibration data. We derive tests based on a condition that incorporates both of these uncertainties. The solution has practical applications in the decision limit problem. We illustrate our results using an example dealing with the estimation of blood alcohol concentration based on breath estimates of the alcohol concentration. In the example, the problem is to test if the unknown blood alcohol concentration of an individual exceeds a threshold that is safe for driving.

Clustered Multi-Task Learning for Automatic Radar Target Recognition

PubMed Central

Li, Cong; Bao, Weimin; Xu, Luping; Zhang, Hua

2017-01-01

Model training is a key technique for radar target recognition. Traditional model training algorithms in the framework of single task leaning ignore the relationships among multiple tasks, which degrades the recognition performance. In this paper, we propose a clustered multi-task learning, which can reveal and share the multi-task relationships for radar target recognition. To further make full use of these relationships, the latent multi-task relationships in the projection space are taken into consideration. Specifically, a constraint term in the projection space is proposed, the main idea of which is that multiple tasks within a close cluster should be close to each other in the projection space. In the proposed method, the cluster structures and multi-task relationships can be autonomously learned and utilized in both of the original and projected space. In view of the nonlinear characteristics of radar targets, the proposed method is extended to a non-linear kernel version and the corresponding non-linear multi-task solving method is proposed. Comprehensive experimental studies on simulated high-resolution range profile dataset and MSTAR SAR public database verify the superiority of the proposed method to some related algorithms. PMID:28953267

Systematic Analysis of Absorbed Anti-Inflammatory Constituents and Metabolites of Sarcandra glabra in Rat Plasma Using Ultra-High-Pressure Liquid Chromatography Coupled with Linear Trap Quadrupole Orbitrap Mass Spectrometry

PubMed Central

Li, Xiong; Zhao, Jin; Liu, Jianxing; Li, Geng; Zhao, Ya; Zeng, Xing

2016-01-01

Ultra-high-pressure liquid chromatography (UHPLC) was coupled with linear ion trap quadrupole Orbitrap mass spectrometry (LTQ-Orbitrap) and was used for the first time to systematically analyze the absorbed components and metabolites in rat plasma after oral administration of the water extract of Sarcandra glabra. This extract is a well-known Chinese herbal medicine for the treatment of inflammation and immunity related diseases. The anti-inflammatory activities of the absorbed components were evaluated by measuring nitric oxide (NO) production and proinflammatory genes expression in lipopolysaccharide (LPS)-stimulated murine RAW 264.7 macrophages. As a result, 54 components in Sarcandra glabra were detected in dosed rat plasma, and 36 of them were positively identified. Moreover, 23 metabolites were characterized and their originations were traced. Furthermore, 20 of the 24 studied components showed anti-inflammatory activities. These results provide evidence that this method efficiency detected constituents in plasma based on the anti-inflammatory mechanism of multiple components and would be a useful technique for screening multiple targets for natural medicine research. PMID:26974321

Surface property modification of silicon

NASA Technical Reports Server (NTRS)

Danyluk, S.

1984-01-01

The main emphasis of this work has been to determine the wear rate of silicon in fluid environments and the parameters that influence wear. Three tests were carried out on single crystal Czochralski silicon wafers: circular and linear multiple-scratch tests in fluids by a pyramidal diamond simulated fixed-particle abrasion; microhardness and three-point bend tests were used to determine the hardness and fracture toughness of abraded silicon and the extent of damage induced by abrasion. The wear rate of (100) and (111) n and p-type single crystal Cz silicon abraded by a pyramidal diamond in ethanol, methanol, acetone and de-ionized water was determined by measuring the cross-sectional areas of grooves of the circular and linear multiple-scratch tests. The wear rate depends on the loads on the diamond and is highest for ethanol and lowest for de-ionized water. The surface morphology of the grooves showed lateral and median cracks as well as a plastically deformed region. The hardness and fracture toughness are critical parameters that influence the wear rate. Microhardness tests were conducted to determine the hardness as influenced by fluids. Median cracks and the damage zone surrounding the indentations were also related to the fluid properties.

Optimized multiple linear mappings for single image super-resolution

NASA Astrophysics Data System (ADS)

Zhang, Kaibing; Li, Jie; Xiong, Zenggang; Liu, Xiuping; Gao, Xinbo

2017-12-01

Learning piecewise linear regression has been recognized as an effective way for example learning-based single image super-resolution (SR) in literature. In this paper, we employ an expectation-maximization (EM) algorithm to further improve the SR performance of our previous multiple linear mappings (MLM) based SR method. In the training stage, the proposed method starts with a set of linear regressors obtained by the MLM-based method, and then jointly optimizes the clustering results and the low- and high-resolution subdictionary pairs for regression functions by using the metric of the reconstruction errors. In the test stage, we select the optimal regressor for SR reconstruction by accumulating the reconstruction errors of m-nearest neighbors in the training set. Thorough experimental results carried on six publicly available datasets demonstrate that the proposed SR method can yield high-quality images with finer details and sharper edges in terms of both quantitative and perceptual image quality assessments.

Robust lane detection and tracking using multiple visual cues under stochastic lane shape conditions

NASA Astrophysics Data System (ADS)

Huang, Zhi; Fan, Baozheng; Song, Xiaolin

2018-03-01

As one of the essential components of environment perception techniques for an intelligent vehicle, lane detection is confronted with challenges including robustness against the complicated disturbance and illumination, also adaptability to stochastic lane shapes. To overcome these issues, we proposed a robust lane detection method named classification-generation-growth-based (CGG) operator to the detected lines, whereby the linear lane markings are identified by synergizing multiple visual cues with the a priori knowledge and spatial-temporal information. According to the quality of linear lane fitting, the linear and linear-parabolic models are dynamically switched to describe the actual lane. The Kalman filter with adaptive noise covariance and the region of interests (ROI) tracking are applied to improve the robustness and efficiency. Experiments were conducted with images covering various challenging scenarios. The experimental results evaluate the effectiveness of the presented method for complicated disturbances, illumination, and stochastic lane shapes.

Quantum Chemically Estimated Abraham Solute Parameters Using Multiple Solvent-Water Partition Coefficients and Molecular Polarizability.

PubMed

Liang, Yuzhen; Xiong, Ruichang; Sandler, Stanley I; Di Toro, Dominic M

2017-09-05

Polyparameter Linear Free Energy Relationships (pp-LFERs), also called Linear Solvation Energy Relationships (LSERs), are used to predict many environmentally significant properties of chemicals. A method is presented for computing the necessary chemical parameters, the Abraham parameters (AP), used by many pp-LFERs. It employs quantum chemical calculations and uses only the chemical's molecular structure. The method computes the Abraham E parameter using density functional theory computed molecular polarizability and the Clausius-Mossotti equation relating the index refraction to the molecular polarizability, estimates the Abraham V as the COSMO calculated molecular volume, and computes the remaining AP S, A, and B jointly with a multiple linear regression using sixty-five solvent-water partition coefficients computed using the quantum mechanical COSMO-SAC solvation model. These solute parameters, referred to as Quantum Chemically estimated Abraham Parameters (QCAP), are further adjusted by fitting to experimentally based APs using QCAP parameters as the independent variables so that they are compatible with existing Abraham pp-LFERs. QCAP and adjusted QCAP for 1827 neutral chemicals are included. For 24 solvent-water systems including octanol-water, predicted log solvent-water partition coefficients using adjusted QCAP have the smallest root-mean-square errors (RMSEs, 0.314-0.602) compared to predictions made using APs estimated using the molecular fragment based method ABSOLV (0.45-0.716). For munition and munition-like compounds, adjusted QCAP has much lower RMSE (0.860) than does ABSOLV (4.45) which essentially fails for these compounds.

Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

PubMed

Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao

2015-08-01

Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.

MRM assay for quantitation of complement components in human blood plasma - a feasibility study on multiple sclerosis.

PubMed

Rezeli, Melinda; Végvári, Akos; Ottervald, Jan; Olsson, Tomas; Laurell, Thomas; Marko-Varga, György

2011-12-10

As a proof-of-principle study, a multiple reaction monitoring (MRM) assay was developed for quantitation of proteotypic peptides, representing seven plasma proteins associated with inflammation (complement components and C-reactive protein). The assay development and the sample analysis were performed on a linear ion trap mass spectrometer. We were able to quantify 5 of the 7 target proteins in depleted plasma digests with reasonable reproducibility over a 2 orders of magnitude linear range (RSD≤25%). The assay panel was utilized for the analysis of a small multiple sclerosis sample cohort with 10 diseased and 8 control patients. Copyright © 2011 Elsevier B.V. All rights reserved.

A case of unilateral, systematized linear hair follicle nevi associated with epidermal nevus-like lesions.

PubMed

Ikeda, Shigaku; Kawada, Juri; Yaguchi, Hitoshi; Ogawa, Hideoki

2003-01-01

Multiple hair follicle nevi are an extremely rare condition. In 1998, a case of unilateral multiple hair follicle nevi, ipsilateral alopecia and ipsilateral leptomeningeal angiomatosis of the brain was first reported from Japan. Very recently, hair follicle nevus in a distribution following Blaschko's lines has also been reported. In this paper, we observed a congenital case of unilateral, systematized linear hair follicle nevi associated with congenital, ipsilateral, multiple plaque lesions resembling epidermal nevi but lacking leptomeningeal angiomatosis of the brain. These cases implicate the possibility of a novel neurocutaneous syndrome. Additional cases should be sought in order to determine whether this condition is pathophysiologically distinct. Copyright 2003 S. Karger AG, Basel

Iterative-method performance evaluation for multiple vectors associated with a large-scale sparse matrix

NASA Astrophysics Data System (ADS)

Imamura, Seigo; Ono, Kenji; Yokokawa, Mitsuo

2016-07-01

Ensemble computing, which is an instance of capacity computing, is an effective computing scenario for exascale parallel supercomputers. In ensemble computing, there are multiple linear systems associated with a common coefficient matrix. We improve the performance of iterative solvers for multiple vectors by solving them at the same time, that is, by solving for the product of the matrices. We implemented several iterative methods and compared their performance. The maximum performance on Sparc VIIIfx was 7.6 times higher than that of a naïve implementation. Finally, to deal with the different convergence processes of linear systems, we introduced a control method to eliminate the calculation of already converged vectors.

Issues in vibration energy harvesting

NASA Astrophysics Data System (ADS)

Zhang, Hui; Corr, Lawrence R.; Ma, Tianwei

2018-05-01

In this study, fundamental issues related to bandwidth and nonlinear resonance in vibrational energy harvesting devices are investigated. The results show that using bandwidth as a criterion to measure device performance can be misleading. For a linear device, an enlarged bandwidth is achieved at the cost of sacrificing device performance near resonance, and thus widening the bandwidth may offer benefits only when the natural frequency of the linear device cannot match the dominant excitation frequency. For a nonlinear device, since the principle of superposition does not apply, the ''broadband" performance improvements achieved for single-frequency excitations may not be achievable for multi-frequency excitations. It is also shown that a large-amplitude response based on the traditional ''nonlinear resonance" does not always result in the optimal performance for a nonlinear device because of the negative work done by the excitation, which indicates energy is returned back to the excitation. Such undesired negative work is eliminated at global resonance, a generalized resonant condition for both linear and nonlinear systems. While the linear resonance is a special case of global resonance for a single-frequency excitation, the maximum potential of nonlinear energy harvesting can be reached for multi-frequency excitations by using global resonance to simultaneously harvest energy distributed over multiple frequencies.

A survey of the state of the art and focused research in range systems, task 2

NASA Technical Reports Server (NTRS)

Yao, K.

1986-01-01

Many communication, control, and information processing subsystems are modeled by linear systems incorporating tapped delay lines (TDL). Such optimized subsystems result in full precision multiplications in the TDL. In order to reduce complexity and cost in a microprocessor implementation, these multiplications can be replaced by single-shift instructions which are equivalent to powers of two multiplications. Since, in general, the obvious operation of rounding the infinite precision TDL coefficients to the nearest powers of two usually yield quite poor system performance, the optimum powers of two coefficient solution was considered. Detailed explanations on the use of branch-and-bound algorithms for finding the optimum powers of two solutions are given. Specific demonstration of this methodology to the design of a linear data equalizer and its implementation in assembly language on a 8080 microprocessor with a 12 bit A/D converter are reported. This simple microprocessor implementation with optimized TDL coefficients achieves a system performance comparable to the optimum linear equalization with full precision multiplications for an input data rate of 300 baud. The philosophy demonstrated in this implementation is dully applicable to many other microprocessor controlled information processing systems.

A Nth-order linear algorithm for extracting diffuse correlation spectroscopy blood flow indices in heterogeneous tissues.

PubMed

Shang, Yu; Yu, Guoqiang

2014-09-29

Conventional semi-infinite analytical solutions of correlation diffusion equation may lead to errors when calculating blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements in tissues with irregular geometries. Very recently, we created an algorithm integrating a N th-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in homogenous tissues with arbitrary geometries for extraction of BFI (i.e., αD B ). The purpose of this study is to extend the capability of the N th-order linear algorithm for extracting BFI in heterogeneous tissues with arbitrary geometries. The previous linear algorithm was modified to extract BFIs in different types of tissues simultaneously through utilizing DCS data at multiple source-detector separations. We compared the proposed linear algorithm with the semi-infinite homogenous solution in a computer model of adult head with heterogeneous tissue layers of scalp, skull, cerebrospinal fluid, and brain. To test the capability of the linear algorithm for extracting relative changes of cerebral blood flow (rCBF) in deep brain, we assigned ten levels of αD B in the brain layer with a step decrement of 10% while maintaining αD B values constant in other layers. Simulation results demonstrate the accuracy (errors < 3%) of high-order ( N  ≥ 5) linear algorithm in extracting BFIs in different tissue layers and rCBF in deep brain. By contrast, the semi-infinite homogenous solution resulted in substantial errors in rCBF (34.5% ≤ errors ≤ 60.2%) and BFIs in different layers. The N th-order linear model simplifies data analysis, thus allowing for online data processing and displaying. Future study will test this linear algorithm in heterogeneous tissues with different levels of blood flow variations and noises.

A simple method for HPLC retention time prediction: linear calibration using two reference substances.

PubMed

Sun, Lei; Jin, Hong-Yu; Tian, Run-Tao; Wang, Ming-Juan; Liu, Li-Na; Ye, Liu-Ping; Zuo, Tian-Tian; Ma, Shuang-Cheng

2017-01-01

Analysis of related substances in pharmaceutical chemicals and multi-components in traditional Chinese medicines needs bulk of reference substances to identify the chromatographic peaks accurately. But the reference substances are costly. Thus, the relative retention (RR) method has been widely adopted in pharmacopoeias and literatures for characterizing HPLC behaviors of those reference substances unavailable. The problem is it is difficult to reproduce the RR on different columns due to the error between measured retention time (t R ) and predicted t R in some cases. Therefore, it is useful to develop an alternative and simple method for prediction of t R accurately. In the present study, based on the thermodynamic theory of HPLC, a method named linear calibration using two reference substances (LCTRS) was proposed. The method includes three steps, procedure of two points prediction, procedure of validation by multiple points regression and sequential matching. The t R of compounds on a HPLC column can be calculated by standard retention time and linear relationship. The method was validated in two medicines on 30 columns. It was demonstrated that, LCTRS method is simple, but more accurate and more robust on different HPLC columns than RR method. Hence quality standards using LCTRS method are easy to reproduce in different laboratories with lower cost of reference substances.

Testing concordance of instrumental variable effects in generalized linear models with application to Mendelian randomization

PubMed Central

Dai, James Y.; Chan, Kwun Chuen Gary; Hsu, Li

2014-01-01

Instrumental variable regression is one way to overcome unmeasured confounding and estimate causal effect in observational studies. Built on structural mean models, there has been considerale work recently developed for consistent estimation of causal relative risk and causal odds ratio. Such models can sometimes suffer from identification issues for weak instruments. This hampered the applicability of Mendelian randomization analysis in genetic epidemiology. When there are multiple genetic variants available as instrumental variables, and causal effect is defined in a generalized linear model in the presence of unmeasured confounders, we propose to test concordance between instrumental variable effects on the intermediate exposure and instrumental variable effects on the disease outcome, as a means to test the causal effect. We show that a class of generalized least squares estimators provide valid and consistent tests of causality. For causal effect of a continuous exposure on a dichotomous outcome in logistic models, the proposed estimators are shown to be asymptotically conservative. When the disease outcome is rare, such estimators are consistent due to the log-linear approximation of the logistic function. Optimality of such estimators relative to the well-known two-stage least squares estimator and the double-logistic structural mean model is further discussed. PMID:24863158

Correlation and simple linear regression.

PubMed

Eberly, Lynn E

2007-01-01

This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression.

On the linear programming bound for linear Lee codes.

PubMed

Astola, Helena; Tabus, Ioan

2016-01-01

Based on an invariance-type property of the Lee-compositions of a linear Lee code, additional equality constraints can be introduced to the linear programming problem of linear Lee codes. In this paper, we formulate this property in terms of an action of the multiplicative group of the field [Formula: see text] on the set of Lee-compositions. We show some useful properties of certain sums of Lee-numbers, which are the eigenvalues of the Lee association scheme, appearing in the linear programming problem of linear Lee codes. Using the additional equality constraints, we formulate the linear programming problem of linear Lee codes in a very compact form, leading to a fast execution, which allows to efficiently compute the bounds for large parameter values of the linear codes.

Single-Trial Classification of Multi-User P300-Based Brain-Computer Interface Using Riemannian Geometry.

PubMed

Korczowski, L; Congedo, M; Jutten, C

2015-08-01

The classification of electroencephalographic (EEG) data recorded from multiple users simultaneously is an important challenge in the field of Brain-Computer Interface (BCI). In this paper we compare different approaches for classification of single-trials Event-Related Potential (ERP) on two subjects playing a collaborative BCI game. The minimum distance to mean (MDM) classifier in a Riemannian framework is extended to use the diversity of the inter-subjects spatio-temporal statistics (MDM-hyper) or to merge multiple classifiers (MDM-multi). We show that both these classifiers outperform significantly the mean performance of the two users and analogous classifiers based on the step-wise linear discriminant analysis. More importantly, the MDM-multi outperforms the performance of the best player within the pair.

Multiple beam antenna/switch system study

NASA Technical Reports Server (NTRS)

1989-01-01

In the study of the Multiple Beam Antenna/Switch for the space to ground link (SGL) uplink and downlink services, several issues related to system engineering, antenna, transmit/receive, and switch systems were addressed and the results are provided. Bandwidth allocation at Ku band is inadequate to serve the data rate requirements for the forward and return services. Rain and depolarization effects at EHF, especially at Ka band, pose a significant threat to the link availabilities at heavy rain areas. Hardware induced effects such as the nonlinear characteristics of the power amplifier may necessitate the use of linearizers and limiters. It is also important to identify the components that are susceptible to the space radiation effects and shield or redesign them with rad-hard technologies for meeting the requirements of the space environment.

Examining age-related shared variance between face cognition, vision, and self-reported physical health: a test of the common cause hypothesis for social cognition

PubMed Central

Olderbak, Sally; Hildebrandt, Andrea; Wilhelm, Oliver

2015-01-01

The shared decline in cognitive abilities, sensory functions (e.g., vision and hearing), and physical health with increasing age is well documented with some research attributing this shared age-related decline to a single common cause (e.g., aging brain). We evaluate the extent to which the common cause hypothesis predicts associations between vision and physical health with social cognition abilities specifically face perception and face memory. Based on a sample of 443 adults (17–88 years old), we test a series of structural equation models, including Multiple Indicator Multiple Cause (MIMIC) models, and estimate the extent to which vision and self-reported physical health are related to face perception and face memory through a common factor, before and after controlling for their fluid cognitive component and the linear effects of age. Results suggest significant shared variance amongst these constructs, with a common factor explaining some, but not all, of the shared age-related variance. Also, we found that the relations of face perception, but not face memory, with vision and physical health could be completely explained by fluid cognition. Overall, results suggest that a single common cause explains most, but not all age-related shared variance with domain specific aging mechanisms evident. PMID:26321998

Tipping points? Curvilinear associations between activity level and mental development in toddlers.

PubMed

Flom, Megan; Cohen, Madeleine; Saudino, Kimberly J

2017-05-01

The Theory of Optimal Stimulation (Zentall & Zentall, Psychological Bulletin, 94, 1983, 446) posits that the relation between activity level (AL) and cognitive performance follows an inverted U shape where midrange AL predicts better cognitive performance than AL at the extremes. We explored this by fitting linear and quadratic models predicting mental development from AL assessed via multiple methods (parent ratings, observations, and actigraphs) and across multiple situations (laboratory play, laboratory test, home) in over 600 twins (2- and 3-year olds). Only observed AL in the laboratory was curvilinearly related to mental development scores. Results replicated across situations, age, and twin samples, providing strong support for the optimal stimulation model for this measure of AL in early childhood. Different measures of AL provide different information. Observations of AL which include both qualitative and quantitative aspects of AL within structured situations are able to capture beneficial aspects of normative AL as well as detriments of both low and high AL. © 2016 Association for Child and Adolescent Mental Health.

The relationship between spiritual well-being and health-related quality of life in college students.

PubMed

Anye, Ernest Tamanji; Gallien, Tara L; Bian, Hui; Moulton, Michael

2013-01-01

This study investigated the relationship between spiritual well-being (SWB) and various aspects of health-related quality of life (HRQL) of college students. Two hundred twenty-five participants were surveyed during October 2010 to assess SWB and HRQL using the Spiritual Well-Being Scale and questions from the Centers for Disease Control and Prevention's scale for HRQL, respectively. Hierarchical multiple linear regression analyses tested the relationship between SWB and multiple measures of HRQL while controlling for sex, age, and race. Participants who reported higher SWB scores were more likely to participate in religious-type activities and report better HRQL compared with students who reported a moderate sense of SWB. Jointly, SWB and participation in religious activities explained 18% of the variance in HQRL in this sample. SWB made a significant contribution to HRQL in a sample of college students. Such a relationship should be considered by campus health program planners to improve the quality of life of young adults.

Estimates of velocity structure and source depth using multiple P waves from aftershocks of the 1987 Elmore Ranch and Superstition Hills, California, earthquakes

USGS Publications Warehouse

Mori, J.

1991-01-01

Event record sections, which are constructed by plotting seismograms from many closely spaced earthquakes recorded on a few stations, show multiple free-surface reflections (PP, PPP, PPPP) of the P wave in the Imperial Valley. The relative timing of these arrivals is used to estimate the strength of the P-wave velocity gradient within the upper 5 km of the sediment layer. Consistent with previous studies, a velocity model with a value of 1.8 km/sec at the surface increasing linearly to 5.8 km/sec at a depth of 5.5 km fits the data well. The relative amplitudes of the P and PP arrivals are used to estimate the source depth for the aftershock distributions of the Elmore Ranch and Superstition Hills main shocks. Although the depth determination has large uncertainties, both the Elmore Ranch and Superstition Hills aftershock sequencs appear to have similar depth distribution in the range of 4 to 10 km. -Author

Learning of Rule Ensembles for Multiple Attribute Ranking Problems

NASA Astrophysics Data System (ADS)

Dembczyński, Krzysztof; Kotłowski, Wojciech; Słowiński, Roman; Szeląg, Marcin

In this paper, we consider the multiple attribute ranking problem from a Machine Learning perspective. We propose two approaches to statistical learning of an ensemble of decision rules from decision examples provided by the Decision Maker in terms of pairwise comparisons of some objects. The first approach consists in learning a preference function defining a binary preference relation for a pair of objects. The result of application of this function on all pairs of objects to be ranked is then exploited using the Net Flow Score procedure, giving a linear ranking of objects. The second approach consists in learning a utility function for single objects. The utility function also gives a linear ranking of objects. In both approaches, the learning is based on the boosting technique. The presented approaches to Preference Learning share good properties of the decision rule preference model and have good performance in the massive-data learning problems. As Preference Learning and Multiple Attribute Decision Aiding share many concepts and methodological issues, in the introduction, we review some aspects bridging these two fields. To illustrate the two approaches proposed in this paper, we solve with them a toy example concerning the ranking of a set of cars evaluated by multiple attributes. Then, we perform a large data experiment on real data sets. The first data set concerns credit rating. Since recent research in the field of Preference Learning is motivated by the increasing role of modeling preferences in recommender systems and information retrieval, we chose two other massive data sets from this area - one comes from movie recommender system MovieLens, and the other concerns ranking of text documents from 20 Newsgroups data set.

Evaluation of measurement errors of temperature and relative humidity from HOBO data logger under different conditions of exposure to solar radiation.

PubMed

da Cunha, Antonio Ribeiro

2015-05-01

This study aimed to assess measurements of temperature and relative humidity obtained with HOBO a data logger, under various conditions of exposure to solar radiation, comparing them with those obtained through the use of a temperature/relative humidity probe and a copper-constantan thermocouple psychrometer, which are considered the standards for obtaining such measurements. Data were collected over a 6-day period (from 25 March to 1 April, 2010), during which the equipment was monitored continuously and simultaneously. We employed the following combinations of equipment and conditions: a HOBO data logger in full sunlight; a HOBO data logger shielded within a white plastic cup with windows for air circulation; a HOBO data logger shielded within a gill-type shelter (multi-plate prototype plastic); a copper-constantan thermocouple psychrometer exposed to natural ventilation and protected from sunlight; and a temperature/relative humidity probe under a commercial, multi-plate radiation shield. Comparisons between the measurements obtained with the various devices were made on the basis of statistical indicators: linear regression, with coefficient of determination; index of agreement; maximum absolute error; and mean absolute error. The prototype multi-plate shelter (gill-type) used in order to protect the HOBO data logger was found to provide the best protection against the effects of solar radiation on measurements of temperature and relative humidity. The precision and accuracy of a device that measures temperature and relative humidity depend on an efficient shelter that minimizes the interference caused by solar radiation, thereby avoiding erroneous analysis of the data obtained.

Bowhead whale localization using asynchronous hydrophones in the Chukchi Sea.

PubMed

Warner, Graham A; Dosso, Stan E; Hannay, David E; Dettmer, Jan

2016-07-01

This paper estimates bowhead whale locations and uncertainties using non-linear Bayesian inversion of their modally-dispersed calls recorded on asynchronous recorders in the Chukchi Sea, Alaska. Bowhead calls were recorded on a cluster of 7 asynchronous ocean-bottom hydrophones that were separated by 0.5-9.2 km. A warping time-frequency analysis is used to extract relative mode arrival times as a function of frequency for nine frequency-modulated whale calls that dispersed in the shallow water environment. Each call was recorded on multiple hydrophones and the mode arrival times are inverted for: the whale location in the horizontal plane, source instantaneous frequency (IF), water sound-speed profile, seabed geoacoustic parameters, relative recorder clock drifts, and residual error standard deviations, all with estimated uncertainties. A simulation study shows that accurate prior environmental knowledge is not required for accurate localization as long as the inversion treats the environment as unknown. Joint inversion of multiple recorded calls is shown to substantially reduce uncertainties in location, source IF, and relative clock drift. Whale location uncertainties are estimated to be 30-160 m and relative clock drift uncertainties are 3-26 ms.

Variables Associated with Communicative Participation in People with Multiple Sclerosis: A Regression Analysis

ERIC Educational Resources Information Center

Baylor, Carolyn; Yorkston, Kathryn; Bamer, Alyssa; Britton, Deanna; Amtmann, Dagmar

2010-01-01

Purpose: To explore variables associated with self-reported communicative participation in a sample (n = 498) of community-dwelling adults with multiple sclerosis (MS). Method: A battery of questionnaires was administered online or on paper per participant preference. Data were analyzed using multiple linear backward stepwise regression. The…

Correlations of neutron multiplicity and γ -ray multiplicity with fragment mass and total kinetic energy in spontaneous fission of Cf 252

DOE PAGES

Wang, Taofeng; Li, Guangwu; Zhu, Liping; ...

2016-01-08

The dependence of correlations of neutron multiplicity ν and γ-ray multiplicity M γ in spontaneous fission of 252Cf on fragment mass A* and total kinetic energy (TKE) have been investigated by employing the ratio of M γ/ν and the form of M γ(ν). We show for the first time that M γ and ν have a complex correlation for heavy fragment masses, while there is a positive dependence of Mγ for light fragment masses and for near-symmetric mass splits. The ratio M γ/ν exhibits strong shell effects for neutron magic number N=50 and near doubly magic number shell closure atmore » Z=50 and N=82. The γ-ray multiplicity Mγ has a maximum for TKE=165-170 MeV. Above 170 MeV M γ(TKE) is approximately linear, while it deviates significantly from a linear dependence at lower TKE. The correlation between the average neutron and γ-ray multiplicities can be partly reproduced by model calculations.« less

An improved multiple linear regression and data analysis computer program package

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

A scalable parallel algorithm for multiple objective linear programs

NASA Technical Reports Server (NTRS)

Wiecek, Malgorzata M.; Zhang, Hong

1994-01-01

This paper presents an ADBASE-based parallel algorithm for solving multiple objective linear programs (MOLP's). Job balance, speedup and scalability are of primary interest in evaluating efficiency of the new algorithm. Implementation results on Intel iPSC/2 and Paragon multiprocessors show that the algorithm significantly speeds up the process of solving MOLP's, which is understood as generating all or some efficient extreme points and unbounded efficient edges. The algorithm gives specially good results for large and very large problems. Motivation and justification for solving such large MOLP's are also included.

Non-Linear Dynamics of Saturn's Rings

NASA Astrophysics Data System (ADS)

Esposito, L. W.

2016-12-01

Non-linear processes can explain why Saturn's rings are so active and dynamic. Ring systems differ from simple linear systems in two significant ways: 1. They are systems of granular material: where particle-to-particle collisions dominate; thus a kinetic, not a fluid description needed. Stresses are strikingly inhomogeneous and fluctuations are large compared to equilibrium. 2. They are strongly forced by resonances: which drive a non-linear response, that push the system across thresholds that lead to persistent states. Some of this non-linearity is captured in a simple Predator-Prey Model: Periodic forcing from the moon causes streamline crowding; This damps the relative velocity. About a quarter phase later, the aggregates stir the system to higher relative velocity and the limit cycle repeats each orbit, with relative velocity ranging from nearly zero to a multiple of the orbit average. Summary of Halo Results: A predator-prey model for ring dynamics produces transient structures like `straw' that can explain the halo morphology and spectroscopy: Cyclic velocity changes cause perturbed regions to reach higher collision speeds at some orbital phases, which preferentially removes small regolith particles; surrounding particles diffuse back too slowly to erase the effect: this gives the halo morphology; this requires energetic collisions (v ≈ 10m/sec, with throw distances about 200km, implying objects of scale R ≈ 20km).Transform to Duffing Eqn : With the coordinate transformation, z = M2/3, the Predator-Prey equations can be combined to form a single second-order differential equation with harmonic resonance forcing.Ring dynamics and history implications: Moon-triggered clumping explains both small and large particles at resonances. We calculate the stationary size distribution using a cell-to-cell mapping procedure that converts the phase-plane trajectories to a Markov chain. Approximating it as an asymmetric random walk with reflecting boundaries determines the power law index, using results of numerical simulations in the tidal environment. Aggregates can explain many dynamic aspects of the rings and can renew rings by shielding and recycling the material within them, depending on how long the mass is sequestered. We can ask: Are Saturn's rings a chaotic non-linear driven system?

Relationship between acculturation, discrimination, and suicidal ideation and attempts among US Hispanics in the National Epidemiologic Survey of Alcohol and Related Conditions.

PubMed

Perez-Rodriguez, M Mercedes; Baca-Garcia, Enrique; Oquendo, Maria A; Wang, Shuai; Wall, Melanie M; Liu, Shang-Min; Blanco, Carlos

2014-04-01

Acculturation is the process by which immigrants acquire the culture of the dominant society. Little is known about the relationship between acculturation and suicidal ideation and attempts among US Hispanics. Our aim was to examine the impact of 5 acculturation measures (age at migration, time in the United States, social network composition, language, race/ethnic orientation) on suicidal ideation and attempts in the largest available nationally representative sample of US Hispanics. Study participants were US Hispanics (N = 6,359) from Wave 2 of the 2004-2005 National Epidemiologic Survey of Alcohol and Related Conditions (N = 34,653). We used linear χ(2) tests and logistic regression models to analyze the association between acculturation and risk of suicidal ideation and attempts. Factors associated with a linear increase in lifetime risk for suicidal ideation and attempts were (1) younger age at migration (linear χ(2)(1) = 57.15; P < .0001), (2) longer time in the United States (linear χ(2)(1)= 36.09; P < .0001), (3) higher degree of English-language orientation (linear χ(2)(1) = 74.08; P <.0001), (4) lower Hispanic composition of social network (linear χ(2)(1) = 36.34; P < .0001), and (5) lower Hispanic racial/ethnic identification (linear χ(2)(1) = 47.77; P <.0001). Higher levels of perceived discrimination were associated with higher lifetime risk for suicidal ideation (β = 0.051; P < .001) and attempts (β = 0.020; P = .003). There was a linear association between multiple dimensions of acculturation and lifetime suicidal ideation and attempts. Discrimination was also associated with lifetime risk for suicidal ideation and attempts. Our results highlight protective aspects of the traditional Hispanic culture, such as high social support, coping strategies, and moral objections to suicide, which are modifiable factors and potential targets for public health interventions aimed at decreasing suicide risk. Culturally sensitive mental health resources need to be made more available to decrease discrimination and stigma. © Copyright 2014 Physicians Postgraduate Press, Inc.

Refill Adherence in Relation to Substitution and the Use of Multiple Medications: A Nationwide Population Based Study on New ACE-Inhibitor Users

PubMed Central

Jönsson, Anna K.; Lesén, Eva; Mårdby, Ann-Charlotte; Sundell, Karolina Andersson

2016-01-01

Objective Generic substitution has contributed to economic savings but switching products may affect patient adherence, particularly among those using multiple medications. The aim was to analyse if use of multiple medications influenced the association between switching products and refill adherence to angiotensin-converting-enzyme (ACE) inhibitors in Sweden. Study Design and Setting New users of ACE-inhibitors, starting between 1 July 2006 and 30 June 2007, were identified in the Swedish Prescribed Drug Register. Refill adherence was assessed using the continuous measure of medication acquisition (CMA) and analysed with linear regression and analysis of covariance. Results The study population included 42735 individuals whereof 51.2% were exposed to switching ACE-inhibitor and 39.6% used multiple medications. Refill adherence was higher among those exposed to switching products than those not, but did not vary depending on the use of multiple medications or among those not. Refill adherence varied with age, educational level, household income, country of birth, previous hospitalisation and previous cardiovascular diagnosis. Conclusion The results indicate a positive association between refill adherence and switching products, mainly due to generic substitution, among new users of ACE-inhibitors in Sweden. This association was independent of use of multiple medications. PMID:27192203

Valid statistical approaches for analyzing sholl data: Mixed effects versus simple linear models.

PubMed

Wilson, Machelle D; Sethi, Sunjay; Lein, Pamela J; Keil, Kimberly P

2017-03-01

The Sholl technique is widely used to quantify dendritic morphology. Data from such studies, which typically sample multiple neurons per animal, are often analyzed using simple linear models. However, simple linear models fail to account for intra-class correlation that occurs with clustered data, which can lead to faulty inferences. Mixed effects models account for intra-class correlation that occurs with clustered data; thus, these models more accurately estimate the standard deviation of the parameter estimate, which produces more accurate p-values. While mixed models are not new, their use in neuroscience has lagged behind their use in other disciplines. A review of the published literature illustrates common mistakes in analyses of Sholl data. Analysis of Sholl data collected from Golgi-stained pyramidal neurons in the hippocampus of male and female mice using both simple linear and mixed effects models demonstrates that the p-values and standard deviations obtained using the simple linear models are biased downwards and lead to erroneous rejection of the null hypothesis in some analyses. The mixed effects approach more accurately models the true variability in the data set, which leads to correct inference. Mixed effects models avoid faulty inference in Sholl analysis of data sampled from multiple neurons per animal by accounting for intra-class correlation. Given the widespread practice in neuroscience of obtaining multiple measurements per subject, there is a critical need to apply mixed effects models more widely. Copyright © 2017 Elsevier B.V. All rights reserved.

Collective Interaction in a Linear Array of Supersonic Rectangular Jets: A Linear Spatial Instability Study

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

1999-01-01

A linear spatial instability model for multiple spatially periodic supersonic rectangular jets is solved using Floquet-Bloch theory. It is assumed that in the region of interest a coherent wave can propagate. For the case studied large spatial growth rates are found. This work is motivated by an increase in mixing found in experimental measurements of spatially periodic supersonic rectangular jets with phase-locked screech and edge tone feedback locked subsonic jets. The results obtained in this paper suggests that phase-locked screech or edge tones may produce correlated spatially periodic jet flow downstream of the nozzles which creates a large span wise multi-nozzle region where a coherent wave can propagate. The large spatial growth rates for eddies obtained by model calculation herein are related to the increased mixing since eddies are the primary mechanism that transfer energy from the mean flow to the large turbulent structures. Calculations of spacial growth rates will be presented for a set of relative Mach numbers and spacings for which experimental measurements have been made. Calculations of spatial growth rates are presented for relative Mach numbers from 1.25 to 1.75 with ratios of nozzle spacing to nozzle width ratios from s/w(sub N) = 4 to s/w(sub N) = 13.7. The model may be of significant scientific and engineering value in the quest to understand and construct supersonic mixer-ejector nozzles which provide increased mixing and reduced noise.

Unambiguous discrimination between linearly dependent equidistant states with multiple copies

NASA Astrophysics Data System (ADS)

Zhang, Wen-Hai; Ren, Gang

2018-07-01

Linearly independent quantum states can be unambiguously discriminated, but linearly dependent ones cannot. For linearly dependent quantum states, however, if C copies of the single states are available, then they may form linearly independent states, and can be unambiguously discriminated. We consider unambiguous discrimination among N = D + 1 linearly dependent states given that C copies are available and that the single copies span a D-dimensional space with equal inner products. The maximum unambiguous discrimination probability is derived for all C with equal a priori probabilities. For this classification of the linearly dependent equidistant states, our result shows that if C is even then adding a further copy fails to increase the maximum discrimination probability.

Update on Linear Mode Photon Counting with the HgCdTe Linear Mode Avalanche Photodiode

NASA Technical Reports Server (NTRS)

Beck, Jeffrey D.; Kinch, Mike; Sun, Xiaoli

2014-01-01

The behavior of the gain-voltage characteristic of the mid-wavelength infrared cutoff HgCdTe linear mode avalanche photodiode (e-APD) is discussed both experimentally and theoretically as a function of the width of the multiplication region. Data are shown that demonstrate a strong dependence of the gain at a given bias voltage on the width of the n- gain region. Geometrical and fundamental theoretical models are examined to explain this behavior. The geometrical model takes into account the gain-dependent optical fill factor of the cylindrical APD. The theoretical model is based on the ballistic ionization model being developed for the HgCdTe APD. It is concluded that the fundamental theoretical explanation is the dominant effect. A model is developed that combines both the geometrical and fundamental effects. The model also takes into account the effect of the varying multiplication width in the low bias region of the gain-voltage curve. It is concluded that the lower than expected gain seen in the first 2 × 8 HgCdTe linear mode photon counting APD arrays, and higher excess noise factor, was very likely due to the larger than typical multiplication region length in the photon counting APD pixel design. The implications of these effects on device photon counting performance are discussed.

Non-linear relationship of cell hit and transformation probabilities in a low dose of inhaled radon progenies.

PubMed

Balásházy, Imre; Farkas, Arpád; Madas, Balázs Gergely; Hofmann, Werner

2009-06-01

Cellular hit probabilities of alpha particles emitted by inhaled radon progenies in sensitive bronchial epithelial cell nuclei were simulated at low exposure levels to obtain useful data for the rejection or support of the linear-non-threshold (LNT) hypothesis. In this study, local distributions of deposited inhaled radon progenies in airway bifurcation models were computed at exposure conditions characteristic of homes and uranium mines. Then, maximum local deposition enhancement factors at bronchial airway bifurcations, expressed as the ratio of local to average deposition densities, were determined to characterise the inhomogeneity of deposition and to elucidate their effect on resulting hit probabilities. The results obtained suggest that in the vicinity of the carinal regions of the central airways the probability of multiple hits can be quite high, even at low average doses. Assuming a uniform distribution of activity there are practically no multiple hits and the hit probability as a function of dose exhibits a linear shape in the low dose range. The results are quite the opposite in the case of hot spots revealed by realistic deposition calculations, where practically all cells receive multiple hits and the hit probability as a function of dose is non-linear in the average dose range of 10-100 mGy.

Multiple-Input Multiple-Output (MIMO) Linear Systems Extreme Inputs/Outputs

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

Smallwood, David O.

2007-01-01

A linear structure is excited at multiple points with a stationary normal random process. The response of the structure is measured at multiple outputs. If the autospectral densities of the inputs are specified, the phase relationships between the inputs are derived that will minimize or maximize the trace of the autospectral density matrix of the outputs. If the autospectral densities of the outputs are specified, the phase relationships between the outputs that will minimize or maximize the trace of the input autospectral density matrix are derived. It is shown that other phase relationships and ordinary coherence less than one willmore » result in a trace intermediate between these extremes. Least favorable response and some classes of critical response are special cases of the development. It is shown that the derivation for stationary random waveforms can also be applied to nonstationary random, transients, and deterministic waveforms.« less

Precision magnetic suspension linear bearing

NASA Technical Reports Server (NTRS)

Trumper, David L.; Queen, Michael A.

1992-01-01

We have shown the design and analyzed the electromechanics of a linear motor suitable for independently controlling two suspension degrees of freedom. This motor, at least on paper, meets the requirements for driving an X-Y stage of 10 Kg mass with about 4 m/sq sec acceleration, with travel of several hundred millimeters in X and Y, and with reasonable power dissipation. A conceptual design for such a stage is presented. The theoretical feasibility of linear and planar bearings using single or multiple magnetic suspension linear motors is demonstrated.

On Holo-Hilbert Spectral Analysis: A Full Informational Spectral Representation for Nonlinear and Non-Stationary Data

NASA Technical Reports Server (NTRS)

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Huang; Peng, Chung Kang;

On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

PubMed Central

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua

2016-01-01

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time–frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and non-stationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities. PMID:26953180

Polarized-interferometer feasibility study

NASA Technical Reports Server (NTRS)

Raab, F. H.

1983-01-01

The feasibility of using a polarized-interferometer system as a rendezvous and docking sensor for two cooperating spacecraft was studied. The polarized interferometer is a radio frequency system for long range, real time determination of relative position and attitude. Range is determined by round trip signal timing. Direction is determined by radio interferometry. Relative roll is determined from signal polarization. Each spacecraft is equipped with a transponder and an antenna array. The antenna arrays consist of four crossed dipoles that can transmit or receive either circularly or linearly polarized signals. The active spacecraft is equipped with a sophisticated transponder and makes all measurements. The transponder on the passive spacecraft is a relatively simple repeater. An initialization algorithm is developed to estimate position and attitude without any a priori information. A tracking algorithm based upon minimum variance linear estimators is also developed. Techniques to simplify the transponder on the passive spacecraft are investigated and a suitable configuration is determined. A multiple carrier CW signal format is selected. The dependence of range accuracy and ambiguity resolution error probability are derived and used to design a candidate system. The validity of the design and the feasibility of the polarized interferometer concept are verified by simulation.

A decline in female baboon hypothalamo-pituitary-adrenal axis activity anticipates aging.

PubMed

Yang, Shanshan; Gerow, Kenneth G; Huber, Hillary F; Considine, McKenna M; Li, Cun; Mattern, Vicki; Comuzzie, Anthony G; Ford, Stephen P; Nathanielsz, Peter W

2017-05-09

Stressors that disrupt homeostasis advance aging. Glucocorticoids regulate multiple processes that determine the aging trajectory. Debate exists regarding life-course circulating glucocorticoid concentrations. Rodent and nonhuman primate studies indicate circulating glucocorticoids fall from early life. We measured fasting morning cortisol in 24 female baboons (6-21 years, human equivalent ~18-70). We also quantified hypothalamic paraventricular nuclear (PVN) arginine vasopressin (AVP), corticotropin-releasing hormone, steroid receptors, and pituitary proopiomelanocortin immunohistochemically in 14 of these females at 6-13 years. We identified significant age-related 1) linear fall in cortisol and PVN AVP from as early as 6 years; 2) increased PVN glucocorticoid and mineralocorticoid receptors; 3) increased PVN 11β-hydroxysteroid dehydrogenase 1 and 2, regulators of local cortisol production, and 4) decreased pituitary proopiomelanocortin. Our data identify increased age-related negative feedback and local PVN cortisol production as potential mechanisms decreasing PVN drive to hypothalamo-pituitary-adrenal axis activity that result in the age-related circulating cortisol fall. Further studies are needed to determine whether the cortisol fall 1) causes aging, 2) protects by slowing aging, or 3) is an epiphenomenon unrelated to aging processes. We conclude that aging processes are best studied by linear life-course analysis beginning early in life.

A global lightning parameterization based on statistical relationships among environmental factors, aerosols, and convective clouds in the TRMM climatology

NASA Astrophysics Data System (ADS)

Stolz, Douglas C.; Rutledge, Steven A.; Pierce, Jeffrey R.; van den Heever, Susan C.

2017-07-01

The objective of this study is to determine the relative contributions of normalized convective available potential energy (NCAPE), cloud condensation nuclei (CCN) concentrations, warm cloud depth (WCD), vertical wind shear (SHEAR), and environmental relative humidity (RH) to the variability of lightning and radar reflectivity within convective features (CFs) observed by the Tropical Rainfall Measuring Mission (TRMM) satellite. Our approach incorporates multidimensional binned representations of observations of CFs and modeled thermodynamics, kinematics, and CCN as inputs to develop approximations for total lightning density (TLD) and the average height of 30 dBZ radar reflectivity (AVGHT30). The results suggest that TLD and AVGHT30 increase with increasing NCAPE, increasing CCN, decreasing WCD, increasing SHEAR, and decreasing RH. Multiple-linear approximations for lightning and radar quantities using the aforementioned predictors account for significant portions of the variance in the binned data set (R2 ≈ 0.69-0.81). The standardized weights attributed to CCN, NCAPE, and WCD are largest, the standardized weight of RH varies relative to other predictors, while the standardized weight for SHEAR is comparatively small. We investigate these statistical relationships for collections of CFs within various geographic areas and compare the aerosol (CCN) and thermodynamic (NCAPE and WCD) contributions to variations in the CF population in a partial sensitivity analysis based on multiple-linear regression approximations computed herein. A global lightning parameterization is developed; the average difference between predicted and observed TLD decreases from +21.6 to +11.6% when using a hybrid approach to combine separate approximations over continents and oceans, thus highlighting the need for regionally targeted investigations in the future.

Measurement bias detection with Kronecker product restricted models for multivariate longitudinal data: an illustration with health-related quality of life data from thirteen measurement occasions

PubMed Central

Verdam, Mathilde G. E.; Oort, Frans J.

2014-01-01

Highlights Application of Kronecker product to construct parsimonious structural equation models for multivariate longitudinal data. A method for the investigation of measurement bias with Kronecker product restricted models. Application of these methods to health-related quality of life data from bone metastasis patients, collected at 13 consecutive measurement occasions. The use of curves to facilitate substantive interpretation of apparent measurement bias. Assessment of change in common factor means, after accounting for apparent measurement bias. Longitudinal measurement invariance is usually investigated with a longitudinal factor model (LFM). However, with multiple measurement occasions, the number of parameters to be estimated increases with a multiple of the number of measurement occasions. To guard against too low ratios of numbers of subjects and numbers of parameters, we can use Kronecker product restrictions to model the multivariate longitudinal structure of the data. These restrictions can be imposed on all parameter matrices, including measurement invariance restrictions on factor loadings and intercepts. The resulting models are parsimonious and have attractive interpretation, but require different methods for the investigation of measurement bias. Specifically, additional parameter matrices are introduced to accommodate possible violations of measurement invariance. These additional matrices consist of measurement bias parameters that are either fixed at zero or free to be estimated. In cases of measurement bias, it is also possible to model the bias over time, e.g., with linear or non-linear curves. Measurement bias detection with Kronecker product restricted models will be illustrated with multivariate longitudinal data from 682 bone metastasis patients whose health-related quality of life (HRQL) was measured at 13 consecutive weeks. PMID:25295016

Measurement bias detection with Kronecker product restricted models for multivariate longitudinal data: an illustration with health-related quality of life data from thirteen measurement occasions.

PubMed

Verdam, Mathilde G E; Oort, Frans J

2014-01-01

Application of Kronecker product to construct parsimonious structural equation models for multivariate longitudinal data.A method for the investigation of measurement bias with Kronecker product restricted models.Application of these methods to health-related quality of life data from bone metastasis patients, collected at 13 consecutive measurement occasions.The use of curves to facilitate substantive interpretation of apparent measurement bias.Assessment of change in common factor means, after accounting for apparent measurement bias.Longitudinal measurement invariance is usually investigated with a longitudinal factor model (LFM). However, with multiple measurement occasions, the number of parameters to be estimated increases with a multiple of the number of measurement occasions. To guard against too low ratios of numbers of subjects and numbers of parameters, we can use Kronecker product restrictions to model the multivariate longitudinal structure of the data. These restrictions can be imposed on all parameter matrices, including measurement invariance restrictions on factor loadings and intercepts. The resulting models are parsimonious and have attractive interpretation, but require different methods for the investigation of measurement bias. Specifically, additional parameter matrices are introduced to accommodate possible violations of measurement invariance. These additional matrices consist of measurement bias parameters that are either fixed at zero or free to be estimated. In cases of measurement bias, it is also possible to model the bias over time, e.g., with linear or non-linear curves. Measurement bias detection with Kronecker product restricted models will be illustrated with multivariate longitudinal data from 682 bone metastasis patients whose health-related quality of life (HRQL) was measured at 13 consecutive weeks.

Use of cardiopulmonary exercise testing to assess early ventilatory changes related to occupational particulate matter

PubMed Central

Chao, T.P.; Sperandio, E.F.; Ostolin, T.L.V.P.; Almeida, V.R.; Romiti, M.; Gagliardi, A.R.T.; Arantes, R.L.; Dourado, V.Z.

2018-01-01

Spirometry has been used as the main strategy for assessing ventilatory changes related to occupational exposure to particulate matter (OEPM). However, in some cases, as one of its limitations, it may not be sensitive enough to show abnormalities before extensive damage, as seen in restrictive lung diseases. Therefore, we hypothesized that cardiopulmonary exercise testing (CPET) may be better than spirometry to detect early ventilatory impairment caused by OEPM. We selected 135 male workers with at least one year of exposure. After collection of self-reported socioeconomic status, educational level, and cardiovascular risk data, participants underwent spirometry, CPET, body composition assessment (bioelectrical impedance), and triaxial accelerometry (for level of physical activity in daily life). CPET was performed using a ramp protocol on a treadmill. Metabolic, cardiovascular, ventilatory, and submaximal relationships were measured. We compared 52 exposed to 83 non-exposed workers. Multiple linear regressions were developed using spirometry and CPET variables as outcomes and OEPM as the main predictor, and adjusted by the main covariates. Our results showed that OEPM was associated with significant reductions in peak minute ventilation, peak tidal volume, and breathing reserve index. Exposed participants presented shallower slope of ΔVT/ΔlnV̇E (breathing pattern), i.e., increased tachypneic breathing pattern. The OEPM explained 7.4% of the ΔVT/ΔlnV̇E variability. We found no significant influence of spirometric indices after multiple linear regressions. We conclude that CPET might be a more sensitive feature of assessing early pulmonary impairment related to OEPM. Our cross-sectional results suggested that CPET is a promising tool for the screening of asymptomatic male workers. PMID:29590255

Masticatory performance and oral health-related quality of life before and after complete denture treatment.

PubMed

Yamamoto, Saori; Shiga, Hiroshi

2018-03-13

To clarify the relationship between masticatory performance and oral health-related quality of life (OHRQoL) before and after complete denture treatment. Thirty patients wearing complete dentures were asked to chew a gummy jelly on their habitual chewing side, and the amount of glucose extraction during chewing was measured as the parameter of masticatory performance. Subjects were asked to answer the Oral Health Impact Profile (OHIP-J49) questionnaire, which consists of 49 questions related to oral problems. The total score of 49 question items along with individual domain scores within the seven domains (functional limitation, pain, psychological discomfort, physical disability, psychological disability, social disability and handicap) were calculated and used as the parameters of OHRQoL. These records were obtained before treatment and 3 months after treatment. Each parameter of masticatory performance and OHRQoL was compared before treatment and after treatment. The relationship between masticatory performance and OHRQoL was investigated, and a stepwise multiple linear regression analysis was performed. Both masticatory performance and OHRQoL were significantly improved after treatment. Furthermore, masticatory performance was significantly correlated with some parameters of OHRQoL. The stepwise multiple linear regression analysis showed functional limitation and pain as important factors affecting masticatory performance before treatment and functional limitation as important factors affecting masticatory performance after treatment. These results suggested that masticatory performance and OHRQoL are significantly improved after treatment and that there is a close relationship between the two. Moreover, functional limitation was found to be the most important factor affecting masticatory performance. Copyright © 2018 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

Dilations and the Equation of a Line

ERIC Educational Resources Information Center

Yopp, David A.

2016-01-01

Students engage in proportional reasoning when they use covariance and multiple comparisons. Without rich connections to proportional reasoning, students may develop inadequate understandings of linear relationships and the equations that model them. Teachers can improve students' understanding of linear relationships by focusing on realistic…

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

Shang, Yu; Yu, Guoqiang, E-mail: guoqiang.yu@uky.edu

Conventional semi-infinite analytical solutions of correlation diffusion equation may lead to errors when calculating blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements in tissues with irregular geometries. Very recently, we created an algorithm integrating a Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in homogenous tissues with arbitrary geometries for extraction of BFI (i.e., αD{sub B}). The purpose of this study is to extend the capability of the Nth-order linear algorithm for extracting BFI in heterogeneous tissues with arbitrary geometries. The previous linear algorithm was modified to extract BFIs in different typesmore » of tissues simultaneously through utilizing DCS data at multiple source-detector separations. We compared the proposed linear algorithm with the semi-infinite homogenous solution in a computer model of adult head with heterogeneous tissue layers of scalp, skull, cerebrospinal fluid, and brain. To test the capability of the linear algorithm for extracting relative changes of cerebral blood flow (rCBF) in deep brain, we assigned ten levels of αD{sub B} in the brain layer with a step decrement of 10% while maintaining αD{sub B} values constant in other layers. Simulation results demonstrate the accuracy (errors < 3%) of high-order (N ≥ 5) linear algorithm in extracting BFIs in different tissue layers and rCBF in deep brain. By contrast, the semi-infinite homogenous solution resulted in substantial errors in rCBF (34.5% ≤ errors ≤ 60.2%) and BFIs in different layers. The Nth-order linear model simplifies data analysis, thus allowing for online data processing and displaying. Future study will test this linear algorithm in heterogeneous tissues with different levels of blood flow variations and noises.« less

Climbing fibers predict movement kinematics and performance errors.

PubMed

Streng, Martha L; Popa, Laurentiu S; Ebner, Timothy J

2017-09-01

Requisite for understanding cerebellar function is a complete characterization of the signals provided by complex spike (CS) discharge of Purkinje cells, the output neurons of the cerebellar cortex. Numerous studies have provided insights into CS function, with the most predominant view being that they are evoked by error events. However, several reports suggest that CSs encode other aspects of movements and do not always respond to errors or unexpected perturbations. Here, we evaluated CS firing during a pseudo-random manual tracking task in the monkey ( Macaca mulatta ). This task provides extensive coverage of the work space and relative independence of movement parameters, delivering a robust data set to assess the signals that activate climbing fibers. Using reverse correlation, we determined feedforward and feedback CSs firing probability maps with position, velocity, and acceleration, as well as position error, a measure of tracking performance. The direction and magnitude of the CS modulation were quantified using linear regression analysis. The major findings are that CSs significantly encode all three kinematic parameters and position error, with acceleration modulation particularly common. The modulation is not related to "events," either for position error or kinematics. Instead, CSs are spatially tuned and provide a linear representation of each parameter evaluated. The CS modulation is largely predictive. Similar analyses show that the simple spike firing is modulated by the same parameters as the CSs. Therefore, CSs carry a broader array of signals than previously described and argue for climbing fiber input having a prominent role in online motor control. NEW & NOTEWORTHY This article demonstrates that complex spike (CS) discharge of cerebellar Purkinje cells encodes multiple parameters of movement, including motor errors and kinematics. The CS firing is not driven by error or kinematic events; instead it provides a linear representation of each parameter. In contrast with the view that CSs carry feedback signals, the CSs are predominantly predictive of upcoming position errors and kinematics. Therefore, climbing fibers carry multiple and predictive signals for online motor control. Copyright © 2017 the American Physiological Society.

Socio-economic factors associated with infant mortality in Italy: an ecological study

PubMed Central

2012-01-01

Introduction One issue that continues to attract the attention of public health researchers is the possible relationship in high-income countries between income, income inequality and infant mortality (IM). The aim of this study was to assess the associations between IM and major socio-economic determinants in Italy. Methods Associations between infant mortality rates in the 20 Italian regions (2006–2008) and the Gini index of income inequality, mean household income, percentage of women with at least 8 years of education, and percentage of unemployed aged 15–64 years were assessed using Pearson correlation coefficients. Univariate linear regression and multiple stepwise linear regression analyses were performed to determine the magnitude and direction of the effect of the four socio-economic variables on IM. Results The Gini index and the total unemployment rate showed a positive strong correlation with IM (r = 0.70; p < 0.001 and r = 0.84; p < 0.001 respectively), mean household income showed a strong negative correlation (r = −0.78; p < 0.001), while female educational attainment presented a weak negative correlation (r = −0.45; p < 0.05). Using a multiple stepwise linear regression model, only unemployment rate was independently associated with IM (b = 0.15, p < 0.001). Conclusions In Italy, a high-income country where health care is universally available, variations in IM were strongly associated with relative and absolute income and unemployment rate. These results suggest that in Italy IM is not only related to income distribution, as demonstrated for other developed countries, but also to economic factors such as absolute income and unemployment. In order to reduce IM and the existing inequalities, the challenge for Italian decision makers is to promote economic growth and enhance employment levels. PMID:22898293

Non-linear effects of the built environment on automobile-involved pedestrian crash frequency: A machine learning approach.

PubMed

Ding, Chuan; Chen, Peng; Jiao, Junfeng

2018-03-01

Although a growing body of literature focuses on the relationship between the built environment and pedestrian crashes, limited evidence is provided about the relative importance of many built environment attributes by accounting for their mutual interaction effects and their non-linear effects on automobile-involved pedestrian crashes. This study adopts the approach of Multiple Additive Poisson Regression Trees (MAPRT) to fill such gaps using pedestrian collision data collected from Seattle, Washington. Traffic analysis zones are chosen as the analytical unit. The effects of various factors on pedestrian crash frequency investigated include characteristics the of road network, street elements, land use patterns, and traffic demand. Density and the degree of mixed land use have major effects on pedestrian crash frequency, accounting for approximately 66% of the effects in total. More importantly, some factors show clear non-linear relationships with pedestrian crash frequency, challenging the linearity assumption commonly used in existing studies which employ statistical models. With various accurately identified non-linear relationships between the built environment and pedestrian crashes, this study suggests local agencies to adopt geo-spatial differentiated policies to establish a safe walking environment. These findings, especially the effective ranges of the built environment, provide evidence to support for transport and land use planning, policy recommendations, and road safety programs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Linear time-varying models can reveal non-linear interactions of biomolecular regulatory networks using multiple time-series data.

PubMed

Kim, Jongrae; Bates, Declan G; Postlethwaite, Ian; Heslop-Harrison, Pat; Cho, Kwang-Hyun

2008-05-15

Inherent non-linearities in biomolecular interactions make the identification of network interactions difficult. One of the principal problems is that all methods based on the use of linear time-invariant models will have fundamental limitations in their capability to infer certain non-linear network interactions. Another difficulty is the multiplicity of possible solutions, since, for a given dataset, there may be many different possible networks which generate the same time-series expression profiles. A novel algorithm for the inference of biomolecular interaction networks from temporal expression data is presented. Linear time-varying models, which can represent a much wider class of time-series data than linear time-invariant models, are employed in the algorithm. From time-series expression profiles, the model parameters are identified by solving a non-linear optimization problem. In order to systematically reduce the set of possible solutions for the optimization problem, a filtering process is performed using a phase-portrait analysis with random numerical perturbations. The proposed approach has the advantages of not requiring the system to be in a stable steady state, of using time-series profiles which have been generated by a single experiment, and of allowing non-linear network interactions to be identified. The ability of the proposed algorithm to correctly infer network interactions is illustrated by its application to three examples: a non-linear model for cAMP oscillations in Dictyostelium discoideum, the cell-cycle data for Saccharomyces cerevisiae and a large-scale non-linear model of a group of synchronized Dictyostelium cells. The software used in this article is available from http://sbie.kaist.ac.kr/software

Imaging complex objects using learning tomography

NASA Astrophysics Data System (ADS)

Lim, JooWon; Goy, Alexandre; Shoreh, Morteza Hasani; Unser, Michael; Psaltis, Demetri

2018-02-01

Optical diffraction tomography (ODT) can be described using the scattering process through an inhomogeneous media. An inherent nonlinearity exists relating the scattering medium and the scattered field due to multiple scattering. Multiple scattering is often assumed to be negligible in weakly scattering media. This assumption becomes invalid as the sample gets more complex resulting in distorted image reconstructions. This issue becomes very critical when we image a complex sample. Multiple scattering can be simulated using the beam propagation method (BPM) as the forward model of ODT combined with an iterative reconstruction scheme. The iterative error reduction scheme and the multi-layer structure of BPM are similar to neural networks. Therefore we refer to our imaging method as learning tomography (LT). To fairly assess the performance of LT in imaging complex samples, we compared LT with the conventional iterative linear scheme using Mie theory which provides the ground truth. We also demonstrate the capacity of LT to image complex samples using experimental data of a biological cell.

Multi-Target Angle Tracking Algorithm for Bistatic MIMO Radar Based on the Elements of the Covariance Matrix

PubMed Central

Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo

2018-01-01

In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar. PMID:29518957

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions

PubMed Central

Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael

2015-01-01

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field. DOI: http://dx.doi.org/10.7554/eLife.08411.001 PMID:26609814

Multivariate meta-analysis using individual participant data

PubMed Central

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2016-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

Assessing Scientific Practices Using Machine-Learning Methods: How Closely Do They Match Clinical Interview Performance?

NASA Astrophysics Data System (ADS)

Beggrow, Elizabeth P.; Ha, Minsu; Nehm, Ross H.; Pearl, Dennis; Boone, William J.

2014-02-01

The landscape of science education is being transformed by the new Framework for Science Education (National Research Council, A framework for K-12 science education: practices, crosscutting concepts, and core ideas. The National Academies Press, Washington, DC, 2012), which emphasizes the centrality of scientific practices—such as explanation, argumentation, and communication—in science teaching, learning, and assessment. A major challenge facing the field of science education is developing assessment tools that are capable of validly and efficiently evaluating these practices. Our study examined the efficacy of a free, open-source machine-learning tool for evaluating the quality of students' written explanations of the causes of evolutionary change relative to three other approaches: (1) human-scored written explanations, (2) a multiple-choice test, and (3) clinical oral interviews. A large sample of undergraduates (n = 104) exposed to varying amounts of evolution content completed all three assessments: a clinical oral interview, a written open-response assessment, and a multiple-choice test. Rasch analysis was used to compute linear person measures and linear item measures on a single logit scale. We found that the multiple-choice test displayed poor person and item fit (mean square outfit >1.3), while both oral interview measures and computer-generated written response measures exhibited acceptable fit (average mean square outfit for interview: person 0.97, item 0.97; computer: person 1.03, item 1.06). Multiple-choice test measures were more weakly associated with interview measures (r = 0.35) than the computer-scored explanation measures (r = 0.63). Overall, Rasch analysis indicated that computer-scored written explanation measures (1) have the strongest correspondence to oral interview measures; (2) are capable of capturing students' normative scientific and naive ideas as accurately as human-scored explanations, and (3) more validly detect understanding than the multiple-choice assessment. These findings demonstrate the great potential of machine-learning tools for assessing key scientific practices highlighted in the new Framework for Science Education.

Modelling leaf photosynthetic and transpiration temperature-dependent responses in Vitis vinifera cv. Semillon grapevines growing in hot, irrigated vineyard conditions

PubMed Central

Greer, Dennis H.

2012-01-01

Background and aims Grapevines growing in Australia are often exposed to very high temperatures and the question of how the gas exchange processes adjust to these conditions is not well understood. The aim was to develop a model of photosynthesis and transpiration in relation to temperature to quantify the impact of the growing conditions on vine performance. Methodology Leaf gas exchange was measured along the grapevine shoots in accordance with their growth and development over several growing seasons. Using a general linear statistical modelling approach, photosynthesis and transpiration were modelled against leaf temperature separated into bands and the model parameters and coefficients applied to independent datasets to validate the model. Principal results Photosynthesis, transpiration and stomatal conductance varied along the shoot, with early emerging leaves having the highest rates, but these declined as later emerging leaves increased their gas exchange capacities in accordance with development. The general linear modelling approach applied to these data revealed that photosynthesis at each temperature was additively dependent on stomatal conductance, internal CO2 concentration and photon flux density. The temperature-dependent coefficients for these parameters applied to other datasets gave a predicted rate of photosynthesis that was linearly related to the measured rates, with a 1 : 1 slope. Temperature-dependent transpiration was multiplicatively related to stomatal conductance and the leaf to air vapour pressure deficit and applying the coefficients also showed a highly linear relationship, with a 1 : 1 slope between measured and modelled rates, when applied to independent datasets. Conclusions The models developed for the grapevines were relatively simple but accounted for much of the seasonal variation in photosynthesis and transpiration. The goodness of fit in each case demonstrated that explicitly selecting leaf temperature as a model parameter, rather than including temperature intrinsically as is usually done in more complex models, was warranted. PMID:22567220

Do religious activities among young-old immigrants act as a buffer against the effect of a lack of resources on well-being?

PubMed

Klokgieters, Silvia S; van Tilburg, Theo G; Deeg, Dorly J H; Huisman, Martijn

2018-01-30

Despite a large body of sociological and psychological literature suggesting that religious activities may mitigate the effects of stress, few studies have investigated the beneficial effects of religious activities among immigrants. Immigrants in particular may stand to benefit from these activities because they often report a religious affiliation and often occupy disadvantaged positions. This study investigates whether private and public religious activities reduce the negative effects of a lack of physical, social, and socio-economic resources on wellbeing among Turkish and Moroccan young-old immigrants in the Netherlands. Using data from the Longitudinal Study Amsterdam, cluster analysis revealed three patterns of absence of resources: physically disadvantaged, multiple disadvantages, and relatively advantaged. Linear regression analysis assessed associations between patterns of resources, religious activities and wellbeing. Persons who are physically disadvantaged or have multiple disadvantages have a lower level of wellbeing compared to persons who are relatively advantaged.  More engagement in private religious activities was associated with higher wellbeing. Among those with multiple disadvantages, however, more engagement in private religious activities was associated with lower wellbeing. Public religious activities were not associated with wellbeing in the disadvantaged group. Private religious activities are positively related to wellbeing among Turkish and Moroccan immigrants. In situations where resources are lacking, however, the relation between private religious activities and wellbeing is negative. The study's results highlight the importance of context, disadvantage and type of religious activity for wellbeing.

Direct localization of poles of a meromorphic function from measurements on an incomplete boundary

NASA Astrophysics Data System (ADS)

Nara, Takaaki; Ando, Shigeru

2010-01-01

This paper proposes an algebraic method to reconstruct the positions of multiple poles in a meromorphic function field from measurements on an arbitrary simple arc in it. A novel issue is the exactness of the algorithm depending on whether the arc is open or closed, and whether it encloses or does not enclose the poles. We first obtain a differential equation that can equivalently determine the meromorphic function field. From it, we derive linear equations that relate the elementary symmetric polynomials of the pole positions to weighted integrals of the field along the simple arc and end-point terms of the arc when it is an open one. Eliminating the end-point terms based on an appropriate choice of weighting functions and a combination of the linear equations, we obtain a simple system of linear equations for solving the elementary symmetric polynomials. We also show that our algorithm can be applied to a 2D electric impedance tomography problem. The effects of the proximity of the poles, the number of measurements and noise on the localization accuracy are numerically examined.

Integrable generalizations of non-linear multiple three-wave interaction models

NASA Astrophysics Data System (ADS)

Jurčo, Branislav

1989-07-01

Integrable generalizations of multiple three-wave interaction models in terms of r-matrix formulation are investigated. The Lax representations, complete sets of first integrals in involution are constructed, the quantization leading to Gaudin's models is discussed.

The enigmatic nature of the circumstellar envelope and bow shock surrounding Betelgeuse as revealed by Herschel. I. Evidence of clumps, multiple arcs, and a linear bar-like structure

NASA Astrophysics Data System (ADS)

Decin, L.; Cox, N. L. J.; Royer, P.; Van Marle, A. J.; Vandenbussche, B.; Ladjal, D.; Kerschbaum, F.; Ottensamer, R.; Barlow, M. J.; Blommaert, J. A. D. L.; Gomez, H. L.; Groenewegen, M. A. T.; Lim, T.; Swinyard, B. M.; Waelkens, C.; Tielens, A. G. G. M.

2012-12-01

Context. The interaction between stellar winds and the interstellar medium (ISM) can create complex bow shocks. The photometers on board the Herschel Space Observatory are ideally suited to studying the morphologies of these bow shocks. Aims: We aim to study the circumstellar environment and wind-ISM interaction of the nearest red supergiant, Betelgeuse. Methods.Herschel PACS images at 70, 100, and 160 μm and SPIRE images at 250, 350, and 500 μm were obtained by scanning the region around Betelgeuse. These data were complemented with ultraviolet GALEX data, near-infrared WISE data, and radio 21 cm GALFA-HI data. The observational properties of the bow shock structure were deduced from the data and compared with hydrodynamical simulations. Results: The infrared Herschel images of the environment around Betelgeuse are spectacular, showing the occurrence of multiple arcs at ~6-7' from the central target and the presence of a linear bar at ~9'. Remarkably, no large-scale instabilities are seen in the outer arcs and linear bar. The dust temperature in the outer arcs varies between 40 and 140 K, with the linear bar having the same colour temperature as the arcs. The inner envelope shows clear evidence of a non-homogeneous clumpy structure (beyond 15''), probably related to the giant convection cells of the outer atmosphere. The non-homogeneous distribution of the material even persists until the collision with the ISM. A strong variation in brightness of the inner clumps at a radius of ~2' suggests a drastic change in mean gas and dust density ~32 000 yr ago. Using hydrodynamical simulations, we try to explain the observed morphology of the bow shock around Betelgeuse. Conclusions: Different hypotheses, based on observational and theoretical constraints, are formulated to explain the origin of the multiple arcs and the linear bar and the fact that no large-scale instabilities are visible in the bow shock region. We infer that the two main ingredients for explaining these phenomena are a non-homogeneous mass-loss process and the influence of the Galactic magnetic field. The hydrodynamical simulations show that a warm interstellar medium, reflecting a warm neutral or partially ionized medium, or a higher temperature in the shocked wind also prevent the growth of strong instabilities. The linear bar is probably an interstellar structure illuminated by Betelgeuse itself. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.Appendices (including movies) are available in electronic form at http://www.aanda.org

How multiplicity determines entropy and the derivation of the maximum entropy principle for complex systems.

PubMed

Hanel, Rudolf; Thurner, Stefan; Gell-Mann, Murray

2014-05-13

The maximum entropy principle (MEP) is a method for obtaining the most likely distribution functions of observables from statistical systems by maximizing entropy under constraints. The MEP has found hundreds of applications in ergodic and Markovian systems in statistical mechanics, information theory, and statistics. For several decades there has been an ongoing controversy over whether the notion of the maximum entropy principle can be extended in a meaningful way to nonextensive, nonergodic, and complex statistical systems and processes. In this paper we start by reviewing how Boltzmann-Gibbs-Shannon entropy is related to multiplicities of independent random processes. We then show how the relaxation of independence naturally leads to the most general entropies that are compatible with the first three Shannon-Khinchin axioms, the (c,d)-entropies. We demonstrate that the MEP is a perfectly consistent concept for nonergodic and complex statistical systems if their relative entropy can be factored into a generalized multiplicity and a constraint term. The problem of finding such a factorization reduces to finding an appropriate representation of relative entropy in a linear basis. In a particular example we show that path-dependent random processes with memory naturally require specific generalized entropies. The example is to our knowledge the first exact derivation of a generalized entropy from the microscopic properties of a path-dependent random process.

Which symptoms contribute the most to patients' perception of health in multiple sclerosis?

PubMed

Green, Rivka; Cutter, Gary; Friendly, Michael; Kister, Ilya

2017-01-01

Multiple sclerosis is a polysymptomatic disease. Little is known about relative contributions of the different multiple sclerosis symptoms to self-perception of health. To investigate the relationship between symptom severity in 11 domains affected by multiple sclerosis and self-rated health. Multiple sclerosis patients in two multiple sclerosis centers assessed self-rated health with a validated instrument and symptom burden with symptoMScreen, a validated battery of Likert scales for 11 domains commonly affected by multiple sclerosis. Pearson correlations and multivariate linear regressions were used to investigate the relationship between symptoMScreen scores and self-rated health. Among 1865 multiple sclerosis outpatients (68% women, 78% with relapsing-remitting multiple sclerosis, mean age 46.38 ± 12.47 years, disease duration 13.43 ± 10.04 years), average self-rated health score was 2.30 ('moderate to good'). Symptom burden (composite symptoMScreen score) highly correlated with self-rated health ( r  = 0.68, P  < 0.0001) as did each of the symptoMScreen domain subscores. In regression analysis, pain ( t  = 7.00), ambulation ( t  = 6.91), and fatigue ( t  = 5.85) contributed the highest amount of variance in self-rated health ( P  < 0.001). Pain contributed the most to multiple sclerosis outpatients' perception of health, followed by gait dysfunction and fatigue. These findings suggest that 'invisible disability' may be more important to patients' sense of wellbeing than physical disability, and challenge the notion that physical disability should be the primary outcome measure in multiple sclerosis.

Characteristics of compound multiplicity in 84Kr36 with various light and heavy targets at 1 GeV per nucleon

NASA Astrophysics Data System (ADS)

Chouhan, N. S.; Singh, M. K.; Singh, V.; Pathak, R.

2013-12-01

Interactions of 84Kr36 having kinetic energy around 1 GeV per nucleon with NIKFI BR-2 nuclear emulsion detector's target reveal some of the important features of compound multiplicity. Present article shows that width of compound multiplicity distributions and value of mean compound multiplicity have linear relationship with mass number of the projectile colliding system.

The optimal hormonal replacement modality selection for multiple organ procurement from brain-dead organ donors

PubMed Central

Mi, Zhibao; Novitzky, Dimitri; Collins, Joseph F; Cooper, David KC

2015-01-01

The management of brain-dead organ donors is complex. The use of inotropic agents and replacement of depleted hormones (hormonal replacement therapy) is crucial for successful multiple organ procurement, yet the optimal hormonal replacement has not been identified, and the statistical adjustment to determine the best selection is not trivial. Traditional pair-wise comparisons between every pair of treatments, and multiple comparisons to all (MCA), are statistically conservative. Hsu’s multiple comparisons with the best (MCB) – adapted from the Dunnett’s multiple comparisons with control (MCC) – has been used for selecting the best treatment based on continuous variables. We selected the best hormonal replacement modality for successful multiple organ procurement using a two-step approach. First, we estimated the predicted margins by constructing generalized linear models (GLM) or generalized linear mixed models (GLMM), and then we applied the multiple comparison methods to identify the best hormonal replacement modality given that the testing of hormonal replacement modalities is independent. Based on 10-year data from the United Network for Organ Sharing (UNOS), among 16 hormonal replacement modalities, and using the 95% simultaneous confidence intervals, we found that the combination of thyroid hormone, a corticosteroid, antidiuretic hormone, and insulin was the best modality for multiple organ procurement for transplantation. PMID:25565890

Improving Prediction Accuracy for WSN Data Reduction by Applying Multivariate Spatio-Temporal Correlation

PubMed Central

Carvalho, Carlos; Gomes, Danielo G.; Agoulmine, Nazim; de Souza, José Neuman

2011-01-01

This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction. PMID:22346626

Conceptualizing Matrix Multiplication: A Framework for Student Thinking, an Historical Analysis, and a Modeling Perspective

ERIC Educational Resources Information Center

Larson, Christine

2010-01-01

Little is known about the variety of ways students conceptualize matrix multiplication, yet this is a fundamental part of most introductory linear algebra courses. My dissertation follows a three-paper format, with the three papers exploring conceptualizations of matrix multiplication from a variety of viewpoints. In these papers, I explore (1)…

Calibration of diatom-pH-alkalinity methodology for the interpretation of the sedimentary record in Emerald Lake Integrated watershed study. Final report, 6 May 1985-10 October 1986

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

Holmes, R.W.

1986-10-10

The present study was designed to establish quantitative relationships between lake air-equilibrated pH, alkalinity, and diatoms occurring in the surface sediments in high-elevation Sierra Nevada Lakes. These relationships provided the necessary information to develop predictive equations relating lake pH to the composition of surface-sediment diatom assemblages in 27 study lakes. Using the Hustedt diatom pH classification system, Index B of Renberg and Hellberg, and multiple linear regression analysis, two equations were developed which predict lake pH from the relative abundance of sediment diatoms occurring in each of four diatom pH groupings.

Work-related determinants of multi-site musculoskeletal pain among employees in the health care sector.

PubMed

Neupane, Subas; Nygård, Clas-Håkan; Oakman, Jodi

2016-06-16

Work-related musculoskeletal pain is a major occupational problem. Those with pain in multiple sites usually report worse health outcomes than those with pain in one site. This study explored prevalence and associated predictors of multi-site pain in health care sector employees. Survey responses from 1348 health care sector employees across three organisations (37% response rate) collected data on job satisfaction, work life balance, psychosocial and physical hazards, general health and work ability. Musculoskeletal discomfort was measured across 5 body regions with pain in ≥ 2 sites defined as multi-site pain. Generalized linear models were used to identify relationships between work-related factors and multi-site pain. Over 52% of the employees reported pain in multiple body sites and 19% reported pain in one site. Poor work life balance (PRR = 2.33, 95% CI = 1.06-5.14). physical (PRR = 7.58, 95% CI = 4.89-11.77) and psychosocial (PRR = 1.59, 95% CI = 1.00-2.57) hazard variables were related to multi-site pain (after controlling for age, gender, health and work ability. Older employees and females were more likely to report multi-site pain. Effective risk management of work related multi-site pain must include identification and control of psychosocial and physical hazards.

Determination of chlorpyrifos and its metabolites in cells and culture media by liquid chromatography-electrospray ionization tandem mass spectrometry.

PubMed

Yang, Xiangkun; Wu, Xian; Brown, Kyle A; Le, Thao; Stice, Steven L; Bartlett, Michael G

2017-09-15

A sensitive method to simultaneously quantitate chlorpyrifos, chlorpyrifos oxon and the detoxified product 3,5,6-trichloro-2-pyridinol (TCP) was developed using either liquid-liquid extraction for culture media samples, or protein precipitation for cell samples. Multiple reaction monitoring in positive ion mode was applied for the detection of chlorpyrifos and chlorpyrifos oxon, and selected ion recording in negative mode was applied to detect TCP. The method provided linear ranges from 5 to 500, 0.2-20 and 20-2000ng/mL for media samples and from 0.5-50, 0.02-2 and 2-200ng/million cells for CPF, CPO and TCP, respectively. The method was validated using selectivity, linearity, precision, accuracy, recovery, stability and dilution tests. All relative standard deviations (RSDs) and relative errors (REs) for QC samples were within 15% (except for LLOQ, within 20%). This method has been successfully applied to study the neurotoxicity and metabolism of chlorpyrifos in a human neuronal model. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling the effects of AADT on predicting multiple-vehicle crashes at urban and suburban signalized intersections.

PubMed

Chen, Chen; Xie, Yuanchang

2016-06-01

Annual Average Daily Traffic (AADT) is often considered as a main covariate for predicting crash frequencies at urban and suburban intersections. A linear functional form is typically assumed for the Safety Performance Function (SPF) to describe the relationship between the natural logarithm of expected crash frequency and covariates derived from AADTs. Such a linearity assumption has been questioned by many researchers. This study applies Generalized Additive Models (GAMs) and Piecewise Linear Negative Binomial (PLNB) regression models to fit intersection crash data. Various covariates derived from minor-and major-approach AADTs are considered. Three different dependent variables are modeled, which are total multiple-vehicle crashes, rear-end crashes, and angle crashes. The modeling results suggest that a nonlinear functional form may be more appropriate. Also, the results show that it is important to take into consideration the joint safety effects of multiple covariates. Additionally, it is found that the ratio of minor to major-approach AADT has a varying impact on intersection safety and deserves further investigations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling non-linear growth responses to temperature and hydrology in wetland trees

NASA Astrophysics Data System (ADS)

Keim, R.; Allen, S. T.

2016-12-01

Growth responses of wetland trees to flooding and climate variations are difficult to model because they depend on multiple, apparently interacting factors, but are a critical link in hydrological control of wetland carbon budgets. To more generally understand tree growth to hydrological forcing, we modeled non-linear responses of tree ring growth to flooding and climate at sub-annual time steps, using Vaganov-Shashkin response functions. We calibrated the model to six baldcypress tree-ring chronologies from two hydrologically distinct sites in southern Louisiana, and tested several hypotheses of plasticity in wetlands tree responses to interacting environmental variables. The model outperformed traditional multiple linear regression. More importantly, optimized response parameters were generally similar among sites with varying hydrological conditions, suggesting generality to the functions. Model forms that included interacting responses to multiple forcing factors were more effective than were single response functions, indicating the principle of a single limiting factor is not correct in wetlands and both climatic and hydrological variables must be considered in predicting responses to hydrological or climate change.

Multiplicity fluctuation analysis of target residues in nucleus-emulsion collisions at a few hundred MeV/nucleon

NASA Astrophysics Data System (ADS)

Zhang, Dong-Hai; Chen, Yan-Ling; Wang, Guo-Rong; Li, Wang-Dong; Wang, Qing; Yao, Ji-Jie; Zhou, Jian-Guo; Zheng, Su-Hua; Xu, Li-Ling; Miao, Hui-Feng; Wang, Peng

2014-07-01

Multiplicity fluctuation of the target evaporated fragments emitted in 290 MeV/u 12C-AgBr, 400 MeV/u 12C-AgBr, 400 MeV/u 20Ne-AgBr and 500 MeV/u 56Fe-AgBr interactions is investigated using the scaled factorial moment method in two-dimensional normal phase space and cumulative variable space, respectively. It is found that in normal phase space the scaled factorial moment (ln) increases linearly with the increase of the divided number of phase space (lnM)for lower q-value and increases linearly with the increase of lnM, and then becomes saturated or decreased for a higher q-value. In cumulative variable space ln decreases linearly with increase of lnM. This indicates that no evidence of non-statistical multiplicity fluctuation is observed in our data sets. So, any fluctuation indicated in the results of normal variable space analysis is totally caused by the non-uniformity of the single-particle density distribution.

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.

Extending the eigCG algorithm to nonsymmetric Lanczos for linear systems with multiple right-hand sides

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

Abdel-Rehim, A M; Stathopoulos, Andreas; Orginos, Kostas

2014-08-01

The technique that was used to build the EigCG algorithm for sparse symmetric linear systems is extended to the nonsymmetric case using the BiCG algorithm. We show that, similarly to the symmetric case, we can build an algorithm that is capable of computing a few smallest magnitude eigenvalues and their corresponding left and right eigenvectors of a nonsymmetric matrix using only a small window of the BiCG residuals while simultaneously solving a linear system with that matrix. For a system with multiple right-hand sides, we give an algorithm that computes incrementally more eigenvalues while solving the first few systems andmore » then uses the computed eigenvectors to deflate BiCGStab for the remaining systems. Our experiments on various test problems, including Lattice QCD, show the remarkable ability of EigBiCG to compute spectral approximations with accuracy comparable to that of the unrestarted, nonsymmetric Lanczos. Furthermore, our incremental EigBiCG followed by appropriately restarted and deflated BiCGStab provides a competitive method for systems with multiple right-hand sides.« less

An Investigation of the Fit of Linear Regression Models to Data from an SAT[R] Validity Study. Research Report 2011-3

ERIC Educational Resources Information Center

Kobrin, Jennifer L.; Sinharay, Sandip; Haberman, Shelby J.; Chajewski, Michael

2011-01-01

This study examined the adequacy of a multiple linear regression model for predicting first-year college grade point average (FYGPA) using SAT[R] scores and high school grade point average (HSGPA). A variety of techniques, both graphical and statistical, were used to examine if it is possible to improve on the linear regression model. The results…

[Use of multiple regression models in observational studies (1970-2013) and requirements of the STROBE guidelines in Spanish scientific journals].

PubMed

Real, J; Cleries, R; Forné, C; Roso-Llorach, A; Martínez-Sánchez, J M

In medicine and biomedical research, statistical techniques like logistic, linear, Cox and Poisson regression are widely known. The main objective is to describe the evolution of multivariate techniques used in observational studies indexed in PubMed (1970-2013), and to check the requirements of the STROBE guidelines in the author guidelines in Spanish journals indexed in PubMed. A targeted PubMed search was performed to identify papers that used logistic linear Cox and Poisson models. Furthermore, a review was also made of the author guidelines of journals published in Spain and indexed in PubMed and Web of Science. Only 6.1% of the indexed manuscripts included a term related to multivariate analysis, increasing from 0.14% in 1980 to 12.3% in 2013. In 2013, 6.7, 2.5, 3.5, and 0.31% of the manuscripts contained terms related to logistic, linear, Cox and Poisson regression, respectively. On the other hand, 12.8% of journals author guidelines explicitly recommend to follow the STROBE guidelines, and 35.9% recommend the CONSORT guideline. A low percentage of Spanish scientific journals indexed in PubMed include the STROBE statement requirement in the author guidelines. Multivariate regression models in published observational studies such as logistic regression, linear, Cox and Poisson are increasingly used both at international level, as well as in journals published in Spanish. Copyright © 2015 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.

Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control

PubMed Central

Brunton, Steven L.; Brunton, Bingni W.; Proctor, Joshua L.; Kutz, J. Nathan

2016-01-01

In this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system. Dominant terms in the Koopman expansion are typically computed using dynamic mode decomposition (DMD). DMD uses linear measurements of the state variables, and it has recently been shown that this may be too restrictive for nonlinear systems. Choosing the right nonlinear observable functions to form an invariant subspace where it is possible to obtain linear reduced-order models, especially those that are useful for control, is an open challenge. Here, we investigate the choice of observable functions for Koopman analysis that enable the use of optimal linear control techniques on nonlinear problems. First, to include a cost on the state of the system, as in linear quadratic regulator (LQR) control, it is helpful to include these states in the observable subspace, as in DMD. However, we find that this is only possible when there is a single isolated fixed point, as systems with multiple fixed points or more complicated attractors are not globally topologically conjugate to a finite-dimensional linear system, and cannot be represented by a finite-dimensional linear Koopman subspace that includes the state. We then present a data-driven strategy to identify relevant observable functions for Koopman analysis by leveraging a new algorithm to determine relevant terms in a dynamical system by ℓ1-regularized regression of the data in a nonlinear function space; we also show how this algorithm is related to DMD. Finally, we demonstrate the usefulness of nonlinear observable subspaces in the design of Koopman operator optimal control laws for fully nonlinear systems using techniques from linear optimal control. PMID:26919740

Evidence for the Concerted Evolution between Short Linear Protein Motifs and Their Flanking Regions

PubMed Central

Chica, Claudia; Diella, Francesca; Gibson, Toby J.

2009-01-01

Background Linear motifs are short modules of protein sequences that play a crucial role in mediating and regulating many protein–protein interactions. The function of linear motifs strongly depends on the context, e.g. functional instances mainly occur inside flexible regions that are accessible for interaction. Sometimes linear motifs appear as isolated islands of conservation in multiple sequence alignments. However, they also occur in larger blocks of sequence conservation, suggesting an active role for the neighbouring amino acids. Results The evolution of regions flanking 116 functional linear motif instances was studied. The conservation of the amino acid sequence and order/disorder tendency of those regions was related to presence/absence of the instance. For the majority of the analysed instances, the pairs of sequences conserving the linear motif were also observed to maintain a similar local structural tendency and/or to have higher local sequence conservation when compared to pairs of sequences where one is missing the linear motif. Furthermore, those instances have a higher chance to co–evolve with the neighbouring residues in comparison to the distant ones. Those findings are supported by examples where the regulation of the linear motif–mediated interaction has been shown to depend on the modifications (e.g. phosphorylation) at neighbouring positions or is thought to benefit from the binding versatility of disordered regions. Conclusion The results suggest that flanking regions are relevant for linear motif–mediated interactions, both at the structural and sequence level. More interestingly, they indicate that the prediction of linear motif instances can be enriched with contextual information by performing a sequence analysis similar to the one presented here. This can facilitate the understanding of the role of these predicted instances in determining the protein function inside the broader context of the cellular network where they arise. PMID:19584925

Patient decision-making related to antirheumatic drugs in rheumatoid arthritis: the importance of patient trust of physician.

PubMed

Martin, Richard W; Head, Andrew J; René, Jonathan; Swartz, Timothy J; Fiechtner, Justus J; McIntosh, Barbara A; Holmes-Rovner, Margaret

2008-04-01

To explore how rheumatoid arthritis (RA) antirheumatic drug-specific knowledge and numeric literacy, patient trust in physician, and demographic and disease-related factors relate to the confidence of patient decision-making related to disease modifying antirheumatic drugs (DMARD). Data were analyzed from 628 randomly selected patients with RA receiving care in community rheumatology practices, who responded to a multicenter, cross-sectional mail survey. We used multiple regression models to predict patient confidence in DMARD decision-making related to their most recently initiated DMARD. Significant positive correlation was found between confidence in DMARD decision and trust in physician, DMARD-specific knowledge, and disease duration, but not risk-related numeric literacy, sex, or education. Negative correlations were found with disease severity and current bother with DMARD side effects. A multiple linear regression model of confidence in DMARD decision had an overall R = 0.788, R2 = 0.620 (p < 0.001). The 4 dependent variables contributing significantly to the model were female sex, Medicaid insurance status, satisfaction with RA disease control, and trust in physician, with standardized beta = 0.077, -0.089, 0.147, and 0.687, respectively. In this sample of community patients with RA, the patient trust in physician had substantially greater effect on confidence in DMARD decision than DMARD-specific knowledge, disease-related factors, or demographic characteristics.

Quantitative work demands, emotional demands, and cognitive stress symptoms in surgery nurses.

PubMed

Elfering, Achim; Grebner, Simone; Leitner, Monika; Hirschmüller, Anja; Kubosch, Eva Johanna; Baur, Heiner

2017-06-01

In surgery, cognitive stress symptoms, including problems in concentrating, deciding, memorising, and reflecting are risks to patient safety. Recent evidence points to social stressors as antecedents of cognitive stress symptoms in surgery personnel. The current study tests whether cognitive stress symptoms are positively associated with emotional abuse, emotional- and task-related demands and resources in surgery work. Forty-eight surgery nurses from two hospitals filled out the Copenhagen Psychosocial Questionnaire in its German version. Task-related and emotional demands were positively related to cognitive stress symptoms. In a stepwise, multiple, linear regression of cognitive stress symptoms on task-related and emotional demands, emotional abuse and emotional demands were unique predictors (p < .05). Efforts to increase patient safety should address emotional abuse, emotional demands, and, therefore, communication and cooperation team climate in surgery personnel.

Noise limitations in optical linear algebra processors.

PubMed

Batsell, S G; Jong, T L; Walkup, J F; Krile, T F

1990-05-10

A general statistical noise model is presented for optical linear algebra processors. A statistical analysis which includes device noise, the multiplication process, and the addition operation is undertaken. We focus on those processes which are architecturally independent. Finally, experimental results which verify the analytical predictions are also presented.

Binding affinity toward human prion protein of some anti-prion compounds - Assessment based on QSAR modeling, molecular docking and non-parametric ranking.

PubMed

Kovačević, Strahinja; Karadžić, Milica; Podunavac-Kuzmanović, Sanja; Jevrić, Lidija

2018-01-01

The present study is based on the quantitative structure-activity relationship (QSAR) analysis of binding affinity toward human prion protein (huPrP C ) of quinacrine, pyridine dicarbonitrile, diphenylthiazole and diphenyloxazole analogs applying different linear and non-linear chemometric regression techniques, including univariate linear regression, multiple linear regression, partial least squares regression and artificial neural networks. The QSAR analysis distinguished molecular lipophilicity as an important factor that contributes to the binding affinity. Principal component analysis was used in order to reveal similarities or dissimilarities among the studied compounds. The analysis of in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) parameters was conducted. The ranking of the studied analogs on the basis of their ADMET parameters was done applying the sum of ranking differences, as a relatively new chemometric method. The main aim of the study was to reveal the most important molecular features whose changes lead to the changes in the binding affinities of the studied compounds. Another point of view on the binding affinity of the most promising analogs was established by application of molecular docking analysis. The results of the molecular docking were proven to be in agreement with the experimental outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

Emergent properties of interacting populations of spiking neurons.

PubMed

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations.

Increased statistical power with combined independent randomization tests used with multiple-baseline design.

PubMed

Tyrrell, Pascal N; Corey, Paul N; Feldman, Brian M; Silverman, Earl D

2013-06-01

Physicians often assess the effectiveness of treatments on a small number of patients. Multiple-baseline designs (MBDs), based on the Wampold-Worsham (WW) method of randomization and applied to four subjects, have relatively low power. Our objective was to propose another approach with greater power that does not suffer from the time requirements of the WW method applied to a greater number of subjects. The power of a design that involves the combination of two four-subject MBDs was estimated using computer simulation and compared with the four- and eight-subject designs. The effect of a delayed linear response to treatment on the power of the test was also investigated. Power was found to be adequate (>80%) for a standardized mean difference (SMD) greater than 0.8. The effect size associated with 80% power from combined tests was smaller than that of the single four-subject MBD (SMD=1.3) and comparable with the eight-subject MBD (SMD=0.6). A delayed linear response to the treatment resulted in important reductions in power (20-35%). By combining two four-subject MBD tests, an investigator can detect better effect sizes (SMD=0.8) and be able to complete a comparatively timelier and feasible study. Copyright © 2013 Elsevier Inc. All rights reserved.

Uncovering Local Trends in Genetic Effects of Multiple Phenotypes via Functional Linear Models.

PubMed

Vsevolozhskaya, Olga A; Zaykin, Dmitri V; Barondess, David A; Tong, Xiaoren; Jadhav, Sneha; Lu, Qing

2016-04-01

Recent technological advances equipped researchers with capabilities that go beyond traditional genotyping of loci known to be polymorphic in a general population. Genetic sequences of study participants can now be assessed directly. This capability removed technology-driven bias toward scoring predominantly common polymorphisms and let researchers reveal a wealth of rare and sample-specific variants. Although the relative contributions of rare and common polymorphisms to trait variation are being debated, researchers are faced with the need for new statistical tools for simultaneous evaluation of all variants within a region. Several research groups demonstrated flexibility and good statistical power of the functional linear model approach. In this work we extend previous developments to allow inclusion of multiple traits and adjustment for additional covariates. Our functional approach is unique in that it provides a nuanced depiction of effects and interactions for the variables in the model by representing them as curves varying over a genetic region. We demonstrate flexibility and competitive power of our approach by contrasting its performance with commonly used statistical tools and illustrate its potential for discovery and characterization of genetic architecture of complex traits using sequencing data from the Dallas Heart Study. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Effect of processor temperature on film dosimetry

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

Srivastava, Shiv P.; Das, Indra J., E-mail: idas@iupui.edu

2012-07-01

Optical density (OD) of a radiographic film plays an important role in radiation dosimetry, which depends on various parameters, including beam energy, depth, field size, film batch, dose, dose rate, air film interface, postexposure processing time, and temperature of the processor. Most of these parameters have been studied for Kodak XV and extended dose range (EDR) films used in radiation oncology. There is very limited information on processor temperature, which is investigated in this study. Multiple XV and EDR films were exposed in the reference condition (d{sub max.}, 10 Multiplication-Sign 10 cm{sup 2}, 100 cm) to a given dose. Anmore » automatic film processor (X-Omat 5000) was used for processing films. The temperature of the processor was adjusted manually with increasing temperature. At each temperature, a set of films was processed to evaluate OD at a given dose. For both films, OD is a linear function of processor temperature in the range of 29.4-40.6 Degree-Sign C (85-105 Degree-Sign F) for various dose ranges. The changes in processor temperature are directly related to the dose by a quadratic function. A simple linear equation is provided for the changes in OD vs. processor temperature, which could be used for correcting dose in radiation dosimetry when film is used.« less

Nonlinear processing of a multicomponent communication signal by combination-sensitive neurons in the anuran inferior colliculus.

PubMed

Lee, Norman; Schrode, Katrina M; Bee, Mark A

2017-09-01

Diverse animals communicate using multicomponent signals. How a receiver's central nervous system integrates multiple signal components remains largely unknown. We investigated how female green treefrogs (Hyla cinerea) integrate the multiple spectral components present in male advertisement calls. Typical calls have a bimodal spectrum consisting of formant-like low-frequency (~0.9 kHz) and high-frequency (~2.7 kHz) components that are transduced by different sensory organs in the inner ear. In behavioral experiments, only bimodal calls reliably elicited phonotaxis in no-choice tests, and they were selectively chosen over unimodal calls in two-alternative choice tests. Single neurons in the inferior colliculus of awake, passively listening subjects were classified as combination-insensitive units (27.9%) or combination-sensitive units (72.1%) based on patterns of relative responses to the same bimodal and unimodal calls. Combination-insensitive units responded similarly to the bimodal call and one or both unimodal calls. In contrast, combination-sensitive units exhibited both linear responses (i.e., linear summation) and, more commonly, nonlinear responses (e.g., facilitation, compressive summation, or suppression) to the spectral combination in the bimodal call. These results are consistent with the hypothesis that nonlinearities play potentially critical roles in spectral integration and in the neural processing of multicomponent communication signals.

Polarimetric LIDAR with FRI sampling for target characterization

NASA Astrophysics Data System (ADS)

Wijerathna, Erandi; Creusere, Charles D.; Voelz, David; Castorena, Juan

2017-09-01

Polarimetric LIDAR is a significant tool for current remote sensing applications. In addition, measurement of the full waveform of the LIDAR echo provides improved ranging and target discrimination, although, data storage volume in this approach can be problematic. In the work presented here, we investigated the practical issues related to the implementation of a full waveform LIDAR system to identify polarization characteristics of multiple targets within the footprint of the illumination beam. This work was carried out on a laboratory LIDAR testbed that features a flexible arrangement of targets and the ability to change the target polarization characteristics. Targets with different retardance characteristics were illuminated with a linearly polarized laser beam and the return pulse intensities were analyzed by rotating a linear analyzer polarizer in front of a high-speed detector. Additionally, we explored the applicability and the limitations of applying a sparse sampling approach based on Finite Rate of Innovations (FRI) to compress and recover the characteristic parameters of the pulses reflected from the targets. The pulse parameter values extracted by the FRI analysis were accurate and we successfully distinguished the polarimetric characteristics and the range of multiple targets at different depths within the same beam footprint. We also demonstrated the recovery of an unknown target retardance value from the echoes by applying a Mueller matrix system model.

Response of dissolved trace metals to land use/land cover and their source apportionment using a receptor model in a subtropic river, China.

PubMed

Li, Siyue; Zhang, Quanfa

2011-06-15

Water samples were collected for determination of dissolved trace metals in 56 sampling sites throughout the upper Han River, China. Multivariate statistical analyses including correlation analysis, stepwise multiple linear regression models, and principal component and factor analysis (PCA/FA) were employed to examine the land use influences on trace metals, and a receptor model of factor analysis-multiple linear regression (FA-MLR) was used for source identification/apportionment of anthropogenic heavy metals in the surface water of the River. Our results revealed that land use was an important factor in water metals in the snow melt flow period and land use in the riparian zone was not a better predictor of metals than land use away from the river. Urbanization in a watershed and vegetation along river networks could better explain metals, and agriculture, regardless of its relative location, however slightly explained metal variables in the upper Han River. FA-MLR analysis identified five source types of metals, and mining, fossil fuel combustion, and vehicle exhaust were the dominant pollutions in the surface waters. The results demonstrated great impacts of human activities on metal concentrations in the subtropical river of China. Copyright © 2011 Elsevier B.V. All rights reserved.

Estimation of the quantification uncertainty from flow injection and liquid chromatography transient signals in inductively coupled plasma mass spectrometry

NASA Astrophysics Data System (ADS)

Laborda, Francisco; Medrano, Jesús; Castillo, Juan R.

2004-06-01

The quality of the quantitative results obtained from transient signals in high-performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICPMS) and flow injection-inductively coupled plasma mass spectrometry (FI-ICPMS) was investigated under multielement conditions. Quantification methods were based on multiple-point calibration by simple and weighted linear regression, and double-point calibration (measurement of the baseline and one standard). An uncertainty model, which includes the main sources of uncertainty from FI-ICPMS and HPLC-ICPMS (signal measurement, sample flow rate and injection volume), was developed to estimate peak area uncertainties and statistical weights used in weighted linear regression. The behaviour of the ICPMS instrument was characterized in order to be considered in the model, concluding that the instrument works as a concentration detector when it is used to monitorize transient signals from flow injection or chromatographic separations. Proper quantification by the three calibration methods was achieved when compared to reference materials, although the double-point calibration allowed to obtain results of the same quality as the multiple-point calibration, shortening the calibration time. Relative expanded uncertainties ranged from 10-20% for concentrations around the LOQ to 5% for concentrations higher than 100 times the LOQ.

Changes in aerobic power of men, ages 25-70 yr

NASA Technical Reports Server (NTRS)

Jackson, A. S.; Beard, E. F.; Wier, L. T.; Ross, R. M.; Stuteville, J. E.; Blair, S. N.

1995-01-01

This study quantified and compared the cross-sectional and longitudinal influence of age, self-report physical activity (SR-PA), and body composition (%fat) on the decline of maximal aerobic power (VO2peak). The cross-sectional sample consisted of 1,499 healthy men ages 25-70 yr. The 156 men of the longitudinal sample were from the same population and examined twice, the mean time between tests was 4.1 (+/- 1.2) yr. Peak oxygen uptake was determined by indirect calorimetry during a maximal treadmill exercise test. The zero-order correlations between VO2peak and %fat (r = -0.62) and SR-PA (r = 0.58) were significantly (P < 0.05) higher that the age correlation (r = -0.45). Linear regression defined the cross-sectional age-related decline in VO2peak at 0.46 ml.kg-1.min-1.yr-1. Multiple regression analysis (R = 0.79) showed that nearly 50% of this cross-sectional decline was due to %fat and SR-PA, adding these lifestyle variables to the multiple regression model reduced the age regression weight to -0.26 ml.kg-1.min-1.yr-1. Statistically controlling for time differences between tests, general linear models analysis showed that longitudinal changes in aerobic power were due to independent changes in %fat and SR-PA, confirming the cross-sectional results.

Dusty Pair Plasma—Wave Propagation and Diffusive Transition of Oscillations

NASA Astrophysics Data System (ADS)

Atamaniuk, Barbara; Turski, Andrzej J.

2011-11-01

The crucial point of the paper is the relation between equilibrium distributions of plasma species and the type of propagation or diffusive transition of plasma response to a disturbance. The paper contains a unified treatment of disturbance propagation (transport) in the linearized Vlasov electron-positron and fullerene pair plasmas containing charged dust impurities, based on the space-time convolution integral equations. Electron-positron-dust/ion (e-p-d/i) plasmas are rather widespread in nature. Space-time responses of multi-component linearized Vlasov plasmas on the basis of multiple integral equations are invoked. An initial-value problem for Vlasov-Poisson/Ampère equations is reduced to the one multiple integral equation and the solution is expressed in terms of forcing function and its space-time convolution with the resolvent kernel. The forcing function is responsible for the initial disturbance and the resolvent is responsible for the equilibrium velocity distributions of plasma species. By use of resolvent equations, time-reversibility, space-reflexivity and the other symmetries are revealed. The symmetries carry on physical properties of Vlasov pair plasmas, e.g., conservation laws. Properly choosing equilibrium distributions for dusty pair plasmas, we can reduce the resolvent equation to: (i) the undamped dispersive wave equations, (ii) and diffusive transport equations of oscillations.

Emergent Properties of Interacting Populations of Spiking Neurons

PubMed Central

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations. PMID:22207844

Exploring the efficacy of replacing linear paper-based patient cases in problem-based learning with dynamic Web-based virtual patients: randomized controlled trial.

PubMed

Poulton, Terry; Ellaway, Rachel H; Round, Jonathan; Jivram, Trupti; Kavia, Sheetal; Hilton, Sean

2014-11-05

Problem-based learning (PBL) is well established in medical education and beyond, and continues to be developed and explored. Challenges include how to connect the somewhat abstract nature of classroom-based PBL with clinical practice and how to maintain learner engagement in the process of PBL over time. A study was conducted to investigate the efficacy of decision-PBL (D-PBL), a variant form of PBL that replaces linear PBL cases with virtual patients. These Web-based interactive cases provided learners with a series of patient management pathways. Learners were encouraged to consider and discuss courses of action, take their chosen management pathway, and experience the consequences of their decisions. A Web-based application was essential to allow scenarios to respond dynamically to learners' decisions, to deliver the scenarios to multiple PBL classrooms in the same timeframe, and to record centrally the paths taken by the PBL groups. A randomized controlled trial in crossover design was run involving all learners (N=81) in the second year of the graduate entry stream for the undergraduate medicine program at St George's University of London. Learners were randomized to study groups; half engaged in a D-PBL activity whereas the other half had a traditional linear PBL activity on the same subject material. Groups alternated D-PBL and linear PBL over the semester. The measure was mean cohort performance on specific face-to-face exam questions at the end of the semester. D-PBL groups performed better than linear PBL groups on questions related to D-PBL with the difference being statistically significant for all questions. Differences between the exam performances of the 2 groups were not statistically significant for the questions not related to D-PBL. The effect sizes for D-PBL-related questions were large and positive (>0.6) except for 1 question that showed a medium positive effect size. The effect sizes for questions not related to D-PBL were all small (≤0.3) with a mix of positive and negative values. The efficacy of D-PBL was indicated by improved exam performance for learners who had D-PBL compared to those who had linear PBL. This suggests that the use of D-PBL leads to better midterm learning outcomes than linear PBL, at least for learners with prior experience with linear PBL. On the basis of tutor and student feedback, St George's University of London and the University of Nicosia, Cyprus have replaced paper PBL cases for midstage undergraduate teaching with D-PBL virtual patients, and 6 more institutions in the ePBLnet partnership will be implementing D-PBL in Autumn 2015.

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.

The Influence of Cochlear Mechanical Dysfunction, Temporal Processing Deficits, and Age on the Intelligibility of Audible Speech in Noise for Hearing-Impaired Listeners

PubMed Central

Johannesen, Peter T.; Pérez-González, Patricia; Kalluri, Sridhar; Blanco, José L.

2016-01-01

The aim of this study was to assess the relative importance of cochlear mechanical dysfunction, temporal processing deficits, and age on the ability of hearing-impaired listeners to understand speech in noisy backgrounds. Sixty-eight listeners took part in the study. They were provided with linear, frequency-specific amplification to compensate for their audiometric losses, and intelligibility was assessed for speech-shaped noise (SSN) and a time-reversed two-talker masker (R2TM). Behavioral estimates of cochlear gain loss and residual compression were available from a previous study and were used as indicators of cochlear mechanical dysfunction. Temporal processing abilities were assessed using frequency modulation detection thresholds. Age, audiometric thresholds, and the difference between audiometric threshold and cochlear gain loss were also included in the analyses. Stepwise multiple linear regression models were used to assess the relative importance of the various factors for intelligibility. Results showed that (a) cochlear gain loss was unrelated to intelligibility, (b) residual cochlear compression was related to intelligibility in SSN but not in a R2TM, (c) temporal processing was strongly related to intelligibility in a R2TM and much less so in SSN, and (d) age per se impaired intelligibility. In summary, all factors affected intelligibility, but their relative importance varied across maskers. PMID:27604779

Spatial feature tracking impedence sensor using multiple electric fields

DOEpatents

Novak, J.L.

1998-08-11

Linear and other features on a workpiece are tracked by measuring the fields generated between electrodes arrayed in pairs. One electrode in each pair operates as a transmitter and the other as a receiver, and both electrodes in a pair are arrayed on a carrier. By combining and subtracting fields between electrodes in one pair and between a transmitting electrode in one pair and a receiving electrode in another pair, information describing the location and orientation of the sensor relative to the workpiece in up to six degrees of freedom may be obtained. Typical applications will measure capacitance, but other impedance components may be measured as well. The sensor is designed to track a linear feature axis or a protrusion or pocket in a workpiece. Seams and ridges can be tracked by this non-contact sensor. The sensor output is useful for robotic applications. 10 figs.

Linear-algebraic bath transformation for simulating complex open quantum systems

DOE PAGES

Huh, Joonsuk; Mostame, Sarah; Fujita, Takatoshi; ...

2014-12-02

In studying open quantum systems, the environment is often approximated as a collection of non-interacting harmonic oscillators, a configuration also known as the star-bath model. It is also well known that the star-bath can be transformed into a nearest-neighbor interacting chain of oscillators. The chain-bath model has been widely used in renormalization group approaches. The transformation can be obtained by recursion relations or orthogonal polynomials. Based on a simple linear algebraic approach, we propose a bath partition strategy to reduce the system-bath coupling strength. As a result, the non-interacting star-bath is transformed into a set of weakly coupled multiple parallelmore » chains. Furthermore, the transformed bath model allows complex problems to be practically implemented on quantum simulators, and it can also be employed in various numerical simulations of open quantum dynamics.« less

Differential Measurement Periodontal Structures Mapping System

NASA Technical Reports Server (NTRS)

Companion, John A. (Inventor)

1998-01-01

This invention relates to a periodontal structure mapping system employing a dental handpiece containing first and second acoustic sensors for locating the Cemento-Enamel Junction (CEJ) and measuring the differential depth between the CEJ and the bottom of the periodontal pocket. Measurements are taken at multiple locations on each tooth of a patient, observed, analyzed by an optical analysis subsystem, and archived by a data storage system for subsequent study and comparison with previous and subsequent measurements. Ultrasonic transducers for the first and second acoustic sensors are contained within the handpiece and in connection with a control computer. Pressurized water is provided for the depth measurement sensor and a linearly movable probe sensor serves as the sensor for the CEJ finder. The linear movement of the CEJ sensor is obtained by a control computer actuated by the prober. In an alternate embodiment, the CEJ probe is an optical fiber sensor with appropriate analysis structure provided therefor.

Spatial feature tracking impedence sensor using multiple electric fields

DOEpatents

Novak, James L.

1998-01-01

Linear and other features on a workpiece are tracked by measuring the fields generated between electrodes arrayed in pairs. One electrode in each pair operates as a transmitter and the other as a receiver, and both electrodes in a pair are arrayed on a carrier. By combining and subtracting fields between electrodes in one pair and between a transmitting electrode in one pair and a receiving electrode in another pair, information describing the location and orientation of the sensor relative to the workpiece in up to six degrees of freedom may be obtained. Typical applications will measure capacitance, but other impedance components may be measured as well. The sensor is designed to track a linear feature axis or a protrusion or pocket in a workpiece. Seams and ridges can be tracked by this non-contact sensor. The sensor output is useful for robotic applications.

Linear finite-difference bond graph model of an ionic polymer actuator

NASA Astrophysics Data System (ADS)

Bentefrit, M.; Grondel, S.; Soyer, C.; Fannir, A.; Cattan, E.; Madden, J. D.; Nguyen, T. M. G.; Plesse, C.; Vidal, F.

2017-09-01

With the recent growing interest for soft actuation, many new types of ionic polymers working in air have been developed. Due to the interrelated mechanical, electrical, and chemical properties which greatly influence the characteristics of such actuators, their behavior is complex and difficult to understand, predict and optimize. In light of this challenge, an original linear multiphysics finite difference bond graph model was derived to characterize this ionic actuation. This finite difference scheme was divided into two coupled subparts, each related to a specific physical, electrochemical or mechanical domain, and then converted into a bond graph model as this language is particularly suited for systems from multiple energy domains. Simulations were then conducted and a good agreement with the experimental results was obtained. Furthermore, an analysis of the power efficiency of such actuators as a function of space and time was proposed and allowed to evaluate their performance.

Shared dosimetry error in epidemiological dose-response analyses

DOE PAGES

Stram, Daniel O.; Preston, Dale L.; Sokolnikov, Mikhail; ...

2015-03-23

Radiation dose reconstruction systems for large-scale epidemiological studies are sophisticated both in providing estimates of dose and in representing dosimetry uncertainty. For example, a computer program was used by the Hanford Thyroid Disease Study to provide 100 realizations of possible dose to study participants. The variation in realizations reflected the range of possible dose for each cohort member consistent with the data on dose determinates in the cohort. Another example is the Mayak Worker Dosimetry System 2013 which estimates both external and internal exposures and provides multiple realizations of "possible" dose history to workers given dose determinants. This paper takesmore » up the problem of dealing with complex dosimetry systems that provide multiple realizations of dose in an epidemiologic analysis. In this paper we derive expected scores and the information matrix for a model used widely in radiation epidemiology, namely the linear excess relative risk (ERR) model that allows for a linear dose response (risk in relation to radiation) and distinguishes between modifiers of background rates and of the excess risk due to exposure. We show that treating the mean dose for each individual (calculated by averaging over the realizations) as if it was true dose (ignoring both shared and unshared dosimetry errors) gives asymptotically unbiased estimates (i.e. the score has expectation zero) and valid tests of the null hypothesis that the ERR slope β is zero. Although the score is unbiased the information matrix (and hence the standard errors of the estimate of β) is biased for β≠0 when ignoring errors in dose estimates, and we show how to adjust the information matrix to remove this bias, using the multiple realizations of dose. The use of these methods in the context of several studies including, the Mayak Worker Cohort, and the U.S. Atomic Veterans Study, is discussed.« less

A trait-based framework for stream algal communities.

PubMed

Lange, Katharina; Townsend, Colin Richard; Matthaei, Christoph David

2016-01-01

The use of trait-based approaches to detect effects of land use and climate change on terrestrial plant and aquatic phytoplankton communities is increasing, but such a framework is still needed for benthic stream algae. Here we present a conceptual framework of morphological, physiological, behavioural and life-history traits relating to resource acquisition and resistance to disturbance. We tested this approach by assessing the relationships between multiple anthropogenic stressors and algal traits at 43 stream sites. Our "natural experiment" was conducted along gradients of agricultural land-use intensity (0-95% of the catchment in high-producing pasture) and hydrological alteration (0-92% streamflow reduction resulting from water abstraction for irrigation) as well as related physicochemical variables (total nitrogen concentration and deposited fine sediment). Strategic choice of study sites meant that agricultural intensity and hydrological alteration were uncorrelated. We studied the relationships of seven traits (with 23 trait categories) to our environmental predictor variables using general linear models and an information-theoretic model-selection approach. Life form, nitrogen fixation and spore formation were key traits that showed the strongest relationships with environmental stressors. Overall, FI (farming intensity) exerted stronger effects on algal communities than hydrological alteration. The large-bodied, non-attached, filamentous algae that dominated under high farming intensities have limited dispersal abilities but may cope with unfavourable conditions through the formation of spores. Antagonistic interactions between FI and flow reduction were observed for some trait variables, whereas no interactions occurred for nitrogen concentration and fine sediment. Our conceptual framework was well supported by tests of ten specific hypotheses predicting effects of resource supply and disturbance on algal traits. Our study also shows that investigating a fairly comprehensive set of traits can help shed light on the drivers of algal community composition in situations where multiple stressors are operating. Further, to understand non-linear and non-additive effects of such drivers, communities need to be studied along multiple gradients of natural variation or anthropogenic stressors.

Vector Adaptive/Predictive Encoding Of Speech

NASA Technical Reports Server (NTRS)

Chen, Juin-Hwey; Gersho, Allen

1989-01-01

Vector adaptive/predictive technique for digital encoding of speech signals yields decoded speech of very good quality after transmission at coding rate of 9.6 kb/s and of reasonably good quality at 4.8 kb/s. Requires 3 to 4 million multiplications and additions per second. Combines advantages of adaptive/predictive coding, and code-excited linear prediction, yielding speech of high quality but requires 600 million multiplications and additions per second at encoding rate of 4.8 kb/s. Vector adaptive/predictive coding technique bridges gaps in performance and complexity between adaptive/predictive coding and code-excited linear prediction.

Estimation of perceptible water vapor of atmosphere using artificial neural network, support vector machine and multiple linear regression algorithm and their comparative study

NASA Astrophysics Data System (ADS)

Shastri, Niket; Pathak, Kamlesh

2018-05-01

The water vapor content in atmosphere plays very important role in climate. In this paper the application of GPS signal in meteorology is discussed, which is useful technique that is used to estimate the perceptible water vapor of atmosphere. In this paper various algorithms like artificial neural network, support vector machine and multiple linear regression are use to predict perceptible water vapor. The comparative studies in terms of root mean square error and mean absolute errors are also carried out for all the algorithms.

Accelerating the weighted histogram analysis method by direct inversion in the iterative subspace.

PubMed

Zhang, Cheng; Lai, Chun-Liang; Pettitt, B Montgomery

The weighted histogram analysis method (WHAM) for free energy calculations is a valuable tool to produce free energy differences with the minimal errors. Given multiple simulations, WHAM obtains from the distribution overlaps the optimal statistical estimator of the density of states, from which the free energy differences can be computed. The WHAM equations are often solved by an iterative procedure. In this work, we use a well-known linear algebra algorithm which allows for more rapid convergence to the solution. We find that the computational complexity of the iterative solution to WHAM and the closely-related multiple Bennett acceptance ratio (MBAR) method can be improved by using the method of direct inversion in the iterative subspace. We give examples from a lattice model, a simple liquid and an aqueous protein solution.

Dynamic characteristics of a multi-wavelength Brillouin-Raman fiber laser assisted by multiple four-wave mixing processes in a ring cavity

NASA Astrophysics Data System (ADS)

Shirazi, M. R.; Mohamed Taib, J.; De La Rue, R. M.; Harun, S. W.; Ahmad, H.

2015-03-01

Dynamic characteristics of a multi-wavelength Brillouin-Raman fiber laser (MBRFL) assisted by four-wave mixing have been investigated through the development of Stokes and anti-Stokes lines under different combinations of Brillouin and Raman pump power levels and different Raman pumping schemes in a ring cavity. For a Stokes line of order higher than three, the threshold power was less than the saturation power of its last-order Stokes line. By increasing the Brillouin pump power, the nth order anti-Stokes and the (n+4)th order Stokes power levels were unexpectedly increased almost the same before the Stokes line threshold power. It was also found out that the SBS threshold reduction (SBSTR) depended linearly on the gain factor for the 1st and 2nd Stokes lines, as the first set. This relation for the 3rd and 4th Stokes lines as the second set, however, was almost linear with the same slope before SBSTR -6 dB, then, it approached to the linear relation in the first set when the gain factor was increased to 50 dB. Therefore, the threshold power levels of Stokes lines for a given Raman gain can be readily estimated only by knowing the threshold power levels in which there is no Raman amplification.

Assessment of Unconstrained Cerebrovascular Reactivity Marker for Large Age-Range fMRI Studies

PubMed Central

Kannurpatti, Sridhar S.; Motes, Michael A.; Biswal, Bharat B.; Rypma, Bart

2014-01-01

Breath hold (BH), a commonly used task to measure cerebrovascular reactivity (CVR) in fMRI studies varies in outcome among individuals due to subject-physiology and/or BH-inspiration/expiration differences (i.e., performance). In prior age-related fMRI studies, smaller task-related BOLD response variability is observed among younger than older individuals. Also, a linear CVR versus task relationship exists in younger individuals which maybe useful to test the accuracy of CVR responses in older groups. Hence we hypothesized that subject-related physiological and/or BH differences, if present, may compromise CVR versus task linearity in older individuals. To test the hypothesis, empirical BH versus task relationships from motor and cognitive areas were obtained in younger (mean age = 26 years) and older (mean age = 58 years) human subjects. BH versus task linearity was observed only in the younger group, confirming our hypothesis. Further analysis indicated BH responses and its variability to be similar in both younger and older groups, suggesting that BH may not accurately represent CVR in a large age range. Using the resting state fluctuation of amplitude (RSFA) as an unconstrained alternative to BH, subject-wise correspondence between BH and RSFA was tested. Correlation between BH versus RSFA was significant within the motor but was not significant in the cognitive areas in the younger and was completely disrupted in both areas in the older subjects indicating that BH responses are constrained by subject-related physiology and/or performance-related differences. Contrasting BH to task, RSFA-task relationships were independent of age accompanied by age-related increases in CVR variability as measured by RSFA, not observed with BH. Together the results obtained indicate that RSFA accurately represents CVR in any age range avoiding multiple and yet unknown physiologic and task-related pitfalls of BH. PMID:24551151

MABE multibeam accelerator

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

Hasti, D.E.; Ramirez, J.J.; Coleman, P.D.

1985-01-01

The Megamp Accelerator and Beam Experiment (MABE) was the technology development testbed for the multiple beam, linear induction accelerator approach for Hermes III, a new 20 MeV, 0.8 MA, 40 ns accelerator being developed at Sandia for gamma-ray simulation. Experimental studies of a high-current, single-beam accelerator (8 MeV, 80 kA), and a nine-beam injector (1.4 MeV, 25 kA/beam) have been completed, and experiments on a nine-beam linear induction accelerator are in progress. A two-beam linear induction accelerator is designed and will be built as a gamma-ray simulator to be used in parallel with Hermes III. The MABE pulsed power systemmore » and accelerator for the multiple beam experiments is described. Results from these experiments and the two-beam design are discussed. 11 refs., 6 figs.« less

A multiple linear regression analysis of hot corrosion attack on a series of nickel base turbine alloys

NASA Technical Reports Server (NTRS)

Barrett, C. A.

1985-01-01

Multiple linear regression analysis was used to determine an equation for estimating hot corrosion attack for a series of Ni base cast turbine alloys. The U transform (i.e., 1/sin (% A/100) to the 1/2) was shown to give the best estimate of the dependent variable, y. A complete second degree equation is described for the centered" weight chemistries for the elements Cr, Al, Ti, Mo, W, Cb, Ta, and Co. In addition linear terms for the minor elements C, B, and Zr were added for a basic 47 term equation. The best reduced equation was determined by the stepwise selection method with essentially 13 terms. The Cr term was found to be the most important accounting for 60 percent of the explained variability hot corrosion attack.

Simultaneous multiple non-crossing quantile regression estimation using kernel constraints

PubMed Central

Liu, Yufeng; Wu, Yichao

2011-01-01

Quantile regression (QR) is a very useful statistical tool for learning the relationship between the response variable and covariates. For many applications, one often needs to estimate multiple conditional quantile functions of the response variable given covariates. Although one can estimate multiple quantiles separately, it is of great interest to estimate them simultaneously. One advantage of simultaneous estimation is that multiple quantiles can share strength among them to gain better estimation accuracy than individually estimated quantile functions. Another important advantage of joint estimation is the feasibility of incorporating simultaneous non-crossing constraints of QR functions. In this paper, we propose a new kernel-based multiple QR estimation technique, namely simultaneous non-crossing quantile regression (SNQR). We use kernel representations for QR functions and apply constraints on the kernel coefficients to avoid crossing. Both unregularised and regularised SNQR techniques are considered. Asymptotic properties such as asymptotic normality of linear SNQR and oracle properties of the sparse linear SNQR are developed. Our numerical results demonstrate the competitive performance of our SNQR over the original individual QR estimation. PMID:22190842

Identifying the Factors That Influence Change in SEBD Using Logistic Regression Analysis

ERIC Educational Resources Information Center

Camilleri, Liberato; Cefai, Carmel

2013-01-01

Multiple linear regression and ANOVA models are widely used in applications since they provide effective statistical tools for assessing the relationship between a continuous dependent variable and several predictors. However these models rely heavily on linearity and normality assumptions and they do not accommodate categorical dependent…

Quantitative structure-activity relationship of the curcumin-related compounds using various regression methods

NASA Astrophysics Data System (ADS)

Khazaei, Ardeshir; Sarmasti, Negin; Seyf, Jaber Yousefi

2016-03-01

Quantitative structure activity relationship were used to study a series of curcumin-related compounds with inhibitory effect on prostate cancer PC-3 cells, pancreas cancer Panc-1 cells, and colon cancer HT-29 cells. Sphere exclusion method was used to split data set in two categories of train and test set. Multiple linear regression, principal component regression and partial least squares were used as the regression methods. In other hand, to investigate the effect of feature selection methods, stepwise, Genetic algorithm, and simulated annealing were used. In two cases (PC-3 cells and Panc-1 cells), the best models were generated by a combination of multiple linear regression and stepwise (PC-3 cells: r2 = 0.86, q2 = 0.82, pred_r2 = 0.93, and r2m (test) = 0.43, Panc-1 cells: r2 = 0.85, q2 = 0.80, pred_r2 = 0.71, and r2m (test) = 0.68). For the HT-29 cells, principal component regression with stepwise (r2 = 0.69, q2 = 0.62, pred_r2 = 0.54, and r2m (test) = 0.41) is the best method. The QSAR study reveals descriptors which have crucial role in the inhibitory property of curcumin-like compounds. 6ChainCount, T_C_C_1, and T_O_O_7 are the most important descriptors that have the greatest effect. With a specific end goal to design and optimization of novel efficient curcumin-related compounds it is useful to introduce heteroatoms such as nitrogen, oxygen, and sulfur atoms in the chemical structure (reduce the contribution of T_C_C_1 descriptor) and increase the contribution of 6ChainCount and T_O_O_7 descriptors. Models can be useful in the better design of some novel curcumin-related compounds that can be used in the treatment of prostate, pancreas, and colon cancers.

SU-E-T-110: Development of An Independent, Monte Carlo, Dose Calculation, Quality Assurance Tool for Clinical Trials

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

Faught, A; University of Texas Health Science Center Houston, Graduate School of Biomedical Sciences, Houston, TX; Davidson, S

2014-06-01

Purpose: To develop a comprehensive end-to-end test for Varian's TrueBeam linear accelerator for head and neck IMRT using a custom phantom designed to utilize multiple dosimetry devices. Purpose: To commission a multiple-source Monte Carlo model of Elekta linear accelerator beams of nominal energies 6MV and 10MV. Methods: A three source, Monte Carlo model of Elekta 6 and 10MV therapeutic x-ray beams was developed. Energy spectra of two photon sources corresponding to primary photons created in the target and scattered photons originating in the linear accelerator head were determined by an optimization process that fit the relative fluence of 0.25 MeVmore » energy bins to the product of Fatigue-Life and Fermi functions to match calculated percent depth dose (PDD) data with that measured in a water tank for a 10x10cm2 field. Off-axis effects were modeled by a 3rd degree polynomial used to describe the off-axis half-value layer as a function of off-axis angle and fitting the off-axis fluence to a piecewise linear function to match calculated dose profiles with measured dose profiles for a 40×40cm2 field. The model was validated by comparing calculated PDDs and dose profiles for field sizes ranging from 3×3cm2 to 30×30cm2 to those obtained from measurements. A benchmarking study compared calculated data to measurements for IMRT plans delivered to anthropomorphic phantoms. Results: Along the central axis of the beam 99.6% and 99.7% of all data passed the 2%/2mm gamma criterion for 6 and 10MV models, respectively. Dose profiles at depths of dmax, through 25cm agreed with measured data for 99.4% and 99.6% of data tested for 6 and 10MV models, respectively. A comparison of calculated dose to film measurement in a head and neck phantom showed an average of 85.3% and 90.5% of pixels passing a 3%/2mm gamma criterion for 6 and 10MV models respectively. Conclusion: A Monte Carlo multiple-source model for Elekta 6 and 10MV therapeutic x-ray beams has been developed as a quality assurance tool for clinical trials.« less

Forecasting daily patient volumes in the emergency department.

PubMed

Jones, Spencer S; Thomas, Alun; Evans, R Scott; Welch, Shari J; Haug, Peter J; Snow, Gregory L

2008-02-01

Shifts in the supply of and demand for emergency department (ED) resources make the efficient allocation of ED resources increasingly important. Forecasting is a vital activity that guides decision-making in many areas of economic, industrial, and scientific planning, but has gained little traction in the health care industry. There are few studies that explore the use of forecasting methods to predict patient volumes in the ED. The goals of this study are to explore and evaluate the use of several statistical forecasting methods to predict daily ED patient volumes at three diverse hospital EDs and to compare the accuracy of these methods to the accuracy of a previously proposed forecasting method. Daily patient arrivals at three hospital EDs were collected for the period January 1, 2005, through March 31, 2007. The authors evaluated the use of seasonal autoregressive integrated moving average, time series regression, exponential smoothing, and artificial neural network models to forecast daily patient volumes at each facility. Forecasts were made for horizons ranging from 1 to 30 days in advance. The forecast accuracy achieved by the various forecasting methods was compared to the forecast accuracy achieved when using a benchmark forecasting method already available in the emergency medicine literature. All time series methods considered in this analysis provided improved in-sample model goodness of fit. However, post-sample analysis revealed that time series regression models that augment linear regression models by accounting for serial autocorrelation offered only small improvements in terms of post-sample forecast accuracy, relative to multiple linear regression models, while seasonal autoregressive integrated moving average, exponential smoothing, and artificial neural network forecasting models did not provide consistently accurate forecasts of daily ED volumes. This study confirms the widely held belief that daily demand for ED services is characterized by seasonal and weekly patterns. The authors compared several time series forecasting methods to a benchmark multiple linear regression model. The results suggest that the existing methodology proposed in the literature, multiple linear regression based on calendar variables, is a reasonable approach to forecasting daily patient volumes in the ED. However, the authors conclude that regression-based models that incorporate calendar variables, account for site-specific special-day effects, and allow for residual autocorrelation provide a more appropriate, informative, and consistently accurate approach to forecasting daily ED patient volumes.

Assessment of triglyceride and cholesterol in overweight people based on multiple linear regression and artificial intelligence model.

PubMed

Ma, Jing; Yu, Jiong; Hao, Guangshu; Wang, Dan; Sun, Yanni; Lu, Jianxin; Cao, Hongcui; Lin, Feiyan

2017-02-20

The prevalence of high hyperlipemia is increasing around the world. Our aims are to analyze the relationship of triglyceride (TG) and cholesterol (TC) with indexes of liver function and kidney function, and to develop a prediction model of TG, TC in overweight people. A total of 302 adult healthy subjects and 273 overweight subjects were enrolled in this study. The levels of fasting indexes of TG (fs-TG), TC (fs-TC), blood glucose, liver function, and kidney function were measured and analyzed by correlation analysis and multiple linear regression (MRL). The back propagation artificial neural network (BP-ANN) was applied to develop prediction models of fs-TG and fs-TC. The results showed there was significant difference in biochemical indexes between healthy people and overweight people. The correlation analysis showed fs-TG was related to weight, height, blood glucose, and indexes of liver and kidney function; while fs-TC was correlated with age, indexes of liver function (P < 0.01). The MRL analysis indicated regression equations of fs-TG and fs-TC both had statistic significant (P < 0.01) when included independent indexes. The BP-ANN model of fs-TG reached training goal at 59 epoch, while fs-TC model achieved high prediction accuracy after training 1000 epoch. In conclusions, there was high relationship of fs-TG and fs-TC with weight, height, age, blood glucose, indexes of liver function and kidney function. Based on related variables, the indexes of fs-TG and fs-TC can be predicted by BP-ANN models in overweight people.

An increase in visceral fat is associated with a decrease in the taste and olfactory capacity

PubMed Central

Fernandez-Garcia, Jose Carlos; Alcaide, Juan; Santiago-Fernandez, Concepcion; Roca-Rodriguez, MM.; Aguera, Zaida; Baños, Rosa; Botella, Cristina; de la Torre, Rafael; Fernandez-Real, Jose M.; Fruhbeck, Gema; Gomez-Ambrosi, Javier; Jimenez-Murcia, Susana; Menchon, Jose M.; Casanueva, Felipe F.; Fernandez-Aranda, Fernando; Tinahones, Francisco J.; Garrido-Sanchez, Lourdes

2017-01-01

Introduction Sensory factors may play an important role in the determination of appetite and food choices. Also, some adipokines may alter or predict the perception and pleasantness of specific odors. We aimed to analyze differences in smell–taste capacity between females with different weights and relate them with fat and fat-free mass, visceral fat, and several adipokines. Materials and methods 179 females with different weights (from low weight to morbid obesity) were studied. We analyzed the relation between fat, fat-free mass, visceral fat (indirectly estimated by bioelectrical impedance analysis with visceral fat rating (VFR)), leptin, adiponectin and visfatin. The smell and taste assessments were performed through the "Sniffin’ Sticks" and "Taste Strips" respectively. Results We found a lower score in the measurement of smell (TDI-score (Threshold, Discrimination and Identification)) in obese subjects. All the olfactory functions measured, such as threshold, discrimination, identification and the TDI-score, correlated negatively with age, body mass index (BMI), leptin, fat mass, fat-free mass and VFR. In a multiple linear regression model, VFR mainly predicted the TDI-score. With regard to the taste function measurements, the normal weight subjects showed a higher score of taste functions. However a tendency to decrease was observed in the groups with greater or lesser BMI. In a multiple linear regression model VFR and age mainly predicted the total taste scores. Discussion We show for the first time that a reverse relationship exists between visceral fat and sensory signals, such as smell and taste, across a population with different body weight conditions. PMID:28158237

Household Food Insecurity is Associated with Health-Related Quality of Life in Rural Type 2 Diabetic Patients.

PubMed

Gholami, Ali; Khazaee-Pool, Maryam; Rezaee, Negar; Amirkalali, Bahareh; A Bbasi Ghahremanlo, Abbas; Moradpour, Farhad; Rajabi, Abdolalhalim; Sohrabi, Masoud Reza; Yarmohammadi, Reyhaneh; Mousavi Jahromi, Zahra

2017-06-01

Health-related quality of life (HRQOL) is associated with household food insecurity (HFI). However, the studies examining the relationship between HFI and HRQOL in patients with type 2 diabetes are scarce. Thus, this study was designed to examine the relationship between HFI and HRQOL in rural type 2 diabetic patients. In this cross-sectional study, we included 1847 rural patients with type 2 diabetes in Neyshabur from April to July 2012. HRQOL and HFI were measured with 36-item HRQOL (SF-36) and 6-item version of Household Food Security questionnaires, respectively. HRQOL was divided into eight dimensions and two summary components. We categorized households as high food secure (HFS), low food secure (LFS), and very low food secure (VLFS). Multiple linear regression model was applied to assess the independent effect of food insecurity on HRQOL. The mean age of participants was 59.65 ± 12.3 years (range: 30-97) with 69.8% women. The overall prevalence of HFI was 46.1%, and the total mean score of HRQOL was 51.11. Multiple linear regression model showed that HFI was significantly associated with the total mean score of HRQOL and its eight dimensions. One-way ANOVA test also showed that HRQOL (in all dimensions) was significantly different between 3 groups of household food security status (HFS, LFS, and VLFS) (P < 0.05). The results of this study showed that HFI was associated with all dimensions of HRQOL and it is one of the strongest variables, in association with HRQOL among rural patients with type 2 diabetes.

Does body image perception relate to quality of life in middle-aged women?

PubMed Central

Medeiros de Morais, Maria Socorro; Vieira, Mariana Carmem Apolinário; Moreira, Mayle Andrade; da Câmara, Saionara Maria Aires; Campos Cavalcanti Maciel, Álvaro; Almeida, Maria das Graças

2017-01-01

Objective In Brazil, information about the influence of body image on the various life domains of women in menopausal transition is scarce. Thus, the objective of the study was to analyze the relationship between body image and quality of life in middle-aged Brazilian women. Methods This was a cross-sectional study of 250 women between 40 and 65 years old, living in Parnamirim/RN, Brazil, who were evaluated in relation to body image and quality of life. For body image, women were classified as: dissatisfied due to low weight, satisfied (with their body weight) and dissatisfied due to being overweight. Quality of life was assessed through a questionnaire in which higher values indicate higher quality of life. Multiple linear regression was performed to analyze the relationship between body image and quality of life, adjusted for covariates that presented p<0.20 in the bivariate analysis. Results The average age was 52.1 (± 5.6) years, 82% of the women reported being dissatisfied due to being overweight, and 4.4% were dissatisfied due to having low weight. After multiple linear regression analyzes, body image remained associated with health (p<0.001), emotional (p = 0.016), and sexual (p = 0.048) domains of quality of life, as well as total score of the questionnaire (p<0.001). Conclusion Women who reported being dissatisfied with their body image due to having low weight or overweight had worse quality of life in comparison to those who were satisfied (with their body weight). PMID:28926575

On Performance of Linear Multiuser Detectors for Wireless Multimedia Applications

NASA Astrophysics Data System (ADS)

Agarwal, Rekha; Reddy, B. V. R.; Bindu, E.; Nayak, Pinki

In this paper, performance of different multi-rate schemes in DS-CDMA system is evaluated. The analysis of multirate linear multiuser detectors with multiprocessing gain is analyzed for synchronous Code Division Multiple Access (CDMA) systems. Variable data rate is achieved by varying the processing gain. Our conclusion is that bit error rate for multirate and single rate systems can be made same with a tradeoff with number of users in linear multiuser detectors.

Sampled-Data Kalman Filtering and Multiple Model Adaptive Estimation for Infinite-Dimensional Continuous-Time Systems

DTIC Science & Technology

2007-03-01

mathematical frame- 1-6 work of linear algebra and functional analysis [122, 33], while Kalman-Bucy filtering [96, 32] is an especially important...Engineering, Air Force Institute of Technology (AU), Wright- Patterson AFB, Ohio, March 2002. 85. Hoffman, Kenneth and Ray Kunze. Linear Algebra (Second Edition...Engineering, Air Force Institute of Technology (AU), Wright- Patterson AFB, Ohio, December 1989. 189. Strang, Gilbert. Linear Algebra and Its Applications

Analysis of the Multiple-Solution Response of a Flexible Rotor Supported on Non-Linear Squeeze Film Dampers

NASA Astrophysics Data System (ADS)

ZHU, C. S.; ROBB, D. A.; EWINS, D. J.

2002-05-01

The multiple-solution response of rotors supported on squeeze film dampers is a typical non-linear phenomenon. The behaviour of the multiple-solution response in a flexible rotor supported on two identical squeeze film dampers with centralizing springs is studied by three methods: synchronous circular centred-orbit motion solution, numerical integration method and slow acceleration method using the assumption of a short bearing and cavitated oil film; the differences of computational results obtained by the three different methods are compared in this paper. It is shown that there are three basic forms for the multiple-solution response in the flexible rotor system supported on the squeeze film dampers, which are the resonant, isolated bifurcation and swallowtail bifurcation multiple solutions. In the multiple-solution speed regions, the rotor motion may be subsynchronous, super-subsynchronous, almost-periodic and even chaotic, besides synchronous circular centred, even if the gravity effect is not considered. The assumption of synchronous circular centred-orbit motion for the journal and rotor around the static deflection line can be used only in some special cases; the steady state numerical integration method is very useful, but time consuming. Using the slow acceleration method, not only can the multiple-solution speed regions be detected, but also the non-synchronous response regions.

Spinal cord atrophy in anterior-posterior direction reflects impairment in multiple sclerosis.

PubMed

Lundell, H; Svolgaard, O; Dogonowski, A-M; Romme Christensen, J; Selleberg, F; Soelberg Sørensen, P; Blinkenberg, M; Siebner, H R; Garde, E

2017-10-01

To investigate how atrophy is distributed over the cross section of the upper cervical spinal cord and how this relates to functional impairment in multiple sclerosis (MS). We analysed the structural brain MRI scans of 54 patients with relapsing-remitting MS (n=22), primary progressive MS (n=9), secondary progressive MS (n=23) and 23 age- and sex-matched healthy controls. We measured the cross-sectional area (CSA), left-right width (LRW) and anterior-posterior width (APW) of the spinal cord at the segmental level C2. We tested for a nonparametric linear relationship between these atrophy measures and clinical impairments as reflected by the Expanded Disability Status Scale (EDSS) and Multiple Sclerosis Impairment Scale (MSIS). In patients with MS, CSA and APW but not LRW were reduced compared to healthy controls (P<.02) and showed significant correlations with EDSS, MSIS and specific MSIS subscores. In patients with MS, atrophy of the upper cervical cord is most evident in the antero-posterior direction. As APW of the cervical cord can be readily derived from standard structural MRI of the brain, APW constitutes a clinically useful neuroimaging marker of disease-related neurodegeneration in MS. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Linear precoding based on polynomial expansion: reducing complexity in massive MIMO.

PubMed

Mueller, Axel; Kammoun, Abla; Björnson, Emil; Debbah, Mérouane

Massive multiple-input multiple-output (MIMO) techniques have the potential to bring tremendous improvements in spectral efficiency to future communication systems. Counterintuitively, the practical issues of having uncertain channel knowledge, high propagation losses, and implementing optimal non-linear precoding are solved more or less automatically by enlarging system dimensions. However, the computational precoding complexity grows with the system dimensions. For example, the close-to-optimal and relatively "antenna-efficient" regularized zero-forcing (RZF) precoding is very complicated to implement in practice, since it requires fast inversions of large matrices in every coherence period. Motivated by the high performance of RZF, we propose to replace the matrix inversion and multiplication by a truncated polynomial expansion (TPE), thereby obtaining the new TPE precoding scheme which is more suitable for real-time hardware implementation and significantly reduces the delay to the first transmitted symbol. The degree of the matrix polynomial can be adapted to the available hardware resources and enables smooth transition between simple maximum ratio transmission and more advanced RZF. By deriving new random matrix results, we obtain a deterministic expression for the asymptotic signal-to-interference-and-noise ratio (SINR) achieved by TPE precoding in massive MIMO systems. Furthermore, we provide a closed-form expression for the polynomial coefficients that maximizes this SINR. To maintain a fixed per-user rate loss as compared to RZF, the polynomial degree does not need to scale with the system, but it should be increased with the quality of the channel knowledge and the signal-to-noise ratio.

An analytical approach to reduce between-plate variation in multiplex assays that measure antibodies to Plasmodium falciparum antigens.

PubMed

Fang, Rui; Wey, Andrew; Bobbili, Naveen K; Leke, Rose F G; Taylor, Diane Wallace; Chen, John J

2017-07-17

Antibodies play an important role in immunity to malaria. Recent studies show that antibodies to multiple antigens, as well as, the overall breadth of the response are associated with protection from malaria. Yet, the variability and reliability of antibody measurements against a combination of malarial antigens using multiplex assays have not been well characterized. A normalization procedure for reducing between-plate variation using replicates of pooled positive and negative controls was investigated. Sixty test samples (30 from malaria-positive and 30 malaria-negative individuals), together with five pooled positive-controls and two pooled negative-controls, were screened for antibody levels to 9 malarial antigens, including merozoite antigens (AMA1, EBA175, MSP1, MSP2, MSP3, MSP11, Pf41), sporozoite CSP, and pregnancy-associated VAR2CSA. The antibody levels were measured in triplicate on each of 3 plates, and the experiments were replicated on two different days by the same technician. The performance of the proposed normalization procedure was evaluated with the pooled controls for the test samples on both the linear and natural-log scales. Compared with data on the linear scale, the natural-log transformed data were less skewed and reduced the mean-variance relationship. The proposed normalization procedure using pooled controls on the natural-log scale significantly reduced between-plate variation. For malaria-related research that measure antibodies to multiple antigens with multiplex assays, the natural-log transformation is recommended for data analysis and use of the normalization procedure with multiple pooled controls can improve the precision of antibody measurements.

Multiple monolithic fiber solid-phase microextraction based on a polymeric ionic liquid with high-performance liquid chromatography for the determination of steroid sex hormones in water and urine.

PubMed

Liao, Keren; Mei, Meng; Li, Haonan; Huang, Xiaojia; Wu, Cuiqin

2016-02-01

The development of a simple and sensitive analytical approach that combines multiple monolithic fiber solid-phase microextraction with liquid desorption followed by high-performance liquid chromatography with diode array detection is proposed for the determination of trace levels of seven steroid sex hormones (estriol, 17β-estradiol, testosterone, ethinylestradiol, estrone, progesterone and mestranol) in water and urine matrices. To extract the target analytes effectively, multiple monolithic fiber solid-phase microextraction based on a polymeric ionic liquid was used to concentrate hormones. Several key extraction parameters including desorption solvent, extraction and desorption time, pH value and ionic strength in sample matrix were investigated in detail. Under the optimal experimental conditions, the limits of detection were found to be in the range of 0.027-0.12 μg/L. The linear range was 0.10-200 μg/L for 17β-estradiol, 0.25-200 μg/L estriol, ethinylestradiol and estrone, and 0.50-200 μg/L for the other hormones. Satisfactory linearities were achieved for analytes with the correlation coefficients above 0.99. Acceptable method reproducibility was achieved by evaluating the repeatability and intermediate precision with relative standard deviations of both less than 8%. The enrichment factors ranged from 54- to 74-fold. Finally, the proposed method was successfully applied to the analysis of steroid sex hormones in environmental water samples and human urines with spiking recoveries ranged from 75.6 to 116%. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multiple scales and phases in discrete chains with application to folded proteins

NASA Astrophysics Data System (ADS)

Sinelnikova, A.; Niemi, A. J.; Nilsson, Johan; Ulybyshev, M.

2018-05-01

Chiral heteropolymers such as large globular proteins can simultaneously support multiple length scales. The interplay between the different scales brings about conformational diversity, determines the phase properties of the polymer chain, and governs the structure of the energy landscape. Most importantly, multiple scales produce complex dynamics that enable proteins to sustain live matter. However, at the moment there is incomplete understanding of how to identify and distinguish the various scales that determine the structure and dynamics of a complex protein. Here we address this impending problem. We develop a methodology with the potential to systematically identify different length scales, in the general case of a linear polymer chain. For this we introduce and analyze the properties of an order parameter that can both reveal the presence of different length scales and can also probe the phase structure. We first develop our concepts in the case of chiral homopolymers. We introduce a variant of Kadanoff's block-spin transformation to coarse grain piecewise linear chains, such as the C α backbone of a protein. We derive analytically, and then verify numerically, a number of properties that the order parameter can display, in the case of a chiral polymer chain. In particular, we propose that in the case of a chiral heteropolymer the order parameter can reveal traits of several different phases, contingent on the length scale at which it is scrutinized. We confirm that this is the case with crystallographic protein structures in the Protein Data Bank. Thus our results suggest relations between the scales, the phases, and the complexity of folding pathways.

gsSKAT: Rapid gene set analysis and multiple testing correction for rare-variant association studies using weighted linear kernels.

PubMed

Larson, Nicholas B; McDonnell, Shannon; Cannon Albright, Lisa; Teerlink, Craig; Stanford, Janet; Ostrander, Elaine A; Isaacs, William B; Xu, Jianfeng; Cooney, Kathleen A; Lange, Ethan; Schleutker, Johanna; Carpten, John D; Powell, Isaac; Bailey-Wilson, Joan E; Cussenot, Olivier; Cancel-Tassin, Geraldine; Giles, Graham G; MacInnis, Robert J; Maier, Christiane; Whittemore, Alice S; Hsieh, Chih-Lin; Wiklund, Fredrik; Catalona, William J; Foulkes, William; Mandal, Diptasri; Eeles, Rosalind; Kote-Jarai, Zsofia; Ackerman, Michael J; Olson, Timothy M; Klein, Christopher J; Thibodeau, Stephen N; Schaid, Daniel J

2017-05-01

Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results. © 2017 WILEY PERIODICALS, INC.

Family bonding and adolescent alcohol use: moderating effect of living with excessive drinking parents.

PubMed

Kuendig, Hervé; Kuntsche, Emmanuel

2006-01-01

Excessive parental drinking has been shown to be positively related to adolescent alcohol use and family bonding negatively related. The aim of the present study was to determine if the perception of parental drinking moderates the relationship between family bonding and adolescent alcohol use. Linear structural equation models for multiple group comparisons were estimated based on a national representative sample of 3,448 eight and ninth graders in Switzerland (mean age 14.77; SD 0.89). Adjusted for gender and age, the results confirm that strong family bonds were negatively related to both frequency of alcohol intake and lifetime frequency of drunkenness. Furthermore, a positive link was found with regard to the perception of parental drinking. However, the multiple group comparison revealed that the negative relationship between bonding and adolescent alcohol use was even stronger among adolescents whose parents drink excessively than among those whose parents did not. These results indicate that it may be particularly important for parents in the former category to establish strong family bonds (e.g. by spending free time with their children, listening to their worries) so as to limit adolescent excessive drinking.

Modification of the USLE K factor for soil erodibility assessment on calcareous soils in Iran

NASA Astrophysics Data System (ADS)

Ostovari, Yaser; Ghorbani-Dashtaki, Shoja; Bahrami, Hossein-Ali; Naderi, Mehdi; Dematte, Jose Alexandre M.; Kerry, Ruth

2016-11-01

The measurement of soil erodibility (K) in the field is tedious, time-consuming and expensive; therefore, its prediction through pedotransfer functions (PTFs) could be far less costly and time-consuming. The aim of this study was to develop new PTFs to estimate the K factor using multiple linear regression, Mamdani fuzzy inference systems, and artificial neural networks. For this purpose, K was measured in 40 erosion plots with natural rainfall. Various soil properties including the soil particle size distribution, calcium carbonate equivalent, organic matter, permeability, and wet-aggregate stability were measured. The results showed that the mean measured K was 0.014 t h MJ- 1 mm- 1 and 2.08 times less than the estimated mean K (0.030 t h MJ- 1 mm- 1) using the USLE model. Permeability, wet-aggregate stability, very fine sand, and calcium carbonate were selected as independent variables by forward stepwise regression in order to assess the ability of multiple linear regression, Mamdani fuzzy inference systems and artificial neural networks to predict K. The calcium carbonate equivalent, which is not accounted for in the USLE model, had a significant impact on K in multiple linear regression due to its strong influence on the stability of aggregates and soil permeability. Statistical indices in validation and calibration datasets determined that the artificial neural networks method with the highest R2, lowest RMSE, and lowest ME was the best model for estimating the K factor. A strong correlation (R2 = 0.81, n = 40, p < 0.05) between the estimated K from multiple linear regression and measured K indicates that the use of calcium carbonate equivalent as a predictor variable gives a better estimation of K in areas with calcareous soils.

Spatial summation revealed in the earliest visual evoked component C1 and the effect of attention on its linearity.

PubMed

Chen, Juan; Yu, Qing; Zhu, Ziyun; Peng, Yujia; Fang, Fang

2016-01-01

In natural scenes, multiple objects are usually presented simultaneously. How do specific areas of the brain respond to multiple objects based on their responses to each individual object? Previous functional magnetic resonance imaging (fMRI) studies have shown that the activity induced by a multiobject stimulus in the primary visual cortex (V1) can be predicted by the linear or nonlinear sum of the activities induced by its component objects. However, there has been little evidence from electroencephelogram (EEG) studies so far. Here we explored how V1 responded to multiple objects by comparing the EEG signals evoked by a three-grating stimulus with those evoked by its two components (the central grating and 2 flanking gratings). We focused on the earliest visual component C1 (onset latency of ∼50 ms) because it has been shown to reflect the feedforward responses of neurons in V1. We found that when the stimulus was unattended, the amplitude of the C1 evoked by the three-grating stimulus roughly equaled the sum of the amplitudes of the C1s evoked by its two components, regardless of the distances between these gratings. When the stimulus was attended, this linear spatial summation existed only when the three gratings were far apart from each other. When the three gratings were close to each other, the spatial summation became compressed. These results suggest that the earliest visual responses in V1 follow a linear summation rule when attention is not involved and that attention can affect the earliest interactions between multiple objects. Copyright © 2016 the American Physiological Society.

Construction of multiple linear regression models using blood biomarkers for selecting against abdominal fat traits in broilers.

PubMed

Dong, J Q; Zhang, X Y; Wang, S Z; Jiang, X F; Zhang, K; Ma, G W; Wu, M Q; Li, H; Zhang, H

2018-01-01

Plasma very low-density lipoprotein (VLDL) can be used to select for low body fat or abdominal fat (AF) in broilers, but its correlation with AF is limited. We investigated whether any other biochemical indicator can be used in combination with VLDL for a better selective effect. Nineteen plasma biochemical indicators were measured in male chickens from the Northeast Agricultural University broiler lines divergently selected for AF content (NEAUHLF) in the fed state at 46 and 48 d of age. The average concentration of every parameter for the 2 d was used for statistical analysis. Levels of these 19 plasma biochemical parameters were compared between the lean and fat lines. The phenotypic correlations between these plasma biochemical indicators and AF traits were analyzed. Then, multiple linear regression models were constructed to select the best model used for selecting against AF content. and the heritabilities of plasma indicators contained in the best models were estimated. The results showed that 11 plasma biochemical indicators (triglycerides, total bile acid, total protein, globulin, albumin/globulin, aspartate transaminase, alanine transaminase, gamma-glutamyl transpeptidase, uric acid, creatinine, and VLDL) differed significantly between the lean and fat lines (P < 0.01), and correlated significantly with AF traits (P < 0.05). The best multiple linear regression models based on albumin/globulin, VLDL, triglycerides, globulin, total bile acid, and uric acid, had higher R2 (0.73) than the model based only on VLDL (0.21). The plasma parameters included in the best models had moderate heritability estimates (0.21 ≤ h2 ≤ 0.43). These results indicate that these multiple linear regression models can be used to select for lean broiler chickens. © 2017 Poultry Science Association Inc.

De-noising of 3D multiple-coil MR images using modified LMMSE estimator.

PubMed

Yaghoobi, Nima; Hasanzadeh, Reza P R

2018-06-20

De-noising is a crucial topic in Magnetic Resonance Imaging (MRI) which focuses on less loss of Magnetic Resonance (MR) image information and details preservation during the noise suppression. Nowadays multiple-coil MRI system is preferred to single one due to its acceleration in the imaging process. Due to the fact that the model of noise in single-coil and multiple-coil MRI systems are different, the de-noising methods that mostly are adapted to single-coil MRI systems, do not work appropriately with multiple-coil one. The model of noise in single-coil MRI systems is Rician while in multiple-coil one (if no subsampling occurs in k-space or GRAPPA reconstruction process is being done in the coils), it obeys noncentral Chi (nc-χ). In this paper, a new filtering method based on the Linear Minimum Mean Square Error (LMMSE) estimator is proposed for multiple-coil MR Images ruined by nc-χ noise. In the presented method, to have an optimum similarity selection of voxels, the Bayesian Mean Square Error (BMSE) criterion is used and proved for nc-χ noise model and also a nonlocal voxel selection methodology is proposed for nc-χ distribution. The results illustrate robust and accurate performance compared to the related state-of-the-art methods, either on ideal nc-χ images or GRAPPA reconstructed ones. Copyright © 2018. Published by Elsevier Inc.

Fuzzy neural network technique for system state forecasting.

PubMed

Li, Dezhi; Wang, Wilson; Ismail, Fathy

2013-10-01

In many system state forecasting applications, the prediction is performed based on multiple datasets, each corresponding to a distinct system condition. The traditional methods dealing with multiple datasets (e.g., vector autoregressive moving average models and neural networks) have some shortcomings, such as limited modeling capability and opaque reasoning operations. To tackle these problems, a novel fuzzy neural network (FNN) is proposed in this paper to effectively extract information from multiple datasets, so as to improve forecasting accuracy. The proposed predictor consists of both autoregressive (AR) nodes modeling and nonlinear nodes modeling; AR models/nodes are used to capture the linear correlation of the datasets, and the nonlinear correlation of the datasets are modeled with nonlinear neuron nodes. A novel particle swarm technique [i.e., Laplace particle swarm (LPS) method] is proposed to facilitate parameters estimation of the predictor and improve modeling accuracy. The effectiveness of the developed FNN predictor and the associated LPS method is verified by a series of tests related to Mackey-Glass data forecast, exchange rate data prediction, and gear system prognosis. Test results show that the developed FNN predictor and the LPS method can capture the dynamics of multiple datasets effectively and track system characteristics accurately.

Regional variability among nonlinear chlorophyll-phosphorus relationships in lakes

USGS Publications Warehouse

Filstrup, Christopher T.; Wagner, Tyler; Soranno, Patricia A.; Stanley, Emily H.; Stow, Craig A.; Webster, Katherine E.; Downing, John A.

2014-01-01

The relationship between chlorophyll a (Chl a) and total phosphorus (TP) is a fundamental relationship in lakes that reflects multiple aspects of ecosystem function and is also used in the regulation and management of inland waters. The exact form of this relationship has substantial implications on its meaning and its use. We assembled a spatially extensive data set to examine whether nonlinear models are a better fit for Chl a—TP relationships than traditional log-linear models, whether there were regional differences in the form of the relationships, and, if so, which regional factors were related to these differences. We analyzed a data set from 2105 temperate lakes across 35 ecoregions by fitting and comparing two different nonlinear models and one log-linear model. The two nonlinear models fit the data better than the log-linear model. In addition, the parameters for the best-fitting model varied among regions: the maximum and lower Chl aasymptotes were positively and negatively related to percent regional pasture land use, respectively, and the rate at which chlorophyll increased with TP was negatively related to percent regional wetland cover. Lakes in regions with more pasture fields had higher maximum chlorophyll concentrations at high TP concentrations but lower minimum chlorophyll concentrations at low TP concentrations. Lakes in regions with less wetland cover showed a steeper Chl a—TP relationship than wetland-rich regions. Interpretation of Chl a—TP relationships depends on regional differences, and theory and management based on a monolithic relationship may be inaccurate.

Food addiction, orthorexia, and food-related stress among dietetics students.

PubMed

Grammatikopoulou, Maria G; Gkiouras, Konstantinos; Markaki, Anastasia; Theodoridis, Xenophon; Tsakiri, Vasiliki; Mavridis, Pantelis; Dardavessis, Theodore; Chourdakis, Michael

2018-05-19

Health sciences, and in particular Nutrition and Dietetics students, have been shown to exhibit an increased prevalence of disordered eating. The aim of the present cross-sectional study was to evaluate other specified feeding and eating disorders (OSFEDs), including stress-related eating, food addiction, and orthorexia, in relation to the dietary intake, among nutrition/dietetics students. A total of 176 undergraduate students from a Department of Nutrition and Dietetics, in Greece, participated in the study. Dietary intake was recorded, and the prevalence of Eating and Appraisal Due to Emotion and Stress (EADES), food addiction (with the modified Yale Food Addition scale mYFAS), and orthorexia were assessed. Chi-square and t tests were performed between sexes, orthorexic and non-orthorexic students, as well as between food-addicted and non-addicted participants. Multiple linear regression analysis assessed relationships between energy intake, BMI or waist circumference, and the food-related psychometric scales. Among participating students, 4.5% had food addiction and 68.2% demonstrated orthorexia. No differences were observed between men and women, concerning the prevalence of food addiction and orthorexia, the sum of mYFAS symptoms, or individual EADES factors. Orthorexic students exhibited increased BMI, reduced energy, and saturated fat intake. In addition, orthorexic men consumed more vegetables. Multiple linear regression analysis revealed that orthorexic behavior was associated with increased BMI, waist circumference and energy intake. Lower BMI was associated with increasing ability to cope with emotion-and-stress-related eating and increasing appraisal of ability and resources to cope with emotions and stress. Emotion-and-stress-related eating was negatively associated with BMI. Appraisal of ability and resources to cope with emotions and stress was associated with the energy intake. Finally, age was positively correlated with the appraisal of outside stressors/influences, indicating increased ability to cope with outside stressors among older students. The study shows that despite the suggested interventions, the problem of OSFEDs among nutrition and dietetics students is still valid. Regular screening, counseling, and education is needed to reduce its prevalence. Level V, cross-sectional descriptive study.

A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation

PubMed Central

Nam, Haewon

2017-01-01

We propose a novel metal artifact reduction (MAR) algorithm for CT images that completes a corrupted sinogram along the metal trace region. When metal implants are located inside a field of view, they create a barrier to the transmitted X-ray beam due to the high attenuation of metals, which significantly degrades the image quality. To fill in the metal trace region efficiently, the proposed algorithm uses multiple prior images with residual error compensation in sinogram space. Multiple prior images are generated by applying a recursive active contour (RAC) segmentation algorithm to the pre-corrected image acquired by MAR with linear interpolation, where the number of prior image is controlled by RAC depending on the object complexity. A sinogram basis is then acquired by forward projection of the prior images. The metal trace region of the original sinogram is replaced by the linearly combined sinogram of the prior images. Then, the additional correction in the metal trace region is performed to compensate the residual errors occurred by non-ideal data acquisition condition. The performance of the proposed MAR algorithm is compared with MAR with linear interpolation and the normalized MAR algorithm using simulated and experimental data. The results show that the proposed algorithm outperforms other MAR algorithms, especially when the object is complex with multiple bone objects. PMID:28604794

Evolutionary tree design: An exploratory study of the influence of linear versus branching format on visitors' interpretation and understanding across age groups

NASA Astrophysics Data System (ADS)

MacDonald, Teresa Elise

This exploratory study sought to investigate the influence of tree graphic design---specifically linear versus branching depictions of taxa---on visitors in three different age groups (aged 11-13, 14-18, adults) interpretation and understanding using a multiple-case study strategy. The findings from this research indicate that linear and branched depictions elicit qualitatively different narratives and explanations about the relationships between the taxa in all age groups. Branched tree graphics support scientifically appropriate explanations of evolutionary relationships, i.e. that taxa are related via shared or common ancestry; while linear representations reinforce intuitive interpretations of ancestor-descendant or anagenic relationships. Furthermore, differences in the language used for linear and branched trees suggests that there is a spectrum within an analogy of developmental change that is thought to serve as a transitional concept between intuitive and scientific understanding--with 'evolved from' for branched depictions of taxa representing a shift towards an interpretation of shared ancestry rather than an individual transformation from one thing into another. In addition, branched graphics appear to support the correct reading and interpretation of shared or common ancestry in tree diagrams. Mixed reasoning was common and overall reasoning patterns were broadly similar among participants in all age groups, however, older youth (aged 14 to 18) and adults often provided more detail in their explanations and sometimes included references to evolutionary ideas such as variation, inheritance and selection.

Computational Modeling of Micro-Crack Induced Attenuation in CFRP Composites

NASA Technical Reports Server (NTRS)

Roberts, R. A.; Leckey, C. A. C.

2012-01-01

A computational study is performed to determine the contribution to ultrasound attenuation in carbon fiber reinforced polymer composite laminates of linear elastic scattering by matrix micro-cracking. Multiple scattering approximations are benchmarked against exact computational approaches. Results support linear scattering as the source of observed increased attenuation in the presence of micro-cracking.

Avoiding Communication in Dense Linear Algebra

DTIC Science & Technology

2013-08-16

Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1.1 Asymptotic Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . 6...and parallelizing Strassen’s matrix multiplication algorithm (Chapter 11). 6 Chapter 2 Preliminaries 2.1 Notation and Definitions In this section we...between computations and algo- rithms). The following definition is based on [56]: Definition 2.1. A classical algorithm in linear algebra is one that

Re-Mediating Classroom Activity with a Non-Linear, Multi-Display Presentation Tool

ERIC Educational Resources Information Center

Bligh, Brett; Coyle, Do

2013-01-01

This paper uses an Activity Theory framework to evaluate the use of a novel, multi-screen, non-linear presentation tool. The Thunder tool allows presenters to manipulate and annotate multiple digital slides and to concurrently display a selection of juxtaposed resources across a wall-sized projection area. Conventional, single screen presentation…

Secret Message Decryption: Group Consulting Projects Using Matrices and Linear Programming

ERIC Educational Resources Information Center

Gurski, Katharine F.

2009-01-01

We describe two short group projects for finite mathematics students that incorporate matrices and linear programming into fictional consulting requests presented as a letter to the students. The students are required to use mathematics to decrypt secret messages in one project involving matrix multiplication and inversion. The second project…

Timber management planning with timber ram and goal programming

Treesearch

Richard C. Field

1978-01-01

By using goal programming to enhance the linear programming of Timber RAM, multiple decision criteria were incorporated in the timber management planning of a National Forest in the southeastern United States. Combining linear and goal programming capitalizes on the advantages of the two techniques and produces operationally feasible solutions. This enhancement may...

An Introduction to Multilinear Formula Score Theory. Measurement Series 84-4.

ERIC Educational Resources Information Center

Levine, Michael V.

Formula score theory (FST) associates each multiple choice test with a linear operator and expresses all of the real functions of item response theory as linear combinations of the operator's eigenfunctions. Hard measurement problems can then often be reformulated as easier, standard mathematical problems. For example, the problem of estimating…

Possible limits of plasma linear colliders

NASA Astrophysics Data System (ADS)

Zimmermann, F.

2017-07-01

Plasma linear colliders have been proposed as next or next-next generation energy-frontier machines for high-energy physics. I investigate possible fundamental limits on energy and luminosity of such type of colliders, considering acceleration, multiple scattering off plasma ions, intrabeam scattering, bremsstrahlung, and betatron radiation. The question of energy efficiency is also addressed.

Renormalizability of the gradient flow in the 2D O(N) non-linear sigma model

NASA Astrophysics Data System (ADS)

Makino, Hiroki; Suzuki, Hiroshi

2015-03-01

It is known that the gauge field and its composite operators evolved by the Yang-Mills gradient flow are ultraviolet (UV) finite without any multiplicative wave function renormalization. In this paper, we prove that the gradient flow in the 2D O(N) non-linear sigma model possesses a similar property: The flowed N-vector field and its composite operators are UV finite without multiplicative wave function renormalization. Our proof in all orders of perturbation theory uses a (2+1)-dimensional field theoretical representation of the gradient flow, which possesses local gauge invariance without gauge field. As an application of the UV finiteness of the gradient flow, we construct the energy-momentum tensor in the lattice formulation of the O(N) non-linear sigma model that automatically restores the correct normalization and the conservation law in the continuum limit.

Using directed information for influence discovery in interconnected dynamical systems

NASA Astrophysics Data System (ADS)

Rao, Arvind; Hero, Alfred O.; States, David J.; Engel, James Douglas

2008-08-01

Structure discovery in non-linear dynamical systems is an important and challenging problem that arises in various applications such as computational neuroscience, econometrics, and biological network discovery. Each of these systems have multiple interacting variables and the key problem is the inference of the underlying structure of the systems (which variables are connected to which others) based on the output observations (such as multiple time trajectories of the variables). Since such applications demand the inference of directed relationships among variables in these non-linear systems, current methods that have a linear assumption on structure or yield undirected variable dependencies are insufficient. Hence, in this work, we present a methodology for structure discovery using an information-theoretic metric called directed time information (DTI). Using both synthetic dynamical systems as well as true biological datasets (kidney development and T-cell data), we demonstrate the utility of DTI in such problems.

Focal points and principal solutions of linear Hamiltonian systems revisited

NASA Astrophysics Data System (ADS)

Šepitka, Peter; Šimon Hilscher, Roman

2018-05-01

In this paper we present a novel view on the principal (and antiprincipal) solutions of linear Hamiltonian systems, as well as on the focal points of their conjoined bases. We present a new and unified theory of principal (and antiprincipal) solutions at a finite point and at infinity, and apply it to obtain new representation of the multiplicities of right and left proper focal points of conjoined bases. We show that these multiplicities can be characterized by the abnormality of the system in a neighborhood of the given point and by the rank of the associated T-matrix from the theory of principal (and antiprincipal) solutions. We also derive some additional important results concerning the representation of T-matrices and associated normalized conjoined bases. The results in this paper are new even for completely controllable linear Hamiltonian systems. We also discuss other potential applications of our main results, in particular in the singular Sturmian theory.

On optimal control of linear systems in the presence of multiplicative noise

NASA Technical Reports Server (NTRS)

Joshi, S. M.

1976-01-01

This correspondence considers the problem of optimal regulator design for discrete time linear systems subjected to white state-dependent and control-dependent noise in addition to additive white noise in the input and the observations. A pseudo-deterministic problem is first defined in which multiplicative and additive input disturbances are present, but noise-free measurements of the complete state vector are available. This problem is solved via discrete dynamic programming. Next is formulated the problem in which the number of measurements is less than that of the state variables and the measurements are contaminated with state-dependent noise. The inseparability of control and estimation is brought into focus, and an 'enforced separation' solution is obtained via heuristic reasoning in which the control gains are shown to be the same as those in the pseudo-deterministic problem. An optimal linear state estimator is given in order to implement the controller.

Fault detection for singular switched linear systems with multiple time-varying delay in finite frequency domain

NASA Astrophysics Data System (ADS)

Zhai, Ding; Lu, Anyang; Li, Jinghao; Zhang, Qingling

2016-10-01

This paper deals with the problem of the fault detection (FD) for continuous-time singular switched linear systems with multiple time-varying delay. In this paper, the actuator fault is considered. Besides, the systems faults and unknown disturbances are assumed in known frequency domains. Some finite frequency performance indices are initially introduced to design the switched FD filters which ensure that the filtering augmented systems under switching signal with average dwell time are exponentially admissible and guarantee the fault input sensitivity and disturbance robustness. By developing generalised Kalman-Yakubovic-Popov lemma and using Parseval's theorem and Fourier transform, finite frequency delay-dependent sufficient conditions for the existence of such a filter which can guarantee the finite-frequency H- and H∞ performance are derived and formulated in terms of linear matrix inequalities. Four examples are provided to illustrate the effectiveness of the proposed finite frequency method.

Multiple time scale analysis of pressure oscillations in solid rocket motors

NASA Astrophysics Data System (ADS)

Ahmed, Waqas; Maqsood, Adnan; Riaz, Rizwan

2018-03-01

In this study, acoustic pressure oscillations for single and coupled longitudinal acoustic modes in Solid Rocket Motor (SRM) are investigated using Multiple Time Scales (MTS) method. Two independent time scales are introduced. The oscillations occur on fast time scale whereas the amplitude and phase changes on slow time scale. Hopf bifurcation is employed to investigate the properties of the solution. The supercritical bifurcation phenomenon is observed for linearly unstable system. The amplitude of the oscillations result from equal energy gain and loss rates of longitudinal acoustic modes. The effect of linear instability and frequency of longitudinal modes on amplitude and phase of oscillations are determined for both single and coupled modes. For both cases, the maximum amplitude of oscillations decreases with the frequency of acoustic mode and linear instability of SRM. The comparison of analytical MTS results and numerical simulations demonstrate an excellent agreement.

Multiple concurrent recursive least squares identification with application to on-line spacecraft mass-property identification

NASA Technical Reports Server (NTRS)

Wilson, Edward (Inventor)

2006-01-01

The present invention is a method for identifying unknown parameters in a system having a set of governing equations describing its behavior that cannot be put into regression form with the unknown parameters linearly represented. In this method, the vector of unknown parameters is segmented into a plurality of groups where each individual group of unknown parameters may be isolated linearly by manipulation of said equations. Multiple concurrent and independent recursive least squares identification of each said group run, treating other unknown parameters appearing in their regression equation as if they were known perfectly, with said values provided by recursive least squares estimation from the other groups, thereby enabling the use of fast, compact, efficient linear algorithms to solve problems that would otherwise require nonlinear solution approaches. This invention is presented with application to identification of mass and thruster properties for a thruster-controlled spacecraft.

Decoding emotional valence from electroencephalographic rhythmic activity.

PubMed

Celikkanat, Hande; Moriya, Hiroki; Ogawa, Takeshi; Kauppi, Jukka-Pekka; Kawanabe, Motoaki; Hyvarinen, Aapo

2017-07-01

We attempt to decode emotional valence from electroencephalographic rhythmic activity in a naturalistic setting. We employ a data-driven method developed in a previous study, Spectral Linear Discriminant Analysis, to discover the relationships between the classification task and independent neuronal sources, optimally utilizing multiple frequency bands. A detailed investigation of the classifier provides insight into the neuronal sources related with emotional valence, and the individual differences of the subjects in processing emotions. Our findings show: (1) sources whose locations are similar across subjects are consistently involved in emotional responses, with the involvement of parietal sources being especially significant, and (2) even though the locations of the involved neuronal sources are consistent, subjects can display highly varying degrees of valence-related EEG activity in the sources.

Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression

ERIC Educational Resources Information Center

Beckstead, Jason W.

2012-01-01

The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic…

A Solution to the Cosmic Conundrum including Cosmological Constant and Dark Energy Problems

NASA Astrophysics Data System (ADS)

Singh, A.

2009-12-01

A comprehensive solution to the cosmic conundrum is presented that also resolves key paradoxes of quantum mechanics and relativity. A simple mathematical model, the Gravity Nullification model (GNM), is proposed that integrates the missing physics of the spontaneous relativistic conversion of mass to energy into the existing physics theories, specifically a simplified general theory of relativity. Mechanistic mathematical expressions are derived for a relativistic universe expansion, which predict both the observed linear Hubble expansion in the nearby universe and the accelerating expansion exhibited by the supernova observations. The integrated model addresses the key questions haunting physics and Big Bang cosmology. It also provides a fresh perspective on the misconceived birth and evolution of the universe, especially the creation and dissolution of matter. The proposed model eliminates singularities from existing models and the need for the incredible and unverifiable assumptions including the superluminous inflation scenario, multiple universes, multiple dimensions, Anthropic principle, and quantum gravity. GNM predicts the observed features of the universe without any explicit consideration of time as a governing parameter.

Transportation of single cell and microbubbles by phase-shift introduced to standing leaky surface acoustic waves

PubMed Central

Meng, Long; Cai, Feiyan; Zhang, Zidong; Niu, Lili; Jin, Qiaofeng; Yan, Fei; Wu, Junru; Wang, Zhanhui; Zheng, Hairong

2011-01-01

A microfluidic device was developed to precisely transport a single cell or multiple microbubbles by introducing phase-shifts to a standing leaky surface acoustic wave (SLSAW). The device consists of a polydimethyl-siloxane (PDMS) microchannel and two phase-tunable interdigital transducers (IDTs) for the generation of the relative phase for the pair of surface acoustic waves (SAW) propagating along the opposite directions forming a standing wave. When the SAW contacts the fluid medium inside the microchannel, some of SAW energy is coupled to the fluid and the SAW becomes the leaky surface wave. By modulating the relative phase between two IDTs, the positions of pressure nodes of the SLSAW in the microchannel change linearly resulting in the transportation of a single cell or microbubbles. The results also reveal that there is a good linear relationship between the relative phase and the displacement of a single cell or microbubbles. Furthermore, the single cell and the microbubbles can be transported over a predetermined distance continuously until they reach the targeted locations. This technique has its distinct advantages, such as precise position-manipulation, simple to implement, miniature size, and noninvasive character, which may provide an effective method for the position-manipulation of a single cell and microbubbles in many biological and biomedical applications. PMID:22662056

Inference regarding multiple structural changes in linear models with endogenous regressors☆

PubMed Central

Hall, Alastair R.; Han, Sanggohn; Boldea, Otilia

2012-01-01

This paper considers the linear model with endogenous regressors and multiple changes in the parameters at unknown times. It is shown that minimization of a Generalized Method of Moments criterion yields inconsistent estimators of the break fractions, but minimization of the Two Stage Least Squares (2SLS) criterion yields consistent estimators of these parameters. We develop a methodology for estimation and inference of the parameters of the model based on 2SLS. The analysis covers the cases where the reduced form is either stable or unstable. The methodology is illustrated via an application to the New Keynesian Phillips Curve for the US. PMID:23805021

Linearity-Preserving Limiters on Irregular Grids

NASA Technical Reports Server (NTRS)

Berger, Marsha; Aftosmis, Michael; Murman, Scott

2004-01-01

This paper examines the behavior of flux and slope limiters on non-uniform grids in multiple dimensions. We note that on non-uniform grids the scalar formulation in standard use today sacrifices k-exactness, even for linear solutions, impacting both accuracy and convergence. We rewrite some well-known limiters in a n way to highlight their underlying symmetry, and use this to examine both traditional and novel limiter formulations. A consistent method of handling stretched meshes is developed, as is a new directional formulation in multiple dimensions for irregular grids. Results are presented demonstrating improved accuracy and convergence using a combination of model problems and complex three-dimensional examples.

Estimating the intensity of a cyclic Poisson process in the presence of additive and multiplicative linear trend

NASA Astrophysics Data System (ADS)

Wayan Mangku, I.

2017-10-01

In this paper we survey some results on estimation of the intensity function of a cyclic Poisson process in the presence of additive and multiplicative linear trend. We do not assume any parametric form for the cyclic component of the intensity function, except that it is periodic. Moreover, we consider the case when there is only a single realization of the Poisson process is observed in a bounded interval. The considered estimators are weakly and strongly consistent when the size of the observation interval indefinitely expands. Asymptotic approximations to the bias and variance of those estimators are presented.

Modeling Learning in Doubly Multilevel Binary Longitudinal Data Using Generalized Linear Mixed Models: An Application to Measuring and Explaining Word Learning.

PubMed

Cho, Sun-Joo; Goodwin, Amanda P

2016-04-01

When word learning is supported by instruction in experimental studies for adolescents, word knowledge outcomes tend to be collected from complex data structure, such as multiple aspects of word knowledge, multilevel reader data, multilevel item data, longitudinal design, and multiple groups. This study illustrates how generalized linear mixed models can be used to measure and explain word learning for data having such complexity. Results from this application provide deeper understanding of word knowledge than could be attained from simpler models and show that word knowledge is multidimensional and depends on word characteristics and instructional contexts.

Detecting multiple outliers in linear functional relationship model for circular variables using clustering technique

NASA Astrophysics Data System (ADS)

Mokhtar, Nurkhairany Amyra; Zubairi, Yong Zulina; Hussin, Abdul Ghapor

2017-05-01

Outlier detection has been used extensively in data analysis to detect anomalous observation in data and has important application in fraud detection and robust analysis. In this paper, we propose a method in detecting multiple outliers for circular variables in linear functional relationship model. Using the residual values of the Caires and Wyatt model, we applied the hierarchical clustering procedure. With the use of tree diagram, we illustrate the graphical approach of the detection of outlier. A simulation study is done to verify the accuracy of the proposed method. Also, an illustration to a real data set is given to show its practical applicability.

Brief report: Associations between adolescent girls’ social emotional intelligence and violence perpetration

PubMed Central

Gower, Amy L.; Shlafer, Rebecca J.; Polan, Julie; McRee, Annie-Laurie; McMorris, Barbara J.; Pettingell, Sandra L.; Sieving, Renee E.

2013-01-01

This study examined associations between social emotional intelligence (SEI) and two measures of violence perpetration (relational aggression and physical violence) in a cross-sectional sample of high-risk adolescent girls (N = 253). We evaluated three aspects of SEI: stress management, intrapersonal, and interpersonal skills. Results of a multiple linear regression model accounting for participants’ age, race/ethnicity, and experiences of relational aggression victimization indicated that girls with better stress management skills were less likely to perpetrate relational aggression. A parallel model for perpetration of physical violence showed a similar pattern of results. Study findings suggest that SEI, and stress management skills in particular, may protect adolescent girls – including those who have been victims of violence – from perpetrating relational aggression and physical violence. Interventions that build adolescent girls’ social and emotional skills may be an effective strategy for reducing their perpetration of violence. PMID:24331306

Father and adolescent son variables related to son's HIV prevention.

PubMed

Glenn, Betty L; Demi, Alice; Kimble, Laura P

2008-02-01

The purpose of this study was to examine the relationship between fathers' influences and African American male adolescents' perceptions of self-efficacy to reduce high-risk sexual behavior. A convenience sample of 70 fathers was recruited from churches in a large metropolitan area in the South. Hierarchical multiple linear regression analysis indicated father-related factors and son-related factors were associated with 26.1% of the variance in son's self-efficacy to be abstinent. In the regression model greater son's perception of the communication of sexual standards and greater father's perception of his son's self-efficacy were significantly related to greater son's self-efficacy for abstinence. The second regression model with son's self-efficacy for safer sex as the criterion was not statistically significant. Data support the need for fathers to express confidence in their sons' ability to be abstinent or practice safer sex and to communicate with their sons regarding sexual issues and standards.

Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure.

PubMed

Louys, Julien; Meloro, Carlo; Elton, Sarah; Ditchfield, Peter; Bishop, Laura C

2015-01-01

We test the performance of two models that use mammalian communities to reconstruct multivariate palaeoenvironments. While both models exploit the correlation between mammal communities (defined in terms of functional groups) and arboreal heterogeneity, the first uses a multiple multivariate regression of community structure and arboreal heterogeneity, while the second uses a linear regression of the principal components of each ecospace. The success of these methods means the palaeoenvironment of a particular locality can be reconstructed in terms of the proportions of heavy, moderate, light, and absent tree canopy cover. The linear regression is less biased, and more precisely and accurately reconstructs heavy tree canopy cover than the multiple multivariate model. However, the multiple multivariate model performs better than the linear regression for all other canopy cover categories. Both models consistently perform better than randomly generated reconstructions. We apply both models to the palaeocommunity of the Upper Laetolil Beds, Tanzania. Our reconstructions indicate that there was very little heavy tree cover at this site (likely less than 10%), with the palaeo-landscape instead comprising a mixture of light and absent tree cover. These reconstructions help resolve the previous conflicting palaeoecological reconstructions made for this site. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

A General Algorithm for Reusing Krylov Subspace Information. I. Unsteady Navier-Stokes

NASA Technical Reports Server (NTRS)

Carpenter, Mark H.; Vuik, C.; Lucas, Peter; vanGijzen, Martin; Bijl, Hester

2010-01-01

A general algorithm is developed that reuses available information to accelerate the iterative convergence of linear systems with multiple right-hand sides A x = b (sup i), which are commonly encountered in steady or unsteady simulations of nonlinear equations. The algorithm is based on the classical GMRES algorithm with eigenvector enrichment but also includes a Galerkin projection preprocessing step and several novel Krylov subspace reuse strategies. The new approach is applied to a set of test problems, including an unsteady turbulent airfoil, and is shown in some cases to provide significant improvement in computational efficiency relative to baseline approaches.

Non-linear analysis of stick/slip motion

NASA Astrophysics Data System (ADS)

Pratt, T. K.; Williams, R.

1981-02-01

The steady state relative motion of two masses with dry (Coulomb) friction contact is investigated. The bodies are assumed to have the same mass and stiffness and are subjected to harmonic excitation. By means of a combined analytical—numerical procedure, results are obtained for arbitrary values of Coulomb friction, excitation frequency, and natural frequencies of the bodies. For certain values of these parameters, multiple lockups per cycle are possible. In this respect, the problem investigated here is a natural extension of the one considered by Den Hartog, who in obtaining his closed form solution assumed a maximum of two lockups per cycle.

Low cigarette consumption and risk of coronary heart disease and stroke: meta-analysis of 141 cohort studies in 55 study reports.

PubMed

Hackshaw, Allan; Morris, Joan K; Boniface, Sadie; Tang, Jin-Ling; Milenković, Dušan

2018-01-24

To use the relation between cigarette consumption and cardiovascular disease to quantify the risk of coronary heart disease and stroke for light smoking (one to five cigarettes/day). Systematic review and meta-analysis. Medline 1946 to May 2015, with manual searches of references. Prospective cohort studies with at least 50 events, reporting hazard ratios or relative risks (both hereafter referred to as relative risk) compared with never smokers or age specific incidence in relation to risk of coronary heart disease or stroke. MOOSE guidelines were followed. For each study, the relative risk was estimated for smoking one, five, or 20 cigarettes per day by using regression modelling between risk and cigarette consumption. Relative risks were adjusted for at least age and often additional confounders. The main measure was the excess relative risk for smoking one cigarette per day (RR 1_per_day -1) expressed as a proportion of that for smoking 20 cigarettes per day (RR 20_per_day -1), expected to be about 5% assuming a linear relation between risk and consumption (as seen with lung cancer). The relative risks for one, five, and 20 cigarettes per day were also pooled across all studies in a random effects meta-analysis. Separate analyses were done for each combination of sex and disorder. The meta-analysis included 55 publications containing 141 cohort studies. Among men, the pooled relative risk for coronary heart disease was 1.48 for smoking one cigarette per day and 2.04 for 20 cigarettes per day, using all studies, but 1.74 and 2.27 among studies in which the relative risk had been adjusted for multiple confounders. Among women, the pooled relative risks were 1.57 and 2.84 for one and 20 cigarettes per day (or 2.19 and 3.95 using relative risks adjusted for multiple factors). Men who smoked one cigarette per day had 46% of the excess relative risk for smoking 20 cigarettes per day (53% using relative risks adjusted for multiple factors), and women had 31% of the excess risk (38% using relative risks adjusted for multiple factors). For stroke, the pooled relative risks for men were 1.25 and 1.64 for smoking one or 20 cigarettes per day (1.30 and 1.56 using relative risks adjusted for multiple factors). In women, the pooled relative risks were 1.31 and 2.16 for smoking one or 20 cigarettes per day (1.46 and 2.42 using relative risks adjusted for multiple factors). The excess risk for stroke associated with one cigarette per day (in relation to 20 cigarettes per day) was 41% for men and 34% for women (or 64% and 36% using relative risks adjusted for multiple factors). Relative risks were generally higher among women than men. Smoking only about one cigarette per day carries a risk of developing coronary heart disease and stroke much greater than expected: around half that for people who smoke 20 per day. No safe level of smoking exists for cardiovascular disease. Smokers should aim to quit instead of cutting down to significantly reduce their risk of these two common major disorders. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Low cigarette consumption and risk of coronary heart disease and stroke: meta-analysis of 141 cohort studies in 55 study reports

PubMed Central

Morris, Joan K; Boniface, Sadie; Tang, Jin-Ling; Milenković, Dušan

2018-01-01

Abstract Objective To use the relation between cigarette consumption and cardiovascular disease to quantify the risk of coronary heart disease and stroke for light smoking (one to five cigarettes/day). Design Systematic review and meta-analysis. Data sources Medline 1946 to May 2015, with manual searches of references. Eligibility criteria for selecting studies Prospective cohort studies with at least 50 events, reporting hazard ratios or relative risks (both hereafter referred to as relative risk) compared with never smokers or age specific incidence in relation to risk of coronary heart disease or stroke. Data extraction/synthesis MOOSE guidelines were followed. For each study, the relative risk was estimated for smoking one, five, or 20 cigarettes per day by using regression modelling between risk and cigarette consumption. Relative risks were adjusted for at least age and often additional confounders. The main measure was the excess relative risk for smoking one cigarette per day (RR1_per_day−1) expressed as a proportion of that for smoking 20 cigarettes per day (RR20_per_day−1), expected to be about 5% assuming a linear relation between risk and consumption (as seen with lung cancer). The relative risks for one, five, and 20 cigarettes per day were also pooled across all studies in a random effects meta-analysis. Separate analyses were done for each combination of sex and disorder. Results The meta-analysis included 55 publications containing 141 cohort studies. Among men, the pooled relative risk for coronary heart disease was 1.48 for smoking one cigarette per day and 2.04 for 20 cigarettes per day, using all studies, but 1.74 and 2.27 among studies in which the relative risk had been adjusted for multiple confounders. Among women, the pooled relative risks were 1.57 and 2.84 for one and 20 cigarettes per day (or 2.19 and 3.95 using relative risks adjusted for multiple factors). Men who smoked one cigarette per day had 46% of the excess relative risk for smoking 20 cigarettes per day (53% using relative risks adjusted for multiple factors), and women had 31% of the excess risk (38% using relative risks adjusted for multiple factors). For stroke, the pooled relative risks for men were 1.25 and 1.64 for smoking one or 20 cigarettes per day (1.30 and 1.56 using relative risks adjusted for multiple factors). In women, the pooled relative risks were 1.31 and 2.16 for smoking one or 20 cigarettes per day (1.46 and 2.42 using relative risks adjusted for multiple factors). The excess risk for stroke associated with one cigarette per day (in relation to 20 cigarettes per day) was 41% for men and 34% for women (or 64% and 36% using relative risks adjusted for multiple factors). Relative risks were generally higher among women than men. Conclusions Smoking only about one cigarette per day carries a risk of developing coronary heart disease and stroke much greater than expected: around half that for people who smoke 20 per day. No safe level of smoking exists for cardiovascular disease. Smokers should aim to quit instead of cutting down to significantly reduce their risk of these two common major disorders. PMID:29367388

The "Knife-Cut Sign" Revisited: A Distinctive Presentation of Linear Erosive Herpes Simplex Virus Infection in Immunocompromised Patients.

PubMed

Cohen, Philip R

2015-10-01

The "knife-cut sign" is a distinctive presentation of linear erosive herpes simplex virus infection in immunocompromised patients. To describe a man whose herpes simplex virus infection-related skin lesions demonstrated the "knife-cut sign" and to review the characteristics of reported immunosuppressed individuals with "knife-cut" cutaneous herpes simplex virus lesions. A man with multiple myeloma and post-stem cell transplant cutaneous graft-versus-host disease managed with systemic prednisone and sirolimus developed disseminated cutaneous herpes simplex virus infection with virus-associated linear ulcers of the inguinal folds and the area between his ear and scalp; the lesions at both sites had a distinctive "knife-cut" appearance. Using the PubMed database, an extensive literature search was performed on herpes simplex virus, immunocompromised patient, and "knife-cut sign". Herpes simplex virus infection-associated skin lesions that demonstrate the "knife-cut sign" present in patients who are immunosuppressed secondary to either an underlying medical condition or a systemic therapy or both. The distinctive virus-related cutaneous lesions appear as linear ulcers and fissures in intertriginous areas, such as the folds in the inguinal area, the vulva, and the abdomen; in addition, other sites include beneath the breast, within the gluteal cleft, and the area between the ear and the scalp. Not only herpes simplex virus-2, but also herpes simplex virus-1 has been observed as the causative viral serotype; indeed, herpes simplex virus-1 has been associated with genital and inframammary lesions in addition to those above the neck. Direct fluorescent antibody testing is a rapid method for confirming the clinically suspected viral infection; however, since false-negative direct fluorescent antibody testing occurred in some of the patients, it may be prudent to also perform viral cultures and possibly lesional skin biopsies to establish the diagnosis. The herpes simplex virus infection-related skin lesions clinically improve once systemic antiviral therapy is initiated. In immunosuppressed individuals, the "knife-cut sign" is a distinctive presentation of cutaneous linear erosive herpes simplex virus infection. Recognition of the linear ulcers in intertriginous areas and body folds should prompt the clinician to consider herpes simplex virus infection-associated skin lesions in an immunocompromised patient and to initiate systemic antiviral treatment while awaiting the results of laboratory evaluation to confirm the suspected diagnosis.

Does transport time help explain the high trauma mortality rates in rural areas? New and traditional predictors assessed by new and traditional statistical methods

PubMed Central

Røislien, Jo; Lossius, Hans Morten; Kristiansen, Thomas

2015-01-01

Background Trauma is a leading global cause of death. Trauma mortality rates are higher in rural areas, constituting a challenge for quality and equality in trauma care. The aim of the study was to explore population density and transport time to hospital care as possible predictors of geographical differences in mortality rates, and to what extent choice of statistical method might affect the analytical results and accompanying clinical conclusions. Methods Using data from the Norwegian Cause of Death registry, deaths from external causes 1998–2007 were analysed. Norway consists of 434 municipalities, and municipality population density and travel time to hospital care were entered as predictors of municipality mortality rates in univariate and multiple regression models of increasing model complexity. We fitted linear regression models with continuous and categorised predictors, as well as piecewise linear and generalised additive models (GAMs). Models were compared using Akaike's information criterion (AIC). Results Population density was an independent predictor of trauma mortality rates, while the contribution of transport time to hospital care was highly dependent on choice of statistical model. A multiple GAM or piecewise linear model was superior, and similar, in terms of AIC. However, while transport time was statistically significant in multiple models with piecewise linear or categorised predictors, it was not in GAM or standard linear regression. Conclusions Population density is an independent predictor of trauma mortality rates. The added explanatory value of transport time to hospital care is marginal and model-dependent, highlighting the importance of exploring several statistical models when studying complex associations in observational data. PMID:25972600

Guidelines and Procedures for Computing Time-Series Suspended-Sediment Concentrations and Loads from In-Stream Turbidity-Sensor and Streamflow Data

USGS Publications Warehouse

Rasmussen, Patrick P.; Gray, John R.; Glysson, G. Douglas; Ziegler, Andrew C.

2009-01-01

In-stream continuous turbidity and streamflow data, calibrated with measured suspended-sediment concentration data, can be used to compute a time series of suspended-sediment concentration and load at a stream site. Development of a simple linear (ordinary least squares) regression model for computing suspended-sediment concentrations from instantaneous turbidity data is the first step in the computation process. If the model standard percentage error (MSPE) of the simple linear regression model meets a minimum criterion, this model should be used to compute a time series of suspended-sediment concentrations. Otherwise, a multiple linear regression model using paired instantaneous turbidity and streamflow data is developed and compared to the simple regression model. If the inclusion of the streamflow variable proves to be statistically significant and the uncertainty associated with the multiple regression model results in an improvement over that for the simple linear model, the turbidity-streamflow multiple linear regression model should be used to compute a suspended-sediment concentration time series. The computed concentration time series is subsequently used with its paired streamflow time series to compute suspended-sediment loads by standard U.S. Geological Survey techniques. Once an acceptable regression model is developed, it can be used to compute suspended-sediment concentration beyond the period of record used in model development with proper ongoing collection and analysis of calibration samples. Regression models to compute suspended-sediment concentrations are generally site specific and should never be considered static, but they represent a set period in a continually dynamic system in which additional data will help verify any change in sediment load, type, and source.

Estimating health state utility values for comorbid health conditions using SF-6D data.

PubMed

Ara, Roberta; Brazier, John

2011-01-01

When health state utility values for comorbid health conditions are not available, data from cohorts with single conditions are used to estimate scores. The methods used can produce very different results and there is currently no consensus on which is the most appropriate approach. The objective of the current study was to compare the accuracy of five different methods within the same dataset. Data collected during five Welsh Health Surveys were subgrouped by health status. Mean short-form 6 dimension (SF-6D) scores for cohorts with a specific health condition were used to estimate mean SF-6D scores for cohorts with comorbid conditions using the additive, multiplicative, and minimum methods, the adjusted decrement estimator (ADE), and a linear regression model. The mean SF-6D for subgroups with comorbid health conditions ranged from 0.4648 to 0.6068. The linear model produced the most accurate scores for the comorbid health conditions with 88% of values accurate to within the minimum important difference for the SF-6D. The additive and minimum methods underestimated or overestimated the actual SF-6D scores respectively. The multiplicative and ADE methods both underestimated the majority of scores. However, both methods performed better when estimating scores smaller than 0.50. Although the range in actual health state utility values (HSUVs) was relatively small, our data covered the lower end of the index and the majority of previous research has involved actual HSUVs at the upper end of possible ranges. Although the linear model gave the most accurate results in our data, additional research is required to validate our findings. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Substituting values for censored data from Texas, USA, reservoirs inflated and obscured trends in analyses commonly used for water quality target development.

PubMed

Grantz, Erin; Haggard, Brian; Scott, J Thad

2018-06-12

We calculated four median datasets (chlorophyll a, Chl a; total phosphorus, TP; and transparency) using multiple approaches to handling censored observations, including substituting fractions of the quantification limit (QL; dataset 1 = 1QL, dataset 2 = 0.5QL) and statistical methods for censored datasets (datasets 3-4) for approximately 100 Texas, USA reservoirs. Trend analyses of differences between dataset 1 and 3 medians indicated percent difference increased linearly above thresholds in percent censored data (%Cen). This relationship was extrapolated to estimate medians for site-parameter combinations with %Cen > 80%, which were combined with dataset 3 as dataset 4. Changepoint analysis of Chl a- and transparency-TP relationships indicated threshold differences up to 50% between datasets. Recursive analysis identified secondary thresholds in dataset 4. Threshold differences show that information introduced via substitution or missing due to limitations of statistical methods biased values, underestimated error, and inflated the strength of TP thresholds identified in datasets 1-3. Analysis of covariance identified differences in linear regression models relating transparency-TP between datasets 1, 2, and the more statistically robust datasets 3-4. Study findings identify high-risk scenarios for biased analytical outcomes when using substitution. These include high probability of median overestimation when %Cen > 50-60% for a single QL, or when %Cen is as low 16% for multiple QL's. Changepoint analysis was uniquely vulnerable to substitution effects when using medians from sites with %Cen > 50%. Linear regression analysis was less sensitive to substitution and missing data effects, but differences in model parameters for transparency cannot be discounted and could be magnified by log-transformation of the variables.

Metabolites as novel biomarkers for childhood obesity-related traits in Mexican-American children.

PubMed

Farook, V S; Reddivari, L; Chittoor, G; Puppala, S; Arya, R; Fowler, S P; Hunt, K J; Curran, J E; Comuzzie, A G; Lehman, D M; Jenkinson, C P; Lynch, J L; DeFronzo, R A; Blangero, J; Hale, D E; Duggirala, R; Vanamala, J

2015-08-01

Although newer approaches have identified several metabolites associated with obesity, there is paucity of such information in paediatric populations, especially among Mexican-Americans (MAs) who are at high risk of obesity. Therefore, we performed a global serum metabolite screening in MA children to identify biomarkers of childhood obesity. We selected 15 normal-weight, 13 overweight and 14 obese MA children (6-17 years) and performed global serum metabolite screening using ultra-performance liquid chromatography/quadruple orthogonal acceleration time of flight tandem micro mass spectrometer. Metabolite values were analysed to assess mean differences among groups using one-way analysis of variance, to test for linear trend across groups and to examine Pearson's correlations between them and seven cardiometabolic traits (CMTs): body mass index, waist circumference, systolic blood pressure, diastolic blood pressure, homeostasis model of assessment-insulin resistance, triglycerides and high-density lipoprotein cholesterol. We identified 14 metabolites exhibiting differences between groups as well as linear trend across groups with nominal statistical significance. After adjustment for multiple testing, mean differences and linear trends across groups remained significant (P < 5.9 × 10(-5) ) for L-thyronine, bradykinin and naringenin. Of the examined metabolite-CMT trait pairs, all metabolites except for 2-methylbutyroylcarnitine were nominally associated with two or more CMTs, some exhibiting significance even after accounting for multiple testing (P < 3.6 × 10(-3) ). To our knowledge, this study - albeit pilot in nature - is the first study to identify these metabolites as novel biomarkers of childhood obesity and its correlates. These findings signify the need for future systematic investigations of metabolic pathways underlying childhood obesity. © 2014 World Obesity.

Multiple-region directed functional connectivity based on phase delays.

PubMed

Goelman, Gadi; Dan, Rotem

2017-03-01

Network analysis is increasingly advancing the field of neuroimaging. Neural networks are generally constructed from pairwise interactions with an assumption of linear relations between them. Here, a high-order statistical framework to calculate directed functional connectivity among multiple regions, using wavelet analysis and spectral coherence has been presented. The mathematical expression for 4 regions was derived and used to characterize a quartet of regions as a linear, combined (nonlinear), or disconnected network. Phase delays between regions were used to obtain network's temporal hierarchy and directionality. The validity of the mathematical derivation along with the effects of coupling strength and noise on its outcomes were studied by computer simulations of the Kuramoto model. The simulations demonstrated correct directionality for a large range of coupling strength and low sensitivity to Gaussian noise compared with pairwise coherences. The analysis was applied to resting-state fMRI data of 40 healthy young subjects to characterize the ventral visual system, motor system and default mode network (DMN). It was shown that the ventral visual system was predominantly composed of linear networks while the motor system and the DMN were composed of combined (nonlinear) networks. The ventral visual system exhibits its known temporal hierarchy, the motor system exhibits center ↔ out hierarchy and the DMN has dorsal ↔ ventral and anterior ↔ posterior organizations. The analysis can be applied in different disciplines such as seismology, or economy and in a variety of brain data including stimulus-driven fMRI, electrophysiology, EEG, and MEG, thus open new horizons in brain research. Hum Brain Mapp 38:1374-1386, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Micronutrient Adequacy and Dietary Diversity Exert Positive and Distinct Effects on Linear Growth in Urban Zambian Infants.

PubMed

Mallard, Simonette R; Houghton, Lisa A; Filteau, Suzanne; Chisenga, Molly; Siame, Joshua; Kasonka, Lackson; Mullen, Anne; Gibson, Rosalind S

2016-10-01

In the monitoring of infant and young child feeding, dietary diversity is used as an indicator of micronutrient adequacy; however, their relation may have weakened with the increasing use of fortified complementary foods. The objectives were to assess the relation between dietary diversity and micronutrient adequacy in an urban infant population with a high consumption of fortified foods and to investigate whether dietary diversity and micronutrient adequacy were independently associated with subsequent growth. We used longitudinal data on 811 infants in the Chilenje Infant Growth, Nutrition, and Infection Study conducted in Lusaka, Zambia. The relation between mean micronutrient adequacies and dietary diversity scores derived from 24-h diet recalls at 6 mo of age was investigated with the use of Spearman rank correlation. Multiple linear regression was used to assess the association between micronutrient adequacy, dietary diversity, and subsequent growth to 18 mo of age. Overall mean micronutrient density adequacy (MMDA) and MMDA of "problem micronutrients," defined as those micronutrients (calcium, iron, zinc) with mean density adequacies less than half of estimated needs, were correlated with dietary diversity scores (ρ = 0.36 and 0.30, respectively, both P < 0.0001). Consumption of "sentinel foods" (iron rich, fortified, animal source, dairy) showed better correlation with MMDA than with dietary diversity (ρ = 0.58-0.69, all P < 0.0001). In fully adjusted analyses, MMDA calcium, iron, zinc, and dietary diversity, but not overall MMDA, were associated with linear growth to 18 mo (both P ≤ 0.028). Micronutrient adequacy in infants consuming fortified foods may be more accurately assessed using locally specific sentinel food indicators rather than dietary diversity scores. Nonetheless, dietary diversity has a positive effect on subsequent linear growth apart from that of micronutrient adequacy, warranting its continued monitoring and further investigation into the mechanisms underlying this finding. This trial was registered at www.controlled-trials.com as ISRCTN37460449. © 2016 American Society for Nutrition.

Psychological status and quality of life among primary caregivers of individuals with mental illness: a hospital based study.

PubMed

Jeyagurunathan, Anitha; Sagayadevan, Vathsala; Abdin, Edimansyah; Zhang, YunJue; Chang, Sherilyn; Shafie, Saleha; Rahman, Restria Fauziana Abdul; Vaingankar, Janhavi Ajit; Chong, Siow Ann; Subramaniam, Mythily

2017-05-19

This study aimed to explore the psychological status and quality of life among primary caregivers of individuals suffering from various mental illnesses including early psychosis, chronic schizophrenia, depressive disorders, anxiety disorders and dementia. A total of 350 primary caregivers with relatives seeking treatment at a tertiary psychiatric hospital were recruited for this study. Socio-demographic data was obtained and the brief version of the World Health Organisation Quality of Life instrument was used to assess caregiver's quality of life (QOL). Psychological status among primary caregivers was assessed using the General Anxiety Disorder - 7 item (GAD-7) and Patient Health Questionnaire - 9 item (PHQ-9) scales. Family Interview Schedule (FIS) was used to assess the impact of caregiving relating to social problems, interpersonal strain among family members, work related problems and financial difficulties as a result of their relative's illness. The socio-demographic and clinical correlates of QOL, PHQ-9 and GAD-7 were examined using multiple linear and logistic regression analyses. Associations between QOL domains and psychological status was examined using multiple linear regression analyses. The mean age of the primary caregivers was 49.7 years (SD = 13.2), ranging from 21 to 82 years, with a preponderance of females (67.6%), aged 50-64 years old (45.7%). Majority were of Chinese ethnicity (57.5%), had secondary level education (43.1%), were married (65.2%), and employed (64.9%). 18.3% of primary caregivers had symptoms of depression (based on PHQ-9 cut-off point of 10 or greater) while 12.7% had symptoms of anxiety (based on GAD-7 cut-off point of 10 or greater). Multiple linear and logistic regression analyses revealed that primary caregivers aged between 35-49 years and 50-64 years, unemployed, living with others, providing care to those diagnosed with dementia and who had higher FIS scores were significantly more likely to report symptoms of depression whilst those who cared for their son/daughter were less likely to be associated with symptoms of depression. Primary caregivers who had lower education, were living with others, were single or divorced/separated, were unemployed and with higher FIS scores were associated with lower QOL domain scores. Those with symptoms of depression were significantly associated with low QOL across all four domains, whilst those with symptoms of anxiety were significantly associated with low QOL in the social relationships domain. Psychological status of caregivers in the current study was associated with the various domains of QOL. In particular, caregivers' symptoms of depression were significantly associated with lower QOL across all four domains of QOL whereas symptoms of anxiety were associated with lower scores in the social relationships domain. The study suggests a need to provide caregivers with social support and psycho-education to improve the QOL as well as aid in developing healthy coping strategies.

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

Quantitative, spectrally-resolved intraoperative fluorescence imaging

PubMed Central

Valdés, Pablo A.; Leblond, Frederic; Jacobs, Valerie L.; Wilson, Brian C.; Paulsen, Keith D.; Roberts, David W.

2012-01-01

Intraoperative visual fluorescence imaging (vFI) has emerged as a promising aid to surgical guidance, but does not fully exploit the potential of the fluorescent agents that are currently available. Here, we introduce a quantitative fluorescence imaging (qFI) approach that converts spectrally-resolved data into images of absolute fluorophore concentration pixel-by-pixel across the surgical field of view (FOV). The resulting estimates are linear, accurate, and precise relative to true values, and spectral decomposition of multiple fluorophores is also achieved. Experiments with protoporphyrin IX in a glioma rodent model demonstrate in vivo quantitative and spectrally-resolved fluorescence imaging of infiltrating tumor margins for the first time. Moreover, we present images from human surgery which detect residual tumor not evident with state-of-the-art vFI. The wide-field qFI technique has broad implications for intraoperative surgical guidance because it provides near real-time quantitative assessment of multiple fluorescent biomarkers across the operative field. PMID:23152935

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

Mosher, J.C.; Leahy, R.M.

A new method for source localization is described that is based on a modification of the well known multiple signal classification (MUSIC) algorithm. In classical MUSIC, the array manifold vector is projected onto an estimate of the signal subspace, but errors in the estimate can make location of multiple sources difficult. Recursively applied and projected (RAP) MUSIC uses each successively located source to form an intermediate array gain matrix, and projects both the array manifold and the signal subspace estimate into its orthogonal complement. The MUSIC projection is then performed in this reduced subspace. Using the metric of principal angles,more » the authors describe a general form of the RAP-MUSIC algorithm for the case of diversely polarized sources. Through a uniform linear array simulation, the authors demonstrate the improved Monte Carlo performance of RAP-MUSIC relative to MUSIC and two other sequential subspace methods, S and IES-MUSIC.« less

[Life satisfaction and related socio-demographic factors during female midlife].

PubMed

Cuadros, José Luis; Pérez-Roncero, Gonzalo R; López-Baena, María Teresa; Cuadros-Celorrio, Angela M; Fernández-Alonso, Ana María

2014-01-01

To assess life satisfaction and related factors in middle-aged Spanish women. This was a cross-sectional study including 235 women aged 40 to 65, living in Granada (Spain), healthy companions of patients visiting the obstetrics and gynecology clinics. They completed the Diener Satisfaction with Life Scale, the Menopause Rating Scale, the Perceived Stress Scale, the Insomnia Severity Index and a sociodemographic questionnaire containing personal and partner data. Internal consistency of each tool was also calculated. Almost two-thirds (61.3%) of the women were postmenopausal, and 43.8% had abdominal obesity, 36.6% had insomnia, 18.7% had poor menopause-related quality of life, 31.9% performed regular exercise, and 5.1% had severe financial problems. Life satisfaction showed significant positive correlations (Spearman's test) with female and male age, and inverse correlations with menopause-related quality of life, perceived stress and insomnia. In the multiple linear regression analysis, high life satisfaction is positively correlated with having a partner who performed exercise, and inversely with having work problems, perceived stress and the suspicion of partner infidelity. These factors explained 40% of the variance of the multiple regression analysis for life satisfaction in middle-aged women. Life satisfaction is a construct related to perceived stress, work problems, and having a partner, while aspects of menopause and general health had no significant influence. Copyright © 2014 Elsevier España, S.L.U. All rights reserved.

Accelerated longitudinal designs: An overview of modelling, power, costs and handling missing data.

PubMed

Galbraith, Sally; Bowden, Jack; Mander, Adrian

2017-02-01

Longitudinal studies are often used to investigate age-related developmental change. Whereas a single cohort design takes a group of individuals at the same initial age and follows them over time, an accelerated longitudinal design takes multiple single cohorts, each one starting at a different age. The main advantage of an accelerated longitudinal design is its ability to span the age range of interest in a shorter period of time than would be possible with a single cohort longitudinal design. This paper considers design issues for accelerated longitudinal studies. A linear mixed effect model is considered to describe the responses over age with random effects for intercept and slope parameters. Random and fixed cohort effects are used to cope with the potential bias accelerated longitudinal designs have due to multiple cohorts. The impact of other factors such as costs and the impact of dropouts on the power of testing or the precision of estimating parameters are examined. As duration-related costs increase relative to recruitment costs the best designs shift towards shorter duration and eventually cross-sectional design being best. For designs with the same duration but differing interval between measurements, we found there was a cutoff point for measurement costs relative to recruitment costs relating to frequency of measurements. Under our model of 30% dropout there was a maximum power loss of 7%.

Elimination of trait blocks from multiple trait mixed model equations with singular (Co)variance parameter matrices

USDA-ARS?s Scientific Manuscript database

Transformations to multiple trait mixed model equations (MME) which are intended to improve computational efficiency in best linear unbiased prediction (BLUP) and restricted maximum likelihood (REML) are described. It is shown that traits that are expected or estimated to have zero residual variance...

Experiment in multiple-criteria energy policy analysis

NASA Astrophysics Data System (ADS)

Ho, J. K.

1980-07-01

An international panel of energy analysts participated in an experiment to use HOPE (holistic preference evaluation): an interactive parametric linear programming method for multiple criteria optimization. The criteria of cost, environmental effect, crude oil, and nuclear fuel were considered, according to BESOM: an energy model for the US in the year 2000.

Development of a technique for estimating noise covariances using multiple observers

NASA Technical Reports Server (NTRS)

Bundick, W. Thomas

1988-01-01

Friedland's technique for estimating the unknown noise variances of a linear system using multiple observers has been extended by developing a general solution for the estimates of the variances, developing the statistics (mean and standard deviation) of these estimates, and demonstrating the solution on two examples.

Log-Multiplicative Association Models as Item Response Models

ERIC Educational Resources Information Center

Anderson, Carolyn J.; Yu, Hsiu-Ting

2007-01-01

Log-multiplicative association (LMA) models, which are special cases of log-linear models, have interpretations in terms of latent continuous variables. Two theoretical derivations of LMA models based on item response theory (IRT) arguments are presented. First, we show that Anderson and colleagues (Anderson & Vermunt, 2000; Anderson & Bockenholt,…

Assessing the Impact of Influential Observations on Multiple Regression Analysis on Human Resource Research.

ERIC Educational Resources Information Center

Bates, Reid A.; Holton, Elwood F., III; Burnett, Michael F.

1999-01-01

A case study of learning transfer demonstrates the possible effect of influential observation on linear regression analysis. A diagnostic method that tests for violation of assumptions, multicollinearity, and individual and multiple influential observations helps determine which observation to delete to eliminate bias. (SK)

Prospective Mathematics Teachers' Sense Making of Polynomial Multiplication and Factorization Modeled with Algebra Tiles

ERIC Educational Resources Information Center

Caglayan, Günhan

2013-01-01

This study is about prospective secondary mathematics teachers' understanding and sense making of representational quantities generated by algebra tiles, the quantitative units (linear vs. areal) inherent in the nature of these quantities, and the quantitative addition and multiplication operations--referent preserving versus referent…

Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels

PubMed Central

Van de Voorde, Tim; Vlaeminck, Jeroen; Canters, Frank

2008-01-01

Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city's inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP) at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing. PMID:27879914

No association of smoke-free ordinances with profits from bingo and charitable games in Massachusetts.

PubMed

Glantz, S A; Wilson-Loots, R

2003-12-01

Because it is widely played, claims that smoking restrictions will adversely affect bingo games is used as an argument against these policies. We used publicly available data from Massachusetts to assess the impact of 100% smoke-free ordinances on profits from bingo and other gambling sponsored by charitable organisations between 1985 and 2001. We conducted two analyses: (1) a general linear model implementation of a time series analysis with net profits (adjusted to 2001 dollars) as the dependent variable, and community (as a fixed effect), year, lagged net profits, and the length of time the ordinance had been in force as the independent variables; (2) multiple linear regression of total state profits against time, lagged profits, and the percentage of the entire state population in communities that allow charitable gaming but prohibit smoking. The general linear model analysis of data from individual communities showed that, while adjusted profits fell over time, this effect was not related to the presence of an ordinance. The analysis in terms of the fraction of the population living in communities with ordinances yielded the same result. Policymakers can implement smoke-free policies without concern that these policies will affect charitable gaming.

Linear free energy correlations for fission product release from the Fukushima-Daiichi nuclear accident.

PubMed

Abrecht, David G; Schwantes, Jon M

2015-03-03

This paper extends the preliminary linear free energy correlations for radionuclide release performed by Schwantes et al., following the Fukushima-Daiichi Nuclear Power Plant accident. Through evaluations of the molar fractionations of radionuclides deposited in the soil relative to modeled radionuclide inventories, we confirm the initial source of the radionuclides to the environment to be from active reactors rather than the spent fuel pool. Linear correlations of the form In χ = −α ((ΔGrxn°(TC))/(RTC)) + β were obtained between the deposited concentrations, and the reduction potentials of the fission product oxide species using multiple reduction schemes to calculate ΔG°rxn (TC). These models allowed an estimate of the upper bound for the reactor temperatures of TC between 2015 and 2060 K, providing insight into the limiting factors to vaporization and release of fission products during the reactor accident. Estimates of the release of medium-lived fission products 90Sr, 121mSn, 147Pm, 144Ce, 152Eu, 154Eu, 155Eu, and 151Sm through atmospheric venting during the first month following the accident were obtained, indicating that large quantities of 90Sr and radioactive lanthanides were likely to remain in the damaged reactor cores.

Combining large number of weak biomarkers based on AUC.

PubMed

Yan, Li; Tian, Lili; Liu, Song

2015-12-20

Combining multiple biomarkers to improve diagnosis and/or prognosis accuracy is a common practice in clinical medicine. Both parametric and non-parametric methods have been developed for finding the optimal linear combination of biomarkers to maximize the area under the receiver operating characteristic curve (AUC), primarily focusing on the setting with a small number of well-defined biomarkers. This problem becomes more challenging when the number of observations is not order of magnitude greater than the number of variables, especially when the involved biomarkers are relatively weak. Such settings are not uncommon in certain applied fields. The first aim of this paper is to empirically evaluate the performance of existing linear combination methods under such settings. The second aim is to propose a new combination method, namely, the pairwise approach, to maximize AUC. Our simulation studies demonstrated that the performance of several existing methods can become unsatisfactory as the number of markers becomes large, while the newly proposed pairwise method performs reasonably well. Furthermore, we apply all the combination methods to real datasets used for the development and validation of MammaPrint. The implication of our study for the design of optimal linear combination methods is discussed. Copyright © 2015 John Wiley & Sons, Ltd.

Combining large number of weak biomarkers based on AUC

PubMed Central

Yan, Li; Tian, Lili; Liu, Song

2018-01-01

Combining multiple biomarkers to improve diagnosis and/or prognosis accuracy is a common practice in clinical medicine. Both parametric and non-parametric methods have been developed for finding the optimal linear combination of biomarkers to maximize the area under the receiver operating characteristic curve (AUC), primarily focusing on the setting with a small number of well-defined biomarkers. This problem becomes more challenging when the number of observations is not order of magnitude greater than the number of variables, especially when the involved biomarkers are relatively weak. Such settings are not uncommon in certain applied fields. The first aim of this paper is to empirically evaluate the performance of existing linear combination methods under such settings. The second aim is to propose a new combination method, namely, the pairwise approach, to maximize AUC. Our simulation studies demonstrated that the performance of several existing methods can become unsatisfactory as the number of markers becomes large, while the newly proposed pairwise method performs reasonably well. Furthermore, we apply all the combination methods to real datasets used for the development and validation of MammaPrint. The implication of our study for the design of optimal linear combination methods is discussed. PMID:26227901

Biomarker selection for medical diagnosis using the partial area under the ROC curve

PubMed Central

2014-01-01

Background A biomarker is usually used as a diagnostic or assessment tool in medical research. Finding an ideal biomarker is not easy and combining multiple biomarkers provides a promising alternative. Moreover, some biomarkers based on the optimal linear combination do not have enough discriminatory power. As a result, the aim of this study was to find the significant biomarkers based on the optimal linear combination maximizing the pAUC for assessment of the biomarkers. Methods Under the binormality assumption we obtain the optimal linear combination of biomarkers maximizing the partial area under the receiver operating characteristic curve (pAUC). Related statistical tests are developed for assessment of a biomarker set and of an individual biomarker. Stepwise biomarker selections are introduced to identify those biomarkers of statistical significance. Results The results of simulation study and three real examples, Duchenne Muscular Dystrophy disease, heart disease, and breast tissue example are used to show that our methods are most suitable biomarker selection for the data sets of a moderate number of biomarkers. Conclusions Our proposed biomarker selection approaches can be used to find the significant biomarkers based on hypothesis testing. PMID:24410929

Using polyacrylate-coated SPME fibers to quantify sorption of polar and ionic organic contaminants to dissolved organic carbon.

PubMed

Haftka, Joris J-H; Scherpenisse, Peter; Jonker, Michiel T O; Hermens, Joop L M

2013-05-07

A passive sampling method using polyacrylate-coated solid-phase microextraction (SPME) fibers was applied to determine sorption of polar and ionic organic contaminants to dissolved organic carbon (DOC). The tested contaminants included pharmaceuticals, industrial chemicals, hormones, and pesticides and represented neutral, anionic, and cationic structures. Prior to the passive sampler application, sorption of the chemicals to the fibers was characterized. This was needed in order to accurately translate concentrations measured in fibers to freely dissolved aqueous concentrations during the sorption tests with DOC. Sorption isotherms of neutral compounds to the fiber were linear, whereas isotherms of basic chemicals covered a nonlinear and a linear range. Sorption of acidic and basic compounds to the fiber was pH-dependent and was dominated by sorption of the neutral sorbate species. Fiber- and DOC-water partition coefficients of neutral compounds were both linearly related to octanol-water partition coefficients (log Kow). The results of this study show that polyacrylate fibers can be used to quantify sorption to DOC of neutral and ionic contaminants, having multiple functional groups and spanning a wide hydrophobicity range (log Kow = 2.5-7.5).

Kelvin-Helmholtz instability for flow in porous media under the influence of oblique magnetic fields: A viscous potential flow analysis

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

Moatimid, Galal M.; Obied Allah, M. H.; Hassan, Mohamed A.

2013-10-15

In this paper, the Kelvin-Helmholtz instability of viscous incompressible magnetic fluid fully saturated porous media is achieved through the viscous potential theory. The flow is considered to be through semi-permeable boundaries above and below the fluids through which the fluid may either be blown in or sucked out, in a direction normal to the main streaming direction of the fluid flow. An oblique magnetic field, mass, heat transfer, and surface tension are present across the interface. Through the linear stability analysis, a general dispersion relation is derived and the natural curves are plotted. Therefore, the linear stability condition is discussedmore » in some depth. In view of the multiple time scale technique, the Ginzburg–Landau equation, which describes the behavior of the system in the nonlinear approach, is obtained. The effects of the orientation of the magnetic fields on the stability configuration in linear, as well as nonlinear approaches, are discussed. It is found that the Darcy's coefficient for the porous layers plays a stabilizing role. The injection of the fluids at both boundaries has a stabilizing effect, in contrast with the suction at both boundaries.« less

Baseline-Subtraction-Free (BSF) Damage-Scattered Wave Extraction for Stiffened Isotropic Plates

NASA Technical Reports Server (NTRS)

He, Jiaze; Leser, Patrick E.; Leser, William P.

2017-01-01

Lamb waves enable long distance inspection of structures for health monitoring purposes. However, this capability is diminished when applied to complex structures where damage-scattered waves are often buried by scattering from various structural components or boundaries in the time-space domain. Here, a baseline-subtraction-free (BSF) inspection concept based on the Radon transform (RT) is proposed to identify and separate these scattered waves from those scattered by damage. The received time-space domain signals can be converted into the Radon domain, in which the scattered signals from structural components are suppressed into relatively small regions such that damage-scattered signals can be identified and extracted. In this study, a piezoelectric wafer and a linear scan via laser Doppler vibrometer (LDV) were used to excite and acquire the Lamb-wave signals in an aluminum plate with multiple stiffeners. Linear and inverse linear Radon transform algorithms were applied to the direct measurements. The results demonstrate the effectiveness of the Radon transform as a reliable extraction tool for damage-scattered waves in a stiffened aluminum plate and also suggest the possibility of generalizing this technique for application to a wide variety of complex, large-area structures.

Application of Multiregressive Linear Models, Dynamic Kriging Models and Neural Network Models to Predictive Maintenance of Hydroelectric Power Systems

NASA Astrophysics Data System (ADS)

Lucifredi, A.; Mazzieri, C.; Rossi, M.

2000-05-01

Since the operational conditions of a hydroelectric unit can vary within a wide range, the monitoring system must be able to distinguish between the variations of the monitored variable caused by variations of the operation conditions and those due to arising and progressing of failures and misoperations. The paper aims to identify the best technique to be adopted for the monitoring system. Three different methods have been implemented and compared. Two of them use statistical techniques: the first, the linear multiple regression, expresses the monitored variable as a linear function of the process parameters (independent variables), while the second, the dynamic kriging technique, is a modified technique of multiple linear regression representing the monitored variable as a linear combination of the process variables in such a way as to minimize the variance of the estimate error. The third is based on neural networks. Tests have shown that the monitoring system based on the kriging technique is not affected by some problems common to the other two models e.g. the requirement of a large amount of data for their tuning, both for training the neural network and defining the optimum plane for the multiple regression, not only in the system starting phase but also after a trivial operation of maintenance involving the substitution of machinery components having a direct impact on the observed variable. Or, in addition, the necessity of different models to describe in a satisfactory way the different ranges of operation of the plant. The monitoring system based on the kriging statistical technique overrides the previous difficulties: it does not require a large amount of data to be tuned and is immediately operational: given two points, the third can be immediately estimated; in addition the model follows the system without adapting itself to it. The results of the experimentation performed seem to indicate that a model based on a neural network or on a linear multiple regression is not optimal, and that a different approach is necessary to reduce the amount of work during the learning phase using, when available, all the information stored during the initial phase of the plant to build the reference baseline, elaborating, if it is the case, the raw information available. A mixed approach using the kriging statistical technique and neural network techniques could optimise the result.

Magnetic positioner having a single moving part

DOEpatents

Trumper, David L.; Kim, Won-Jong

1999-01-01

A magnetic positioner is provided which is capable of providing long travel in two dimension and short travel in the remaining four dimensions. The positioner has a movable stage and a stator oriented adjacent and substantially parallel to this stage. At least three sets of first magnetic elements, which for preferred embodiments are winding sets capable of generating forces in two directions, are on the portion of the stator adjacent to the stage at any given time, and at least two second magnetic elements, which are magnet arrays for the preferred embodiment, are on the stage adjacent to the stator. At least one of the second magnetic elements overlaps multiple first magnetic elements for all positions of the stage relative to the stator, with one magnet overlapping multiple windings for one preferred embodiment of the invention and two magnets on the stage overlapping multiple windings on the stator for a second embodiment. The windings form a linear motor providing forces in both a corresponding long travel dimension and in a dimension perpendicular to both long travel dimensions.

Multivariate meta-analysis using individual participant data.

PubMed

Riley, R D; Price, M J; Jackson, D; Wardle, M; Gueyffier, F; Wang, J; Staessen, J A; White, I R

2015-06-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment-covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. © 2014 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

Comparison of Nonlinear Random Response Using Equivalent Linearization and Numerical Simulation

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Muravyov, Alexander A.

2000-01-01

A recently developed finite-element-based equivalent linearization approach for the analysis of random vibrations of geometrically nonlinear multiple degree-of-freedom structures is validated. The validation is based on comparisons with results from a finite element based numerical simulation analysis using a numerical integration technique in physical coordinates. In particular, results for the case of a clamped-clamped beam are considered for an extensive load range to establish the limits of validity of the equivalent linearization approach.

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models

PubMed Central

Chiu, Chi-yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-ling; Xiong, Momiao; Fan, Ruzong

2017-01-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data. PMID:28000696

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models.

PubMed

Chiu, Chi-Yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-Ling; Xiong, Momiao; Fan, Ruzong

2017-02-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data.

Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

PubMed

Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

2017-05-01

This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Analysis of key factors influencing the evaporation performances of an oriented linear cutting copper fiber sintered felt

NASA Astrophysics Data System (ADS)

Pan, Minqiang; Zhong, Yujian

2018-01-01

Porous structure can effectively enhance the heat transfer efficiency. A kind of micro vaporizer using the oriented linear cutting copper fiber sintered felt is proposed in this work. Multiple long cutting copper fibers are firstly fabricated with a multi-tooth tool and then sintered together in parallel to form uniform thickness metal fiber sintered felts that provided a characteristic of oriented microchannels. The temperature rise response and thermal conversion efficiency are experimentally investigated to evaluate the influences of porosity, surface structure, feed flow rate and input power on the evaporation characteristics. It is indicated that the temperature rise response of water is mainly affected by input power and feed flow rate. High input power and low feed flow rate present better temperature rise response of water. Porosity rather than surface structure plays an important role in the temperature rise response of water at a relatively high input power. The thermal conversion efficiency is dominated by the input power and surface structure. The oriented linear cutting copper fiber sintered felts for three kinds of porosities show better thermal conversion efficiency than that of the oriented linear copper wire sintered felt when the input power is less than 115 W. All the sintered felts have almost the same performance of thermal conversion at a high input power.

Linearized image reconstruction method for ultrasound modulated electrical impedance tomography based on power density distribution

NASA Astrophysics Data System (ADS)

Song, Xizi; Xu, Yanbin; Dong, Feng

2017-04-01

Electrical resistance tomography (ERT) is a promising measurement technique with important industrial and clinical applications. However, with limited effective measurements, it suffers from poor spatial resolution due to the ill-posedness of the inverse problem. Recently, there has been an increasing research interest in hybrid imaging techniques, utilizing couplings of physical modalities, because these techniques obtain much more effective measurement information and promise high resolution. Ultrasound modulated electrical impedance tomography (UMEIT) is one of the newly developed hybrid imaging techniques, which combines electric and acoustic modalities. A linearized image reconstruction method based on power density is proposed for UMEIT. The interior data, power density distribution, is adopted to reconstruct the conductivity distribution with the proposed image reconstruction method. At the same time, relating the power density change to the change in conductivity, the Jacobian matrix is employed to make the nonlinear problem into a linear one. The analytic formulation of this Jacobian matrix is derived and its effectiveness is also verified. In addition, different excitation patterns are tested and analyzed, and opposite excitation provides the best performance with the proposed method. Also, multiple power density distributions are combined to implement image reconstruction. Finally, image reconstruction is implemented with the linear back-projection (LBP) algorithm. Compared with ERT, with the proposed image reconstruction method, UMEIT can produce reconstructed images with higher quality and better quantitative evaluation results.

Relationship between Health Literacy, Health-Related Behaviors and Health Status: A Survey of Elderly Chinese

PubMed Central

Liu, Yong-Bing; Liu, Liu; Li, Yan-Fei; Chen, Yan-Li

2015-01-01

Background: Despite the large volume of research dedicated to health-related behavior change, chronic disease costs continue to rise, thus creating a major public health burden. Health literacy, the ability to seek, understand, and utilize health information, has been identified as an important factor in the course of chronic conditions. Little research has been conducted on the relationship between health literacy and health-related behaviors and health status in elderly Chinese. The aim of this study was to elucidate the relationship between health literacy and health-related behaviors and health status in China. Methods: The subjects enrolled in this study were selected based on a stratified cluster random sampling design. Information involving >4500 older adults in 44 pension institutions in Urumqi, Changji, Karamay, and Shihezi of Xinjiang between September 2011 and June 2012 was collected. The Chinese Citizen Health Literacy Questionnaire (China Health Education Centre, 2008) and a Scale of the General Status were administered and the information was obtained through face-to-face inquiries by investigators. A total of 1452 respondents met the inclusion criteria. A total of 1452 questionnaires were issued and the valid response rate was 96.14% (1396 of 1452). Factors affecting health literacy and the relationship to health literacy were identified by one-way ANOVA and a multiple linear regression model. Results: The average health literacy level of the elderly in nursing homes was relatively low (71.74 ± 28.35 points). There were significant differences in the health literacy score among the factors of age, gender, race, education level, household income, marital conditions, and former occupation (p < 0.001). The health literacy score was significantly associated with smoking, drinking, physical exercise, and health examination (p < 0.001). The elderly with higher health literacy scores were significantly less likely to have risky behaviors (smoking, regular drinking, and lack of physical exercise), and in turn significantly more likely to undergo health examinations regularly, report good self-rated health, and significantly more likely to access sufficient health information from multiple sources (p < 0.001). No differences were noted between the health literacy score and BMI (p > 0.05). Multiple linear regression analysis showed that the independent influencing factors of health literacy included education level, race, former occupation, household income, age, physical exercise, health examination, smoking, and health information access (p < 0.001). Conclusions: Health literacy was significantly associated with health-related behaviors in elderly Chinese. Further longitudinal studies are needed to help confirm that improving health literacy in the elderly may be effective in changing health-related behaviors. To reduce risky habits, educational interventions to improve health literacy should be simultaneously conducted in health promotion work. PMID:26295246

Relationship between Health Literacy, Health-Related Behaviors and Health Status: A Survey of Elderly Chinese.

PubMed

Liu, Yong-Bing; Liu, Liu; Li, Yan-Fei; Chen, Yan-Li

2015-08-18

Despite the large volume of research dedicated to health-related behavior change, chronic disease costs continue to rise, thus creating a major public health burden. Health literacy, the ability to seek, understand, and utilize health information, has been identified as an important factor in the course of chronic conditions. Little research has been conducted on the relationship between health literacy and health-related behaviors and health status in elderly Chinese. The aim of this study was to elucidate the relationship between health literacy and health-related behaviors and health status in China. The subjects enrolled in this study were selected based on a stratified cluster random sampling design. Information involving >4500 older adults in 44 pension institutions in Urumqi, Changji, Karamay, and Shihezi of Xinjiang between September 2011 and June 2012 was collected. The Chinese Citizen Health Literacy Questionnaire (China Health Education Centre, 2008) and a Scale of the General Status were administered and the information was obtained through face-to-face inquiries by investigators. A total of 1452 respondents met the inclusion criteria. A total of 1452 questionnaires were issued and the valid response rate was 96.14% (1396 of 1452). Factors affecting health literacy and the relationship to health literacy were identified by one-way ANOVA and a multiple linear regression model. The average health literacy level of the elderly in nursing homes was relatively low (71.74 ± 28.35 points). There were significant differences in the health literacy score among the factors of age, gender, race, education level, household income, marital conditions, and former occupation (p < 0.001). The health literacy score was significantly associated with smoking, drinking, physical exercise, and health examination (p < 0.001). The elderly with higher health literacy scores were significantly less likely to have risky behaviors (smoking, regular drinking, and lack of physical exercise), and in turn significantly more likely to undergo health examinations regularly, report good self-rated health, and significantly more likely to access sufficient health information from multiple sources (p < 0.001). No differences were noted between the health literacy score and BMI (p > 0.05). Multiple linear regression analysis showed that the independent influencing factors of health literacy included education level, race, former occupation, household income, age, physical exercise, health examination, smoking, and health information access (p < 0.001). Health literacy was significantly associated with health-related behaviors in elderly Chinese. Further longitudinal studies are needed to help confirm that improving health literacy in the elderly may be effective in changing health-related behaviors. To reduce risky habits, educational interventions to improve health literacy should be simultaneously conducted in health promotion work.

An extended car-following model considering random safety distance with different probabilities

NASA Astrophysics Data System (ADS)

Wang, Jufeng; Sun, Fengxin; Cheng, Rongjun; Ge, Hongxia; Wei, Qi

2018-02-01

Because of the difference in vehicle type or driving skill, the driving strategy is not exactly the same. The driving speeds of the different vehicles may be different for the same headway. Since the optimal velocity function is just determined by the safety distance besides the maximum velocity and headway, an extended car-following model accounting for random safety distance with different probabilities is proposed in this paper. The linear stable condition for this extended traffic model is obtained by using linear stability theory. Numerical simulations are carried out to explore the complex phenomenon resulting from multiple safety distance in the optimal velocity function. The cases of multiple types of safety distances selected with different probabilities are presented. Numerical results show that the traffic flow with multiple safety distances with different probabilities will be more unstable than that with single type of safety distance, and will result in more stop-and-go phenomena.

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Tuning diagonal components of static linear and first nonlinear polarizabilities of doped quantum dots by Gaussian white noise

NASA Astrophysics Data System (ADS)

Ganguly, Jayanta; Ghosh, Manas

2015-07-01

We investigate the modulation of diagonal components of static linear (αxx, αyy) and first nonlinear (βxxx, βyyy) polarizabilities of quantum dots by Gaussian white noise. Quantum dot is doped with impurity represented by a Gaussian potential and repulsive in nature. The study reveals the importance of mode of application of noise (additive/multiplicative) on the polarizability components. The doped system is further exposed to a static external electric field of given intensity. As important observation we have found that the strength of additive noise becomes unable to influence the polarizability components. However, the multiplicative noise influences them conspicuously and gives rise to additional interesting features. Multiplicative noise even enhances the magnitude of the polarizability components immensely. The present investigation deems importance in view of the fact that noise seriously affects the optical properties of doped quantum dot devices.

Multiple continuous coverage of the earth based on multi-satellite systems with linear structure

NASA Astrophysics Data System (ADS)

Saulskiy, V. K.

2009-04-01

A new and wider definition is given to multi-satellite systems with linear structure (SLS), and efficiency of their application to multiple continuous coverage of the Earth is substantiated. Owing to this widening, SLS have incorporated already well-recognized “polar systems” by L. Rider and W.S. Adams, “kinematically regular systems” by G.V. Mozhaev, and “delta-systems” by J.G. Walker, as well as “near-polar systems” by Yu.P. Ulybyshev, and some other satellite constellations unknown before. A universal method of SLS optimization is presented, valid for any values of coverage multiplicity and the number of satellites in a system. The method uses the criterion of minimum radius of a circle seen from a satellite on the surface of the globe. Among the best SLS found in this way there are both systems representing the well-known classes mentioned above and new orbit constellations of satellites.

Indoor molds and lung function in healthy adults.

PubMed

Hernberg, Samu; Sripaiboonkij, Penpatra; Quansah, Reginald; Jaakkola, Jouni J K; Jaakkola, Maritta S

2014-05-01

Indoor mold exposure is common worldwide and constitutes an important health problem. There are very few studies assessing the relation between mold exposure and lung function levels among non-asthmatic adults. Our objective was to assess the relations between dampness and mold exposures at home and at work and lung function. In particular, we elaborated the importance of different exposure indicators. In a population-based study, 269 non-asthmatic adults from South Finland answered a questionnaire on indoor dampness and mold exposures at home or at work and other factors potentially influencing lung function, and performed spirometry. Multiple linear regression model was applied to study the relations between exposures and spirometric lung function levels. In linear regression adjusting for confounding, FEV1 level was reduced on average 200 ml related to mold odor at home (effect estimate -0.20, 95% CI -0.60 to 0.21) and FVC level was reduced on average 460 ml (-0.46, -0.95 to 0.03) respectively. Exposure to mold odor at home or at work or both was related to reduced FEV1 (-0.15, -0.42 to 0.12) and FVC (-0.22, -0.55 to 0.11) levels. Women had on average 510 ml reduced FEV1 levels (-0.51, -1.0 to 0.03) and 820 ml reduced FVC levels (-0.82, -1.4 to -0.20) related to mold odor exposure at home. Mold odor exposure was related to lower lung function levels among non-asthmatic adults, especially among women. Copyright © 2014 Elsevier Ltd. All rights reserved.

Scalable parallel communications

NASA Technical Reports Server (NTRS)

Maly, K.; Khanna, S.; Overstreet, C. M.; Mukkamala, R.; Zubair, M.; Sekhar, Y. S.; Foudriat, E. C.

1992-01-01

Coarse-grain parallelism in networking (that is, the use of multiple protocol processors running replicated software sending over several physical channels) can be used to provide gigabit communications for a single application. Since parallel network performance is highly dependent on real issues such as hardware properties (e.g., memory speeds and cache hit rates), operating system overhead (e.g., interrupt handling), and protocol performance (e.g., effect of timeouts), we have performed detailed simulations studies of both a bus-based multiprocessor workstation node (based on the Sun Galaxy MP multiprocessor) and a distributed-memory parallel computer node (based on the Touchstone DELTA) to evaluate the behavior of coarse-grain parallelism. Our results indicate: (1) coarse-grain parallelism can deliver multiple 100 Mbps with currently available hardware platforms and existing networking protocols (such as Transmission Control Protocol/Internet Protocol (TCP/IP) and parallel Fiber Distributed Data Interface (FDDI) rings); (2) scale-up is near linear in n, the number of protocol processors, and channels (for small n and up to a few hundred Mbps); and (3) since these results are based on existing hardware without specialized devices (except perhaps for some simple modifications of the FDDI boards), this is a low cost solution to providing multiple 100 Mbps on current machines. In addition, from both the performance analysis and the properties of these architectures, we conclude: (1) multiple processors providing identical services and the use of space division multiplexing for the physical channels can provide better reliability than monolithic approaches (it also provides graceful degradation and low-cost load balancing); (2) coarse-grain parallelism supports running several transport protocols in parallel to provide different types of service (for example, one TCP handles small messages for many users, other TCP's running in parallel provide high bandwidth service to a single application); and (3) coarse grain parallelism will be able to incorporate many future improvements from related work (e.g., reduced data movement, fast TCP, fine-grain parallelism) also with near linear speed-ups.

Locomotive syndrome is associated not only with physical capacity but also degree of depression.

PubMed

Ikemoto, Tatsunori; Inoue, Masayuki; Nakata, Masatoshi; Miyagawa, Hirofumi; Shimo, Kazuhiro; Wakabayashi, Toshiko; Arai, Young-Chang P; Ushida, Takahiro

2016-05-01

Reports of locomotive syndrome (LS) have recently been increasing. Although physical performance measures for LS have been well investigated to date, studies including psychiatric assessment are still scarce. Hence, the aim of this study was to investigate both physical and mental parameters in relation to presence and severity of LS using a 25-question geriatric locomotive function scale (GLFS-25) questionnaire. 150 elderly people aged over 60 years who were members of our physical-fitness center and displayed well-being were enrolled in this study. Firstly, using the previously determined GLFS-25 cutoff value (=16 points), subjects were divided into two groups accordingly: an LS and non-LS group in order to compare each parameter (age, grip strength, timed-up-and-go test (TUG), one-leg standing with eye open, back muscle and leg muscle strength, degree of depression and cognitive impairment) between the groups using the Mann-Whitney U-test followed by multiple logistic regression analysis. Secondly, a multiple linear regression was conducted to determine which variables showed the strongest correlation with severity of LS. We confirmed 110 people for non-LS (73%) and 40 people for LS using the GLFS-25 cutoff value. Comparative analysis between LS and non-LS revealed significant differences in parameters in age, grip strength, TUG, one-leg standing, back muscle strength and degree of depression (p < 0.006, after Bonferroni correction). Multiple logistic regression revealed that functional decline in grip strength, TUG and one-leg standing and degree of depression were significantly associated with LS. On the other hand, we observed that the significant contributors towards the GLFS-25 score were TUG and degree of depression in multiple linear regression analysis. The results indicate that LS is associated with not only the capacity of physical performance but also the degree of depression although most participants fell under the criteria of LS. Copyright © 2016 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Extending substructure based iterative solvers to multiple load and repeated analyses

NASA Technical Reports Server (NTRS)

Farhat, Charbel

1993-01-01

Direct solvers currently dominate commercial finite element structural software, but do not scale well in the fine granularity regime targeted by emerging parallel processors. Substructure based iterative solvers--often called also domain decomposition algorithms--lend themselves better to parallel processing, but must overcome several obstacles before earning their place in general purpose structural analysis programs. One such obstacle is the solution of systems with many or repeated right hand sides. Such systems arise, for example, in multiple load static analyses and in implicit linear dynamics computations. Direct solvers are well-suited for these problems because after the system matrix has been factored, the multiple or repeated solutions can be obtained through relatively inexpensive forward and backward substitutions. On the other hand, iterative solvers in general are ill-suited for these problems because they often must restart from scratch for every different right hand side. In this paper, we present a methodology for extending the range of applications of domain decomposition methods to problems with multiple or repeated right hand sides. Basically, we formulate the overall problem as a series of minimization problems over K-orthogonal and supplementary subspaces, and tailor the preconditioned conjugate gradient algorithm to solve them efficiently. The resulting solution method is scalable, whereas direct factorization schemes and forward and backward substitution algorithms are not. We illustrate the proposed methodology with the solution of static and dynamic structural problems, and highlight its potential to outperform forward and backward substitutions on parallel computers. As an example, we show that for a linear structural dynamics problem with 11640 degrees of freedom, every time-step beyond time-step 15 is solved in a single iteration and consumes 1.0 second on a 32 processor iPSC-860 system; for the same problem and the same parallel processor, a pair of forward/backward substitutions at each step consumes 15.0 seconds.

Spacecraft Formation Flying Maneuvers Using Linear Quadratic Regulation With No Radial Axis Inputs

NASA Technical Reports Server (NTRS)

Starin, Scott R.; Yedavalli, R. K.; Sparks, Andrew G.; Bauer, Frank H. (Technical Monitor)

2001-01-01

Regarding multiple spacecraft formation flying, the observation has been made that control thrust need only be applied coplanar to the local horizon to achieve complete controllability of a two-satellite (leader-follower) formation. A formulation of orbital dynamics using the state of one satellite relative to another is used. Without the need for thrust along the radial (zenith-nadir) axis of the relative reference frame, propulsion system simplifications and weight reduction may be accomplished. This work focuses on the validation of this control system on its own merits, and in comparison to a related system which does provide thrust along the radial axis of the relative frame. Maneuver simulations are performed using commercial ODE solvers to propagate the Keplerian dynamics of a controlled satellite relative to an uncontrolled leader. These short maneuver simulations demonstrate the capacity of the controller to perform changes from one formation geometry to another. Control algorithm performance is evaluated based on measures such as the fuel required to complete a maneuver and the maximum acceleration required by the controller. Based on this evaluation, the exclusion of the radial axis of control still allows enough control authority to use Linear Quadratic Regulator (LQR) techniques to design a gain matrix of adequate performance over finite maneuvers. Additional simulations are conducted including perturbations and using no radial control inputs. A major conclusion presented is that control inputs along the three axes have significantly different relationships to the governing orbital dynamics that may be exploited using LQR.

The Physical Origin of Long Gas Depletion Times in Galaxies

NASA Astrophysics Data System (ADS)

Semenov, Vadim A.; Kravtsov, Andrey V.; Gnedin, Nickolay Y.

2017-08-01

We present a model that explains why galaxies form stars on a timescale significantly longer than the timescales of processes governing the evolution of interstellar gas. We show that gas evolves from a non-star-forming to a star-forming state on a relatively short timescale, and thus the rate of this evolution does not limit the star formation rate (SFR). Instead, the SFR is limited because only a small fraction of star-forming gas is converted into stars before star-forming regions are dispersed by feedback and dynamical processes. Thus, gas cycles into and out of a star-forming state multiple times, which results in a long timescale on which galaxies convert gas into stars. Our model does not rely on the assumption of equilibrium and can be used to interpret trends of depletion times with the properties of observed galaxies and the parameters of star formation and feedback recipes in simulations. In particular, the model explains how feedback self-regulates the SFR in simulations and makes it insensitive to the local star formation efficiency. We illustrate our model using the results of an isolated L *-sized galaxy simulation that reproduces the observed Kennicutt-Schmidt relation for both molecular and atomic gas. Interestingly, the relation for molecular gas is almost linear on kiloparsec scales, although a nonlinear relation is adopted in simulation cells. We discuss how a linear relation emerges from non-self-similar scaling of the gas density PDF with the average gas surface density.

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

Semenov, Vadim A.; Kravtsov, Andrey V.; Gnedin, Nickolay Y., E-mail: semenov@uchicago.edu

We present a model that explains why galaxies form stars on a timescale significantly longer than the timescales of processes governing the evolution of interstellar gas. We show that gas evolves from a non-star-forming to a star-forming state on a relatively short timescale, and thus the rate of this evolution does not limit the star formation rate (SFR). Instead, the SFR is limited because only a small fraction of star-forming gas is converted into stars before star-forming regions are dispersed by feedback and dynamical processes. Thus, gas cycles into and out of a star-forming state multiple times, which results inmore » a long timescale on which galaxies convert gas into stars. Our model does not rely on the assumption of equilibrium and can be used to interpret trends of depletion times with the properties of observed galaxies and the parameters of star formation and feedback recipes in simulations. In particular, the model explains how feedback self-regulates the SFR in simulations and makes it insensitive to the local star formation efficiency. We illustrate our model using the results of an isolated L {sub *}-sized galaxy simulation that reproduces the observed Kennicutt–Schmidt relation for both molecular and atomic gas. Interestingly, the relation for molecular gas is almost linear on kiloparsec scales, although a nonlinear relation is adopted in simulation cells. We discuss how a linear relation emerges from non-self-similar scaling of the gas density PDF with the average gas surface density.« less

Maximum likelihood pedigree reconstruction using integer linear programming.

PubMed

Cussens, James; Bartlett, Mark; Jones, Elinor M; Sheehan, Nuala A

2013-01-01

Large population biobanks of unrelated individuals have been highly successful in detecting common genetic variants affecting diseases of public health concern. However, they lack the statistical power to detect more modest gene-gene and gene-environment interaction effects or the effects of rare variants for which related individuals are ideally required. In reality, most large population studies will undoubtedly contain sets of undeclared relatives, or pedigrees. Although a crude measure of relatedness might sometimes suffice, having a good estimate of the true pedigree would be much more informative if this could be obtained efficiently. Relatives are more likely to share longer haplotypes around disease susceptibility loci and are hence biologically more informative for rare variants than unrelated cases and controls. Distant relatives are arguably more useful for detecting variants with small effects because they are less likely to share masking environmental effects. Moreover, the identification of relatives enables appropriate adjustments of statistical analyses that typically assume unrelatedness. We propose to exploit an integer linear programming optimisation approach to pedigree learning, which is adapted to find valid pedigrees by imposing appropriate constraints. Our method is not restricted to small pedigrees and is guaranteed to return a maximum likelihood pedigree. With additional constraints, we can also search for multiple high-probability pedigrees and thus account for the inherent uncertainty in any particular pedigree reconstruction. The true pedigree is found very quickly by comparison with other methods when all individuals are observed. Extensions to more complex problems seem feasible. © 2012 Wiley Periodicals, Inc.

Interactive influences of neighborhood and individual socioeconomic status on alcohol consumption and problems.

PubMed

Mulia, Nina; Karriker-Jaffe, Katherine J

2012-01-01

To assess cross-level interactions between neighborhood and individual socioeconomic status (SES) on alcohol consumption and problems, and investigate three possible explanations for such interactions, including the double jeopardy, status inconsistency and relative deprivation hypotheses. Data from the 2000 and 2005 US National Alcohol Surveys were linked to the 2000 US Census to define respondent census tracts as disadvantaged, middle-class and advantaged. Risk drinking (consumption exceeding national guidelines), monthly drunkenness and alcohol problems were examined among low-, middle- and high-SES past-year drinkers (n = 8728). Gender-stratified, multiple logistic regression models were employed, and for outcomes with a significant omnibus F-test, linear contrasts were used to interpret interactions. Cross-level SES interactions observed for men indicated that residence in advantaged neighborhoods was associated with markedly elevated odds of risk drinking and drunkenness for low-SES men. Linear contrasts further revealed a nearly 5-fold increased risk for alcohol problems among these men, relative to middle-SES and high-SES men also living in advantaged neighborhoods. Among women, neighborhood disadvantage was related to increased risk for alcohol problems, but there were no significant SES interactions. These findings did not support theories of double jeopardy and status inconsistency. Consistent with the relative deprivation hypothesis, findings highlight alcohol-related health risks among low-SES men living in affluent neighborhoods. Future research should assess whether this pattern extends to other health risk behaviors, investigate causal mechanisms and consider how gender may influence these.

The Integration of Teacher's Pedagogical Content Knowledge Components in Teaching Linear Equation

ERIC Educational Resources Information Center

Yusof, Yusminah Mohd.; Effandi, Zakaria

2015-01-01

This qualitative research aimed to explore the integration of the components of pedagogical content knowledge (PCK) in teaching Linear Equation with one unknown. For the purpose of the study, a single local case study with multiple participants was used. The selection of the participants was made based on various criteria: having more than 5 years…

The Effects of Multiple Linked Representations on Students' Learning of Linear Relationships

ERIC Educational Resources Information Center

Ozgun-Koca, S. Asli

2004-01-01

The focus of this study was on comparing three groups of Algebra I 9th-year students: one group using linked representation software, the second group using similar software but with semi-linked representations, and the control group in order to examine the effects on students' understanding of linear relationships. Data collection methods…